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视频中适应光照可变情况下的人脸识别方法
王华锋; 王蕴红; 马凯迪; 张兆翔; Hua-Feng Wang
Source Publication模式识别与人工智能
2011-12-25
Volume24Issue:6Pages:856-861
Other AbstractA method is proposed, which combines adaptive histogram equalization (AHE), Gabor wavelet and LTP, to improve the video-based facial recognition under left, right, up, down and front illumination. Firstly, the AHE is used to reduce illumination variations on the existed face images from YaleB and CMU PIE face databases. Then, the images are convolved with Gabor filters to extract their corresponding Gabor feature maps and the LTP is used on each Gabor feature map to extract the local neighbor pattern. Finally, the input face image is described by using the histogram sequence extracted from all these region patterns. The results compared with the published results on YaleB and CMU PIE face databases of changing illumination verified the validity of the proposed method.
KeywordFace Recognition Gabor Wavelets Local Ternary Patterns(Ltp) Adaptive Histogram Equalization (Ahe)
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/13233
Collection类脑智能研究中心
Corresponding AuthorHua-Feng Wang
Recommended Citation
GB/T 7714
王华锋,王蕴红,马凯迪,等. 视频中适应光照可变情况下的人脸识别方法[J]. 模式识别与人工智能,2011,24(6):856-861.
APA 王华锋,王蕴红,马凯迪,张兆翔,&Hua-Feng Wang.(2011).视频中适应光照可变情况下的人脸识别方法.模式识别与人工智能,24(6),856-861.
MLA 王华锋,et al."视频中适应光照可变情况下的人脸识别方法".模式识别与人工智能 24.6(2011):856-861.
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