摘要
在正面人面像中,下颌轮廓线是一种相对稳定的形状特征.但人面像下颌区域灰度分布复杂,下颌轮廓线边缘性差,难以提取.文中提出一种新的人面像下颌轮廓线的提取算法.该算法采用了基于先验分布和局部判别的方法,先根据先验知识估计轮廓线的大致位置,然后在其附近搜索局部极值点,最后对得到的点集做一定的平滑连接.试验表明,应用该算法得到的下颌曲线保留了下颌轮廓丰富的细节,可以作为一个新的特征应用到人面像识别算法中.
In face front-view images, chin contour is a relative stable shape feature. But it is hard to be extracted by conventional edge detection methods due to the complexity of grayscale distribution in chin area. In this paper, a novel algorithm for chin contour extraction is presented, which is based on prior distribution and local decision. The chin contour area is first approximately located according to prior statistical knowledge, then local gray-scale peak points is scaned in this area, and lastly necessary smoothing and linking is processed. Experimental results show that by this algorithm, the extracted chin contour can be used as a new feature preserves lots of details and in face recognition.
出处
《模式识别与人工智能》
EI
CSCD
北大核心
2002年第1期75-79,共5页
Pattern Recognition and Artificial Intelligence
基金
清华大学科技发展基金
公安部资助