CAJ | 학술논문

双密度双树复小波对图像细节信息描述更加清晰，使用双密度双树复小波对人脸图像进行信息提取，可使图像中的信息更好的保留下来。针对Gabor小波进行特征提取时的频域重叠以及频域遗漏和双树复小波提取的方向信息确失，提出利用两种小波对人脸图像提取的特征信息进行组合，得到人脸图像的特征信息。再针对提取到的特征信息维数过多不利于信息处理，提出了利用LLTSA算法对经过小波变换得到的特征信息进行降维。在降维的过程中先利用改进的局部切空间排列算法进行降维，然后使用三阶近邻算法进行分类。实验结果表明：使用该算法在ORL及YALE人脸库进行的人脸识别较传统的识别算法的识别结果更好，识别速率更高。
쌍밀도쌍수복소파대도상세절신식묘술경가청석，사용쌍밀도쌍수복소파대인검도상진행신식제취，가사도상중적신식경호적보류하래。침대Gabor소파진행특정제취시적빈역중첩이급빈역유루화쌍수복소파제취적방향신식학실，제출이용량충소파대인검도상제취적특정신식진행조합，득도인검도상적특정신식。재침대제취도적특정신식유수과다불리우신식처리，제출료이용LLTSA산법대경과소파변환득도적특정신식진행강유。재강유적과정중선이용개진적국부절공간배렬산법진행강유，연후사용삼계근린산법진행분류。실험결과표명：사용해산법재ORL급YALE인검고진행적인검식별교전통적식별산법적식별결과경호，식별속솔경고。
Dual-density tree complex wavelet will obtain more clearer image details, so many researchers use it for face image information extraction which can be better preserved. However, due to the restriction of its direction and the overlap and omissions for frequency-domain information which is obtained from Gabor wavelet feature extraction, we combine the Dual-density tree complex wavelet and Gabor wavelet to extract the feature information for the face images. For the extracted feature information has a large number of dimension which is not conducive to information processing, so we try to use lltsa (Linear Local Tangent Space Alignment) to reduce the dimension information that is obtained through the wavelet transform. In the process of dimension reduction ,we first use the improved local tangent space alignment algorithm to reduce the dimension, and then use the third-order nearest neighbor algorithm for classification. Experimental results show that:this face recognition algorithm in ORL and YALE face database recognition have better results and higher recognition rate than traditional recognition algorithm.