Scilab implementation of the famous Canny's algorithm.

The purpose of this project is to treat a given image to find its edges, and to create a new image to display them.

1. Normalize given image: application of a Gaussian filter.
2. Compute gradient and gradient norm (E_s_,E_o_).
3. Delete non-maximum values from the image.
4. Hysteresis thresholding.
5. Display result (concat given image and result image).

Note that the hysteresis threshold can be changed: for a good value, pick something between 70% and 85%.

1. applyMask(imgMatrix,mask) : apply a given mask to a given image. Mask can look like [1,2,1;2,4,2;1,2,1].
2. hysteresisThreshold(image,Eo,Es,95); : compute hysteresis threshold for the given image, last parameter is the threshold you want to pick.

• Possible issues if you use Scilab x64 (Scilab x32 preferred).
• Don't forget to increase the stack size! stack size('max');

• Clone project.
• Run script.
  • img = loadImage('./img3.jpg',1); l.372: Choose image to load.
  • mask = [2,4,5,4,2;4,9,12,9,4;5,12,15,12,5;4,9,12,9,4;2,4,5,4,2]; l.375: init your mask.
  • writeImage(uint8(resultImage),'./tests/img3_res_95.jpg'); l.395: write result of execution on disk.
• Done!
• Tests & results of previous executions provided in "./tests" folder.

Results of several execution can be found in "./tests" folder.