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非线性Radon变换及其在人脸识别中的应用 被引量：3

Nonlinear Radon Transform and Its Application to Face Recognition
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摘要 探讨抛物线、双曲线、椭圆3种非线性Radon变换及其性质,分析它们之间的关系,并将所述3种非线性Radon变换应用于人脸识别.通过对这3种非线性Radon变换及其性质研究得出,当抛物线、双曲线及椭圆的形状参数趋于无穷大时,图像抛物线Radon变换与线性Radon变换相等,双曲线Radon变换与椭圆Radon变换相等;同时,非线性Radon变换具有降噪功能和表达图像纹理特征的特点.文中将受噪声污染的人脸图像分别表示为3种非线性Radon变换下的特征矩阵,并结合PCA算法应用于人脸识别.实验结果表明非线性Radon变换在人脸识别中的有效性. Three nonlinear Radon transforms, including parabola, hyperbola, and ellipse Radon transform, are studied respectively, and the relationships among them are analyzed. Then, the three nonlinear Radon transforms are applied to face recognition. When shape parameters of parabola, hyperbola, and ellipse are approximately infinite, linear Radon transform of image is equal to parabola Radon transform and hyperbola Radon transform is equal to ellipse Radon transform. Nonlinear Radon transform possesses the characters of reducing noise and can be used to represent texture features of image. Moreover, polluted face images are represented by feature matrix via three nonlinear Radon transforms, and then combined with principal component analysis in face recognition. Experimental results demonstrate the validity of nonlinear Radon transform in face recognition.
作者 甘俊英 何思斌
机构地区 五邑大学信息工程学院
出处 《模式识别与人工智能》 EI CSCD 北大核心 2011年第3期405-410,共6页 Pattern Recognition and Artificial Intelligence
基金 国家自然科学基金项目(No.61072127 No.61070167) 广东省自然科学基金项目(No.10152902001000002 No.07010869) 广东省高等学校高层次人才项目(粤教师函[2010]79号)资助
关键词 非线性Radon变换 线性Radon变换 主元分析 人脸识别 Nonlinear Radon Transform, Linear Radon Transform, Principal Component Analysis,Face Recognition
分类号 TP391.41 [自动化与计算机技术—计算机应用技术]
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参考文献12

  • 1Zhang Daoqiang, Chen Songcan, Zhou Zhihua. A New Face Recog- nition Method Based on SVD Perturbation for Single Example Image per Person. Applied Mathematics and Computation, 2005, 163 ( 2 ) : 895 - 907.
  • 2Moon H, Phillips P J. Computational and Performance Aspects of PCA-Based Face Recognition Algorithms. Perception, 2001, 30 (3) : 303 -321.
  • 3Lu Juwen, Plataniotis K N, Venetsanopoulos A N. Face Recognition Using LDA-Based Algorithms. IEEE Trans on Neural Network, 2003, 14(1) : 195 -200.
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  • 5Hendriks C L L, van Ginkel M, Verbeek P W, et al. The General- ized Radon Transform: Sampling, Accuracy and Memory Considera- tions. Pattern Recognition, 2005, 38(12): 2494-2505.
  • 6Gui Peiling, Li Junhong, Pan Quan, et al. Rotation and Scaling In- variant Texture Classification Based on Radon Transform and Multi- Scale Analysis. Pattern Recognition Letters, 2006, 27 (5) : 408 - 413.
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同被引文献17

  • 1田沄,徐亮,张琦,薛耿剑,郝重阳.基于Radon变换的医学图像增强方法[J].微电子学与计算机,2006,23(5):12-14. 被引量：8
  • 2赵凌君,贾承丽,匡纲要.SAR图像边缘检测方法综述[J].中国图象图形学报,2007,12(12):2042-2049. 被引量：36
  • 3Zhang Junhua,Yang Cun,Xu Hui,et al.High Resolution Parabolic Radon Transform by Frquency Domain Method for Eliminating Multiple[C]//Proc of Cogress on Image and Signal Processing.Sanya,China,2008:233-237.
  • 4Trad D O,Ulry ch T J,Sacchi M D.Accurate Interpolation with High-Resolution Time-Variant Radon Transform[J].Geophysics,2002,67 (2):644-656.
  • 5Terrades O R,Valveny E.Radon Transform for Lineal Symbol Representation[C]//Proc of the 7th International Conference on Document Analysis and Recognition.Edinburgh,Scotland,2003,I:195-199.
  • 6Gui Peiling,Li Junhong,Pan Quan,et al.Rotation and Scaling Invariant Texture Classification Based on Radon Transformand Multi-scale Analysis[J].Pattern Recognition Letters,2006,27 (5):408-413.
  • 7Maiorana E,Campisi P,Neri A.Biometric Signature Authentication Using Radon Transform-Based Watermarking Techniques[C]//Proc of the Biometrics Symposium.Baltimore,USA,2007:1-6.
  • 8Dattatray V.Jadhav,Raghunath S.Holambe.Radon and discrete cosine transforms based feature extreaction and dimensioality reduction approach for face recognition[J].Signal Processing,2008,88 (10):2604-2609.
  • 9Tan X,Triggs B.Enhanced local texture feature sets for face recongnition under difficult lighting conditions[J].IEEE Trans on Image Processing,2010,19 (6):1635-1650.
  • 10ZHANG Yi,XIONG Fei,ZHANG Guilin.A Preprocessing Algorithm for Illimination Invariant Face Recognition[J].Journal of Image and Graphics,2008,13(9):1707-1712.

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模式识别与人工智能
2011年 第3期

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