7 September 2010 Image registration under affine transformation using cellular simultaneous recurrent networks
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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.
© (2010) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Khan M. Iftekharuddin, Khan M. Iftekharuddin, Keith Anderson, Keith Anderson, "Image registration under affine transformation using cellular simultaneous recurrent networks", Proc. SPIE 7797, Optics and Photonics for Information Processing IV, 77970E (7 September 2010); doi: 10.1117/12.862316; https://doi.org/10.1117/12.862316


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