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Proceedings Paper

Gradient-based registration of rotated, scaled, and translated images
Author(s): Xiangguo Li
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Paper Abstract

The paper presents a gradient-based algorithm for image registration. The algorithm is extended from the classical Lucas-Kanade algorithm, and it aims to solve the rotation-scale-translation (RST) model. To solve the problem, the 6- parameter affine model is used, and the algorithm is derived according to the idea of the Lucas-Kanade algorithm, then the RST model parameters are obtained from the estimated affine model values. Due to its Taylor approximation nature, iterative scheme is needed, and the inverse compositional scheme by Keren et al. is used. To further increase the speed and convergence range, coarse-to-fine strategy is also used. In the final, simulations are performed to verify and evaluate the algorithm, and the results demonstrate that it can obtain sub-pixel estimation with high accuracy.

Paper Details

Date Published: 27 October 2013
PDF: 4 pages
Proc. SPIE 8919, MIPPR 2013: Pattern Recognition and Computer Vision, 891917 (27 October 2013); doi: 10.1117/12.2031607
Show Author Affiliations
Xiangguo Li, Henan Univ. of Technology (China)

Published in SPIE Proceedings Vol. 8919:
MIPPR 2013: Pattern Recognition and Computer Vision
Zhiguo Cao, Editor(s)

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