关键词: 运动目标实时检测, 分块处理, HSI混合高斯模型, 三帧差分, 目标轮廓清晰度

Abstract:

The traditional mixture Gaussian models require much computation and have little clarity of objects’ contours. Therefore, a new moving objects realtime detection algorithm is proposed. Firstly, the threeframedifferencing method is introduced in the algorithm in order to improve the contours’ clarity of detection objects. Secondly, the computation is reduced by block processing in the Gaussian mixture models on HSI, so the realtime performance of the algorithm is improved. Thirdly, the threeframedifferencing method and the adaptive Gaussian mixture model on HSI are merged by logic computation so as to extract background efficiently. Finally, the detection result is optimized further by the mathematical morphology. The experimental results show the new algorithm can detect the moving objects in the surveillance video sequences faster and more accurately than the classic mixture Gaussian models and improve the clarity of objects’ contours.

Key words: moving object real-time detection;block processing;Gaussian mixture model on HSI;three-frame-differencing;clarity of objects&rsquo, contours