Comparative analysis of color and texture features in content based image retrieval

Content-based image retrieval is a system which extracts the relevant set of images and matches with query image from large number of dataset. CBIR is used in many important areas such as education, defense, biomedical, crime prevention etc. In CBIR, the images are indexed according to content of image i.e. color, texture and shape that are derived from images. Many features and algorithms can be used to improve retrieval accuracy and to reduce the retrieval time. In this paper, we compare the different algorithms to extract color and texture features of an image and retrieve the relevant images. We measure the similarity between two images using different distance measures. The performance of each method has been individually evaluated in terms of average precision.