Using SharpMap (Windows Forms) how can I display an overlay image over the map tile background so that the image scales and moves accordingly with the map zoom and pan? I want to implement a georeferencing like functionality.
I tried using SharpMap.Layers.GdiImageLayer but I didn't find a way to position it to a custom position (real world coordinate) - it is getting placed by default at origin [0,0] (the background tile coordinates). Is there a way to define a relation (transformation) to place it in a particular position?
I managed to get closer to a solution using VectorLayer with RasterPointSymbolizer but the symbol (image loaded for symbol) would need to be transformed on map scaling/zoom (so that corners remain in the same real world coordinates) - the math calculation behind looks a little complicated for a solution that seems more like a workaround than a natural one. As a note - I don't need precise calculation using projection/real geoid as I am doing this only at building level.
Using GDAL - GeoTIFF might be a choice here by generating a GeoTIFF based on the original image and making the georeferencing metadata dynamic based on UI controls? The original image is in raster format (JPG) with no geographic metadata.
Is there a better solution?
If VectorLayer - RasterPointSymbolizer is the best choice, do you have an example for symbol(image) synchronization with the map view?
As far as i can tell the GdiImageLayer calculates the position based on a world-file (GdiImageLayer.SetEnvelope()). Here is the link to the method. This meta file has to have the same name in the same location but the filetype must be of type *.wld. There you set the position (top left corner) and the skew in x and y axis. So rotation will be perserved. I never tried this but i would suggest correct zooming would work
(The wiki article offers also some good understanding for world files)
There might be another way if no world file is present and the information rests in the header. There is a GDalSample loading a GeoTiff Image onto an existing map. The example can be found in the WinFormSamples and the Different kind of layers supported by [MapBox] Example. The map is showing the overlay only while magnifying and not fully function but maybe a good hint
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I am trying to create a WPF application using C# to run on Pixelsense that is basic version of the tangram puzzle. I am able to draw my 7 shapes and translate and rotate them all around the screen.
Could anyone give me advise regarding how I should go about saving the pattern (with shapes in specific positions and orientations) so that when a user creates the pattern next time, the application can match it to the saved one and tell the user if it's correct.
It's a pattern matching and recognition problem that I am trying to solve.
I have been stuck on this for a while now :(
Define the solution as a collection of objects with shapeType, position, and orientation properties. Have the solution include one shape at position 0, 0 and an orientation of 0. Now loop over all the shapes the user has actually placed to find the ones with a shapeType that matches the shape your solution has at 0,0,0. Calculate the position and orientation of every other shape relative to where the user put this one. Compare those values to the rest of your solution. You'll need to experiment with how much tolerance to allow because this stuff is not precise - to make the game fun, err on the side of having high tolerances. If needed, you can follow this up with some performance optimizations to only re-evaluate pieces that moved.
Hopefully you are using physical shape prices with tags on them instead of this purely a virtual game. I always wanted to build this when I was on the Surface team but it never happened. One challenge you will run into is defining how the tag's position/orientation relates to the actual shape. If you'll be putting tag stickers on multiple tangram sets, you almost certainly won't get the on precisely the same each time so you may need to add a "calibration" mode to your app (have the user place each piece in a specific spot and then push a button so you can record where the tag is relative to those spots). The TagVisualizer WPF control should help a lot for building your UI - definitely look into using it (this scenario was top of mind when we designed that API). The default behavior of that control (if you tell it the ID of a tag to look for but not how to visualize it) is a "crosshair" that can help you find tune your offset values.
Good luck! If you wouldn't mind recording a YouTube video when you are done and posting a comment here linking to it, I'd really appreciate that
You can use ObservableCollection or List of a custom class. That class can consist of various values such as position, orientation etc as properties.
When a new pattern is drawn or when the pattern change its position you can update that particular object stored in the collection. As you have all the details of the pattern(positions and orientation) you can iterate the for loop and check the position of the new pattern when added.
I have an image that is a depth heatmap that I've filtered out anything further away than the first 25% of the image.
It looks something like this:
There are two blobs of color in the image, one is my hand (with part of my face behind it), and the other is the desk in the lower left corner. How can I search the image to find these blobs? I would like to be able to draw a rectangle around them if possible.
I can also do this (ignore shades, and filter to black or white):
Pick a random pixel as a seed pixel. This becomes area A. Repeatedly expand A until A doesn't get any bigger. That's your area.
