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Proposed Image Similarity Measurement Model based on Hypergraph

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International Journal of Computer Applications
© 2014 by IJCA Journal
Volume 96 - Number 21
Year of Publication: 2014
Authors:
A. E. A. Elaraby
Alain Bretto
10.5120/16918-6543

A E A Elaraby and Alain Bretto. Article: Proposed Image Similarity Measurement Model based on Hypergraph. International Journal of Computer Applications 96(21):41-43, June 2014. Full text available. BibTeX

@article{key:article,
	author = {A. E. A. Elaraby and Alain Bretto},
	title = {Article: Proposed Image Similarity Measurement Model based on Hypergraph},
	journal = {International Journal of Computer Applications},
	year = {2014},
	volume = {96},
	number = {21},
	pages = {41-43},
	month = {June},
	note = {Full text available}
}

Abstract

In this article, we propose a new image similarity measurement model (SMM) based hypergraph which is easy to calculate and applicable to various image processing application. Hypergraphs are now used in many domains such as chemistry, engineering and image processing. We present an overview of a hypergraph-based Image representation and the Image Adaptive Neighborhood Hypergraph (IANH). With the IANH it is possible to build a new powerful similarity measurement model. Although the new model is mathematically defined and no human visual system model is explicitly employed, our experiments on various image distortion types indicate the efficient of proposed model.

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