I used this code for segmentation, I'm trying to detect pixels one by one because my object is a binary, not a grayscale. when i run the program, it draws 2 object. The first object is successfully drawn (object still has a black color and a red rectangle), but the second object fails get drawn. Screenshot is here. Please help me, why does this happen?
#region Edge Detection
private void btnSegmentasi_Click(object sender, EventArgs e)
{
Segments = new List<ImageSegment>();
Bitmap bmp = (Bitmap)pb2.Image;
imageArea = new Rectangle(0, 0, pb2.Image.Width - 1, pb2.Image.Height - 1);
for (int y = 0; y < pb2.Image.Height; y++)
{
for (int x = 0; x < pb2.Image.Width; x++)
{
bool skip = false;
foreach (ImageSegment segment in Segments)
{
if (pointIsInRect(x, y, segment.Rect))
{
skip = true;
break;
}
}
if (skip) continue;
Color warna = bmp.GetPixel(x, y);
if (warna.G == 0)
startEdgeDetection(x, y, ref bmp);
}
}
DGVProses.DataSource = Segments;
if (Segments.Count > 0)
{
Graphics g = pb2.CreateGraphics();
Rectangle[] rects = (from theSegment in Segments select theSegment.Rect).ToArray();
g.DrawRectangles(new Pen(Brushes.Red), rects);
g.Dispose();
}
}
private void startEdgeDetection(int x, int y, ref Bitmap bmp)
{
Point startPoint = new Point(x, y);
Point currPoint = new Point(x, y);
int sudut = 180;
int xMin = x, yMin = y, xMax = x, yMax = y;
do
{
sudut -= 45;
Point offset = angleToPoint(ref sudut);
Point trialPoint = new Point(currPoint.X + offset.X, currPoint.Y + offset.Y);
if (!pointIsInRect(trialPoint.X, trialPoint.Y, imageArea))
continue;
Color theColor = bmp.GetPixel(trialPoint.X, trialPoint.Y);
if (theColor.G == 0)
{
currPoint = trialPoint;
sudut -= 180;
if (currPoint.X > xMax)
xMax = currPoint.X;
else if (currPoint.X < xMin)
xMin = currPoint.X;
if (currPoint.Y > yMax)
yMax = currPoint.Y;
else if (currPoint.Y < yMin)
yMin = currPoint.Y;
if (sudut < 0)
sudut += 360;
if (currPoint == startPoint && sudut == 180)
break;
}
}
while (!(currPoint == startPoint && sudut == 180));
Rectangle r = new Rectangle(xMin, yMin, xMax - xMin + 1, yMax - yMin + 1);
Bitmap newImage = new Bitmap(r.Width + 2, r.Height + 2);
using (Graphics g = Graphics.FromImage(newImage))
{
g.FillRectangle(Brushes.White, 0, 0, newImage.Width, newImage.Height);
g.DrawImage(bmp, new Rectangle(1, 1, r.Width, r.Height), r, GraphicsUnit.Pixel);
g.Dispose();
}
Segments.Add(new ImageSegment(r, newImage));
}
private Point angleToPoint(ref int sudut)
{
if (sudut < 0)
sudut += 360;
switch (sudut)
{
case 135: return new Point(-1, -1);
case 90: return new Point(0, -1);
case 45: return new Point(1, -1);
case 0: return new Point(1, 0);
case 315: return new Point(1, 1);
case 270: return new Point(0, 1);
case 225: return new Point(-1, 1);
default: return new Point(-1, 0);
}
}
private bool pointIsInRect(int x, int y, Rectangle rect)
{
if (x < rect.X)
return false;
if (x > rect.X + rect.Width)
return false;
if (x < rect.Y)
return false;
if (x > rect.Y + rect.Height)
return false;
return true;
}
#endregion
Okay, I think I've now got a clue of how your algorithm is supposed to work. I'd guess you are running around in circles within the object. I do not really know why it does not happen for the first object, but this is another story.
When you enter startEdgeDetection you start at some point, check if it's black, move by an angle and repeat the whole procedure. You stop when the current point reaches the starting point. The crux is, that this algorithm does not guarantee to walk the whole object, but may just do the following (I do not know it is exactly like this, but pretty much):
OOOOOO
O####O
O####O
OOOOOO
OOOOOO
O*###O
O####O
OOOOOO
OOOOOO
O**##O
O####O
OOOOOO
OOOOOO
O**##O
O#*##O
OOOOOO
OOOOOO
O**##O
O**##O
OOOOOO
O = pixels filled with white
# = pixels filled with black
* = pixels you stepped through
You've reached your starting point again and the algorithm stops, but the bounding box does not contain the whole object, but just a part. If all of your objects bounding boxes have either a width or a height of 1 you fill up your whole object with bounding boxes, hence it appears red.
You'll have to fix the startEdgeDetection to avoid the described case and make sure that you really detect the edge.
I made up a simple class that finds the bounding box of an object. It should be easy to apply it to your problem.
public class BoundingBoxCalculator
{
Bitmap bitmapToCalculateBoundingBoxFor;
Point startingPoint;
Point[] neighborOffsets =
{new Point(-1,-1),
new Point(0,-1),
new Point(1,-1),
new Point(-1, 0),
new Point(1, 0),
new Point(-1,1),
new Point(0,1),
new Point(1,1)};
public BoundingBoxCalculator(Bitmap bitmapContainingObject, Point borderPoint)
{
this.bitmapToCalculateBoundingBoxFor = bitmapContainingObject;
this.startingPoint = borderPoint;
}
public Rectangle CalculateBoundingBox()
{
List<Point> edgePoints = CalculateEdge();
int minX = edgePoints.Min(p => p.X);
int maxX = edgePoints.Max(p => p.X);
int minY = edgePoints.Min(p => p.Y);
int maxY = edgePoints.Max(p => p.Y);
return new Rectangle(minX, minY, maxX - minX, maxY - minY);
}
List<Point> CalculateEdge()
{
List<Point> edgePoints = new List<Point>();
Point currentPoint = startingPoint;
do
{
IEnumerable<Point> neighboringEdgePoints = GetNeighboringEdgePoints(currentPoint);
IEnumerable<Point> neighboringEdgePointsNotVisited = from p in neighboringEdgePoints where !edgePoints.Contains(p) select p;
edgePoints.Add(currentPoint);
if(neighboringEdgePointsNotVisited.Count() == 0
&& neighboringEdgePoints.Contains(startingPoint))
{
currentPoint = startingPoint;
}
else if(neighboringEdgePointsNotVisited.Count() == 1)
{
Point nextPoint = neighboringEdgePointsNotVisited.First();
currentPoint = nextPoint;
}
else if(neighboringEdgePointsNotVisited.Count() > 1)
{
Point nextPoint = GetPointWithMinDistance(currentPoint, neighboringEdgePointsNotVisited);
currentPoint = nextPoint;
}
else
{
throw new Exception();
}
} while(currentPoint != startingPoint);
return edgePoints;
}
Point GetPointWithMinDistance(Point origin, IEnumerable<Point> pointsToTest)
{
double minDistance = double.MaxValue;
Point pointWithMinDistance = new Point(0,0);
foreach(Point pointToTest in pointsToTest)
{
double currentDistance = GetPointsDistance(origin, pointToTest);
if(currentDistance < minDistance)
{
minDistance = currentDistance;
pointWithMinDistance = pointToTest;
}
}
return pointWithMinDistance;
}
double GetPointsDistance(Point p1, Point p2)
{
return Math.Sqrt((p1.X - p2.X) * (p1.X - p2.X) + (p1.Y - p2.Y) * (p1.Y - p2.Y));
}
IEnumerable<Point> GetNeighboringEdgePoints(Point currentPoint)
{
IEnumerable<Point> neighboringPoints = GetNeighboringPoints(currentPoint);
List<Point> neighboringEdgePoints = new List<Point>();
foreach(Point pointToTest in neighboringPoints)
{
if(GetNeighboringPoints(pointToTest).Count() < 8)
{
neighboringEdgePoints.Add(pointToTest);
}
}
return neighboringEdgePoints;
}
IEnumerable<Point> GetNeighboringPoints(Point currentPoint)
{
List<Point> neighbors = new List<Point>();
for(int offsetsCount = 0; offsetsCount < neighborOffsets.Length; offsetsCount++)
{
Point currentPointWithOffset = AddPointOffset(currentPoint, neighborOffsets[offsetsCount]);
if(IsInImage(currentPointWithOffset) &&
IsInObject(currentPointWithOffset))
{
neighbors.Add(currentPointWithOffset);
}
}
return neighbors;
}
bool IsInImage(Point pointToTest)
{
return pointToTest.X >= 0
&& pointToTest.X < bitmapToCalculateBoundingBoxFor.Width
&& pointToTest.Y >= 0
&& pointToTest.Y < bitmapToCalculateBoundingBoxFor.Height;
}
bool IsInObject(Point pointToTest)
{
Color colorInPointPosition = bitmapToCalculateBoundingBoxFor.GetPixel(pointToTest.X, pointToTest.Y);
//assume object is color is not white
return colorInPointPosition.R != 255
|| colorInPointPosition.G != 255
|| colorInPointPosition.B != 255;
}
Point AddPointOffset(Point point, Point offset)
{
return new Point(point.X + offset.X, point.Y + offset.Y);
}
}
Find an example at:
https://dotnetfiddle.net/49bnTV
I just tested it with a rectangle, but I guess it should work with any shape. Just give it a try.
