A new content-based image retrieval technique using color and texture information

Article history: Available online 8 February 2013 Feature extraction and representation is one of the most important issues in the contentbased image retrieval. In this paper, we propose a new content-based image retrieval technique using color and texture information, which achieves higher retrieval efficiency. Firstly, the image is transformed from RGB space to opponent chromaticity space, and the characteristics of the color contents of an image is captured by using Zernike chromaticity distribution moments from the chromaticity space. Secondly, the texture features are extracted using a rotation-invariant and scale-invariant image descriptor in Contourlet domain, which offers an efficient and flexible approximation of early processing in the human visual system. Finally, the combination of the color and texture information provides a robust feature set for color image retrieval. Experimental results show that the proposed color image retrieval is more accurate and efficient in retrieving the user-interested images. 2013 Elsevier Ltd. All rights reserved.