Face recognition using vector quantization histogram method
Face recognition using vector quantization histogram method
复制标题
使用矢量量化直方图方法进行人脸识别
DOI：
10.1109/icip.2002.1039898
复制
发表时间：
2002
期刊：
影响因子：
--
通讯作者：
T. Ohmi
中科院分区：
文献类型：
--
作者：
K. Kotani;Feifei Lee;Qiu Chen;T. Ohmi
我们已经开发了一种非常简单但高度可靠的人脸识别方法，称为VQ直方图方法。一个码矢量参考（或匹配）计数直方图，这是通过矢量量化（VQ）处理的面部图像，被用作一个非常有效的个人特征。通过对人脸图像进行适当的低通滤波和矢量量化处理，可以提取用于人脸识别的有用特征。实验结果表明，从公开的ORL数据库中，40人（每人10张图像）的400张图像的识别率为95.6%，其中包含照明，姿势和表情的变化。验证实验的等误差率（ERR）为2.6%。通过结合多个低通滤波过程，识别率提高到97%或更高。
We have developed a very simple yet highly reliable face recognition method called the VQ histogram method. A codevector referred (or matched) count histogram, which is obtained by vector quantization (VQ) processing of the facial image, is utilized as a very effective personal feature. By applying appropriate low pass filtering and VQ processing to a facial image, useful features for face recognition can be extracted. Experimental results show a recognition rate of 95.6% for 400 images of 40 persons (10 images per person), which contain variations in lighting, pose, and expression, from the publicly available ORL database. Equal error rate (ERR) of 2.6% is obtained for the verification experiment. By combining multiple low pass filtering procedures, the recognition rate is increased to 97% or higher.