A hybrid approach based on MEP and CSP for contour registration

  • Authors:

  • Xiuyang Zhao;Caiming Zhang;Yanan Wang;Bo Yang

  • Affiliations:

  • School of Information Science and Engineering, University of Jinan, No. 106 Jiwei Road, Jinan 250022, Shandong, PR China and School of Computer Science and Technology, Shandong University, Jinan 2 ...;School of Computer Science and Technology, Shandong University, Jinan 250101, Shandong, PR China;School of Information Science and Engineering, University of Jinan, No. 106 Jiwei Road, Jinan 250022, Shandong, PR China;School of Information Science and Engineering, University of Jinan, No. 106 Jiwei Road, Jinan 250022, Shandong, PR China

  • Venue:
  • Applied Soft Computing
  • Year:
  • 2011

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Abstract

Image registration is a fundamental task in 3D reconstruction from an image sequence. Although has been studied for decades, it is still rare to find a general, robust and automatic image registration method, and most existing image registration methods are designed for particular application. In this paper, image registration is boil down to a formula discovery problem to match feature points, we develop a new feature-based algorithm for contour registration automatically based on a hybrid approach combining Multi Expression Programming (MEP) with Clonal Selection Principle (CSP). Firstly, the image contours are extracted by fast global minimization of the active contour model, the feature point pairs which are used to establish training set of the hybrid approach are obtained using invariable moments. Secondly, the registration equations are acquired automatically by the proposed hybrid approach and the contours are then registered based on the equations. Experiments show that the proposed approach can be successfully applied to register the image pairs in which the contour information is well preserved.