A color image retrieval algorithm based on the integration of Zernike moment and Contourlet transform
Li Pin · 2015
Using the content-based image retrieval technology(Content-Based Image Retrieval,CBIR)can be more quickly find the user to query image from the vast network of image library,but a single visual features can not adequately describe the image content information and other issues,thus reducing the accuracy of the search results.In light of this,this paper presents a fusion of a variety of image retrieval algorithm,the method first construct a chromaticity distribution Zernike moments for color image feature extraction,and then use the Contourlet transform multi-directional image multiscale decomposition,and calculating the variance and entropy of each sub-band decomposition,as texture features of images,then these features and calculating normalized weights corresponding to each feature.Finally,calculate the similarity between the images of these features,the search result is returned and sorted.Simulation results show that this multi-feature fusion method can multi-level search algorithm describes the semantic information of the image,to some extent,improve the image retrieval precision and recall.