CAJ | 학술논문

为克服人脸表情、光照变化等对图像中人脸识别结果的影响，文中提出一种加权的多尺度多分辨率人脸描述与识别方法。首先使用多分辨率分析分解图像为子带图像，并选择3个不同尺度的低频子带图像构建多尺度和多分辨率图像序列。然后针对图像序列的每幅图像编码人脸局部区域的中心像素与其邻域像素的灰度差的符号分量，体现人脸局部结构的重要性。再利用人脸局部区域中心像素与邻域像素的灰度差的幅值分量作为像素局部二值模式的权重。最后利用块Fisher线性判别降低特征描述符的维数，同时增强判别能力。在ORL和FERET人脸库上的实验表明该方法可获得明显的性能提升。
위극복인검표정、광조변화등대도상중인검식별결과적영향，문중제출일충가권적다척도다분변솔인검묘술여식별방법。수선사용다분변솔분석분해도상위자대도상，병선택3개불동척도적저빈자대도상구건다척도화다분변솔도상서렬。연후침대도상서렬적매폭도상편마인검국부구역적중심상소여기린역상소적회도차적부호분량，체현인검국부결구적중요성。재이용인검국부구역중심상소여린역상소적회도차적폭치분량작위상소국부이치모식적권중。최후이용괴Fisher선성판별강저특정묘술부적유수，동시증강판별능력。재ORL화FERET인검고상적실험표명해방법가획득명현적성능제승。
To overcome the effect of different illuminations and expressions on the recognition results of face images, a weighted multiscale and multiresolution face description and recognition method is presented. Multiresolution analysis is firstly employed to decompose a image into subimages, and three low frequence subbands with different scales are selected to construct multi-scale and multi-resolution image sequences. Then, the sign components of gray level difference between central pixel and its neighbors for each image in image sequences are encoded to express the importance of local face structure. Next, the magnitude components of gray level difference between central pixel and its neighbors are used as the weight of local binary pattern. Finally, block-based fisher linear discriminant analysis is utilized to reduce dimensions of the feature descriptor and enhance its discriminative ability. Experimental results on ORL and FERET face databases show that the proposed method gets significant performance improvement.