摘要
为提高Gabor对人脸结构特征和内容信息的保留能力,解决人脸识别中对表情等抗噪性差的缺点,提出一种基于改进Gabor加权分析的人脸识别算法。该方法通过对归一化的人脸进行多尺度Gabor分析,并依据相同滤波窗口参数进行归类合并,最后对该信号进行加权比对得到识别结果。实验证明,该方法很好地兼顾人脸结构特征和内容信息,具有良好的抗噪性和识别率。
To improve the Gabor ability to retain face structure and content information,and solve the problem of low anti-noise property in human face recognition,this paper proposes a new face recognition algorithm based on weighted analysis and modified Gabor filter.This method analyzes normalized face in multiscale by Gabor filter,and classifies Gabor signal under the principle of uniform filter parameter.Owing to this,classified Gabor signal can be a decision threshold by weighted match.Experiments show that this method not only robust in retaining face structure and content information,but also has strong anti-noise ability in face recognition.
出处
《计算机工程与应用》
CSCD
北大核心
2011年第23期194-196,200,共4页
Computer Engineering and Applications
关键词
人脸识别
Gabor分析
信号归类
加权匹配
face recognition
Gabor analysis
signal classification
weighted match
