A New Algorithm Using Variations of Image Pixels to Classify Face Images

When the interest operator is used as a feature extraction algorithm for face recognition, the algorithm may encounter the following problem: under complex imaging conditions such as varying facial expression, the feature extraction results of two corresponding blocks from two face images of the sam...

Full description

Saved in:
Bibliographic Details
Published inCISP 2008 : Proceedings, First International Congress on Image and Signal Processing, 27-30 May 2008, Sanya, Hainan, China Vol. 2; pp. 625 - 629
Main Authors Yao, Lu, Xu, Yong
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.05.2008
Subjects
2DFLD
2DPCA
Biomedical signal processing
Biometrics
Computer science
Digital signal processing
Face recognition
Feature extraction
Image databases
Interest operator
Pixel
Robustness
Signal processing algorithms
variations of image pixels
Online AccessGet full text

Cover

More Information
Summary:When the interest operator is used as a feature extraction algorithm for face recognition, the algorithm may encounter the following problem: under complex imaging conditions such as varying facial expression, the feature extraction results of two corresponding blocks from two face images of the same subject may have low similarity. In order to address this problem, we propose a new algorithm in which an original image is first divided into a number of overlapping blocks and then the variations of pixel gray values of each block is calculated. Face recognition based on the new algorithm is able to obtain results with high similarity for the corresponding blocks from two images of the same subject. Experimental results on the FERET face database show that the combination of the proposed algorithm and 2DPCA or 2DFLD offers significant accuracy improvement over the combination of the interest operator and 2DPCA or 2DFLD.
ISBN:9780769531199
0769531199
DOI:10.1109/CISP.2008.139