The Science and Information (SAI) Organization
  • Home
  • About Us
  • Journals
  • Conferences
  • Contact Us

Publication Links

  • IJACSA
  • Author Guidelines
  • Publication Policies
  • Digital Archiving Policy
  • Promote your Publication
  • Metadata Harvesting (OAI2)

IJACSA

  • About the Journal
  • Call for Papers
  • Editorial Board
  • Author Guidelines
  • Submit your Paper
  • Current Issue
  • Archives
  • Indexing
  • Fees/ APC
  • Reviewers
  • Apply as a Reviewer

IJARAI

  • About the Journal
  • Archives
  • Indexing & Archiving

Special Issues

  • Home
  • Archives
  • Proposals
  • Guest Editors
  • SUSAI-EE 2025
  • ICONS-BA 2025
  • IoT-BLOCK 2025

Computing Conference

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Intelligent Systems Conference (IntelliSys)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Computer Vision Conference (CVC)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact
  • Home
  • Call for Papers
  • Editorial Board
  • Guidelines
  • Submit
  • Current Issue
  • Archives
  • Indexing
  • Fees
  • Reviewers
  • Subscribe

DOI: 10.14569/IJACSA.2015.060801
PDF

Competitive Sparse Representation Classification for Face Recognition

Author 1: Ying Liu
Author 2: Jian-Xun Mi
Author 3: Cong Li
Author 4: Chao Li

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 6 Issue 8, 2015.

  • Abstract and Keywords
  • How to Cite this Article
  • {} BibTeX Source

Abstract: A method, named competitive sparse representation classification (CSRC), is proposed for face recognition in this paper. CSRC introduces a lowest competitive deletion mechanism which removes the lowest competitive sample based on the competitive ability of training samples for representing a probe in multiple rounds collaborative linear representation. In other words, in each round of competing, whether a training sample is retained or not in the next round depends on the ability of representing the input probe. Because of the number of training samples used for representing the probe decreases in CSRC, the coding vector is transformed into a low dimensional space comparing with the initial coding vector. Then the sparse representation makes CSRC discriminative for classifying the probe. In addition, due to the fast algorithm, the FR system has less computational cost. To verify the validity of CSRC, we conduct a series of experiments on AR, Extended YB, and ORL databases respectively.

Keywords: face recognition; collaborative representation sparse representation; and competitive representation

Ying Liu, Jian-Xun Mi, Cong Li and Chao Li, “Competitive Sparse Representation Classification for Face Recognition” International Journal of Advanced Computer Science and Applications(IJACSA), 6(8), 2015. http://dx.doi.org/10.14569/IJACSA.2015.060801

@article{Liu2015,
title = {Competitive Sparse Representation Classification for Face Recognition},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2015.060801},
url = {http://dx.doi.org/10.14569/IJACSA.2015.060801},
year = {2015},
publisher = {The Science and Information Organization},
volume = {6},
number = {8},
author = {Ying Liu and Jian-Xun Mi and Cong Li and Chao Li}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

IJACSA

Upcoming Conferences

IntelliSys 2025

28-29 August 2025

  • Amsterdam, The Netherlands

Future Technologies Conference 2025

6-7 November 2025

  • Munich, Germany

Healthcare Conference 2026

21-22 May 2026

  • Amsterdam, The Netherlands

Computing Conference 2026

9-10 July 2026

  • London, United Kingdom

IntelliSys 2026

3-4 September 2026

  • Amsterdam, The Netherlands

Computer Vision Conference 2026

15-16 October 2026

  • Berlin, Germany
The Science and Information (SAI) Organization
BACK TO TOP

Computer Science Journal

  • About the Journal
  • Call for Papers
  • Submit Paper
  • Indexing

Our Conferences

  • Computing Conference
  • Intelligent Systems Conference
  • Computer Vision Conference
  • Healthcare Conference

Help & Support

  • Contact Us
  • About Us
  • Terms and Conditions
  • Privacy Policy

© The Science and Information (SAI) Organization Limited. All rights reserved. Registered in England and Wales. Company Number 8933205. thesai.org