Combining Invariant and Corner-Like Features to Optimize Image Matching

  • Jimmy Addison Lee
  • Kin-Choong Yow
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5414)

Abstract

Significance and usefulness of local invariant features and traditional corner-like features have been widely proven in the literature. In this paper, we novelly combine the two types of features to select salient keypoints with the invariant and corner-like properties, which are highly distinctive and improving match performance. We use moment-derived complex image patterns (e.g., corner, T-junction, sectional cut, and chess-cross) to find corner-like features. We further optimize the matching results by finding corner-like patterns in the invariant matched point correspondences; and rebuff point correspondences that have dissimilar pattern responses which are most likely false matches.

Keywords

Keypoint extraction salient keypoints distinctive key-points corner-like patterns 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Jimmy Addison Lee
    • 1
  • Kin-Choong Yow
    • 1
  1. 1.School of Computer EngineeringNanyang Technological UniversitySingapore

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