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Video surveillance system will produce a lot of video information in the monitoring process over time,how to search needed information quickly,which based on content,in the massive videos has become an urgent problem to be solved. This paper,during the video retrieval process,combines the SIFT feature extraction and matching of the video image with the MapReduce parallel mode,and meanwhile uses the LSH mapping to divide the video image into groups and stores it in the HBase database ,which reduces the amount of calculation in conjunction with the parallel analysis. Finally,the experiments show that by using MapReduce parallel mode to extract the SIFT extraction characteristic value of image,time will continue to decrease with the increase of the cluster nodes,and finally tend to be stable. Therefore,to the video retrieval based on content,it can improve the efficiency remarkably by using the parallel analysis,and it realizes the expansion of the application of Hadoop architecture in the video analysis.