Bag of visual words model based on content-based image retrieval has been widely used,traditional bag of visual words model generally uses the SIFT descriptors for feature extraction.In view of the high complexity of SIFT descriptors and the long time of feature extraction,this paper proposes to use a faster binary feature descriptor ORB for the image feature extraction,creating visual dictionary,using the distance between two vectors to compare the image similarity,so as to achieve fast image retrieval.Experimental results show that the method proposed in this paper can improve the efficiency of image retrieval obviously,while maintains a relatively high robustness.