Texture image retrieval using contourlet transform

• Published in: 2009 International Symposium on Signals, Circuits and Systems pp. 1 - 4
• Main Authors: Mosleh, A., Zargari, F., Azizi, R.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.07.2009
• Subjects: Content based retrieval; Content management; Digital images; Feature extraction; Gaussian distribution; Image databases; Image retrieval; Information retrieval; Software libraries; Spatial databases
• ISBN: 9781424437856; 1424437857
• DOI: 10.1109/ISSCS.2009.5206182

Content based image retrieval is a challenging issue in management of existing large digital image libraries and databases. The accuracy of image retrieval methods 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. We use the properties of contourlet coefficients to assign the normal distribution function to the distribution of coefficients in each sub-band. The assigned normal distribution functions are used to extract the texture feature vector at the next stage. 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 method.