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Proceedings Paper

Color feature and density-based image mosaicing using repeated application of the ICP algorithm
Author(s): Samuel H Chang; Joseph Fuller; Ali Farsaie; Les Elkins
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Paper Abstract

A Color Feature and Density based (CFD) image mosaicing (IM) algorithm is presented in this paper. In the initial step, color image segmentation is used to provide a global match between an image pair. The well-known Iterated Closest Point (ICP) algorithm is used to find a transformation for global alignment. Finally, the ICP algorithm is applied again to find a transformation for local adjustment. By using this approach, it is shown that we can guarantee global alignment accuracy because the feature based method is used to find the initial matching of two image frames. We achieve local optimal pixel alignment based on the minimization of the Sum of Squares of Differences (SSD) between two images from the same overlapping area.

Paper Details

Date Published: 21 May 2004
PDF: 9 pages
Proc. SPIE 5299, Computational Imaging II, (21 May 2004); doi: 10.1117/12.524846
Show Author Affiliations
Samuel H Chang, Spatial Integrated Systems, Inc. (United States)
Joseph Fuller, Spatial Integrated Systems, Inc. (United States)
Ali Farsaie, Spatial Integrated Systems, Inc. (United States)
Les Elkins, Spatial Integrated Systems, Inc. (United States)


Published in SPIE Proceedings Vol. 5299:
Computational Imaging II
Charles A. Bouman; Eric L. Miller, Editor(s)

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