Dimensionality reduction for content-based image classification

Effective ways of organizing image descriptors is a critical design step of content-based image classification systems. Suitable descriptors are selected according to the problem domain for generating the feature space. Using several descriptors improves accuracy of representation but rises some challenges such as non linear combination, expensive computation and the curse of dimensionality. In this paper an approach using a non parametric statitical test for effective dimensionality reduction is presented. The proposed method facilitates feature discrimination and keeps relevant information.