Face Recognition using Probabilistic Neural Networks

被引:0
作者
Vinitha, K. V. [1 ]
Kumar, G. Santhosh [1 ]
机构
[1] Cochin Univ Sci & Technol, Dept Comp Sci, Cochin 682016, Kerala, India
来源
2009 WORLD CONGRESS ON NATURE & BIOLOGICALLY INSPIRED COMPUTING (NABIC 2009) | 2009年
关键词
voronoi / delaunay triangulation; ellipse fitting; template matching; cross correlation; edge gradients; peak to side lobe ratio; probabilistic radial basis neural networks;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper we address the problem of face detection and recognition of grey scale frontal view images. We propose a face recognition system based on probabilistic neural networks (PNN) architecture. The system is implemented using voronoi/ delaunay tessellations and template matching. Images are segmented successfully into homogeneous regions by virtue of voronoi diagram properties. Face verification is achieved using matching scores computed by correlating edge gradients of reference images. The advantage of classification using PNN models is its short training time. The correlation based template matching guarantees good classification results.
引用
收藏
页码:1387 / 1392
页数:6
相关论文
共 24 条
[1]  
ANAGNOSTOPOULOS C, 2002, IEEE MELECON 2002 UA
[2]  
[Anonymous], 2004, IEEE T CIRCUITS SYST
[3]  
[Anonymous], BioID Face Database
[4]  
BEVILACQUA V, 2007, AUT ID ADV TECHN 200, P107
[5]   Face recognition based on fitting a 3D morphable model [J].
Blanz, V ;
Vetter, T .
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2003, 25 (09) :1063-1074
[6]   Exploiting Voronoi diagram properties in face segmentation and feature extraction [J].
Cheddad, Abbas ;
Mohamad, Dzulkifli ;
Manaf, Azizah Abd .
PATTERN RECOGNITION, 2008, 41 (12) :3842-3859
[7]  
Costa L., 2001, SHAPE ANAL CLASSIFIC
[8]  
GANDHE ST, 2008, IAENG INT J COMPUTER, V35
[9]  
JIAO F, 2002, 5 AS C COMP VIS 23 2
[10]  
KANAN HR, 2005, INFORM TELECOMMU MAR