Content Based Image Retrieval Using Texture And Color Features

The purpose of this paper is to describe solution to the problem of designing a Content Based Image Retrieval (CBIR) system. It outlines the problem, the proposed solution, the final solution and the accomplishments achieved. Due to the enormous increase in image database sizes, as well as its vast deployment in various applications, the need for CBIR development arose. Content-based image retrieval (CBIR) is an important research area for manipulating large amount of image databases and archives. Extraction of invariant features is the basis of CBIR. This paper focuses on the texture & color feature extractions. Using just one feature information for comparing images may cause inaccuracy hence compared with more than one features. CBIR requires feature extraction and computation of similarity. The Haar wavelet transform is used for texture feature extraction, and for color feature extraction i use color moments. The distance between the query image features and the database images features is computed. Experiment results reflect the importance of the Haar wavelet transform and color moments in the performance of proposed CBIR method.