Non-subsampled contourlet texture image retrieval system utilizing three features

Contourlet transform has better performance in directional information representation than wavelet transform and has been studied by many researchers in retrieval systems and has been shown that it is superior to wavelet ones at retrieval rate. In order to improve the retrieval rate further, a non-subsampled contourlet transform based texture image retrieval system was proposed in this paper. In the system, sub-band absolute mean energy, standard deviations and kurtosis in non-subsampled contourlet domain were cascaded to form feature vectors, and the similarity metric was Canberra distance. Experimental results show that this contourlet transform based image retrieval system is superior to that of the contourlet transform with absolute mean sub-bands energy and standard deviations features widely used today under the same system structure, the retrieval rate can be improved about 6 to 7 percent.