I have three points, for example:
Start 194 171
Right 216 131
Left 216 203
I want to get all the points within that triangle. How would I do that efficiently?
see z3nth10n's answer for better input validation
Introduction:
The general idea was to get the triangle's edges (y-Wise) for every x in it's range, and then you have all the y's that exist within the triangle for every single x, which with simple conversion turns into all points within the triangle.
You can look at it as if you cut the triangle into stripes, each being of width 1.
So for X=0, on the line between A and B, the Y is 6, and on the line between A and C, the Y is -2, so you can see that the stripe of X=0 is between -2 and 6. Therefore, you can tell that (0, -2) (0, -1) (0, 0) ... (0, 5) (0, 6) are all in the triangle. Doing that for X's between the smallest and the largest within the triangle, and you have all the points in the triangle!
Speed:
For the triangle (0, 0) (1, 8) (4, 6) - found 16 points.
Done 1,000,000 times in 3.68 seconds.
Implementation:
public IEnumerable<Point> PointsInTriangle(Point pt1, Point pt2, Point pt3)
{
if (pt1.Y == pt2.Y && pt1.Y == pt3.Y)
{
throw new ArgumentException("The given points must form a triangle.");
}
Point tmp;
if (pt2.X < pt1.X)
{
tmp = pt1;
pt1 = pt2;
pt2 = tmp;
}
if (pt3.X < pt2.X)
{
tmp = pt2;
pt2 = pt3;
pt3 = tmp;
if (pt2.X < pt1.X)
{
tmp = pt1;
pt1 = pt2;
pt2 = tmp;
}
}
var baseFunc = CreateFunc(pt1, pt3);
var line1Func = pt1.X == pt2.X ? (x => pt2.Y) : CreateFunc(pt1, pt2);
for (var x = pt1.X; x < pt2.X; x++)
{
int maxY;
int minY = GetRange(line1Func(x), baseFunc(x), out maxY);
for (var y = minY; y <= maxY; y++)
{
yield return new Point(x, y);
}
}
var line2Func = pt2.X == pt3.X ? (x => pt2.Y) : CreateFunc(pt2, pt3);
for (var x = pt2.X; x <= pt3.X; x++)
{
int maxY;
int minY = GetRange(line2Func(x), baseFunc(x), out maxY);
for (var y = minY; y <= maxY; y++)
{
yield return new Point(x, y);
}
}
}
private int GetRange(double y1, double y2, out int maxY)
{
if (y1 < y2)
{
maxY = (int)Math.Floor(y2);
return (int)Math.Ceiling(y1);
}
maxY = (int)Math.Floor(y1);
return (int)Math.Ceiling(y2);
}
private Func<int, double> CreateFunc(Point pt1, Point pt2)
{
var y0 = pt1.Y;
if (y0 == pt2.Y)
{
return x => y0;
}
var m = (double)(pt2.Y - y0) / (pt2.X - pt1.X);
return x => m * (x - pt1.X) + y0;
}
#SimpleVar answer is well, but it lacks a good check for valid triangles. (This can cause an overflow problem).
So I do my own implementation for Unity3D:
public static IEnumerable<T> PointsInTriangle<T>(T pt1, T pt2, T pt3)
where T : IPoint
{
/*
// https://www.geeksforgeeks.org/check-whether-triangle-valid-not-sides-given/
a + b > c
a + c > b
b + c > a
*/
float a = Vector2.Distance(new Vector2(pt1.x, pt1.y), new Vector2(pt2.x, pt2.y)),
b = Vector2.Distance(new Vector2(pt2.x, pt2.y), new Vector2(pt3.x, pt3.y)),
c = Vector2.Distance(new Vector2(pt3.x, pt3.y), new Vector2(pt1.x, pt1.y));
if (a + b <= c || a + c <= b || b + c <= a)
{
Debug.LogWarning($"The given points must form a triangle. {{{pt1}, {pt2}, {pt3}}}");
yield break;
}
if (TriangleArea(pt1, pt2, pt3) <= 1)
{
Point center = GetTriangleCenter(pt1, pt2, pt3);
yield return (T)Activator.CreateInstance(typeof(T), center.x, center.y);
return;
}
T tmp;
if (pt2.x < pt1.x)
{
tmp = pt1;
pt1 = pt2;
pt2 = tmp;
}
if (pt3.x < pt2.x)
{
tmp = pt2;
pt2 = pt3;
pt3 = tmp;
if (pt2.x < pt1.x)
{
tmp = pt1;
pt1 = pt2;
pt2 = tmp;
}
}
var baseFunc = CreateFunc(pt1, pt3);
var line1Func = pt1.x == pt2.x ? (x => pt2.y) : CreateFunc(pt1, pt2);
for (var x = pt1.x; x < pt2.x; ++x)
{
int maxY;
int minY = GetRange(line1Func(x), baseFunc(x), out maxY);
for (int y = minY; y <= maxY; ++y)
yield return (T)Activator.CreateInstance(typeof(T), x, y);
}
var line2Func = pt2.x == pt3.x ? (x => pt2.y) : CreateFunc(pt2, pt3);
for (var x = pt2.x; x <= pt3.x; ++x)
{
int maxY;
int minY = GetRange(line2Func(x), baseFunc(x), out maxY);
for (int y = minY; y <= maxY; ++y)
yield return (T)Activator.CreateInstance(typeof(T), x, y);
}
}
private static int GetRange(float y1, float y2, out int maxY)
{
if (y1 < y2)
{
maxY = Mathf.FloorToInt(y2);
return Mathf.CeilToInt(y1);
}
maxY = Mathf.FloorToInt(y1);
return Mathf.CeilToInt(y2);
}
private static Func<int, float> CreateFunc<T>(T pt1, T pt2)
where T : IPoint
{
var y0 = pt1.y;
if (y0 == pt2.y)
return x => y0;
float m = (float)(pt2.y - y0) / (pt2.x - pt1.x);
return x => m * (x - pt1.x) + y0;
}
public static float TriangleArea<T>(T p1, T p2, T p3)
where T : IPoint
{
float a, b, c;
if (!CheckIfValidTriangle(p1, p2, p3, out a, out b, out c))
return 0;
return TriangleArea(a, b, c);
}
public static float TriangleArea(float a, float b, float c)
{
// Thanks to: http://james-ramsden.com/area-of-a-triangle-in-3d-c-code/
float s = (a + b + c) / 2.0f;
return Mathf.Sqrt(s * (s - a) * (s - b) * (s - c));
}
public static Point GetTriangleCenter<T>(T p0, T p1, T p2)
where T : IPoint
{
// Thanks to: https://stackoverflow.com/questions/524755/finding-center-of-2d-triangle
return new Point(p0.x + p1.x + p2.x / 3, p0.y + p1.y + p2.y / 3);
}
public static bool CheckIfValidTriangle<T>(T v1, T v2, T v3, out float a, out float b, out float c)
where T : IPoint
{
a = Vector2.Distance(new Vector2(v1.x, v1.y), new Vector2(v2.x, v2.y));
b = Vector2.Distance(new Vector2(v2.x, v2.y), new Vector2(v3.x, v3.y));
c = Vector2.Distance(new Vector2(v3.x, v3.y), new Vector2(v1.x, v1.y));
if (a + b <= c || a + c <= b || b + c <= a)
return false;
return true;
}
IPoint interface could be a good point for own Point implementations (for libs like Clipper, TessDotNet or Poly2Tri). You can change it at any time (two UnityEngine.Vector2 or System.Drawing.Point).
Hope this helps!
EDIT: I solved all bugs here:
Also I answered my own question asking this: https://stackoverflow.com/a/53734816/3286975
I've got a program that allows users to draw curves. But these curves don't look nice - they look wobbly and hand-drawn.
So I want an algorithm that will automatically smooth them. I know there are inherent ambiguities in the smoothing process, so it won't be perfect every time, but such algorithms do seem to exist in several drawing packages and they work quite well.
Are there any code samples for something like this? C# would be perfect, but I can translate from other languages.
You can reduce the number of points using the Ramer–Douglas–Peucker algorithm there is a C# implementation here. I gave this a try using WPFs PolyQuadraticBezierSegment and it showed a small amount of improvement depending on the tolerance.
After a bit of searching sources (1,2) seem to indicate that using the curve fitting algorithm from Graphic Gems by Philip J Schneider works well, the C code is available. Geometric Tools also has some resources that could be worth investigating.
This is a rough sample I made, there are still some glitches but it works well a lot of the time. Here is the quick and dirty C# port of FitCurves.c. One of the issues is that if you don't reduce the original points the calculated error is 0 and it terminates early the sample uses the point reduction algorithm beforehand.