The way to expand A is by looking for neighbor pixels to A, such that they have similar color to at least one neighboring pixel in A.
What "similar color" means to you is somewhat variable. If you can make exactly two colors, as you say in another answer, then "similar" is "equal". Otherwise, "similar" would mean colors that have RGB values or whatnot where each component of the two colors is within a small amount of each other (i.e. 255, 128, 128 is similar to 252, 125, 130).
You can also limit the selected pixels so they must be similar to the seed pixel, but that works better when a human is picking the seed. (I believe this is what is done in Photoshop, for example.)
This can be better than edge detection because you can deal with gradients without filtering them out of existence, and you don't need to process the resulting detected edges into a coherent area. It has the disadvantage that a gradient can go all the way from black to white and it'll register as the same area, but that may be what you want. Also, you have to be careful with the implementation or else it will be too slow.
It might be overkill for what you need, but there's a great wrapper for C# for the OpenCV libraries.
I have successfully used OpenCV in C++ for blob detection, so you might find it useful for what you're trying to do.
http://www.emgu.com/wiki/index.php/Main_Page
and the wiki page on OpenCV:
http://en.wikipedia.org/wiki/OpenCV
Edited to add: Here is a blobs detection library for Emgu in C#. There is even some nice features of ordering the blobs by descending area (useful for filtering out noise).
http://www.emgu.com/forum/viewtopic.php?f=3&t=205
Edit Again:
If Emgu is too heavyweight, Aforge.NET also includes some blob detection methods
http://www.aforgenet.com/framework/
If the image really is only two or more distinct colours (very little blur between colours), it is an easy case for an edge detection algorithm.
You can use something like the code sample from this question : find a color in an image in c#
It will help you find the x/y of specific colors in your image. Then you could use the min x/max x and the min y/max y to draw your rectangles.
Detect object from image based on object color by C#.
To detect a object based on its color, there is an easy algorithm for that. you have to choose a filtering method. Steps normally are:
Take the image
Apply ur filtering
Apply greyscalling
Subtract background and get your objects
Find position of all objects
Mark the objects
First you have to choose a filtering method, there are many filtering method provided for C#. Mainly I prefer AForge filters, for this purpose they have few filter:
ColorFiltering
ChannelFiltering
HSLFiltering
YCbCrFiltering
EuclideanColorFiltering
My favorite is EuclideanColorFiltering. It is easy and simple. For information about other filters you can visit link below. You have to download AForge dll for apply these in your code.
More information about the exact steps can be found here: Link
We're currently creating a simple application for image manipulation in Silverlight, and we've hit a bit of a snag. We want users to be able to select an area of an image (either by drawing a freehand line around their chosen area or by creating a polygon around it), and then be able to apply effects to the pixels within that selection.
Creating a selection of images is easy enough, but we want a really fast algorithm for deciding which pixels should be manipulated (ie. something to detect which pixels are within the user's selection).
We've thought of three possibilities so far, but we're sure that there must be a really efficient and quick way of doing this that's better than these.
1. Pixel by pixel.
We just go through every pixel in an image and check whether it's within the user selection. Obviously this is far too slow!
2. Using a Line Crossing Algorithim.
The type of thing seen here.
3. Flood Fill.
Select the pixels along the path of the selection and then perform a flood fill within that selection. This might work fine.
This must a problem that's commonly solved, so we're guessing there's a ton more solutions that we've not even thought of.
What would you recommend?
Flood fill algorithm is a good choice.
Take a look at this implementation:
Queue-Linear Flood Fill: A Fast Flood Fill Algorithm
You should be able to use your polygon to create a clipping path. The mini-language for describing polygons for Silverlight is quiet well documented.
Alter the pixels on a copy of your image (all pixels is usually easy to modify than some pixels), then use the clipping path to render only the desired area of the changes back to the original image (probably using an extra buffer bitmap for the result).
Hope this helps. Just throwing the ideas out and see if any stick :)
I have the following needs. There are some number of forms, i.e blanks - for example the ones used in surveys. The ones which aren't filled with information, I will call image templates from now on. Apart from the image templates, I have also many images, which are essentially the image templates filled with information. For example, there is a survey and there are two blanks for filling - these are the image templates. Many people have filled the blanks with their personal information and these are the images.
The image templates are scanned in a perfect shape. But many of the scanned images are tilted or not properly aligned, or maybe scaled. So I have the following requirement - every image must be recognized to which image template it belongs. After it is recognized, it must be properly skewed, aligned and scaled to the image template.
