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Comparative analysis of face recognition algorithms and investigation on the significance of color

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Comparative analysis of face recognition algorithms and investigation on the significance of color

Karimi, Behnam (2006) Comparative analysis of face recognition algorithms and investigation on the significance of color. Masters thesis, Concordia University.

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Abstract

Face recognition technology has rapidly evolved and become more popular in recent years. It is being used for both research and other applications such as security systems. One of the key challenges in face recognition systems is to identify the role of different cues for face identification. The role of color, which appears to be a salient attribute of faces, is debated within the literature. Some research has suggested that it confers little recognition advantage for identifying faces. Other research suggests that color is a very important cue in face identification. The clear perception of colors in the environment illustrates that color must be important in the interpretation of complex scenes and recognizing objects in the environment. In this thesis several face recognition methods are introduced. Experiments were conducted using both grayscale and color images. The accuracy of each algorithm has been identified and a comparison was performed between them in terms of recognition rates. A system is also proposed, which uses color features for face recognition. This system can be used by different face recognition algorithms. The goal of this study is to show the differences between some popular face recognition methods (new and traditional) and also the role of color in face recognition using different face recognition algorithms. The results of our experiments show that using color improves the recognition rate for traditional and new methods. The improvement is more obvious for traditional methods because the recognition rate is not near the peak

Divisions:Concordia University > Faculty of Engineering and Computer Science > Computer Science and Software Engineering
Item Type:Thesis (Masters)
Authors:Karimi, Behnam
Pagination:x, 133 leaves : ill. ; 29 cm.
Institution:Concordia University
Degree Name:M. Comp. Sc.
Program:Computer Science and Software Engineering
Date:2006
Thesis Supervisor(s):Krzyzak, Adam
ID Code:9196
Deposited By:Concordia University Libraries
Deposited On:18 Aug 2011 14:46
Last Modified:18 Aug 2011 14:46
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