/*
An Algorithm for Automatically Fitting Digitized Curves
by Philip J. Schneider
from "Graphics Gems", Academic Press, 1990
*/
public static class FitCurves
{
/* Fit the Bezier curves */
private const int MAXPOINTS = 10000;
public static List<Point> FitCurve(Point[] d, double error)
{
Vector tHat1, tHat2; /* Unit tangent vectors at endpoints */
tHat1 = ComputeLeftTangent(d, 0);
tHat2 = ComputeRightTangent(d, d.Length - 1);
List<Point> result = new List<Point>();
FitCubic(d, 0, d.Length - 1, tHat1, tHat2, error,result);
return result;
}
private static void FitCubic(Point[] d, int first, int last, Vector tHat1, Vector tHat2, double error,List<Point> result)
{
Point[] bezCurve; /*Control points of fitted Bezier curve*/
double[] u; /* Parameter values for point */
double[] uPrime; /* Improved parameter values */
double maxError; /* Maximum fitting error */
int splitPoint; /* Point to split point set at */
int nPts; /* Number of points in subset */
double iterationError; /*Error below which you try iterating */
int maxIterations = 4; /* Max times to try iterating */
Vector tHatCenter; /* Unit tangent vector at splitPoint */
int i;
iterationError = error * error;
nPts = last - first + 1;
/* Use heuristic if region only has two points in it */
if(nPts == 2)
{
double dist = (d[first]-d[last]).Length / 3.0;
bezCurve = new Point[4];
bezCurve[0] = d[first];
bezCurve[3] = d[last];
bezCurve[1] = (tHat1 * dist) + bezCurve[0];
bezCurve[2] = (tHat2 * dist) + bezCurve[3];
result.Add(bezCurve[1]);
result.Add(bezCurve[2]);
result.Add(bezCurve[3]);
return;
}
/* Parameterize points, and attempt to fit curve */
u = ChordLengthParameterize(d, first, last);
bezCurve = GenerateBezier(d, first, last, u, tHat1, tHat2);
/* Find max deviation of points to fitted curve */
maxError = ComputeMaxError(d, first, last, bezCurve, u,out splitPoint);
if(maxError < error)
{
result.Add(bezCurve[1]);
result.Add(bezCurve[2]);
result.Add(bezCurve[3]);
return;
}
/* If error not too large, try some reparameterization */
/* and iteration */
if(maxError < iterationError)
{
for(i = 0; i < maxIterations; i++)
{
uPrime = Reparameterize(d, first, last, u, bezCurve);
bezCurve = GenerateBezier(d, first, last, uPrime, tHat1, tHat2);
maxError = ComputeMaxError(d, first, last,
bezCurve, uPrime,out splitPoint);
if(maxError < error)
{
result.Add(bezCurve[1]);
result.Add(bezCurve[2]);
result.Add(bezCurve[3]);
return;
}
u = uPrime;
}
}
/* Fitting failed -- split at max error point and fit recursively */
tHatCenter = ComputeCenterTangent(d, splitPoint);
FitCubic(d, first, splitPoint, tHat1, tHatCenter, error,result);
tHatCenter.Negate();
FitCubic(d, splitPoint, last, tHatCenter, tHat2, error,result);
}
static Point[] GenerateBezier(Point[] d, int first, int last, double[] uPrime, Vector tHat1, Vector tHat2)
{
int i;
Vector[,] A = new Vector[MAXPOINTS,2];/* Precomputed rhs for eqn */
int nPts; /* Number of pts in sub-curve */
double[,] C = new double[2,2]; /* Matrix C */
double[] X = new double[2]; /* Matrix X */
double det_C0_C1, /* Determinants of matrices */
det_C0_X,
det_X_C1;
double alpha_l, /* Alpha values, left and right */
alpha_r;
Vector tmp; /* Utility variable */
Point[] bezCurve = new Point[4]; /* RETURN bezier curve ctl pts */
nPts = last - first + 1;
/* Compute the A's */
for (i = 0; i < nPts; i++) {
Vector v1, v2;
v1 = tHat1;
v2 = tHat2;
v1 *= B1(uPrime[i]);
v2 *= B2(uPrime[i]);
A[i,0] = v1;
A[i,1] = v2;
}
/* Create the C and X matrices */
C[0,0] = 0.0;
C[0,1] = 0.0;
C[1,0] = 0.0;
C[1,1] = 0.0;
X[0] = 0.0;
X[1] = 0.0;
for (i = 0; i < nPts; i++) {
C[0,0] += V2Dot(A[i,0], A[i,0]);
C[0,1] += V2Dot(A[i,0], A[i,1]);
/* C[1][0] += V2Dot(&A[i][0], &A[i][9]);*/
C[1,0] = C[0,1];
C[1,1] += V2Dot(A[i,1], A[i,1]);
tmp = ((Vector)d[first + i] -
(
((Vector)d[first] * B0(uPrime[i])) +
(
((Vector)d[first] * B1(uPrime[i])) +
(
((Vector)d[last] * B2(uPrime[i])) +
((Vector)d[last] * B3(uPrime[i]))))));
X[0] += V2Dot(A[i,0], tmp);
X[1] += V2Dot(A[i,1], tmp);
}
/* Compute the determinants of C and X */
det_C0_C1 = C[0,0] * C[1,1] - C[1,0] * C[0,1];
det_C0_X = C[0,0] * X[1] - C[1,0] * X[0];
det_X_C1 = X[0] * C[1,1] - X[1] * C[0,1];
/* Finally, derive alpha values */
alpha_l = (det_C0_C1 == 0) ? 0.0 : det_X_C1 / det_C0_C1;
alpha_r = (det_C0_C1 == 0) ? 0.0 : det_C0_X / det_C0_C1;
/* If alpha negative, use the Wu/Barsky heuristic (see text) */
/* (if alpha is 0, you get coincident control points that lead to
* divide by zero in any subsequent NewtonRaphsonRootFind() call. */
double segLength = (d[first] - d[last]).Length;
double epsilon = 1.0e-6 * segLength;
if (alpha_l < epsilon || alpha_r < epsilon)
{
/* fall back on standard (probably inaccurate) formula, and subdivide further if needed. */
double dist = segLength / 3.0;
bezCurve[0] = d[first];
bezCurve[3] = d[last];
bezCurve[1] = (tHat1 * dist) + bezCurve[0];
bezCurve[2] = (tHat2 * dist) + bezCurve[3];
return (bezCurve);
}
/* First and last control points of the Bezier curve are */
/* positioned exactly at the first and last data points */
/* Control points 1 and 2 are positioned an alpha distance out */
/* on the tangent vectors, left and right, respectively */
bezCurve[0] = d[first];
bezCurve[3] = d[last];
bezCurve[1] = (tHat1 * alpha_l) + bezCurve[0];
bezCurve[2] = (tHat2 * alpha_r) + bezCurve[3];
return (bezCurve);
}
/*
* Reparameterize:
* Given set of points and their parameterization, try to find
* a better parameterization.
*
*/
static double[] Reparameterize(Point[] d,int first,int last,double[] u,Point[] bezCurve)
{
int nPts = last-first+1;
int i;
double[] uPrime = new double[nPts]; /* New parameter values */
for (i = first; i <= last; i++) {
uPrime[i-first] = NewtonRaphsonRootFind(bezCurve, d[i], u[i-first]);
}
return uPrime;
}
/*
* NewtonRaphsonRootFind :
* Use Newton-Raphson iteration to find better root.
*/
static double NewtonRaphsonRootFind(Point[] Q,Point P,double u)
{
double numerator, denominator;
Point[] Q1 = new Point[3], Q2 = new Point[2]; /* Q' and Q'' */
Point Q_u, Q1_u, Q2_u; /*u evaluated at Q, Q', & Q'' */
double uPrime; /* Improved u */
int i;
/* Compute Q(u) */
Q_u = BezierII(3, Q, u);
/* Generate control vertices for Q' */
for (i = 0; i <= 2; i++) {
Q1[i].X = (Q[i+1].X - Q[i].X) * 3.0;
Q1[i].Y = (Q[i+1].Y - Q[i].Y) * 3.0;
}
/* Generate control vertices for Q'' */
for (i = 0; i <= 1; i++) {
Q2[i].X = (Q1[i+1].X - Q1[i].X) * 2.0;
Q2[i].Y = (Q1[i+1].Y - Q1[i].Y) * 2.0;
}
/* Compute Q'(u) and Q''(u) */
Q1_u = BezierII(2, Q1, u);
Q2_u = BezierII(1, Q2, u);
/* Compute f(u)/f'(u) */
numerator = (Q_u.X - P.X) * (Q1_u.X) + (Q_u.Y - P.Y) * (Q1_u.Y);
denominator = (Q1_u.X) * (Q1_u.X) + (Q1_u.Y) * (Q1_u.Y) +
(Q_u.X - P.X) * (Q2_u.X) + (Q_u.Y - P.Y) * (Q2_u.Y);
if (denominator == 0.0f) return u;
/* u = u - f(u)/f'(u) */
uPrime = u - (numerator/denominator);
return (uPrime);
}
/*
* Bezier :
* Evaluate a Bezier curve at a particular parameter value
*
*/
static Point BezierII(int degree,Point[] V,double t)
{
int i, j;
Point Q; /* Point on curve at parameter t */
Point[] Vtemp; /* Local copy of control points */
/* Copy array */
Vtemp = new Point[degree+1];
for (i = 0; i <= degree; i++) {
Vtemp[i] = V[i];
}
/* Triangle computation */
for (i = 1; i <= degree; i++) {
for (j = 0; j <= degree-i; j++) {
Vtemp[j].X = (1.0 - t) * Vtemp[j].X + t * Vtemp[j+1].X;
Vtemp[j].Y = (1.0 - t) * Vtemp[j].Y + t * Vtemp[j+1].Y;
}
}
Q = Vtemp[0];
return Q;
}
/*
* B0, B1, B2, B3 :
* Bezier multipliers
*/
static double B0(double u)
{
double tmp = 1.0 - u;
return (tmp * tmp * tmp);
}
static double B1(double u)
{
double tmp = 1.0 - u;
return (3 * u * (tmp * tmp));
}
static double B2(double u)
{
double tmp = 1.0 - u;
return (3 * u * u * tmp);
}
static double B3(double u)
{
return (u * u * u);
}
/*
* ComputeLeftTangent, ComputeRightTangent, ComputeCenterTangent :
*Approximate unit tangents at endpoints and "center" of digitized curve
*/
static Vector ComputeLeftTangent(Point[] d,int end)
{
Vector tHat1;
tHat1 = d[end+1]- d[end];
tHat1.Normalize();
return tHat1;
}
static Vector ComputeRightTangent(Point[] d,int end)
{
Vector tHat2;
tHat2 = d[end-1] - d[end];
tHat2.Normalize();
return tHat2;
}
static Vector ComputeCenterTangent(Point[] d,int center)
{
Vector V1, V2, tHatCenter = new Vector();
V1 = d[center-1] - d[center];
V2 = d[center] - d[center+1];
tHatCenter.X = (V1.X + V2.X)/2.0;
tHatCenter.Y = (V1.Y + V2.Y)/2.0;
tHatCenter.Normalize();
return tHatCenter;
}
/*
* ChordLengthParameterize :
* Assign parameter values to digitized points
* using relative distances between points.
