CAJ | 학술논문

针对人脸识别中人脸图像的特征提取问题,提出了一种将全局特征与局部特征相融合的人脸识别方法.全局特征的提取采用主成分分析算法.主动外观模型定位58个特征点,在其中17个特征点处进行Gabor小波变换则可提取局部特征.归一化的全局匹配度(局部匹配度)可由测试图像和训练图像的全局特征(局部特征)得到.对归一化的全局匹配度和局部匹配度进行融合后,融合匹配度最大的训练图像所属的类即为识别结果.实验利用2个人脸图像数据库(AR和SJTU-IP-PR)测试该方法的识别率,结果表明该方法要优于PCA和EBGM,并且在一定的表情、光照和姿态变化的条件下是有效、稳健的.
침대인검식별중인검도상적특정제취문제,제출료일충장전국특정여국부특정상융합적인검식별방법.전국특정적제취채용주성분분석산법.주동외관모형정위58개특정점,재기중17개특정점처진행Gabor소파변환칙가제취국부특정.귀일화적전국필배도(국부필배도)가유측시도상화훈련도상적전국특정(국부특정)득도.대귀일화적전국필배도화국부필배도진행융합후,융합필배도최대적훈련도상소속적류즉위식별결과.실험이용2개인검도상수거고(AR화SJTU-IP-PR)측시해방법적식별솔,결과표명해방법요우우PCA화EBGM,병차재일정적표정、광조화자태변화적조건하시유효、은건적.
With the aim of extracting the features of face images in face recognition, a new method of face recognition by fusing global features and local features is presented. The global features are extracted using principal component analysis (PCA). Active appearance model (AAM) locates 58 facial fiducial points, from which 17 points are characterized as local features using the Gabor wavelet transform (GWT). Normalized global match degree (local match degree) can be obtained by global features (local features) of the probe image and each gallery image. After the fusion of normalized global match degree and normalized local match degree,the recognition result is the class that included the gallery image corresponding to the largest fused match degree. The method is evaluated by the recognition rates over two face image databases (AR and SJTU-IPPR).The experimental results show that the method outperforms PCA and elastic bunch graph matching (EBGM).Moreover, it is effective and robust to expression, illumination and pose variation in some degree.