Quaternion Zernike moments and their invariants for color image analysis and object recognition

  • Authors:

  • B. J. Chen;H. Z. Shu;H. Zhang;G. Chen;C. Toumoulin;J. L. Dillenseger;L. M. Luo

  • Affiliations:

  • Laboratory of Image Science and Technology, Southeast University, Nanjing 210096, China and Centre de Recherche en Information Biomédicale Sino-Français (CRIBs), Nanjing 210096, China an ...;Laboratory of Image Science and Technology, Southeast University, Nanjing 210096, China and Centre de Recherche en Information Biomédicale Sino-Français (CRIBs), Nanjing 210096, China;Laboratory of Image Science and Technology, Southeast University, Nanjing 210096, China;Laboratory of Image Science and Technology, Southeast University, Nanjing 210096, China;INSERM, U642, Rennes, F-35000, France and Université de Rennes 1, LTSI, Rennes, F-35000, France and Centre de Recherche en Information Biomédicale Sino-Français (CRIBs), Nanjing 210 ...;INSERM, U642, Rennes, F-35000, France and Université de Rennes 1, LTSI, Rennes, F-35000, France and Centre de Recherche en Information Biomédicale Sino-Français (CRIBs), Nanjing 210 ...;Laboratory of Image Science and Technology, Southeast University, Nanjing 210096, China and Centre de Recherche en Information Biomédicale Sino-Français (CRIBs), Nanjing 210096, China

  • Venue:
  • Signal Processing
  • Year:
  • 2012

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Abstract

Moments and moment invariants have become a powerful tool in pattern recognition and image analysis. Conventional methods to deal with color images are based on RGB decomposition or graying, which may lose some significant color information. In this paper, by using the algebra of quaternions, we introduce the quaternion Zernike moments (QZMs) to deal with the color images in a holistic manner. It is shown that the QZMs can be obtained from the conventional Zernike moments of each channel. We also provide the theoretical framework to construct a set of combined invariants with respect to rotation, scaling and translation (RST) transformation. Experimental results are provided to illustrate the efficiency of the proposed descriptors.