*/
static double[] ChordLengthParameterize(Point[] d,int first,int last)
{
int i;
double[] u = new double[last-first+1]; /* Parameterization */
u[0] = 0.0;
for (i = first+1; i <= last; i++) {
u[i-first] = u[i-first-1] + (d[i-1] - d[i]).Length;
}
for (i = first + 1; i <= last; i++) {
u[i-first] = u[i-first] / u[last-first];
}
return u;
}
/*
* ComputeMaxError :
* Find the maximum squared distance of digitized points
* to fitted curve.
*/
static double ComputeMaxError(Point[] d,int first,int last,Point[] bezCurve,double[] u,out int splitPoint)
{
int i;
double maxDist; /* Maximum error */
double dist; /* Current error */
Point P; /* Point on curve */
Vector v; /* Vector from point to curve */
splitPoint = (last - first + 1)/2;
maxDist = 0.0;
for (i = first + 1; i < last; i++) {
P = BezierII(3, bezCurve, u[i-first]);
v = P - d[i];
dist = v.LengthSquared;
if (dist >= maxDist) {
maxDist = dist;
splitPoint = i;
}
}
return maxDist;
}
private static double V2Dot(Vector a,Vector b)
{
return((a.X*b.X)+(a.Y*b.Y));
}
}
Kris's answer is a very good port of the original to C#, but the performance isn't ideal and there are some places where floating point instability can cause some issues and return NaN values (this is true in the original code too). I created a library that contains my own port of it as well as Ramer-Douglas-Peuker, and should work not only with WPF points, but the new SIMD-enabled vector types and Unity 3D also:
https://github.com/burningmime/curves
Maybe this WPF+Bezier-based article is a good start: Draw a Smooth Curve through a Set of 2D Points with Bezier Primitives
Well, the job of Kris was very useful.
I realized that the problem he pointed out about the algorithm terminating earlier because of a miscalculated error ending on 0, is due to the fact that one point is repeated and the computed tangent is infinite.
I have done a translation to Java, based on the code of Kris, it works fine I believe:
EDIT:
I still working and trying to get a better behavior on the algorithm. I realized that on very spiky angles, the Bezier curves simply don't behave good. So I tried to combine Bezier curves with Lines and this is the result:
import java.awt.Point;
import java.awt.Shape;
import java.awt.geom.CubicCurve2D;
import java.awt.geom.Line2D;
import java.awt.geom.Point2D;
import java.util.LinkedList;
import java.util.List;
import java.util.concurrent.atomic.AtomicInteger;
import javax.vecmath.Point2d;
import javax.vecmath.Tuple2d;
import javax.vecmath.Vector2d;
/*
An Algorithm for Automatically Fitting Digitized Curves
by Philip J. Schneider
from "Graphics Gems", Academic Press, 1990
*/
public class FitCurves
{
/* Fit the Bezier curves */
private final static int MAXPOINTS = 10000;
private final static double epsilon = 1.0e-6;
/**
* Rubén:
* This is the sensitivity. When it is 1, it will create a line if it is at least as long as the
* distance from the previous control point.
* When it is greater, it will create less lines, and when it is lower, more lines.
* This is based on the previous control point since I believe it is a good indicator of the curvature
* where it is coming from, and we don't want long and second derived constant curves to be modeled with
* many lines.
*/
private static final double lineSensitivity=0.75;
public interface ResultCurve {
public Point2D getStart();
public Point2D getEnd();
public Shape getShape();
}
public static class BezierCurve implements ResultCurve {
public Point start;
public Point end;
public Point ctrl1;
public Point ctrl2;
public BezierCurve(Point2D start, Point2D ctrl1, Point2D ctrl2, Point2D end) {
this.start=new Point((int)Math.round(start.getX()), (int)Math.round(start.getY()));
this.end=new Point((int)Math.round(end.getX()), (int)Math.round(end.getY()));
this.ctrl1=new Point((int)Math.round(ctrl1.getX()), (int)Math.round(ctrl1.getY()));
this.ctrl2=new Point((int)Math.round(ctrl2.getX()), (int)Math.round(ctrl2.getY()));
if(this.ctrl1.x<=1 || this.ctrl1.y<=1) {
throw new IllegalStateException("ctrl1 invalid");
}
if(this.ctrl2.x<=1 || this.ctrl2.y<=1) {
throw new IllegalStateException("ctrl2 invalid");
}
}
public Shape getShape() {
return new CubicCurve2D.Float(start.x, start.y, ctrl1.x, ctrl1.y, ctrl2.x, ctrl2.y, end.x, end.y);
}
public Point getStart() {
return start;
}
public Point getEnd() {
return end;
}
}
public static class CurveSegment implements ResultCurve {
Point2D start;
Point2D end;
public CurveSegment(Point2D startP, Point2D endP) {
this.start=startP;
this.end=endP;
}
public Shape getShape() {
return new Line2D.Float(start, end);
}
public Point2D getStart() {
return start;
}
public Point2D getEnd() {
return end;
}
}
public static List<ResultCurve> FitCurve(double[][] points, double error) {
Point[] allPoints=new Point[points.length];
for(int i=0; i < points.length; i++) {
allPoints[i]=new Point((int) Math.round(points[i][0]), (int) Math.round(points[i][1]));
}
return FitCurve(allPoints, error);
}
public static List<ResultCurve> FitCurve(Point[] d, double error)
{
Vector2d tHat1, tHat2; /* Unit tangent vectors at endpoints */
int first=0;
int last=d.length-1;
tHat1 = ComputeLeftTangent(d, first);
tHat2 = ComputeRightTangent(d, last);
List<ResultCurve> result = new LinkedList<ResultCurve>();
FitCubic(d, first, last, tHat1, tHat2, error, result);
return result;
}
private static void FitCubic(Point[] d, int first, int last, Vector2d tHat1, Vector2d tHat2, double error, List<ResultCurve> result)
{
PointE[] bezCurve; /*Control points of fitted Bezier curve*/
double[] u; /* Parameter values for point */
double[] uPrime; /* Improved parameter values */
double maxError; /* Maximum fitting error */
int nPts; /* Number of points in subset */
double iterationError; /*Error below which you try iterating */
int maxIterations = 4; /* Max times to try iterating */
Vector2d tHatCenter; /* Unit tangent vector at splitPoint */
int i;
double errorOnLine=error;
iterationError = error * error;
nPts = last - first + 1;
AtomicInteger outputSplitPoint=new AtomicInteger();
/**
* Rubén: Here we try to fit the form with a line, and we mark the split point if we find any line with a minimum length
*/
/*
* the minimum distance for a length (so we don't create a very small line, when it could be slightly modeled with the previous Bezier,
* will be proportional to the distance of the previous control point of the last Bezier.
*/
BezierCurve res=null;
for(i=result.size()-1; i >0; i--) {
ResultCurve thisCurve=result.get(i);
if(thisCurve instanceof BezierCurve) {
res=(BezierCurve)thisCurve;
break;
}
}
Line seg=new Line(d[first], d[last]);
int nAcceptableTogether=0;
int startPoint=-1;
int splitPointTmp=-1;
if(Double.isInfinite(seg.getGradient())) {
for (i = first; i <= last; i++) {
double dist=Math.abs(d[i].x-d[first].x);
if(dist<errorOnLine) {
nAcceptableTogether++;
if(startPoint==-1) startPoint=i;
} else {
if(startPoint!=-1) {
double minLineLength=Double.POSITIVE_INFINITY;
if(res!=null) {
minLineLength=lineSensitivity * res.ctrl2.distance(d[startPoint]);
}
double thisFromStart=d[startPoint].distance(d[i]);
if(thisFromStart >= minLineLength) {
splitPointTmp=i;
startPoint=-1;
break;
}
}
nAcceptableTogether=0;
startPoint=-1;
}
}
} else {
//looking for the max squared error
for (i = first; i <= last; i++) {
Point thisPoint=d[i];
Point2D calculatedP=seg.getByX(thisPoint.getX());
double dist=thisPoint.distance(calculatedP);
if(dist<errorOnLine) {
nAcceptableTogether++;
if(startPoint==-1) startPoint=i;
} else {
if(startPoint!=-1) {
double thisFromStart=d[startPoint].distance(thisPoint);
double minLineLength=Double.POSITIVE_INFINITY;
if(res!=null) {
minLineLength=lineSensitivity * res.ctrl2.distance(d[startPoint]);
}
if(thisFromStart >= minLineLength) {
splitPointTmp=i;
startPoint=-1;
break;
}
}
nAcceptableTogether=0;
startPoint=-1;
}
}
}
if(startPoint!=-1) {
double minLineLength=Double.POSITIVE_INFINITY;
if(res!=null) {
minLineLength=lineSensitivity * res.ctrl2.distance(d[startPoint]);
}
if(d[startPoint].distance(d[last]) >= minLineLength) {
splitPointTmp=startPoint;
startPoint=-1;
} else {
nAcceptableTogether=0;
}
}
outputSplitPoint.set(splitPointTmp);
if(nAcceptableTogether==(last-first+1)) {
//This is a line!
