[1]顼 聪,朱 毅,陶永鹏.面向方向选择的差值局部方向模式的人脸识别[J].南京师大学报(自然科学版),2020,43(04):113-118.[doi:10.3969/j.issn.1001-4616.2020.04.016]
 Xu Cong,Zhu Yi,Tao Yongpeng.Face Recognition Based on Direction-SelectedDifference Local Direction Pattern[J].Journal of Nanjing Normal University(Natural Science Edition),2020,43(04):113-118.[doi:10.3969/j.issn.1001-4616.2020.04.016]
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面向方向选择的差值局部方向模式的人脸识别()
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《南京师大学报(自然科学版)》[ISSN:1001-4616/CN:32-1239/N]

卷:
第43卷
期数:
2020年04期
页码:
113-118
栏目:
·智慧应急信息技术·
出版日期:
2020-12-30

文章信息/Info

Title:
Face Recognition Based on Direction-SelectedDifference Local Direction Pattern
文章编号:
1001-4616(2020)04-0113-06
作者:
顼 聪朱 毅陶永鹏
大连外国语大学软件学院,辽宁 大连 116044
Author(s):
Xu CongZhu YiTao Yongpeng
College of Software,Dalian University of Foreign Language,Dalian 116044,China
关键词:
人脸识别特征提取Kirsch算子局部方向模式
Keywords:
face recognitionfeature extractionKirsch operatorlocal direction pattern
分类号:
TP391
DOI:
10.3969/j.issn.1001-4616.2020.04.016
文献标志码:
A
摘要:
针对目前人脸识别方法中的特征提取缺乏细节和运算量较大的问题,提出一种面向方向选择的差值局部方向模式人脸识别算法(Direction-Selected Difference Local Direction Pattern)DSDLDP,首先利用Kirsch算子计算像素的卷积值,并进行第一次相邻差值计算,然后选择特定方向进行二次差值计算生成DSDLDP模式编码,并利用等价模式降低编码模式种类. 最后人脸图像被划分成多个通过DSDLDP编码的图像块,生成对应的直方图,串联起来表示人脸向量. 实验结果表明,与当前主流的人脸识别算法相比,DSDLDP算法提取人脸特征更为细致,识别率更高,抗噪声有更好的鲁棒性.
Abstract:
Aiming at the problems of lack of detail and large amount of computation in feature extraction in current face recognition methods,a direction-selected difference local direction pattern was proposed. This method uses Kirsch operator to calculate the convolution value of the pixel,and performs the first adjacent difference calculation,and then selects the specific direction for the second difference calculation to generate DSDLDP mode encoding,and uses the equivalent mode to reduce the type of encoding mode.Finally,the face image is divided into multiple image blocks encoded by DSDLDP to generate corresponding histograms,which are connected in series to represent the face vector.Simulation experiment results show that compared with the current mainstream face recognition algorithms,DSDLDP algorithm extracts facial features more meticulously,with higher recognition rate,and has better robustness against noise.

参考文献/References:

[1] AMIT D,ALIN D. Probabilistic characterization of nearest neighbor classifier[J]. International journal of machine learning and cybernetics,2013,4(4):259-272.
[2]HUANG D,SHAN C F,ARDABILIAN M,et al. Local binary patterns and its application to facial image analysis:a survey[J]. IEEE transactions on systems man and cybernetics,part C—applications and reviews,2011,41(6):765-781.
[3]TAN X Y,TRIGGS B. Enhanced local texture feature sets for face recognition under difficult lighting conditions[J]. IEEE transactions on image processing,2010,19(6):1635-1650.
[4]张毅,廖巧珍,罗元. 融合二阶HOG与CS-LBP的头部姿态估计[J]. 智能系统学报,2015,10(5):741-746.
[5]WANG K,BICHOT C E,LI Y,et al. Local binary circumferential and radial derivative pattern for texture classification[J]. Pattern recognition,2017,67(1):213-229.
[6]GUO Z H,LI Q,YOU J,et al. Local directional derivative pattern for rotation invariant texture classification[J]. Neural computing and applications,2012,21(8):1893-1904.
[7]JABID T,KABIR M H,CHAE O. Local Directional Pattern(LDP)for face recognition[C]//Proceedings of 2010 Digest of Technical Papers International Conference on Consumer Electronics. Las Vegas,America,2010:329-330.(2).
[8]李照奎,丁立新,王岩,等. 基于差值局部方向模式的人脸特征表示[J]. 软件学报,2015,26(11):2912-2929.
[9]王晓华,李瑞静,胡敏,等. 融合局部特征的面部遮挡表情识别[J]. 中国图象图形学报,2016,21(11):1473-1482.
[10]ISSAM E K,ABDERRAZAK C,YOUSSEF E M,,et al. Local directional ternary pattern:a new texture descriptor for texture classification[J]. Computer vision and image understanding,2018,169(1):14-27.
[11]YANG H,WANG Y D. A LBP-based face recognition method with Hamming distance constraint[C]//Fourth International Conference on Image and Graphics. Beijing,China,2007:645-649.
[12]LAJEVARDI S M,HUSSAIN Z M. Higher order orthogonal moments for invariant facial expression recognition[J]. Digital signal processing,2010,20(6):1771-1779.
[13]王玮,黄非非,李见为. 采用LBP金字塔的人脸描述与识别[J]. 计算机辅助设计与图形学学报,2009,21(1):94-100.
[14]杨恢先,刘建,张孟娟,等. 双差值局部方向模式的人脸识别[J]. 智能系统学报,2018,13(5):751-759.
[15]OJALA T,PIETIKAINEN M. Multiresolution gray-scale and rotation invariant texture classification with local binary patterns[J]. IEEE transactions on pattern analysis and machine intelligence,2002,24(7):971-987.
[16]RAHULAMATHAVAN Y,PHANR C W,CHAMBERS J A,et al. Facial expression recognition in the encrypted domain based on local fisher discriminant analysis[J]. IEEE transactions on affective computing,2013,4(1):83-92.

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备注/Memo

备注/Memo:
收稿日期:2020-07-08.
基金项目:辽宁省自然科学基金指导项目(2019-ZD-0514)、大连外国语大学科研基金项目(2018XJYB29).
通讯作者:顼聪,讲师,研究方向:图像处理. E-mail:xucongdlmu@163.com
更新日期/Last Update: 2020-11-15