Develop Reference

Native WPF vs. Custom DirectX for displaying large images

I need to speed up my image viewer, and wondering if I should be looking into creating my own DirectX control to do so.
My image viewer displays medical images. They can be pretty large. We're talking 55mb when it comes to mammography. The pixel data is 16bit greyscale stored in a ushort array. Without getting into the gory details, my current approach is loading the pixel data into an ImageSource, and using the WPF Image control.
I've never done anything with DirectX. Is it worth diving into it? Would it be any faster than the native WPF stuff? If so how significantly? Or, should I just forget about DirectX and look into areas where I can improve my current approach?
Before somebody says so, I know WPF utilize DirectX. I'm wondering If removing the WPF layer and writing the DirectX myself will improve performance.

I have some experience drawing multi-gigabyte satellite and chart imagery. Working with imagery around 55MB should probably work okay even without trying to optimize it too much. You haven't really given enough detail to recommend one alternative over the other, so I will give my opinion on the pros and cons.
Using 2D windows APIs will be the simplest to implement and should always be fast enough if you don't need to rotate and simply want to display an image and zoom and pan around. If you treat it as one large image the performance will not be as good when you zoom out if you are drawing with halftoning to give a nice smooth image. This is because it will effectively have to read all 55mb of image every time it draws.
To get around this performance issue you can make multiple bitmaps, effectively mip-mapping your image. As you zoom out you can pick the reduced resolution image closest to the resolution you are trying to draw . If you are not familiar with mip-mapping here is a Wikipedia link:
http://en.wikipedia.org/wiki/Mipmap
Implementing it with DirectX will be 10x as difficult. Different graphics hardware has different maximum texture sizes. Most likely you will need to break your image up in to multiple textures to draw and you will also have to keep track of render states, viewing matrices, etc.
However, if you do use DirectX, you can implement lots of real-time photo adjustments You can do real-time rotation by simply adjusting view matrices. You can do real-time contrast, brightness, gamma, and sharpness easily in a pixel shader.
There are two other API's I might suggest. If you are willing to limit yourself to Vista or later then Direct2D would be a little simpler than Direct3D. Also if you ever will need to implement it on a non-windows platform I would suggest using OpenGL instead. My current project is in Direct3D because a few years ago when we started it OpenGL was falling behind and I didn't forsee the popularity of Android devices. I now wish we had used OpenGL instead.

Try profiling to see where WPF is spending its time. Are you displaying the images at their native resolution? If not it might be worthwhile to do some preprocessing and create 1/2 resolution versions.

Marking an interest point in an image using c++

I have a bitmap image like this
My requirement is to create a GUI to load the image and for changing the contrast and other things on the image and algorithm to mark the particular area in silver colour as shown in the fig using C++ or C#.I am new to image processing and through my search I have found out that I can use the Histogram of the image for finding the required area.These are the steps.
Get the histogram
Search for intensity difference
Search for break in the line
Can someone suggest me how can I proceed from here.Can I use Opencv for this or any other efficient methods are available..?
NOTE:
This image have many bright points and the blob algorithm is not successful.
Any other suggestions to retrieve the correct coordinates of the rectangle like object.
Thanks

OpenCV should work.
Convert your input image to greyscale.
adaptiveThreshold converts it to black and white
Feature detection has a whole list of OpenCV feature detectors; choose one depending on the exact feature that you're trying to detect.
E.g. have a look at the Simple Blob Detector which lists the basic steps needed. Your silver rectangle certainly qualifies as "simple blob" (no holes or other hard bits)

If all of your pictures look like that, it seems to me not complicate to segment the silver area and find its centre. Basically you will need to apply these algorithms in the sequence below:
I would suggest binaryze the image using Otsu adaptive threshold algorithm
Apply a labelling (blob) algorithm
If you have some problem with noise you can use an opening filter or median before the blob algorithm
If you end up with only one blob (with the biggest area I guess) use moment algorithm to find its centre of mass. Then you have the X,Y coordinate you are looking for
These algorithms are classical image processing, I guess it wouldn't be hard to find then. In any case, I may have they implemented in C# and I can post here latter in case you think they solve your problem.

May be a research on Directshow, a multi media framework from Microsoft will help you to accomplish your task.

