A Novel Hierarchical Approach for Image Retrieval Using Color and Spatial Information

A novel hierarchical approach for image retrieval is proposed in this paper. First, a color label histogram is used to effectively filter out the images that are not similar to the query image in color. The color label matrix is built by categorizing the pixel colors into a set of 13 colors and by labeling each pixel based on its color category ID. Next, the class parameters of those images passing the first filter are used to identify the images similar to the query image in spatial layout. These class parameters are obtained automatically from the proposed unsupervised segmentation algorithm. Moreover, the wavelet decomposition coefficients are used to generate the initial partition for the segmentation algorithm. It doubles the segmentation performance. At the last stage, all images passing two filters are ranked based on the total normalized distance in color and spatial layout. The experiments conducted on 500 images show the effectiveness of this approach.