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

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

NIE Hai-tao1, 2, LONG Ke-hui1, MA Jun1, ZHANG Lei1, MA Xi-qiang3   

  1. 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

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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

CLC Number: 

  • TP391
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