Classifying of Human Face Images Based on the Graph Theory Concepts

Classifying of Human Face Images Based on the Graph Theory Concepts

α

Mohammed Abed

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σ

Dr. Jassim T.Sarsoh

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ρ

Kadhem M.Hashem

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Ѡ

Mohammed Abed .Al-Hadi daykh

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α Thi Qar University

Classifying of Human Face Images Based on the Graph Theory Concepts

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Abstract

The purpose of this paper is to propose an effective clustering algorithm. The principle idea of this algorithm depends on the graphic theory by using the terms and definitions of the graph and the tree. The proposed algorithm was applied on different human face images taken from ORL database, and it gives good clustering results with small rate of error. Matlab version (8) was used to implement this algorithm.

References

13 Cites in Article

Reference Format

V Starovoitov,D Samal,B Sankur (1997). Matching of faces in camera images and document photographs.
I Craw,D,A Beautt (1992). Finding Face Features.
T Kande (1977). Analysis of Human-Face Pictures.
R Gonzalez,Wintz (2002). Digital Image Processing.
A Jain,M Murty,P Flynn (1999). Data Clustering Review.
Osama Abu,Abbas (2008). Comparison Between Data Clustering Algorithms.
Z Chen (1978). Clustering with k-nearest Neighbors Threshold of Edge Detection.
Erik Mooi,Marko Sarstedt (2011). Cluster Analysis.
J O ' Callachan (1975). An Alternative Definition for "Neighborhood of a Point".
Ore Oystein (1978). Graphs and Their Uses.
W Chen (1971). Applied Graph Theory.
T Jassim,Kadhem Sarsoh,Hashem (2007). Jassim M. Jawad Bochner curvature tensor of Almost Kahler manifold.
T Jassim,Saraoh (2007). Effects of Facial Segments Features on Human Face Classification.

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Mohammed Abed. 2012. \u201cClassifying of Human Face Images Based on the Graph Theory Concepts\u201d. Global Journal of Computer Science and Technology - F: Graphics & Vision GJCST-F Volume 12 (GJCST Volume 12 Issue F13): .

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GJCST Volume 12 Issue F13
Pg. 23- 27

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Keywords

Clustering Face recognition Graph Theory image processing Neighborhood

Submission ReceivedFebruary 11, 2012
Peer Review Double Blind
Handling Editor
Accepted March 2, 2012
Published March 15, 2012

Version of record

v1.2

Issue date

October 22, 2012

Language

en

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Article Matrices

Total Score: 108

Country: Iraq

Subject: Global Journal of Computer Science and Technology - F: Graphics & Vision

Authors: Dr. Jassim T.Sarsoh, Kadhem M.Hashem, Mohammed Abed .Al-Hadi daykh (PhD/Dr. count: 1)

View Count (all-time): 242

Total Views (Real + Logic): 10108

Total Downloads (simulated): 2807

Publish Date: 2012 10, Mon

Monthly Totals (Real + Logic):

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Total Views: 10108

Total Downloads: 2807

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Published Article

The purpose of this paper is to propose an effective clustering algorithm. The principle idea of this algorithm depends on the graphic theory by using the terms and definitions of the graph and the tree. The proposed algorithm was applied on different human face images taken from ORL database, and it gives good clustering results with small rate of error. Matlab version (8) was used to implement this algorithm.

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