Please use this identifier to cite or link to this item:
|Title:||Face recognition using voting technique for the Gabor and LDP features||Authors:||Dagher, Issam
|Affiliations:||Department of Computer Engineering||Keywords:||Visual databases
|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|
Show full item record
checked on Oct 25, 2021
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.