Face recognition using support vector model classifier for user authentication

作者：

Highlights：

• We present an online SVM-based face-recognition system using user facial features.

• The Olivetti, NCKU, and FERET Research Lab database of user facial features were used.

• The global precision of face recognition was over 97% with cross-validation scheme.

• Our scheme provided a higher precision of face recognition than that of the existing schemes (89%).

摘要

•We present an online SVM-based face-recognition system using user facial features.•The Olivetti, NCKU, and FERET Research Lab database of user facial features were used.•The global precision of face recognition was over 97% with cross-validation scheme.•Our scheme provided a higher precision of face recognition than that of the existing schemes (89%).

论文关键词：E-commerce,SVM,Face recognition,Wavelet transforms,Local binary pattern

论文评审过程：Received 12 March 2015, Revised 24 January 2016, Accepted 31 January 2016, Available online 9 February 2016, Version of Record 25 July 2016.

论文官网地址：https://doi.org/10.1016/j.elerap.2016.01.005