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DOI: 10.14569/SpecialIssue.2011.010111
PDF

Automatic Image Registration Using Mexican Hat Wavelet, Invariant Moment, and Radon Transform

Author 1: Jignesh N Sarvaiya
Author 2: Dr. Suprava Patnaik

International Journal of Advanced Computer Science and Applications(IJACSA), Special Issue on Image Processing and Analysis, 2011.

  • Abstract and Keywords
  • How to Cite this Article
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Abstract: Image registration is an important and fundamental task in image processing used to match two different images. Given two or more different images to be registered, image registration estimates the parameters of the geometrical transformation model that maps the sensed images back to its reference image. A feature-based approach to automated imageto- image registration is presented. The characteristic of this approach is that it combines Mexican-Hat Wavelet, Invariant Moments and Radon Transform. Feature Points from both images are extracted using Mexican-Hat Wavelet and controlpoint correspondence is achieved with invariant moments. After detecting corresponding control points from reference and sensed images, to recover scaling and rotation a line and triangle is form in both images respectively and applied radon transform to register images.

Keywords: Image Registration; Mexican-hat wavelet; Invariant Moments; Radon Transform.

Jignesh N Sarvaiya and Dr. Suprava Patnaik, “Automatic Image Registration Using Mexican Hat Wavelet, Invariant Moment, and Radon Transform” International Journal of Advanced Computer Science and Applications(IJACSA), Special Issue on Image Processing and Analysis, 2011. http://dx.doi.org/10.14569/SpecialIssue.2011.010111

@article{Sarvaiya2011,
title = {Automatic Image Registration Using Mexican Hat Wavelet, Invariant Moment, and Radon Transform},
journal = {International Journal of Advanced Computer Science and Applications(IJACSA), Special Issue on Image Processing and Analysis}
doi = {10.14569/SpecialIssue.2011.010111},
url = {http://dx.doi.org/10.14569/SpecialIssue.2011.010111},
year = {2011},
publisher = {The Science and Information Organization},
volume = {1},
number = {1},
author = {Jignesh N Sarvaiya and Dr. Suprava Patnaik},
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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