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Article Details

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.

NEB in Analysis of Natural Image 8 × 8 and 9 × 9 High-contrast Patches

Author 1: Shengxiang Xia
Author 2: Wen Wang

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Digital Object Identifier (DOI) : 10.14569/IJACSA.2016.070572

Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 7 Issue 5, 2016.

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Abstract: In this paper we use the nudged elastic band tech-nique from computational chemistry to investigate sampled high-dimensional data from a natural image database. We randomly sample 8 × 8 and 9 × 9 high-contrast patches of natural images and create a density estimator believed as a Morse function. By the Morse function we build one-dimensional cell complexes from the sampled data. Using one-dimensional cell complexes, we identify topological properties of 8 × 8 and 9 × 9 high-contrast natural image patches, we show that there exist two kinds of subsets of high-contrast 8 × 8 and 9 × 9 patches modeled as a circle, by the new method we confirm some results obtained through the method of computational topology.

Keywords: nudged elastic band; natural image high-contrast patch; cell complex; density function

Shengxiang Xia and Wen Wang, “NEB in Analysis of Natural Image 8 × 8 and 9 × 9 High-contrast Patches” International Journal of Advanced Computer Science and Applications(IJACSA), 7(5), 2016. http://dx.doi.org/10.14569/IJACSA.2016.070572

@article{Xia2016,
title = {NEB in Analysis of Natural Image 8 × 8 and 9 × 9 High-contrast Patches},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2016.070572},
url = {http://dx.doi.org/10.14569/IJACSA.2016.070572},
year = {2016},
publisher = {The Science and Information Organization},
volume = {7},
number = {5},
author = {Shengxiang Xia and Wen Wang}
}


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