I have some images of tags with shapes on them (circle, rectangle and blank). After processing the images with median blur and Gabor filters I can eliminate most of the effect that variable illumination had on the images and they look like this:
I've tried training an SVM using HOG, LDA, PCA and the pixels themselves but I can barely get past 40-60% accuracy. What I really want to do is use in the information in the shapes of the images. I had Fourier descriptors recommended to me, and while I've found a good tutorial about applying Fourier transform to images using NumPy and OpenCV, I'm not sure how to go about extracting Fourier descriptors from an image and then identifying the ones that are unique to the different shapes. Does anyone know how to do this or can recommend an alternative technique to get features from these images that would allow an SVM to distinguish between them?