Aiming at the problem of low retrieval rate of basic contourlet transform texture image retrieval system, a texture image retrieval system based on Complex Contourlet Transform (CCT) was proposed. The contourlet transform used in the system was constructed by dual tree complex wavelet transform followed by critically subsampled directional filter banks, sub-bands energy and standard deviations were cascaded to form feature vectors, and the similarity metric was Canberra distance. The performance of retrieval system was compared including original contourlet transform, non-subsampled contourlet transform, semi-subsampled contourlet transform (CTS) and CCT under the same system structure. Experimental results show that the image retrieval system based on CCT has higher retrieval rate than those of CT, CTS and NSCT with almost same length of feature vectors, retrieval time and memory needed, and decomposition scale number can make significant effects on average retrieval rates.