System.out.println("line, length: " + d[first].distance(d[last]));
result.add(new CurveSegment(d[first], d[last]));
return;
}
/*********************** END of the Line approach, lets try the normal algorithm *******************************************/
if(splitPointTmp < 0) {
if(nPts == 2) {
double dist = d[first].distance(d[last]) / 3.0; //sqrt((last.x-first.x)^2 + (last.y-first.y)^2) / 3.0
bezCurve = new PointE[4];
bezCurve[0] = new PointE(d[first]);
bezCurve[3] = new PointE(d[last]);
bezCurve[1]=new PointE(tHat1).scaleAdd(dist, bezCurve[0]); //V2Add(&bezCurve[0], V2Scale(&tHat1, dist), &bezCurve[1]);
bezCurve[2]=new PointE(tHat2).scaleAdd(dist, bezCurve[3]); //V2Add(&bezCurve[3], V2Scale(&tHat2, dist), &bezCurve[2]);
result.add(new BezierCurve(bezCurve[0],bezCurve[1],bezCurve[2],bezCurve[3]));
return;
}
/* Parameterize points, and attempt to fit curve */
u = ChordLengthParameterize(d, first, last);
bezCurve = GenerateBezier(d, first, last, u, tHat1, tHat2);
/* Find max deviation of points to fitted curve */
maxError = ComputeMaxError(d, first, last, bezCurve, u, outputSplitPoint);
if(maxError < error) {
result.add(new BezierCurve(bezCurve[0],bezCurve[1],bezCurve[2],bezCurve[3]));
return;
}
/* If error not too large, try some reparameterization */
/* and iteration */
if(maxError < iterationError)
{
for(i = 0; i < maxIterations; i++) {
uPrime = Reparameterize(d, first, last, u, bezCurve);
bezCurve = GenerateBezier(d, first, last, uPrime, tHat1, tHat2);
maxError = ComputeMaxError(d, first, last, bezCurve, uPrime, outputSplitPoint);
if(maxError < error) {
result.add(new BezierCurve(bezCurve[0],bezCurve[1],bezCurve[2],bezCurve[3]));
return;
}
u = uPrime;
}
}
}
/* Fitting failed -- split at max error point and fit recursively */
tHatCenter = ComputeCenterTangent(d, outputSplitPoint.get());
FitCubic(d, first, outputSplitPoint.get(), tHat1, tHatCenter, error,result);
tHatCenter.negate();
FitCubic(d, outputSplitPoint.get(), last, tHatCenter, tHat2, error,result);
}
//Checked!!
static PointE[] GenerateBezier(Point2D[] d, int first, int last, double[] uPrime, Vector2d tHat1, Vector2d tHat2)
{
int i;
Vector2d[][] A = new Vector2d[MAXPOINTS][2]; /* Precomputed rhs for eqn */
int nPts; /* Number of pts in sub-curve */
double[][] C = new double[2][2]; /* Matrix C */
double[] X = new double[2]; /* Matrix X */
double det_C0_C1, /* Determinants of matrices */
det_C0_X,
det_X_C1;
double alpha_l, /* Alpha values, left and right */
alpha_r;
PointE[] bezCurve = new PointE[4]; /* RETURN bezier curve ctl pts */
nPts = last - first + 1;
/* Compute the A's */
for (i = 0; i < nPts; i++) {
Vector2d v1=new Vector2d(tHat1);
Vector2d v2=new Vector2d(tHat2);
v1.scale(B1(uPrime[i]));
v2.scale(B2(uPrime[i]));
A[i][0] = v1;
A[i][1] = v2;
}
/* Create the C and X matrices */
C[0][0] = 0.0;
C[0][1] = 0.0;
C[1][0] = 0.0;
C[1][1] = 0.0;
X[0] = 0.0;
X[1] = 0.0;
for (i = 0; i < nPts; i++) {
C[0][0] += A[i][0].dot(A[i][0]); //C[0][0] += V2Dot(&A[i][0], &A[i][0]);
C[0][1] += A[i][0].dot(A[i][1]); //C[0][1] += V2Dot(&A[i][0], &A[i][1]);
/* C[1][0] += V2Dot(&A[i][0], &A[i][9]);*/
C[1][0] = C[0][1]; //C[1][0] = C[0][1]
C[1][1] += A[i][1].dot(A[i][1]); //C[1][1] += V2Dot(&A[i][1], &A[i][1]);
Tuple2d scaleLastB2=new Vector2d(PointE.getPoint2d(d[last])); scaleLastB2.scale(B2(uPrime[i])); // V2ScaleIII(d[last], B2(uPrime[i]))
Tuple2d scaleLastB3=new Vector2d(PointE.getPoint2d(d[last])); scaleLastB3.scale(B3(uPrime[i])); // V2ScaleIII(d[last], B3(uPrime[i]))
Tuple2d dLastB2B3Sum=new Vector2d(scaleLastB2); dLastB2B3Sum.add(scaleLastB3); //V2AddII(V2ScaleIII(d[last], B2(uPrime[i])), V2ScaleIII(d[last], B3(uPrime[i]))
Tuple2d scaleFirstB1=new Vector2d(PointE.getPoint2d(d[first])); scaleFirstB1.scale(B1(uPrime[i])); //V2ScaleIII(d[first], B1(uPrime[i]))
Tuple2d sumScaledFirstB1andB2B3=new Vector2d(scaleFirstB1); sumScaledFirstB1andB2B3.add(dLastB2B3Sum); //V2AddII(V2ScaleIII(d[first], B1(uPrime[i])), V2AddII(V2ScaleIII(d[last], B2(uPrime[i])), V2ScaleIII(d[last], B3(uPrime[i])))
Tuple2d scaleFirstB0=new Vector2d(PointE.getPoint2d(d[first])); scaleFirstB0.scale(B0(uPrime[i])); //V2ScaleIII(d[first], B0(uPrime[i])
Tuple2d sumB0Rest=new Vector2d(scaleFirstB0); sumB0Rest.add(sumScaledFirstB1andB2B3); //V2AddII(V2ScaleIII(d[first], B0(uPrime[i])), V2AddII( V2ScaleIII(d[first], B1(uPrime[i])), V2AddII(V2ScaleIII(d[last], B2(uPrime[i])), V2ScaleIII(d[last], B3(uPrime[i]))))));
Vector2d tmp=new Vector2d(PointE.getPoint2d(d[first + i]));
tmp.sub(sumB0Rest);
X[0] += A[i][0].dot(tmp);
X[1] += A[i][1].dot(tmp);
}
/* Compute the determinants of C and X */
det_C0_C1 = C[0][0] * C[1][1] - C[1][0] * C[0][1];
det_C0_X = C[0][0] * X[1] - C[1][0] * X[0];
det_X_C1 = X[0] * C[1][1] - X[1] * C[0][1];
/* Finally, derive alpha values */
alpha_l = (det_C0_C1 == 0) ? 0.0 : det_X_C1 / det_C0_C1;
alpha_r = (det_C0_C1 == 0) ? 0.0 : det_C0_X / det_C0_C1;
/* If alpha negative, use the Wu/Barsky heuristic (see text) */
/* (if alpha is 0, you get coincident control points that lead to
* divide by zero in any subsequent NewtonRaphsonRootFind() call. */
double segLength = d[first].distance(d[last]); //(d[first] - d[last]).Length;
double epsilonRel = epsilon * segLength;
if (alpha_l < epsilonRel || alpha_r < epsilonRel) {
/* fall back on standard (probably inaccurate) formula, and subdivide further if needed. */
double dist = segLength / 3.0;
bezCurve[0] = new PointE(d[first]);
bezCurve[3] = new PointE(d[last]);
Vector2d b1Tmp=new Vector2d(tHat1); b1Tmp.scaleAdd(dist, bezCurve[0].getPoint2d());
bezCurve[1] = new PointE(b1Tmp); //(tHat1 * dist) + bezCurve[0];
Vector2d b2Tmp=new Vector2d(tHat2); b2Tmp.scaleAdd(dist, bezCurve[3].getPoint2d());
bezCurve[2] = new PointE(b2Tmp); //(tHat2 * dist) + bezCurve[3];
return (bezCurve);
}
/* First and last control points of the Bezier curve are */
/* positioned exactly at the first and last data points */
/* Control points 1 and 2 are positioned an alpha distance out */
/* on the tangent vectors, left and right, respectively */
bezCurve[0] = new PointE(d[first]);
bezCurve[3] = new PointE(d[last]);
Vector2d alphaLTmp=new Vector2d(tHat1); alphaLTmp.scaleAdd(alpha_l, bezCurve[0].getPoint2d());
bezCurve[1] = new PointE(alphaLTmp); //(tHat1 * alpha_l) + bezCurve[0]
Vector2d alphaRTmp=new Vector2d(tHat2); alphaRTmp.scaleAdd(alpha_r, bezCurve[3].getPoint2d());
bezCurve[2] = new PointE(alphaRTmp); //(tHat2 * alpha_r) + bezCurve[3];
return (bezCurve);
}
/*
* Reparameterize:
* Given set of points and their parameterization, try to find
* a better parameterization.
