Image Indexing Using Weighted Color Co-occurrence Matrix and Feature Selection

In this paper, image indexing based on weighted color co-occurrence matrix (WCCM) feature and isolation parameter-based feature selection is introduced. In this method, isolation parameter (IP) is used to indicate the visual perception complexity and conduct feature selection for each query image. When indexing images from database in the reduced feature space, the similarities of diagonal elements and non-diagonal elements of CCM feature are weighted separately with different values based on the isolation parameters of query image and images from database. The experiments show that the proposed method provides better results than modified color co-occurrence matrix (MCCM) based method and sub-range cumulative histogram (SCH) based method