doi:10.16186/j.cnki.1673-9787.2020040103

Received:2020/04/28

Revised:2020/06/15

Published:2021/09/15

Research and implementation of face recognition algorithm based on LBP and ELM

WANG Hongxing1, HU Yongyang2, DENG Chao1

1.School of Physics and Electronic Information Engineering， Henan Polytechnic University， Jiaozuo  454000 ， Henan， China;2.School of Mechanical and Power Engineering， Henan Polytechnic University， Jiaozuo  454000 ， Henan， China

Abstract:Aiming at the problem that traditional local binary pattern（ LBP） is easy to be affected by gray and noise in face feature extraction ， an improved LBP algorithm was proposed based on traditional LBP. This meth-od calculated the sum of the squares of the difference between each pixel in the neighborhood and the center pixel C.lf the C was within a limited range ， the central pixel was selected as the threshold for calculation ， and the roles of the central pixel value and the domain pixel value was fully considered to describe the local features more accurately. Otherwise ，the median value of the neighborhood pixel and the center pixel was selected as the threshold value for comparison to reduce the influence of noise points. Principal component analysis（ PCA ）was used to reduce the face feature dimension extracted by LBP. In order solve to the shortcomings of the ordinary extreme learning machine （ ELM ） ， a weighted conjugate kernel extreme learning machine（WCCKELM） was introduced to classify the face features. Experimental results showed that the algorithm can effectively improve the face recognition rate.

Key words:weighted conjugate kernel extreme learning machine;local binary pattern;principal component analysis;face recognition feature extraction

 基于LBP和ELM的人脸识别算法研究与实现_王红星.pdf