Enhanced linear block algorithm with improved similarity measure

Content Based Image Retrieval (CBIR) is a technique of finding appropriate images based on the features that are automatically extracted from the image itself. An important low-level feature in any image is dominant color. Dominant Color Descriptor (DCD) was proposed by MPEG-7 and is extensively used in image retrieval. An improvement over DCD was Linear Block Algorithm (LBA). In this paper, we propose an improved similarity measure for dominant color descriptor. We improve LBA by making two significant changes. First is improvement in the similarity measure and second is local implementation through region based dominant colors. The proposed similarity measure takes into account the number of dominant colors of the two images to be compared. The earlier well known methods like MPEG-7 DCD and LBA use the RGB color components and their percentages to find similarity between the query and target images. In our work, it is now weighted by the number of dominant colors in the two images and their mutual distances. The experimental results demonstrate that the proposed method outperforms LBA and other prominent color based retrieval techniques.