中文摘要：

结合人脸图像的对称性在非迭代双边二维主成分分析（NIB2DPCA）的基础上，提出了对称非迭代双边二维主成分分析（SNIB2DPCA）的人脸识别方法。该方法引入镜像变换，根据奇偶分解原理分别生成奇、偶对称样本，用NIB2DPCA分别对奇偶对称样本提取特征，通过奇偶加权因子对奇偶对称样本的特征矩阵进行组合得到最终的分类特征矩阵，最后用最近邻分类器分类。在Yale、ORL和YaleB人脸库上的实验表明该方法不仅显著提高了识别率，而且对光照影响有一定的鲁棒性。

英文摘要：

This paper proposed a new algorithm called SNIB2DPCA, which combined the theory of NIB2DPCA with frontal fa- cial symmetry. Firstly, it introduced mirror transform. After that, it decomposed original face samples into even symmetrical ima- ges and odd symmetrical ones through the theory of odd/even decomposition. Then employed NIB2DPCA to extract feature in- formation from odd and even.symmetrical samples separately. After that, combined the odd and even feature matric to form the final feature matrie by the odd/even weighted factors. Finally,it employed the nearest neighbor classifier to classify the final feature matrie. The method was evaluated on the Yale , ORL and YaleB face image databases. Both theoretical analysis and experimental results demonstrate that the proposed method not only significantly raises the recognition rate, but also has certain robustness to the influence of light.