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Proceedings Paper

Smart mapping for quick detection of dissimilar binary images
Author(s): Adnan A. Y. Mustafa
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Paper Abstract

In previous work, a probabilistic image matching model for binary images was developed that predicts the number of mappings required to detect dissimilarity between any pair of binary images based on the amount of similarity between them. The model showed that dissimilarity can be detected quickly by randomly comparing corresponding points between two binary images. In this paper, we improve on this quickness for images that have dissimilarity concentrated near their centers. We apply smart mapping schemes to different image sets and analyze the results to show the effectiveness of this mapping scheme for images that have dissimilarity concentrated near their center. We compare three different smart mapping schemes with three different mapping densities to find the best mapping / best density performance.

Paper Details

Date Published: 19 June 2017
PDF: 5 pages
Proc. SPIE 10443, Second International Workshop on Pattern Recognition, 104430U (19 June 2017); doi: 10.1117/12.2280291
Show Author Affiliations
Adnan A. Y. Mustafa, Kuwait Univ. (Kuwait)

Published in SPIE Proceedings Vol. 10443:
Second International Workshop on Pattern Recognition
Xudong Jiang; Masayuki Arai; Guojian Chen, Editor(s)

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