*
*/
static double[] Reparameterize(Point2D[] d,int first,int last,double[] u, Point2D[] bezCurve)
{
int nPts = last-first+1;
int i;
double[] uPrime = new double[nPts]; /* New parameter values */
for (i = first; i <= last; i++) {
uPrime[i-first] = NewtonRaphsonRootFind(bezCurve, d[i], u[i-first]);
}
return uPrime;
}
/*
* NewtonRaphsonRootFind :
* Use Newton-Raphson iteration to find better root.
*/
static double NewtonRaphsonRootFind(Point2D[] Q, Point2D P, double u)
{
double numerator, denominator;
Point2D[] Q1 = new Point2D[3]; //Q'
Point2D[] Q2 = new Point2D[2]; //Q''
Point2D Q_u, Q1_u, Q2_u; /*u evaluated at Q, Q', & Q'' */
double uPrime; /* Improved u */
int i;
/* Compute Q(u) */
Q_u = BezierII(3, Q, u);
/* Generate control vertices for Q' */
for (i = 0; i <= 2; i++) {
double qXTmp=(Q[i+1].getX() - Q[i].getX()) * 3.0; //Q1[i].x = (Q[i+1].x - Q[i].x) * 3.0;
double qYTmp=(Q[i+1].getY() - Q[i].getY()) * 3.0; //Q1[i].y = (Q[i+1].y - Q[i].y) * 3.0;
Q1[i]=new Point2D.Double(qXTmp, qYTmp);
}
/* Generate control vertices for Q'' */
for (i = 0; i <= 1; i++) {
double qXTmp=(Q1[i+1].getX() - Q1[i].getX()) * 2.0; //Q2[i].x = (Q1[i+1].x - Q1[i].x) * 2.0;
double qYTmp=(Q1[i+1].getY() - Q1[i].getY()) * 2.0; //Q2[i].y = (Q1[i+1].y - Q1[i].y) * 2.0;
Q2[i]=new Point2D.Double(qXTmp, qYTmp);
}
/* Compute Q'(u) and Q''(u) */
Q1_u = BezierII(2, Q1, u);
Q2_u = BezierII(1, Q2, u);
/* Compute f(u)/f'(u) */
numerator = (Q_u.getX() - P.getX()) * (Q1_u.getX()) + (Q_u.getY() - P.getY()) * (Q1_u.getY());
denominator = (Q1_u.getX()) * (Q1_u.getX()) + (Q1_u.getY()) * (Q1_u.getY()) + (Q_u.getX() - P.getX()) * (Q2_u.getX()) + (Q_u.getY() - P.getY()) * (Q2_u.getY());
if (denominator == 0.0f) return u;
/* u = u - f(u)/f'(u) */
uPrime = u - (numerator/denominator);
return (uPrime);
}
/*
* Bezier :
* Evaluate a Bezier curve at a particular parameter value
*
*/
static Point2D BezierII(int degree, Point2D[] V, double t)
{
int i, j;
Point2D Q; /* Point on curve at parameter t */
Point2D[] Vtemp; /* Local copy of control points */
/* Copy array */
Vtemp = new Point2D[degree+1];
for (i = 0; i <= degree; i++) {
Vtemp[i] = new Point2D.Double(V[i].getX(), V[i].getY());
}
/* Triangle computation */
for (i = 1; i <= degree; i++) {
for (j = 0; j <= degree-i; j++) {
double tmpX, tmpY;
tmpX = (1.0 - t) * Vtemp[j].getX() + t * Vtemp[j+1].getX();
tmpY = (1.0 - t) * Vtemp[j].getY() + t * Vtemp[j+1].getY();
Vtemp[j].setLocation(tmpX, tmpY);
}
}
Q = Vtemp[0];
return Q;
}
/*
* B0, B1, B2, B3 :
* Bezier multipliers
*/
static double B0(double u)
{
double tmp = 1.0 - u;
return (tmp * tmp * tmp);
}
static double B1(double u)
{
double tmp = 1.0 - u;
return (3 * u * (tmp * tmp));
}
static double B2(double u)
{
double tmp = 1.0 - u;
return (3 * u * u * tmp);
}
static double B3(double u)
{
return (u * u * u);
}
/*
* ComputeLeftTangent, ComputeRightTangent, ComputeCenterTangent :
*Approximate unit tangents at endpoints and "center" of digitized curve
*/
static Vector2d ComputeLeftTangent(Point[] d, int end)
{
Vector2d tHat1=new Vector2d(PointE.getPoint2d(d[end+1]));
tHat1.sub(PointE.getPoint2d(d[end]));
tHat1.normalize();
return tHat1;
}
static Vector2d ComputeRightTangent(Point[] d, int end)
{
//tHat2 = V2SubII(d[end-1], d[end]); tHat2 = *V2Normalize(&tHat2);
Vector2d tHat2=new Vector2d(PointE.getPoint2d(d[end-1]));
tHat2.sub(PointE.getPoint2d(d[end]));
tHat2.normalize();
return tHat2;
}
static Vector2d ComputeCenterTangent(Point[] d ,int center)
{
//V1 = V2SubII(d[center-1], d[center]);
Vector2d V1=new Vector2d(PointE.getPoint2d(d[center-1]));
V1.sub(new PointE(d[center]).getPoint2d());
//V2 = V2SubII(d[center], d[center+1]);
Vector2d V2=new Vector2d(PointE.getPoint2d(d[center]));
V2.sub(PointE.getPoint2d(d[center+1]));
//tHatCenter.x = (V1.x + V2.x)/2.0;
//tHatCenter.y = (V1.y + V2.y)/2.0;
//tHatCenter = *V2Normalize(&tHatCenter);
Vector2d tHatCenter=new Vector2d((V1.x + V2.x)/2.0, (V1.y + V2.y)/2.0);
tHatCenter.normalize();
return tHatCenter;
}
/*
* ChordLengthParameterize :
* Assign parameter values to digitized points
* using relative distances between points.
*/
static double[] ChordLengthParameterize(Point[] d,int first,int last)
{
int i;
double[] u = new double[last-first+1]; /* Parameterization */
u[0] = 0.0;
for (i = first+1; i <= last; i++) {
u[i-first] = u[i-first-1] + d[i-1].distance(d[i]);
}
for (i = first + 1; i <= last; i++) {
u[i-first] = u[i-first] / u[last-first];
}
return u;
}
/*
* ComputeMaxError :
* Find the maximum squared distance of digitized points
* to fitted curve.
*/
static double ComputeMaxError(Point2D[] d, int first, int last, Point2D[] bezCurve, double[] u, AtomicInteger splitPoint)
{
int i;
double maxDist; /* Maximum error */
double dist; /* Current error */
Point2D P; /* Point on curve */
Vector2d v; /* Vector from point to curve */
int tmpSplitPoint=(last - first + 1)/2;
maxDist = 0.0;
for (i = first + 1; i < last; i++) {
P = BezierII(3, bezCurve, u[i-first]);
v = new Vector2d(P.getX() - d[i].getX(), P.getY() - d[i].getY()); //P - d[i];
dist = v.lengthSquared();
if (dist >= maxDist) {
maxDist = dist;
tmpSplitPoint=i;
}
}
splitPoint.set(tmpSplitPoint);
return maxDist;
}
/**
* This is kind of a bridge between javax.vecmath and java.util.Point2D
* #author Ruben
* #since 1.24
*/
public static class PointE extends Point2D.Double {
private static final long serialVersionUID = -1482403817370130793L;
public PointE(Tuple2d tup) {
super(tup.x, tup.y);
}
public PointE(Point2D p) {
super(p.getX(), p.getY());
}
public PointE(double x, double y) {
super(x, y);
}
public PointE scale(double dist) {
return new PointE(getX()*dist, getY()*dist);
}
public PointE scaleAdd(double dist, Point2D sum) {
return new PointE(getX()*dist + sum.getX(), getY()*dist + sum.getY());
}
public PointE substract(Point2D p) {
return new PointE(getX() - p.getX(), getY() - p.getY());
}
public Point2d getPoint2d() {
return getPoint2d(this);
}
public static Point2d getPoint2d(Point2D p) {
return new Point2d(p.getX(), p.getY());
}
}
Here an image of the latter working, white are lines, and red are Bezier:
Using this approach we use less control points and more accurate.
The sensitivity for the lines creation can be adjusted through the lineSensitivity attribute. If you don't want lines to be used at all just set it to infinite.
I'm sure this can be improved. Feel free to contribute :)
The algorithm is not doing any reduction, and because of the first explained in my post we have to run one. Here is a DouglasPeuckerReduction implementation, which for me works in some cases even more efficiently (less points to store and faster to render) than an additional FitCurves
import java.awt.Point;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.LinkedList;
import java.util.List;
public class DouglasPeuckerReduction {
public static List<Point> reduce(Point[] points, double tolerance)
{
if (points == null || points.length < 3) return Arrays.asList(points);
int firstPoint = 0;
int lastPoint = points.length - 1;
SortedList<Integer> pointIndexsToKeep;
try {
pointIndexsToKeep = new SortedList<Integer>(LinkedList.class);
} catch (Throwable t) {
t.printStackTrace(System.out);
ErrorReport.process(t);
return null;
}
//Add the first and last index to the keepers
pointIndexsToKeep.add(firstPoint);
pointIndexsToKeep.add(lastPoint);
//The first and the last point cannot be the same
while (points[firstPoint].equals(points[lastPoint])) {
lastPoint--;
}
reduce(points, firstPoint, lastPoint, tolerance, pointIndexsToKeep);
List<Point> returnPoints = new ArrayList<Point>(pointIndexsToKeep.size());
for (int pIndex : pointIndexsToKeep) {
returnPoints.add(points[pIndex]);
}
return returnPoints;
}
private static void reduce(Point[] points, int firstPoint, int lastPoint, double tolerance, List<Integer> pointIndexsToKeep) {
double maxDistance = 0;
int indexFarthest = 0;
Line tmpLine=new Line(points[firstPoint], points[lastPoint]);
for (int index = firstPoint; index < lastPoint; index++) {
double distance = tmpLine.getDistanceFrom(points[index]);
if (distance > maxDistance) {
maxDistance = distance;
indexFarthest = index;
}
}
if (maxDistance > tolerance && indexFarthest != 0) {
//Add the largest point that exceeds the tolerance
pointIndexsToKeep.add(indexFarthest);
reduce(points, firstPoint, indexFarthest, tolerance, pointIndexsToKeep);
reduce(points, indexFarthest, lastPoint, tolerance, pointIndexsToKeep);
}
}
}
I am using here my own implementation of a SortedList, and of a Line. You will have to make it yourself, sorry.
