CAJ | 학술논문

为了解决人脸识别算法双向二维主元分析（2D2PCA）表征的信息不全面，鲁棒性差、识别速率较慢的问题，提出了一种结合二维离散余弦变换（DCT）算法和改进的双向二维主成分分析算法（模块（2D）2PCA）的新的人脸图像识别算法，该算法首先利用二维离散余弦逆变换（DCT）对人脸图像进行压缩，利用二维离散余弦逆变换（IDCT）对图像进行重建，可以去除了人脸图像中的干扰冗余信息。然后通过改进的2D2PCA 算法即分块2D2PCA 提取重建人脸图像中的特征。最后，用最近邻法对人脸图像进行识别，并定义了人脸图像相似度的概念。本文对 ORL 人脸图像数据库进行了实验。实验表明，本文算法有效的增强了识别的鲁棒性，缩短了识别的时间。
위료해결인검식별산법쌍향이유주원분석（2D2PCA）표정적신식불전면，로봉성차、식별속솔교만적문제，제출료일충결합이유리산여현변환（DCT）산법화개진적쌍향이유주성분분석산법（모괴（2D）2PCA）적신적인검도상식별산법，해산법수선이용이유리산여현역변환（DCT）대인검도상진행압축，이용이유리산여현역변환（IDCT）대도상진행중건，가이거제료인검도상중적간우용여신식。연후통과개진적2D2PCA 산법즉분괴2D2PCA 제취중건인검도상중적특정。최후，용최근린법대인검도상진행식별，병정의료인검도상상사도적개념。본문대 ORL 인검도상수거고진행료실험。실험표명，본문산법유효적증강료식별적로봉성，축단료식별적시간。
In order to solve the problems in face recognition algorithm of bidirectional two-dimensional principal component analysis(2D2PCA),such as uncomprehensive information,poor robustness and slower identification rate,this paper proposes a new face recognition algorithm combining two-dimensional discrete cosine transform (DCT)with the improved two-directional two-dimensional principal component analysis algorithm(modules(2D) 2PCA). The algorithm firstly compresses the face image by using two-dimensional discrete cosine inverse transfor-mation(DCT). Using two-dimensional discrete cosine inverse transformation(IDCT)to reconstruct the image can remove the redundant information of the face image. Then the features of face image reconstruction can be extracted by the improved 2D2PCA algorithm called module 2D2PCA. Finally,face image is identified by using the nearest neighbor method and the concept of face image similarity is defined. In this paper,experiments of ORL face image database are conducted,which shows that the new algorithm enhances the robustness of recognition effectively and shortens the time of the recognition.