基于SIFT和Hough变换的人脸识别  

Face Recognition Based on SIFT and Hough Transform

作　　者：叶汉能[1] 姚茂群[1] 赵武锋[2] 

机构地区：[1]杭州师范大学信息科学与工程学院,杭州310036 [2]浙江大学信息与电子工程学系,杭州310027

出　　处：《计算机工程》2012年第14期144-146,共3页Computer Engineering

摘　　要：针对光照、表情、遮挡、几何变化等情况下的人脸识别问题,提出一种基于尺度不变特征变换(SIFT)和增强Hough变换的人脸识别方法。利用SIFT的位置、尺度、方向和描述符4个信息,通过增强Hough变换消除错配,将候选匹配点和离散点距离进行加权累计获得高辨别力的匹配分。在AR人脸数据库上的测试结果表明,在只选取每人1幅图像作为模板的情况下,能够获得近99.6%的识别率。Aiming at the difficulties of face recognition such as change in illumination, expression variation, partial occlusion and geometrical transformation, a face recognition method based on Scale-invariant Feature Transform（SIFT） and enhanced Hough transform is proposed. By using four parts of SIFT features and the enhanced Hough transform, the false matches are removed effectively, and the score having high discrimination ability is obtained through weighting more information. Experimental results performed on the AR face database demonstrate that about 99.6% of recognition rates are achieved under selecting only one image per person as template.

关 键 词：尺度不变特征变换 HOUGH变换 人脸识别 特征提取 匹配策略 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]