MATLAB: Which segmentation methods are preferable

Image Processing Toolboxradiographic imagessegmentation

Hi friends!I am writing a paper on segmentation methods.I need to apply the segmentation technique to a radiographic image. The size of the image is too large(5000*7000). Can you suggest me some methods so that I can get the result fastly?

Best Answer

imresize() will make the image smaller, if that's what you want.

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MATLAB: Image Processing Question – Correlating Watershed Segmented Image with Original Image

You can extract the edge pixels with the edge mask like this:

edgePixels = grayImage(edgeMask);

where edgeMask is the binary image (true/false, 1/0, white/black) of your edge locations. Then get the mean value of that by

meanEdgeGrayLevel = mean(edgePixels(:));

MATLAB: Image processing of confocal images (flattening)

I think this is quite difficult. There seem to be two problems with the images: one is the defocusing; the other is the change in illumination (especially visible in the second image).

I am not sure how to deal with the change in focus, but anyway what to do depends on exactly what you need to measure. It may be that the lack of sharpness in part of the image is not a problem, if, for example, you just need to estimate the area of the darker structures. It is possible that deconvolution techniques may be some help, and if the blurring is a major problem then you could investigate that.

The gradient in illumination is easier to deal with, using adaptive thresholding. There's a file exchange contribution which might be applicable, and also a relevant demo with the Image Processing Toolbox.

Try fixing the illumination problems first, and then assess how much the blurring matters. What you do then depends on what exactly you need to get out of the images.

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MATLAB: Image Processing Question – Correlating Watershed Segmented Image with Original Image

MATLAB: Image processing of confocal images (flattening)

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