Global registration of overlapping images using accumulative image features

  • Authors:
  • Karthik Krish;Stuart Heinrich;Wesley E. Snyder;Halil Cakir;Siamak Khorram

  • Affiliations:
  • North Carolina State University, Raleigh, NC 27695, USA;North Carolina State University, Raleigh, NC 27695, USA;North Carolina State University, Raleigh, NC 27695, USA;North Carolina State University, Raleigh, NC 27695, USA;North Carolina State University, Raleigh, NC 27695, USA

  • Venue:
  • Pattern Recognition Letters
  • Year:
  • 2010

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Abstract

This paper introduces a new feature-based image registration technique which registers images by finding rotation- and scale-invariant features and matching them using a novel feature matching algorithm based on an evidence accumulation process reminiscent of the generalized Hough transform. Once feature correspondence has been established, the transformation parameters are then estimated using non-linear least squares (NLLS) and the standard RANSAC (random sample consensus) algorithm. The technique is evaluated under similarity transforms - translation, rotation and scale (zoom) and also under illumination changes.