关键词: K-均值聚类, 背景差, 边缘信息, 虚假运动目标

Abstract: In order to overcome the drawbacks of the traditional background subtraction method, a moving target detection method based on the combination of edge features and improved K-means clustering is provided. Background model is established using improved K-means clustering method. The difference between foreground image and background image is calculated and the binarization process is employed. False targets are judged and rejected with the foreground edge information. Experimental results show that the method can effectively eliminate the false moving target resulted from object move-in or move-out and improve the accuracy of moving target detection.

Key words: K-means clustering, background subtraction, edge information, false moving target