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Content Based Image Retrieval using Advanced Color and Texture Features

Author(s): Sagar Soman | Mitali Ghorpade | Vrushali Sonone | Satish Chavan

Journal: International Journal of Computer Applications
ISSN 0975-8887

Volume: iccia;
Issue: 9;
Date: 2012;
Original page

Keywords: Content Based Image Retrieval | Color Models | DCT | Color Moments

The paper presents an efficient Content Based Image Retrieval (CBIR) system using color and texture. In proposed system, two different feature extraction techniques are employed. A universal content based image retrieval system uses color, texture and shape based feature extraction techniques for better matched images from the database. In proposed CBIR system, color and texture features are used. The texture features were extracted from the query image by applying block wise Discrete Cosine Transforms (DCT) on the entire image and from the retrieved images the color features were extracted by using moments of colors (Mean, Deviation and Skewness) theory. The proposed system has used Corel database of 1000 images. The feature vectors of the query image will then be compared with feature vectors of the database to obtain similar images. Individual and combined vectors using color and texture features were computed and the combined feature vector results were comparatively better. The proposed system provides an efficiency of 60%.
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