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 risen some challenges such as non linear combination, expensive computation and the curse of dimensionality. In This work an approach using a non parametric statistical test for effective dimensionality reduction is presented. The proposed method facilitates feature discrimination and keeps relevant information.