Data fusion for face recognition

Jamal Ahmad Dargham, and Chekima, Ali and Ervin Moung, and S. Omatu, (2010) Data fusion for face recognition. In: 7th International Symposium on Distributed Computing and Artificial Intelligence, 7th October 2010, Polytech Univ Valencia, Valencia, SPAIN.

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Face recognition is an important biometric because of its potential applications in many fields, such as access control, surveillance, and human-computer interface. In this paper, we propose a rule-based face recognition system that fuses the output of two face recognition systems based on principal component analysis (PCA). One system uses the face image while the other use the Radon transform of the same face image. In addition, both systems use the Euclidean distance is the matching criteria. Both systems are trained using the same training images database, and fed with the same test input image at same time and the recognition result of each system is serving as input for the fusion decision stage. The proposed system is found to be better (97% recognition rate for recall and 93% for reject) than either system alone

Item Type: Conference or Workshop Item (UNSPECIFIED)
Uncontrolled Keywords: Data fusion, Face recognition
Subjects: ?? TK8300-8360 ??
Divisions: SCHOOL > School of Engineering and Information Technology
Depositing User: Unnamed user with email
Date Deposited: 15 Aug 2011 06:37
Last Modified: 30 Dec 2014 01:35

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