Fast Bilateral Symmetry Detection Using Inverted Gradient Hash Maps

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Author(s)
Gonzalez, R
Lincoln, L
Year published
2016
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This paper presents a fast and novel algorithm for bilateral symmetry detection based on inverted gradient hash maps (IGHMs). A hash map is an associative array that stores image gradient magnitudes and orientations in the form of an inverted index. This mapping of image gradients to their locations permits points of interest to be located very rapidly without needing to search through the image. Unlike many symmetry operators it is able to detect large-scale symmetry. The method is described and experimentally evaluated against existing methods for bilateral symmetry detection.This paper presents a fast and novel algorithm for bilateral symmetry detection based on inverted gradient hash maps (IGHMs). A hash map is an associative array that stores image gradient magnitudes and orientations in the form of an inverted index. This mapping of image gradients to their locations permits points of interest to be located very rapidly without needing to search through the image. Unlike many symmetry operators it is able to detect large-scale symmetry. The method is described and experimentally evaluated against existing methods for bilateral symmetry detection.
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Conference Title
NATURE OF COMPUTATION AND COMMUNICATION (ICTCC 2016)
Volume
168
Copyright Statement
© 2016 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering. This is the author-manuscript version of this paper. Reproduced in accordance with the copyright policy of the publisher. The original publication is available at www.springerlink.com.
Subject
Computer vision