I asked my question here and found my answer http://stackoverflow.com/questions/14005245/fuzzy-color-image-segmentation-matlab
Fuzzy Color Image Segmentation
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I'm working on a color image segmentation in HSV color space using Matlab fuzzy toolbox. the goal is to read an RGB image->convert to hsv->use H,S,V values as an input for fuzzy system and then find which class(here is our 16 constant output color) does this pixel belongs. here is the fuzzy system :
"The reasoning procedure is based on a zero-order Takagi-Sugeno model, so that the consequent part of each fuzzy rule is a crisp discrete value of the set{Black, White, Red, Orange,etc}. Since this model has 10 fuzzy sets for Hue, 5 for Saturation and 4 for Value, the total number of rules required for this model is 10*5*4=200".(1)
The problem is that when I use this line in my program to get output value
segimg=reshape(evalfis([h s v],hsvRuleSugeno),imgh,imgw);
the out put is not any of my constant classes, because it uses centroid for defuzzification and as you see below I can't rely on it, as an output !
I search many papers and websites but I think it's so simple that no one explained it! I'm missing something or probably i don't have enough knowledge would you please help me to understand this problem ?
reference: (1): Human Perception-based Color Segmentation Using Fuzzy Logic,Lior Shamir Department of Computer Science, Michigan Tech.
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