How to calculate The classification error rate (E) of iris recognition

Hello, How to calculate The classification error rate (E) of iris recognition in this article by using MATLAB? http://www.di.ubi.pt/~hugomcp/doc/ProencaAlexandreNICE1BTAS2007.pdf A lot of articles used this to calculate the segmentation accuracy. I want to compare the segmentation accuracy of two iris images (ground truth & enhanced image) TQ

Answer 1

[Image Analyst]

What's the question? You should know if it identified the correct individual or not. Whatever rates you want to compute can be determined by the true positive, true negative, false positive, and false negative (TP, TN, FP, FN) numbers. From that you can construct the ROC curve.

[shahrizan jamaludin]

</matlabcentral/answers/uploaded_files/36362/Untitled.png> yes i'm going to plot the roc later but right now i want to calculate the segmentation error just like the equation in the picture. i want to implement it in matlab. i want to use that equation to compare the iris image of b (ground truth image) and c (enhanced image). according to the equation, i need to use XOR both images.

[shahrizan jamaludin]

this is the equation

[Image Analyst]

OK, they're not defining ground truth by whether it identified the correct individual based on the iris, but by whether their algorithm matches up pixel for pixel with some other binary image that they call "ground truth" which is possibly some binary image created by someone hand-drawing the boundaries.

So, is there something about the xor() function that you don't understand? Just use it like this:

differentPixels = xor(thisImage, groundTruthImage);
fractionDiffPixels = sum(differentPixels(:)) / numel(differentPixels);