I haven't tested it, but one approach that comes to mind would be sampling values in some interval and creating a spline to connect the dots.
For example, say the x value of your curve starts at 0 and ends at 10. So you sample the y values at x=1,2,3,4,5,6,7,8,9,10 and create a spline from the points (0, y(0)), (1,y(1)), ... (10, y(10))
It would probably have problems such as accidental spikes drawn by the user, but it may be worth a shot
For Silverlight users of Kris' answer, Point is hobbled and Vector doesn't exist. This is a minimal Vector class that supports the code:
public class Vector
{
public double X { get; set; }
public double Y { get; set; }
public Vector(double x=0, double y=0)
{
X = x;
Y = y;
}
public static implicit operator Vector(Point b)
{
return new Vector(b.X, b.Y);
}
public static Point operator *(Vector left, double right)
{
return new Point(left.X * right, left.Y * right);
}
public static Vector operator -(Vector left, Point right)
{
return new Vector(left.X - right.X, left.Y - right.Y);
}
internal void Negate()
{
X = -X;
Y = -Y;
}
internal void Normalize()
{
double factor = 1.0 / Math.Sqrt(LengthSquared);
X *= factor;
Y *= factor;
}
public double LengthSquared { get { return X * X + Y * Y; } }
}
Also had to address use of Length and +,- operators. I chose to just add functions to the FitCurves class, and rewrite their usages where the compiler complained.
public static double Length(Point a, Point b)
{
double x = a.X-b.X;
double y = a.Y-b.Y;
return Math.Sqrt(x*x+y*y);
}
public static Point Add(Point a, Point b)
{
return new Point(a.X + b.X, a.Y + b.Y);
}
public static Point Subtract(Point a, Point b)
{
return new Point(a.X - b.X, a.Y - b.Y);
}
I'm trying to determine if a point is inside a polygon. the Polygon is defined by an array of Point objects. I can easily figure out if the point is inside the bounded box of the polygon, but I'm not sure how to tell if it's inside the actual polygon or not. If possible, I'd like to only use C# and WinForms. I'd rather not call on OpenGL or something to do this simple task.
Here's the code I have so far:
private void CalculateOuterBounds()
{
//m_aptVertices is a Point[] which holds the vertices of the polygon.
// and X/Y min/max are just ints
Xmin = Xmax = m_aptVertices[0].X;
Ymin = Ymax = m_aptVertices[0].Y;
foreach(Point pt in m_aptVertices)
{
if(Xmin > pt.X)
Xmin = pt.X;
if(Xmax < pt.X)
Xmax = pt.X;
if(Ymin > pt.Y)
Ymin = pt.Y;
if(Ymax < pt.Y)
Ymax = pt.Y;
}
}
public bool Contains(Point pt)
{
bool bContains = true; //obviously wrong at the moment :)
if(pt.X < Xmin || pt.X > Xmax || pt.Y < Ymin || pt.Y > Ymax)
bContains = false;
else
{
//figure out if the point is in the polygon
}
return bContains;
}
I've checked codes here and all have problems.
The best method is:
/// <summary>
/// Determines if the given point is inside the polygon
/// </summary>
/// <param name="polygon">the vertices of polygon</param>
/// <param name="testPoint">the given point</param>
/// <returns>true if the point is inside the polygon; otherwise, false</returns>
public static bool IsPointInPolygon4(PointF[] polygon, PointF testPoint)
{
bool result = false;
int j = polygon.Count() - 1;
for (int i = 0; i < polygon.Count(); i++)
{
if (polygon[i].Y < testPoint.Y && polygon[j].Y >= testPoint.Y || polygon[j].Y < testPoint.Y && polygon[i].Y >= testPoint.Y)
{
if (polygon[i].X + (testPoint.Y - polygon[i].Y) / (polygon[j].Y - polygon[i].Y) * (polygon[j].X - polygon[i].X) < testPoint.X)
{
result = !result;
}
}
j = i;
}
return result;
}
The accepted answer did not work for me in my project. I ended up using the code found here.
public static bool IsInPolygon(Point[] poly, Point p)
{
Point p1, p2;
bool inside = false;
if (poly.Length < 3)
{
return inside;
}
var oldPoint = new Point(
poly[poly.Length - 1].X, poly[poly.Length - 1].Y);
for (int i = 0; i < poly.Length; i++)
{
var newPoint = new Point(poly[i].X, poly[i].Y);
if (newPoint.X > oldPoint.X)
{
p1 = oldPoint;
p2 = newPoint;
}
else
{
p1 = newPoint;
p2 = oldPoint;
}
if ((newPoint.X < p.X) == (p.X <= oldPoint.X)
&& (p.Y - (long) p1.Y)*(p2.X - p1.X)
< (p2.Y - (long) p1.Y)*(p.X - p1.X))
{
inside = !inside;
}
oldPoint = newPoint;
}
return inside;
}
See this it's in c++ and can be done in c# in a same way.
for convex polygon is too easy:
If the polygon is convex then one can
consider the polygon as a "path" from
the first vertex. A point is on the
interior of this polygons if it is
always on the same side of all the
line segments making up the path.
Given a line segment between P0
(x0,y0) and P1 (x1,y1), another point
P (x,y) has the following relationship
to the line segment. Compute (y - y0)
(x1 - x0) - (x - x0) (y1 - y0)
if it is less than 0 then P is to the
right of the line segment, if greater
than 0 it is to the left, if equal to
0 then it lies on the line segment.
Here is its code in c#, I didn't check edge cases.
public static bool IsInPolygon(Point[] poly, Point point)
{
var coef = poly.Skip(1).Select((p, i) =>
(point.Y - poly[i].Y)*(p.X - poly[i].X)
- (point.X - poly[i].X) * (p.Y - poly[i].Y))
.ToList();
if (coef.Any(p => p == 0))
return true;
for (int i = 1; i < coef.Count(); i++)
{
if (coef[i] * coef[i - 1] < 0)
return false;
}
return true;
}
I test it with simple rectangle works fine:
Point[] pts = new Point[] { new Point { X = 1, Y = 1 },
new Point { X = 1, Y = 3 },
new Point { X = 3, Y = 3 },
new Point { X = 3, Y = 1 } };
IsInPolygon(pts, new Point { X = 2, Y = 2 }); ==> true
IsInPolygon(pts, new Point { X = 1, Y = 2 }); ==> true
IsInPolygon(pts, new Point { X = 0, Y = 2 }); ==> false
Explanation on the linq query:
poly.Skip(1) ==> creates a new list started from position 1 of the poly list and then by
(point.Y - poly[i].Y)*(p.X - poly[i].X) - (point.X - poly[i].X) * (p.Y - poly[i].Y) we'll going to calculate the direction (which mentioned in referenced paragraph).
similar example (with another operation):
lst = 2,4,8,12,7,19
lst.Skip(1) ==> 4,8,12,7,19
lst.Skip(1).Select((p,i)=>p-lst[i]) ==> 2,4,4,-5,12
meowNET anwser does not include Polygon vertices in the polygon and points exactly on horizontal edges. If you need an exact "inclusive" algorithm:
public static bool IsInPolygon(this Point point, IEnumerable<Point> polygon)
{
bool result = false;
var a = polygon.Last();
foreach (var b in polygon)
{
if ((b.X == point.X) && (b.Y == point.Y))
return true;
if ((b.Y == a.Y) && (point.Y == a.Y))
{
if ((a.X <= point.X) && (point.X <= b.X))
return true;
if ((b.X <= point.X) && (point.X <= a.X))
return true;
}
if ((b.Y < point.Y) && (a.Y >= point.Y) || (a.Y < point.Y) && (b.Y >= point.Y))
{
if (b.X + (point.Y - b.Y) / (a.Y - b.Y) * (a.X - b.X) <= point.X)
result = !result;
}
a = b;
}
return result;
}
You can use the ray casting algorithm. It is well-described in the wikipedia page for the Point in polygon problem.
It's as simple as counting the number of times a ray from outside to that point touches the polygon boundaries. If it touches an even number of times, the point is outside the polygon. If it touches an odd number of times, the point is inside.
To count the number of times the ray touches, you check intersections between the ray and all of the polygon sides.
