Volume 38 Issue 8
Aug.  2012
Turn off MathJax
Article Contents
Xue Bindang, Xing Yanqi. Fresnel transform based invariant moments extraction and object recognition method[J]. Journal of Beijing University of Aeronautics and Astronautics, 2012, 38(8): 1001-1004,1063. (in Chinese)
Citation: Xue Bindang, Xing Yanqi. Fresnel transform based invariant moments extraction and object recognition method[J]. Journal of Beijing University of Aeronautics and Astronautics, 2012, 38(8): 1001-1004,1063. (in Chinese)

Fresnel transform based invariant moments extraction and object recognition method

  • Received Date: 12 Apr 2011
  • Publish Date: 30 Aug 2012
  • An invariant moments feature extraction method based on Fresnel transform was proposed, and applied to image recognition. The original image was mapped into the Fresnel diffraction projection space by using the Fresnel transform. The geometric or orthogonal moment invariants were extracted in the diffraction space, from which the characterization of the global image information can be obtained. The k-nearest neighbor classifier was employed to implement objects classification. Experimental results show that the proposed moment invariants extraction method achieves high recognition rates for different combinations of translation, scaling and rotation and is very robust to noise.

     

  • loading
  • [1]
    Flusser J,Zitova B,Suk T.Moments and moment invariants in pattern recognition[M].United Kingdom:John Wiley & Sons Ltd,2009
    [2]
    Zhang Lei,Pu Jiexin,Yu Jia.Object recognition based on modified invariant moments[C]//International Conference on Mechatronics and Automation,2009.Changchun:IEEE,2009:2542-2547
    [3]
    Han Jianning,Wang Mingquan.Research on digital image recognition system based on multiple invariant moments theory and BP neural network[C]//2010 2nd International Asia Conference on Informatics in Control,Automation and Robotics (CAR).Wuhan:IEEE,2010,3:399-403
    [4]
    Papakostas G A,Karakasis E G,Koulouriotis D E.Novel moment invariants for improved classification performance in computer vision applications[J].Pattern Recognition,2010,43(1):58-68
    [5]
    Papakostas G A,Boutalis Y S,Karras D A,et al.Pattern classification by using improved wavelet compressed Zernike moments[J].Applied Mathematics and Computation,2009,212(1):162-176
    [6]
    Hu M K.Visual pattern recognition by moment invariants[J].IRE Transactions on Information Theory,1962,8(2):179-187
    [7]
    Singh C,Walia E.Fast and numerically stable methods for the computation of Zernike moments[J].Pattern Recognition,2010,43(7):2497-2506
    [8]
    Hosny K M.A systematic method for efficient computation of full and subsets Zernike moments[J].Information Sciences,2010,180(11):2299-2313
    [9]
    Zhang Hui,Shu Huazhong,Han Guoniu,et al.Blurred image recognition by Legendre moment invariants[J].IEEE Transactions on Image Processing,2010,19(3):596-611
    [10]
    Papakostas G A,Karakasis E G,Koulouriotis D E.Accurate and speedy computation of image Legendre moments for computer vision applications[J].Image and Vision Computing,2010,28(3):414-423
    [11]
    Papakostas G,Boutalis Y,Karras D,et al.Efficient computation of Zernike and Pseudo-Zernike moments for pattern classification applications[J].Pattern Recognition and Image Analysis,2010,20(1):56-64
    [12]
    Mukundan R,Ong S H,Lee P A.Image analysis by tchebichef moments[J].IEEE Transactions on Image Processing,2001,10(9):1357-1364
    [13]
    Deng Cheng,Gao Xinbo,Li Xuelong,et al.A local tchebichef moments-based robust image watermarking[J].Signal Processing,2009,89(8):1531-1539
    [14]
    Kan C,Srinath M D.Invariant character recognition with Zernike and orthogonal Fourier-Mellin moments[J].Pattern Recognition,2002,35(1):143-154
    [15]
    Zhang Hui,Shu Huahzong,Haigron P,et al.Construction of a complete set of orthogonal Fourier-Mellin moment invariants for pattern recognition applications[J].Image and Vision Computing,2010,28(1):38-44
    [16]
    Flusser J.On the independence of rotation moment invariants[J].Pattern Recognition,2000,33(9):1405-1410
    [17]
    Miao Zhenjiang.Zernike moment-based image shape analysis and its application[J].Pattern Recognition Letters,2000,21(2):169-177
    [18]
    Born M,Wolf E.Principles of optics:electromagnetic theory of propagation,interference and diffraction of light[M].New York:Cambridge University Press,1999
    [19]
    Billinge S J L,Thorpe M F.Local structure from diffraction[M].New York:Springer Us,1998
    [20]
    Garcia-Sucerquia J,Medina F F,Barrera J F.Minute details detection through Fresnel diffraction domain[J].Optics Communications,2005,253(4-6):250-256
    [21]
    Sabatyan A,Taghi Tavassoly M.Determination of refractive indices of liquids by Fresnel diffraction[J].Optics & Laser Technology,2009,41(7):892-896
    [22]
    Goodman J W.Introduction to Fourier optics[M].Greenwood Village,Colorado,USA:Roberts & Company Publishers,2005
    [23]
    Liebling M,Blu T,Unser M.Fresnelets:new multiresolution wavelet bases for digital holography[J].IEEE Transactions on,Image Processing,2003,12(1):29-43
    [24]
    Liebling M,Blu T,Unser M.Fresnelets:A new wavelet basis for digital holography[C]//Proceedings of the SPIE Conference on Mathematical Imaging:Wavelet Applications in Signal and Image Processing IX.San Diego,CA,USA:Citeseer,2001,4478:347-352
    [25]
    蔡履中,王永钤.菲涅耳衍射在标度-距离变换下的相似性[J].山东大学学报:理学版,2001,36(1):56-61
    Cai Lvzhong ,Wang Yongqian.The Similiarity of Fresnel diffraction under scale-distance transform[J].Journal of Shandong University:Natural Science Edition,2001,36(1):56-61(in Chinese)
    [26]
    Lazebnik S,Schmid C,Ponce J.A maximum entropy framework for part-based texture and object recognition[C]//Tenth IEEE International Conference on Computer Vision,2005.2005,1:832-838
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Article Metrics

    Article views(1885) PDF downloads(527) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return