Order reprints

Feature extraction of face image based on LBP and 2-D Gabor wavelet transform

Qian Zhang Haigang Li Ming Li Lei Ding

*Corresponding author: Haigang Li lihaigang@cumt.edu.cn


Affected by illumination, gesture, expression and other factor’s variation, face image pattern is easy to be changed, so it is important to find a robust data representation for the correct classification of face pattern. In this paper, a face image recognition algorithm based on 2-D Gabor wavelet transform and Local Binary Pattern (LBP) is proposed. LBP is a local describe operator, which is invariant against illumination variation. 2-D Gabor wavelet transform have the invariant property against pose and expression variation. Experimental results show that the large scale 2-D Gabor wavelet representation could get good classification accuracy. Using LBP to describe 2-D Gabor wavelet representation of face image, together with image block, histogram statistics, PCA dimensionality reduction, nearestneighbors classification, we finally find this algorithm can get a better classification performance in different scales and directions.

Please supply your name and a valid email address you yourself

Fields marked*are required

Article URL   http://www.aimspress.com/MBE/article/4476.html
Article ID   mbe-17-02-082
Editorial Email  
Your Name *
Your Email *
Quantity *

Copyright © AIMS Press All Rights Reserved