摘要
研究了下颌轮廓线的分类方法,并通过下颌轮廓线分类改进人脸识别系统人脸识别系统的性能。将下颌作为人脸识别的新特征,并综合其他特征进行人脸分类,可以提高人脸识别的识别率;同时,人脸数据库根据下颌的类属分类,可以提高识别速度。通过对下颌轮廓线进行主元分析得到下颌的(PCA)特征字串,并用K mean自动聚类方法和两类划分进行了下颌轮廓线分类的尝试。实验结果表明,这种方法在人脸识别系统中取得了较好的应用,识别率和识别速度都有明显提高。
Face recognition system can be improved in two ways： increasing recognition rate and increasing recognition speed. Recognition rate depends on the feature selection and the space dividing. Chin is a stable feature in front-view face image. Using chin as a new feature can improve the recognition rate. Further, huge database of human faces is organized in different categories with the chin features. So the consequent recognition module will work on a group of smaller database,and the correct rate and the speed of recognition will be improved. This paper introduces that how to get the chin contour,how to cluster the chin contours and how to use the cluster result in face recognition system. The experimental results show this approach improves the performance of face recognition system with huge database greatly.
出处
《光电子．激光》
EI
CAS
CSCD
北大核心
2005年第11期1368-1372,1377,共6页
Journal of Optoelectronics·Laser
基金
国家重点攻关资助项目(2001BA801B07)
关键词
下颌轮廓线分类
人脸识别
特征提取
chin contours classification
face recognition
feature extraction
