Research Article
Proposed Image Similarity Measurement Model based on Hypergraph
|
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
|
| Volume 96 - Issue 21 |
| Published: June 2014 |
| Authors: A. E. A. Elaraby, Alain Bretto |
10.5120/16918-6543
|
A. E. A. Elaraby, Alain Bretto . Proposed Image Similarity Measurement Model based on Hypergraph. International Journal of Computer Applications. 96, 21 (June 2014), 41-43. DOI=10.5120/16918-6543
@article{ 10.5120/16918-6543,
author = { A. E. A. Elaraby,Alain Bretto },
title = { Proposed Image Similarity Measurement Model based on Hypergraph },
journal = { International Journal of Computer Applications },
year = { 2014 },
volume = { 96 },
number = { 21 },
pages = { 41-43 },
doi = { 10.5120/16918-6543 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2014
%A A. E. A. Elaraby
%A Alain Bretto
%T Proposed Image Similarity Measurement Model based on Hypergraph%T
%J International Journal of Computer Applications
%V 96
%N 21
%P 41-43
%R 10.5120/16918-6543
%I Foundation of Computer Science (FCS), NY, USA
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.
References
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