Image retrieval algorithm based on Contourlet transform and Hu invariant moments

An image retrieval algorithm was proposed based on Contourlet transform (CT) and Hu invariant moments in this paper. Firstly, each image was decomposed into low frequency sub-band and high frequency sub-bands by using Contourlet transform. The Hu invariant moments of the low frequency sub-band coefficient, as well as the mean and the standard deviation of each high frequency sub-band coefficients were computed and used as image feature vector. Secondly, Manhattan distance was used as similarity measure between the query image and every image in the image database. After these two procedures, the content -based image retrieval was achieved. In order to evaluate the effect of the proposed algorithm, the algorithm based on CT and Hu invariant moments were tested respectively. Comparing the results of the average retrieval rate, the experimental results of the proposed algorithm were superior to other image retrieval algorithms. The proposed algorithm gets a higher average retrieval rate and the average retrieval rate is up to 73.94%.