基于快速SIFT算法和模糊控制的人脸识别

doi:10.13229/j.cnki.jdxbgxb201602033

吉林大学学报(工学版) ›› 2016, Vol. 46 ›› Issue (2): 549-555.doi: 10.13229/j.cnki.jdxbgxb201602033

基于快速SIFT算法和模糊控制的人脸识别

聂海涛^{1, 2}, 龙科慧¹, 马军¹, 张雷¹, 马喜强³

1.中国科学院长春光学精密机械与物理研究所, 长春130033;
2.中国科学院大学, 北京 100039;
3.河南科技大学河南省机械设计及传动系统重点实验室,河南洛阳 471003

收稿日期:2014-07-22 出版日期:2016-02-20 发布日期:2016-02-20
通讯作者: 龙科慧(1958-),女,研究员,博士生导师.研究方向:航天相机调焦系统.E-mail:long_kh@163.com E-mail:kelek2@126.com
作者简介:聂海涛(1986-),男,博士研究生.研究方向:图像处理.E-mail:kelek2@126.com
基金资助:
中科院长春光机所创新基金项目(Y2CX1SS125)

Face recognition based on fast scale invariant feature transform algorithm and fuzzy control

NIE Hai-tao^{1, 2}, LONG Ke-hui¹, MA Jun¹, ZHANG Lei¹, MA Xi-qiang³

1.Changchun Institute of Optics, Fine Mechanics and Physics, University of Chinese Academy of Science ,Changchun 130033,China;
2. University of Chinese Academy of Sciences, Beijing 100039, China;
3. He'nan Key Lab for Machinery Design & Transmission System, He'nan University of Technology and Science, Luoyang 471003, China

Received:2014-07-22 Online:2016-02-20 Published:2016-02-20

摘要/Abstract

摘要： 针对传统的人脸识别系统在复杂背景情况下不能实时准确进行人脸识别的问题,提出一种基于快速尺度不变特征变换(SIFT)算法结合模糊控制的人脸识别方法.首先,由SIFT特征点子区域方向直方图计算得到4个新角度,代表特征点方向信息.然后,在特征匹配阶段,根据SIFT特征点角度信息以及大小限制特征点匹配范围,简化算法复杂程度,得到快速SIFT算法.最后,引入闭环模糊控制系统,减少SIFT特征误匹配,提高人脸识别率.实验结果表明:基于快速SIFT算法的人脸识别方法平均识别时间提升了40%,在发生光照,姿态,表情等均有变化的复杂环境下人脸识别精度提高10%.

关键词: 计算机应用, 人脸识别, SIFT算法, 特征匹配, 模糊控制

Abstract: Most traditional face recognition systems can not be implemented for fast and accurate face recognition under cluttered background. To solve this problem, an improved Scale Invariant Feature Transform (SIFT) method and a fuzzy control strategy are proposed. First, four new angles are computed from the sub-region orientation histogram, which represent the orientation information of each SIFT feature. Then, the progress of face recognition is limited in a range based on the new angles, meanwhile the SIFT features are split into two types according to the size; only the features of the same type are computed, leading to significant simplification of the algorithm, thus a fast SIFT algorithm is obtained. Finally, a fuzzy closed loop control system is applied to increase the accuracy of face recognition, which leads to a decrement of the incorrect matching. The results show that the computing speed of the improved SIFT method is raised more than 40% comparing with the original SIFT algorithm and the recognition rate is raised 10% even under the clutter conditions where the illumination, posture or expression are changing.

Key words: computer application, face recognition, SIFT algorithm, feature matching, fuzzy control

中图分类号:

TP391

聂海涛, 龙科慧, 马军, 张雷, 马喜强. 基于快速SIFT算法和模糊控制的人脸识别[J]. 吉林大学学报(工学版), 2016, 46(2): 549-555.

NIE Hai-tao, LONG Ke-hui, MA Jun, ZHANG Lei, MA Xi-qiang. Face recognition based on fast scale invariant feature transform algorithm and fuzzy control[J]. 吉林大学学报(工学版), 2016, 46(2): 549-555.

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基于快速SIFT算法和模糊控制的人脸识别

Face recognition based on fast scale invariant feature transform algorithm and fuzzy control

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