CAJ | 학술논문

针对单独的纹理特征只能提取图像的纹理信息而不能得到图像轮廓边缘信息的问题，在人脸识别的特征提取研究中提出了分层CS-LBP和分层 HOG特征的融合方法。对图像分别进行多次CS-LBP和HOG特征的提取，得到分层CS-LBP特征提取图像和分层 HOG特征提取图像，对分层的特征提取图像再次提取分层CS-LBP和分层HOG特征，并将两种分层特征进行融合，得到更有效的人脸的纹理及边缘轮廓特征。在ORL和GT人脸库上的实验结果验证了所提出的分层特征融合方法的有效性。
침대단독적문리특정지능제취도상적문리신식이불능득도도상륜곽변연신식적문제，재인검식별적특정제취연구중제출료분층CS-LBP화분층 HOG특정적융합방법。대도상분별진행다차CS-LBP화HOG특정적제취，득도분층CS-LBP특정제취도상화분층 HOG특정제취도상，대분층적특정제취도상재차제취분층CS-LBP화분층HOG특정，병장량충분층특정진행융합，득도경유효적인검적문리급변연륜곽특정。재ORL화GT인검고상적실험결과험증료소제출적분층특정융합방법적유효성。
Texture feature extracts image texture information only ,and is not capable of capturing the edge information ,thus a new method of feature extraction is proposed ,called layered fusion of CS-LBP and HOG feature .Firstly ,the CS-LBP and HOG feature are utilized to extract the multi-layered feature from the original image ,get different multi-layered feature images ;then extract the layered CS-LBP and layered HOG from feature extraction image ;finally ,mix these two features to represent original image more effectively .The experiment conducted in the ORL and GT standard face image database show s that the fusion method proposed is better than single method ,and the rate of recogni-tion has greatly improved .