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FACE LOCALIZATION AND DETECTION BASED ON SYMMETRY DETECTION AND TEXTURE FEATURES

International Journal of Electronic Commerce Studies

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Title FACE LOCALIZATION AND DETECTION BASED ON SYMMETRY DETECTION AND TEXTURE FEATURES
 
Creator Lin, Chuen-Horng
Cai, Jyun-An
Liao, Shik-Kuan
 
Subject Face Detection; Adaptive Smoothing; Symmetry Detection; Texture Feature
 
Description This study refers mainly to the characteristics of symmetry and texture features in order to correctly locate a face within an image. Since we target facial expression and illumination variation in a facial image, this first requires an equalization process of adaptive smoothing of the shadows of the face caused by varying illumination. Following this, for symmetry axis detection, the study will address: Gradient Detection, Image Width and Location of Symmetry Axes, Symmetry Axes for Gradient Histogram (SAGH) and Selection; Weight is also added to strengthen symmetry characteristics. In order to verify the accuracy of the method, this study will use 6 experimental methods, namely SAGH, SAPG, WSAGH, WSAPG, WSAGH for no adaptive smoothing, and WSAPG for no adaptive smoothing. The image database used for this experiment is the Yale Face Database, with facial images that are subjected to different illumination, masked by shelters and displaying varying facial expressions. The experiment results show that the WSAPG method is the most accurate; achieving a 96.36% LM value, with the lowest GM value; it was the most successful at locating a face in the image. Hopefully it will be applied to enhancing current face recognition technology.


To cite this document: Chuen-Horng Lin, Jyun-An Cai, and Shik-Kuan Liao, "Face localization and detection based on symmetry detection and texture features", International Journal of Electronic Commerce Studies, Vol.3, No.2, pp.191-210, 2012.

Permanent link to this document:
http://dx.doi.org/10.7903/ijecs.1076
 
Publisher Academy of Taiwan Information Systems Research
 
Date 2013-01-17
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion

 
Format application/pdf
 
Identifier http://academic-pub.org/ojs/index.php/ijecs/article/view/1076
 
Source International Journal of Electronic Commerce Studies; Vol 3, No 2 (2012); 191-210
2073-9729
 
Language eng
 
Relation http://academic-pub.org/ojs/index.php/ijecs/article/view/1076/134
 
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