计算机应用与软件2016，Vol.33Issue(9)：143-146,153,5.DOI:10.3969/j.issn.1000-386x.2016.09.034
自适应中心对称局部三值模式的人脸识别
FACE RECOGNITION BASED ON CENTROSYMMETRIC LOCAL TERNARY PATTERN WITH ADAPTIVE THRESHOLD
摘要
Abstract
In this paper we propose a new method called centrosymmetric local ternary pattern with adaptive threshold (CS-LTPAT)to ad-dress the shortcomings of local ternary pattern in too high the histogram dimension and not being able to adaptively select threshold when de-scribing the texture features of face image.First,the method encodes the face image with the dimension-lowered centrosymmetric local ternary pattern (CS-LTP)operator,and introduces the neighbourhood pixel mean value to encoding for enhancing the anti-noise performance;Second-ly,it embeds the standard deviation of statistical neighbourhood average and neighbourhood surrounding pixel as the threshold to extract the fa-cial feature adaptively,and counts the features histograms.Finally,it uses chi-square to measure the similarity of training sample features histo-gram and test sample features histogram,and employs the nearest neighbour classifier in recognition.The proposed approach is applied to YALE and Extended Yale B standard face database,result shows that the highest correct recognition rates reach 99.67% and 99.33% respec-tively,and the speed of identifying a face reach 0.1984s and 0.3988 s respectively.Experimental result demonstrates that the proposed method effectively improves the accuracy and speed of the face recognition,and is more robust on the illumination variation and noise.关键词
人脸识别/中心对称/局部三值模式/自适应阈值Key words
Face recognition/Centrosymmetry/Local ternary pattern/Adaptive threshold分类
信息技术与安全科学引用本文复制引用
闫河,王朴,刘婕,陈伟栋..自适应中心对称局部三值模式的人脸识别[J].计算机应用与软件,2016,33(9):143-146,153,5.基金项目
国家自然科学基金面上项目（61173184）；重庆理工大学研究生创新基金项目（YCX2013219）。 （）
