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Proceedings Paper

Image registration under affine transformation using cellular simultaneous recurrent networks
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Paper Abstract

Cellular simultaneous recurrent networks (CSRN)s have been traditionally exploited to solve the digital control and conventional maze traversing problems. In previous works, we investigated the use of CSRNs to register simulated binary images with in-plane rotations between ±20° using two different CSRN architectures such as one with a general multi-layered perceptron (GMLP) architecture; and another with modified MLP architecture with multilayered feedback. We further exploit the CSRN for registration of realistic binary and gray scale images under rotation. In this current work we report results of applying CSRNs to perform image registration under affine transformations such as rotation and translation. We further provide extensive analyses of CSRN affine registration results for appropriate cost function formulation. Our CSRN results analyses show that formulation of locally varying cost function is desirable for robust image registration under affine transformation.

Paper Details

Date Published: 7 September 2010
PDF: 8 pages
Proc. SPIE 7797, Optics and Photonics for Information Processing IV, 77970E (7 September 2010); doi: 10.1117/12.862316
Show Author Affiliations
Khan M. Iftekharuddin, The Univ. of Memphis (United States)
Keith Anderson, The Univ. of Memphis (United States)

Published in SPIE Proceedings Vol. 7797:
Optics and Photonics for Information Processing IV
Abdul Ahad Sami Awwal; Khan M. Iftekharuddin; Scott C. Burkhart, Editor(s)

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