My answer is taken from here:Link
I took the C code and converted it to C# and made it work
static bool pnpoly(PointD[] poly, PointD pnt )
{
int i, j;
int nvert = poly.Length;
bool c = false;
for (i = 0, j = nvert - 1; i < nvert; j = i++)
{
if (((poly[i].Y > pnt.Y) != (poly[j].Y > pnt.Y)) &&
(pnt.X < (poly[j].X - poly[i].X) * (pnt.Y - poly[i].Y) / (poly[j].Y - poly[i].Y) + poly[i].X))
c = !c;
}
return c;
}
You can test it with this example:
PointD[] pts = new PointD[] { new PointD { X = 1, Y = 1 },
new PointD { X = 1, Y = 2 },
new PointD { X = 2, Y = 2 },
new PointD { X = 2, Y = 3 },
new PointD { X = 3, Y = 3 },
new PointD { X = 3, Y = 1 }};
List<bool> lst = new List<bool>();
lst.Add(pnpoly(pts, new PointD { X = 2, Y = 2 }));
lst.Add(pnpoly(pts, new PointD { X = 2, Y = 1.9 }));
lst.Add(pnpoly(pts, new PointD { X = 2.5, Y = 2.5 }));
lst.Add(pnpoly(pts, new PointD { X = 1.5, Y = 2.5 }));
lst.Add(pnpoly(pts, new PointD { X = 5, Y = 5 }));
My business critical implementation of PointInPolygon function working on integers (as OP seems to be using) is unit tested for horizontal, vertical and diagonal lines, points on the line are included in the test (function returns true).
This seems to be an old question but all previous examples of tracing have some flaws: do not consider horizontal or vertical polygon lines, polygon boundary line or the order of edges (clockwise, counterclockwise).
The following function passes the tests I came up with (square, rhombus, diagonal cross, total 124 tests) with points on edges, vertices and just inside and outside edge and vertex.
The code does the following for every consecutive pair of polygon coordinates:
Checks if polygon vertex equals the point
Checks if the point is on a horizontal or vertical line
Calculates (as double) and collects intersects with conversion to integer
Sorts intersects so the order of edges is not affecting the algorithm
Checks if the point is on the even intersect (equals - in polygon)
Checks if the number of intersects before point x coordinate is odd - in polygon
Algorithm can be easily adapted for floats and doubles if necessary.
As a side note - I wonder how much software was created in the past nearly 10 years which check for a point in polygon and fail in some cases.
public static bool IsPointInPolygon(Point point, IList<Point> polygon)
{
var intersects = new List<int>();
var a = polygon.Last();
foreach (var b in polygon)
{
if (b.X == point.X && b.Y == point.Y)
{
return true;
}
if (b.X == a.X && point.X == a.X && point.X >= Math.Min(a.Y, b.Y) && point.Y <= Math.Max(a.Y, b.Y))
{
return true;
}
if (b.Y == a.Y && point.Y == a.Y && point.X >= Math.Min(a.X, b.X) && point.X <= Math.Max(a.X, b.X))
{
return true;
}
if ((b.Y < point.Y && a.Y >= point.Y) || (a.Y < point.Y && b.Y >= point.Y))
{
var px = (int)(b.X + 1.0 * (point.Y - b.Y) / (a.Y - b.Y) * (a.X - b.X));
intersects.Add(px);
}
a = b;
}
intersects.Sort();
return intersects.IndexOf(point.X) % 2 == 0 || intersects.Count(x => x < point.X) % 2 == 1;
}
Complete algorithm along with C code is available at http://alienryderflex.com/polygon/
Converting it to c# / winforms would be trivial.
For those using NET Core, Region.IsVisible is available from NET Core 3.0. After adding package System.Drawing.Common,
using System;
using System.Drawing;
using System.Drawing.Drawing2D;
namespace Example
{
class Program
{
static bool IsPointInsidePolygon(Point[] polygon, Point point)
{
var path = new GraphicsPath();
path.AddPolygon(polygon);
var region = new Region(path);
return region.IsVisible(point);
}
static void Main(string[] args)
{
Point vt1 = new Point(0, 0);
Point vt2 = new Point(100, 0);
Point vt3 = new Point(100, 100);
Point vt4 = new Point(0, 100);
Point[] polygon = { vt1, vt2, vt3, vt4 };
Point pt = new Point(50, 50);
bool isPointInsidePolygon = IsPointInsidePolygon(polygon, pt);
Console.WriteLine(isPointInsidePolygon);
}
}
}
Of lesser importance is that, adding System.Drawing.Common package increased size of publish folder by 400 KB. Maybe compared to custom code, this implementation could also be slower (above function timed to be 18 ms on i7-8665u). But still, I prefer this, for one less thing to worry about.
All you really need are 4 lines to implement the winding number method. But first, reference the System.Numerics to use complex library. The code below assumes that you have translate a loop of points (stored in cpyArr) so that your candidate point stands at 0,0.
For each point pair, create a complex number c1 using the first point and c2 using the 2nd point ( the first 2 lines within the loop)
Now here is some complex number theory. Think of c1 and c2 as complex number representation of vectors. To get from vector c1 to vector c2, you can multiply c1 by a complex number Z (c1Z=c2). Z rotates c1 so that it points at c2. Then it also stretches or squishes c1 so that it matces c2. To get such a magical number Z, you divide c2 by c1 (since c1Z=c2, Z=c2/c1). You can look up your high school notes on dividing complex number or use that method provided by Microsoft. After you get that number, all we really care is the phase angle.
To use the winding method, we add up all the phases and we should +/- 2 pi if the point is within the area. Otherwise, the sum should be 0
I added edge cases, 'literally'. If your phase angle is +/- pi, you're right on the edge between the points pair. In that case, I'd say the point is a part of the area and break out of the loop
/// <param name="cpyArr">An array of 2 coordinates (points)</param>
public static bool IsOriginInPolygon(double[,] cpyArr)
{
var sum = 0.0;
var tolerance = 1e-4;
var length = cpyArr.GetLength(0);
for (var i = 0; i < length-1; i++)
{
//convert vertex point pairs to complex numbers for simplified coding
var c2 = new Complex(cpyArr[i+1, 0], cpyArr[i+1, 1]);
var c1 = new Complex(cpyArr[i, 0], cpyArr[i, 1]);
//find the rotation angle from c1 to c2 when viewed from the origin
var phaseDiff = Complex.Divide(c2, c1).Phase;
//add the rotation angle to the sum
sum += phaseDiff;
//immediately exit the loop if the origin is on the edge of polygon or it is one of the vertices of the polygon
if (Math.Abs(Math.Abs(phaseDiff) - Math.PI) < tolerance || c1.Magnitude < tolerance || c2.Magnitude < tolerance)
{
sum = Math.PI * 2;
break;
}
}
return Math.Abs((Math.PI*2 ) - Math.Abs(sum)) < tolerance;
}
I recommend this wonderful 15-page paper by Kai Hormann (University of Erlangen) and Alexander Agathos (University of Athens). It consolidates all the best algorithms and will allow you to detect both winding and ray-casting solutions.
The Point in Polygon Problem for Arbitrary Polygons
The algorithm is interesting to implement, and well worth it. However, it is so complex that it is pointless for me to any portion of it directly. I'll instead stick with saying that if you want THE most efficient and versatile algorithm, I am certain this is it.
The algorithm gets complex because is is very highly optimized, so it will require a lot of reading to understand and implement. However, it combines the benefits of both the ray-cast and winding number algorithms and the result is a single number that provides both answers at once. If the result is greater than zero and odd, then the point is completely contained, but if the result is an even number, then the point is contained in a section of the polygon that folds back on itself.
Good luck.
This is an old question, but I optimized Saeed answer:
public static bool IsInPolygon(this List<Point> poly, Point point)
{
var coef = poly.Skip(1).Select((p, i) =>
(point.y - poly[i].y) * (p.x - poly[i].x)
- (point.x - poly[i].x) * (p.y - poly[i].y));
var coefNum = coef.GetEnumerator();
if (coef.Any(p => p == 0))
return true;
int lastCoef = coefNum.Current,
count = coef.Count();
coefNum.MoveNext();
do
{
if (coefNum.Current - lastCoef < 0)
return false;
lastCoef = coefNum.Current;
}
while (coefNum.MoveNext());
return true;
}
Using IEnumerators and IEnumerables.
If you are drawing Shapes on a Canvas this is a quick and easy Solution.
private void Canvas_MouseMove(object sender, MouseEventArgs e)
{
if (e.OriginalSource is Polygon)
{
//do something
}
}
"Polygon" can be any shape from System.Windows.Shapes.
Here's some modern C# code:
public record Point(double X, double Y);
public record Box(Point LowerLeft, Point UpperRight)
{
public Box(Point[] points)
: this(
new Point(
points.Select(x => x.X).Min(),
points.Select(x => x.Y).Min()),
new Point(
points.Select(x => x.X).Max(),
points.Select(x => x.Y).Max()))
{
}
public bool ContainsPoint(Point point)
{
return point.X >= LowerLeft.X
&& point.X <= UpperRight.X
&& point.Y >= LowerLeft.Y
&& point.Y <= UpperRight.Y;
}
}
public record Polygon(Point[] Points, Box Box)
{
public Polygon(Point[] points)
: this(points, new(points))
{
}
public bool ContainsPoint(Point point)
{
do
{
if (Box.ContainsPoint(point) == false)
{
break;
}
bool result = false;
int j = Points.Length - 1;
for (int i = 0; i < Points.Length; i++)
{
if ((Points[i].Y < point.Y && Points[j].Y >= point.Y)
|| (Points[j].Y < point.Y && Points[i].Y >= point.Y))
{
if (Points[i].X +
((point.Y - Points[i].Y) / (Points[j].Y - Points[i].Y) * (Points[j].X - Points[i].X))
< point.X)
{
result = !result;
}
}
j = i;
}
return result;
}
while (false);
return false;
}
}