Facial Expression Recognition Based on Gabor Wavelet Phase Features

Gabor wavelet transform usually extracts features using Gabor amplitude features, because the Gabor amplitude reflects the energy spectrum of the image, but the phase information contains rich texture information. This paper proposes a facial expression recognition algorithm using Gabor wavelet phas...

Full description

Saved in:
Bibliographic Details
Published in2013 Seventh International Conference on Image and Graphics pp. 520 - 523
Main Authors Shi Dongcheng, Cai Fang, Du Guangyi
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.07.2013
Subjects
Expression feature extraction
Face
Face recognition
Facial expression recognition
Feature extraction
Gabor filters
Gabor wavelet transform
Image recognition
Phase feature
Wavelet transforms
Online AccessGet full text

Cover

More Information
Summary:Gabor wavelet transform usually extracts features using Gabor amplitude features, because the Gabor amplitude reflects the energy spectrum of the image, but the phase information contains rich texture information. This paper proposes a facial expression recognition algorithm using Gabor wavelet phase features. First, facial positioning on the human face, extracting facial sub-graphs, and normalizing the expression features of the sub-graphs. Then, using a multi-orientation and multi-frequency set of 2D Gabor wavelet to transform expression, and combining of Gabor coefficient after the transformation so that it can extract the phase characteristics. With K - nearest neighbor classifier to classify, the experimental results that conducted on the JAFFE database demonstrates its efficiency and validity.
DOI:10.1109/ICIG.2013.110