Image descriptors to train SVM on
I've been processing some tags (circles, rectangles and blank) using a median blur, Gabor filters and increasing the contrast. The result, which seems to remedy most of the variation in lighting, looks like this:
Does anyone know of some reliable descriptors (such as shape) that I could extract from images like this to feed into an SVM in order to identify the type of tag? I've tried feeding HOG, LDA, PCA and the raw pixels into an SVM without success (accuracy in the 40% range).
I'd try a BoW approach, i.e. compute many local descriptors e.g. by using dense SIFT and then form one large descriptor by using k-means.