A New Content Based Image Retrieval Method Using Contourlet Transform

Subject Areas : Journal of Computer & Robotics

Farzad Zargari ¹ (Multimedia Systems Research Group, IT Research Institute, Iran Telecom Research Center, Tehran, Iran)
Ali Mosleh ² (Department of Computer Engineering, Science & Research Branch, Islamic Azad University, Tehran, Iran)

Received: 2009-01-15 Accepted : 2009-10-18 Published : 2012-06-11

Keywords: Content-based image retrieval, Contourlet Transform, Feature vector, Texture,

Abstract :

One of the challenging issues in managing the existing large digital image libraries and databases is Content Based Image Retrieval (CBIR). The accuracy of image retrieval methods in CBIR is subject to effective extraction of image features such as color, texture, and shape. In this paper, we propose a new image retrieval method using contourlet transform coefficients to index texture of the images. We employ the properties of contourlet coefficients to model the distribution of coefficients in each sub-band using the normal distribution function. The assigned normal distribution functions are used effectively at the next stage to extract the texture feature vector. Simulation results indicate that the proposed method outperforms other conventional texture image retrieval methods such as, Gabor filter and wavelet transform. Moreover, this method shows a noticeable higher performance compared to another contourlet based CBIR method.

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