Get all pixel in shape

i have 4 shapes in image
i want to get pixels of one shape in list of point
the shapes have same color
List<point> GetAllPixelInShape(point x)
{
//imp
}
where x point of this shape

Long story short, you could begin with a connected components / region labeling algorithm.
http://en.wikipedia.org/wiki/Connected-component_labeling
In OpenCV you can call findContours() to identify contours, which are the borders of your connected regions.
http://dasl.mem.drexel.edu/~noahKuntz/openCVTut7.html
OCR is an extremely difficult task, especially for a script like Arabic. Creating an OCR algorithm from scratch takes a lot of work and numerous algorithms working together. OCR for machine printed text is hard enough. Implementing an algorithm to read handwriting is not something I'd suggest trying until you have a year or two of image processing experience. If you haven't read textbooks and academic papers on OCR, you're likely to spend a lot of time reproducing work that has already been done.
If you're not familiar with contour tracing and/or blob analysis, then working with OpenCV may not be a good first step. Since you have a specific goal in mind, you might first try different algorithms in a user-friendly GUI that will save you coding time.
Consider downloading ImageJ so that you can see how the algorithms work. There are plugins for a variety of common image processing algorithms.
http://rsbweb.nih.gov/ij/

Your proposed method signature doesn't provide enough information to solve this. Your method will need to know the bounds of your shape, how long and wide it is etc, ideally a set of points that indicate those bounds.
Once you have those, you could potentially apply the details of this article, in particular the algorithms specified in the answer to solve your problem.

Large bitmap maniuplation in WPF

Is WPF be able to manipulate large bitmaps where GDI+ cannot due to memory limitations?
I have bitmaps that are 10,000x10,000 easily, and could even be much larger than that. Worst case I think I can break the single bitmap into large tiles and work with that I guess.
I basically need to do four things
Take an set of tiled images
Put all of those tiles into a single bitmap
Convert the bitmap to black and white
Scan the bitmap looking for changes from black to white
I know how to do these things in GDI+, but the problem I am running into is that the size of my bitmap is too large for the machine I am using, and it causes the program to crash, and I cannot make the image any smaller, so I am hoping that WPF will be able to succeed where GDI+ has failed me.

I don't think WPF will be able to help you here.
Why do you want to use bitmap object? You may as well work with an two-dimensional array of bytes or doubles (or any other type, depending oh what accuracy and range do you need), especially if you work with one channel only. Bitmaps have accessor methods (GetPixel and such) with huge computational overhead, working with arrays is by orders of magnitude faster (I know from personal experience), the only issue is that you can't display them as they are (you would have to convert the array back into image, which is fairly simple). But since you seem to want to do some sort of analysis on the data, I think array would be much more suitable for your needs.
I can post code samples detailing conversion from bitmap (either WPF or WinForms) to array an back if you want.
But remember, that 32bit .NET application can use approximately 1.2-1.4 gigabytes of memory - you have to fit in this space or you start getting OutOfMemory exceptions.

I eventually decided that the best course of action was to only work with the tiles, and then have an array that holds the actual information about each tile that I need. Given the number of tiles, it was the only sensible thing I could do.

Like CommanderZ said. Its Windows PRESENTATION Foundation, not Windows Image-manipulation Foundation.
You should try to either find some kind of image-manipulation library, but looking at size of your image, then doing everything yourself might be only way.
Especialy, you probably wont be able to work with bitmap as a whole, so you are going to work with tiles. Then it becomes problematic if you need to work with neighboring pixels. But I guess you should look into this yourself.

Picture matching from webcam pictures with picture noise problem

Hy
I take two pictures from a webcam and split them into a 9 pieces. Then i match the pieces of the two pictures. The problem is that my webcam have a picture noise. So my programm thinks that in every piece of the second picture have chanced something.
I need a logical push to solve my problem please help.

The pictures from the web cam will never exactly match - even the slightest change in lighting will cause a difference. For this kind of picture matching you have to use a forgiving algorithm that allows at least some change and still makes a match. Create a histogram of each image, then calculating the difference seems to be a promising approach.
See the following threads on SO (just for examples, there are many more threads):
Image comparison - fast algorithm
Image comparison algorithm
Also I would check out Emgu if you are working with .NET, this is a .NET wrapper for openCV, a computer vision library.