Optimal Feature Selection based on Image Pre-processing using Accelerated Binary Particle Swarm Optimization for Enhanced Face Recognition

被引：11
|
作者：
Aneesh, M. U. [1 ]
Masand, Abhishek A. K. [1 ]
Manikantan, K. [1 ]
机构：
[1] MS Ramaiah Inst Technol, Bangalore 560054, Karnataka, India
来源：
INTERNATIONAL CONFERENCE ON COMMUNICATION TECHNOLOGY AND SYSTEM DESIGN 2011 | 2012年 / 30卷
关键词：
Face Recognition; Image Pre-processing; Feature Selection; Feature Extraction; DCT; ABPSO;
D O I：
10.1016/j.proeng.2012.01.924
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Feature Selection is an optimization problem in any Face Recognition technology. This paper proposes a novel method of Binary Particle Swarm Optimization called Accelerated Binary Particle Swarm Optimization (ABPSO) by intelligent acceleration of particles. Together with Image Pre-processing techniques such as Resolution Conversion, Histogram Equalization and Edge Detection, ABPSO is used for feature selection to obtain significantly reduced feature subset and improved recognition rate. The performance of ABPSO is established by computing the recognition rate and the number of selected features on ORL database and Cropped Yale B database. (C) 2011 Published by Elsevier Ltd. Selection and/or peer-review under responsibility of ICCTSD 2011.
引用
收藏
页码：750 / 758
页数：9
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