CAJ | 학술논문

为了提高人脸的识别率，提出一种方向梯度直方图和多流形判别分析相融合的人脸识别算法。将一幅图像划分为多个子块图像块，并采用方向梯度直方图算法对每一个小块进行处理；采用多流形判别分析提取特征，并采用最小二乘支持向量机建立分类器对人脸进行分类和识别；在Yale和AR人脸库进行仿真实验。实验结果表明，相对于传统人脸别算法，该算法不仅提高了人脸识别率和识别速度，并且对光照和姿态变化具有较强的鲁棒性。
위료제고인검적식별솔，제출일충방향제도직방도화다류형판별분석상융합적인검식별산법。장일폭도상화분위다개자괴도상괴，병채용방향제도직방도산법대매일개소괴진행처리；채용다류형판별분석제취특정，병채용최소이승지지향량궤건립분류기대인검진행분류화식별；재Yale화AR인검고진행방진실험。실험결과표명，상대우전통인검별산법，해산법불부제고료인검식별솔화식별속도，병차대광조화자태변화구유교강적로봉성。
In order to improve the recognition rate of face, a new face recognition method is proposed based on histogram oriented gradient and discriminative multi-manifold. Firstly, the face image is divided into several patches and the patches are processed by histogram oriented gradient to form an image set. Secondly, discriminative multi-manifold is used to select the features, and least squares support vector machine is used to establish the classifier to recognized the face. Finally, the simulation experiments are carried out to test the performance on Yale and AR face data set. The experimental results show that the proposed method can improve the recognition rate and recognition speed compared with traditional face recognition methods, and has well robust for face recognition in illumination and pose conditions.