Please use this identifier to cite or link to this item: https://scholarhub.balamand.edu.lb/handle/uob/554
Title: Face recognition using voting technique for the Gabor and LDP features
Authors: Dagher, Issam 
Hassanieh, Jamal
Younes, Ahmad
Affiliations: Department of Computer Engineering 
Keywords: Visual databases
Face recognition
Feature extraction
Gabor filters
Image matching
Issue Date: 2014
Publisher: IEEE
Part of: The 2013 International Joint Conference on Neural Networks (IJCNN)
Start page: 1
End page: 6
Conference: International Joint Conference on Neural Networks (IJCNN) (4-9 Aug. 2013 : Dallas, TX, USA) 
Abstract: 
Face recognition can be described by a sophisticated mathematical representation and matching procedures. In this paper, Local Derivative Pattern (LDP) descriptors along with the Gabor feature extraction technique were used to achieve highest percentage of recognition possible. A robust comparison method, the Chi Square Distance, was used as a matching algorithm. Four databases involving different image capturing conditions: positioning, illumination and expressions were used. The best results were obtained after applying a voting technique to the Gabor and the LDP features.
URI: https://scholarhub.balamand.edu.lb/handle/uob/554
Ezproxy URL: Link to full text
Type: Conference Paper
Appears in Collections:Department of Computer Engineering

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