I know this is a complex task and that's why I need a library, preferably a C# one. I have found AForge, but till now I have only seen a suitable method for skewing. Essentially I need a library which takes as input an image template and an image, and sets a flag if the image does not match to the image template. But if it matchs it must return the appropriate skew angle, alignment and scaling.
If you have any ideas or used such a library, I will appreciate it greatly.
Wish you all the best,
Petar
The problem seems to be an image registration problem coupled with some template matching problem.
image registration
Depending on how the scanned document may be distorted (scale factor, rotation, skew...) one can register images using simple rigid transform (i.e. translation + rotation, only two corresponding points are needed) to more complex one such as non rigid transform (more corresponding point are needed). The corresponding points can be manually given but ideally should be automatically detected.
ITK library includes several methods for image registration
template matching problem
Once your images are aligned, the comparison between an image and possible templates database could be achieved by first extracting characteristic features in the image and comparing them to your template database. This is very general and should be refined with respect to the image used.
There is other way that combine both image registration and template matching
the Bag Of Features approach which consists in extracting interesting points (robust to several types of image deformation) from the image, the points generate a signature that characterizes the image, the image comparison being in fact a signature comparison.
I used to work for a company, Accusoft Pegasus, which has some interesting forms recognition software. I've not seen their FormFix tool in action in a few years, but it should be able to do what you are needing.
My program is working with fax documents stored as separate bitmaps
I wonder if there is a way to detect automatically page orientation (vertical or horizontal) to show image preview for user in right order (meant rotate if neccesary)
Any advices much appreciated!
EDIT: Clarification:
When Faxmachine receives multi-page document it saves each page as separate TIFF file.
My app has built-in viewer displaying those files. All files are scaled to A4 format and saved in TIFF (so there is no change to detect orientation by height/width parameters)
My viewer displays images in portrait mode by default
What I'd like to do is automagically detect situation when org document was printed in landscape mode (eg wide Excel tables) then I'd like to show rotated preview for end user to speed up preview process
Obviously there are 4 possible fax orientation portrait / landscape x 2 kinds of rotations.
I'm even interested simplified solution detecting when org doc was landscape or portrait (I've noticed most of landscape docs needs to be rotated clockwise)
EDIT2: Idea
I think it might be some idea:
If I could draw horizontal and vertical lines and check if line doesn't cut any (black) point. Then we can compare what are more type of lines (horizontal or vertical) and his decides about page orientation.
What do you think ?
You could perform a Fast Fourier Transform (FFT) to convert your spatial image to a frequency/angle representation. Then find the angle with the most prominent frequency. It sounds complicated but it's not that hard, it's pretty efficient, and in effect it tests every possible angle at once, instead of being a hard-coded hack that only works for specific angles. Search for a sample implementation with search terms like Numerical Recipes and FFT.
You'd need OCR for that. Rolling your own OCR would be a bit difficult, but there might be library or something out there worth looking into? Also, even with good OCR, it's not a 100% reliable solution.
I wonder if there are some properties of text you could use to help you do this.
For instance based on a quick glance, there are far more vertical lines in text (l,j,k,m,n etc) than horizontal ones so maybe you could start with this.
But even detecting these isn't straightforward, you'd need to use some sort of filter like a Sobel or Prewitt. They both have horizontal and vertical versions, see here for more info.
Of course the vertical/horizontal lines of an excel spreadsheet would be the strongest edges so you'd have to ignore these and look only at the text.
Alternative: Can you not just give the user an easy way to rotate the images, like the arrows in Windows Picture viewer or just show 4 thumbnail previews they can click on. You might need to cache the 4 versions (if you are rotating) so it's quick, but only if speed turns out to be an issue?
Here's a paper entitled "Combined Script and Page Orientation Estimation using
the Tesseract OCR engine" [pdf]
I haven't been able to find an implementation of their work, but the approach looks good to me:
The basic idea behind the proposed approach is simple.
A shape classifier is trained on characters (classes) from all the scripts of interest. At run-time, the classifier is run independently on each connected component (CC) in the image and the process is repeated after rotating each CC into three other candidate orientations (90°, 180° and 270° from the input orientation).
The algorithm keeps track of the estimated number of characters in each script for a given orientation, and the accumulated classifier confidence score across all candidate orientations. The estimate of page orientation is chosen as the one with the highest cumulative confidence score, and the estimate of script is chosen as the one with the highest number of characters in that script for the best orientation estimate.