Comparative Analysis in Content Based Image Retrieval System Using Color and Texture
K. Nirmala, A. Subramani · 2013
Searching digital images from a large database ca n be solved by the Content Based Image Retrieval System based on the extraction of features such as color, texture and shape of the image. CBIR is the most ef ficient image retrieval method. Most of techniques for CBIR use n umerical representations called feature vectors to allow contentbased searching in large image collections. Analyzi ng images based on the colors is one of the most wi dely used techniques since the color does not depend on image size or orientation. Texture analysis is mainly us ed to identify the image given by the shape, size, brightness etc. The proposed method uses image features such as color and texture to retrieve the images from database. In ad dition, it uses auto color correlogram for identify ing images based on the feature and Spatial texture for identifying images based on the texture. Moreover, this system has operated on a Corel database containing 1000 general-use color images. The study shows that the performance and accuracy of retrieving images in the large database.