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
相关论文
共 50 条
  • [31] A face recognition algorithm based on optimal feature selection
    Zhao K.
    Wang D.
    Wang Y.
    Revue d'Intelligence Artificielle, 2019, 33 (02) : 105 - 109
  • [32] Chaotic binary particle swarm optimization for feature selection using logistic map
    Chuang, Li-Yeh
    Li, Jung-Chike
    Yang, Cheng-Hong
    IMECS 2008: INTERNATIONAL MULTICONFERENCE OF ENGINEERS AND COMPUTER SCIENTISTS, VOLS I AND II, 2008, : 131 - +
  • [33] Fast Static Particle Swarm Optimization based Feature Selection For Face Detection
    Lei, Fan
    Lu, Yao
    Huang, Wei
    Yu, Lujun
    Jia, Lin
    PROCEEDINGS OF THE 2012 EIGHTH INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND SECURITY (CIS 2012), 2012, : 401 - 405
  • [34] Improved binary particle swarm optimization using catfish effect for feature selection
    Chuang, Li-Yeh
    Tsai, Sheng-Wei
    Yang, Cheng-Hong
    EXPERT SYSTEMS WITH APPLICATIONS, 2011, 38 (10) : 12699 - 12707
  • [35] Hybrid feature selection and weighting method based on binary particle swarm optimization
    Severo, Diogo S.
    Verissimo, Everson
    Cavalcanti, George D. C.
    Ren, Tsang Ing
    2013 IEEE 25TH INTERNATIONAL CONFERENCE ON TOOLS WITH ARTIFICIAL INTELLIGENCE (ICTAI), 2013, : 433 - 438
  • [36] EMG Feature Selection and Classification Using a Pbest-Guide Binary Particle Swarm Optimization
    Too, Jingwei
    Abdullah, Abdul Rahim
    Saad, Norhashimah Mohd
    Tee, Weihown
    COMPUTATION, 2019, 7 (01):
  • [37] An Improved Niching Binary Particle Swarm Optimization For Feature Selection
    Dong, Hongbin
    Sun, Jing
    Li, Tao
    Li, Lijie
    2018 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC), 2018, : 3571 - 3577
  • [38] Feature Selection using Feature Ranking, Correlation Analysis and Chaotic Binary Particle Swarm Optimization
    Wang, Fei
    Yang, Yi
    Lv, Xianchao
    Xu, Jiao
    Li, Lian
    2014 5TH IEEE INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING AND SERVICE SCIENCE (ICSESS), 2014, : 305 - 309
  • [39] Enhanced Particle Swarm Optimization Algorithm Based on SVM Classifier for Feature Selection
    Wang, Xing
    Liu, Huazhen
    Hussien, Abdelazim G.
    Hu, Gang
    Zhang, Li
    CMES-COMPUTER MODELING IN ENGINEERING & SCIENCES, 2025, 142 (03): : 2791 - 2839
  • [40] Face recognition using particle swarm optimization based block ICA
    Rasmikanta Pati
    Arun K Pujari
    Padmavati Gahan
    Multimedia Tools and Applications, 2021, 80 : 35685 - 35695
12345