Face Recognition under Varying Illumination with Logarithmic Fractal Analysis

Face recognition under illumination variations is a challenging research area. This paper presents a new method based on the log function and the fractal analysis (FA) to produce a logarithmic fractal dimension (LFD) image which is illumination invariant. The proposed FA feature-based method is a ve...

Full description

Saved in:
Bibliographic Details
Published inIEEE signal processing letters Vol. 21; no. 12; pp. 1457 - 1461
Main Authors Faraji, Mohammad Reza, Xiaojun Qi
Format Journal Article
LanguageEnglish
Published New York IEEE 01.12.2014
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Accuracy
Eyes
Face
Face recognition
Facial
Fractal analysis
Fractals
Illumination
illumination variation
Image edge detection
Invariants
Lighting
logarithmic fractal dimension
Nose
Online AccessGet full text

Cover

More Information
Summary:Face recognition under illumination variations is a challenging research area. This paper presents a new method based on the log function and the fractal analysis (FA) to produce a logarithmic fractal dimension (LFD) image which is illumination invariant. The proposed FA feature-based method is a very effective edge enhancer technique to extract and enhance facial features such as eyes, eyebrows, nose, and mouth. Our extensive experiments show the proposed method achieves the best recognition accuracy using one image per subject for training when compared to six recently proposed state-of-the-art methods.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ObjectType-Article-2
ObjectType-Feature-1
content type line 23
ISSN:1070-9908
1558-2361
DOI:10.1109/LSP.2014.2343213