A new adaptive object detection technique based on the wavelet co-occurrence features

摘要：

This Object detection involves processing images for detecting, classifying, and tracking targets embedded in a background scene. This paper presents an adaptive algorithm for detecting a specified target objects embedded in visual images for tracking application. The developed algorithm employs a novel technique using the wavelet co-occurrence features for detecting object based on template matching. Several signatures as contrast, energy-, entropy and maximum probability are computed from wavelet cooccurrence features for object window and compares with features of image windows. The results of the proposed algorithm are very adaptive in variant condition with clutters.

关键词： Wavelet packet transform (WPT) co-occurrence matrices contrast energy entropy maximum probability

作者: Keivan Ashabi Ali Mahmoodi Elmira Vafabakhsh Hamid Borji

作者单位: Department of applied science, Malek Ashtar University of Technology Esfahan, Iran Department of electrical engineering. Malek Ashtar University of Technology Tehran, Iran Department of electrical engineering, Malek Ashtar University of Technology Tehran, Iran

会议类型: 国际会议

会议名称: Third International Conference on Digital Image Processing(ICDIP 2011)(第三届数字图像处理国际会议)

会议地点: 成都

会议语种:英文

页码: 681-685

在线出版日期: 2011-04-15（万方平台首次上网日期，不代表论文的发表时间）