Fast Methods Research In Content-Based Video Retrieval

With the enlargement of the data quantity of the video, not merely require the database and other information systems to carry on storing and retrieval based on key word to the video, and should carry on semantic analysis to the content of the multimedia data, in order to reach deeper retrieval level, thus realize content-based video retrieval. Because the amount of analyzed video data is enormous, we need reduce it. This paper carried on the work around the reduce of video data and enhance the retrieval speed.This paper proposed two methods to compress the video data, enhance the retrieval data. The first one is an improved HSV quantization method, to reduce the colors. The other method need detect the shot boundary, and then select key frame. The purpose of this method is to reduce the frames need to be searched.The improved HSV quantization method is to the color feature. This paper has non-uniform quantize pure color to six colors, to saturation and luminance, non-uniform quantize to three grades. Finally , there are 27 colors altogether. The result of the experiment indicates, the quantization method we proposed computational cost is low; The quality of the image is better; Because not sensitive to the luminance and saturation, reduce the possibility of color skew. Meanwhile,because it was the non-uniform quantization which accords with the human vision characteristic, it contributes to finding the color features of user's interest.This paper proposed a shot boundary detection method that based on HSV histogram and directed Divergence. This method calculates out HSV histograms of two frames, then regard the histograms of two frames as the parameter of directed divergence function, return the last distance value. This algorithm is easy to be realized, Accuracy is relatively high to compare with the results of other methods.A good key frames select method can reduce the frames need to be searched, enhance the speed of retrieval. This paper used a cumulative directed divergence method choose key frames. Cumulative directed divergence and shot boundary affect the select of key frames. Meeting two conditions only at the same time, it could be elected as key frames of the video. Realization of this algorithm is very simple, the chosen key frames is more representative.