A Hybrid Algorithm for Detecting Contour of Moving Object Based on Merging Mean Shift and GVF Snake Model

摘要：

In this paper, a new algorithm for extracting contour of moving objects through video sequences based on merging Mean Shift Algorithm and GVF Snake model is proposed. Firstly, object region (i.e. image region a moving object covers) is determined, thus actual contour searching activity is restricted to a small area; and then an initial position, which is usually within the extracted object region, of a Snake curve is given; Finally, the contour of a moving object is obtained by using a GVF Snake model. Experimental results show that the number of iterations as well as computation complexity for extracting contour are greatly reduced than that of by using the GVF Snake model alone, and also that it holds the advantage of extracting actual contour of a moving object effectively.

关键词： Mean Shift algorithm GVF snake model contour extraction moving objects

作者: Gu-quan Li Zhong-ze Chen

作者单位: Department of Electronics and Information Engineering University of South China Hengyang, Hunan Province, P. R. China

会议类型: 国际会议

会议名称: 2011 4th International Congress on Image and Signal Processing(第四届图像与信号处理国际学术会议 CISP 2011)

会议地点: 上海

会议语种:英文

页码: 1308-1312

在线出版日期: 2011-10-15（万方平台首次上网日期，不代表论文的发表时间）