Projective invariants of co-moments of 2D images

  • Authors:

  • Wang Yuanbin;Zhang Bin;Yao Tianshun

  • Affiliations:

  • School of Information Science and Engineering, Northeastern University, Shenyang 110004, PR China;School of Information Science and Engineering, Northeastern University, Shenyang 110004, PR China;School of Information Science and Engineering, Northeastern University, Shenyang 110004, PR China

  • Venue:
  • Pattern Recognition
  • Year:
  • 2010

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Abstract

Functions of moments of 2D images that are invariant under some changes are important in image analysis and pattern recognition. One of the most basic changes to a 2D image is geometric change. Two images of the same plane taken from different viewpoints are related by a projective transformation. Unfortunately, it is well known that geometric moment invariants for projective transformations do not exist in general. Yet if we generalize the standard definition of the geometric moments and utilize some additional information from the images, certain type of projective invariants of 2D images can be derived. This paper first defines co-moment as a moment-like function of image that contains two reference points. Then a set of functions of co-moments that is invariant under general projective transformations is derived. The invariants are simple and in explicit form. Experimental results validated the mathematical derivations.