Skip to main content
padlock icon - secure page this page is secure

Application of Particle Swarm Optimization in Face Sketch Recognition

Buy Article:

$106.51 + tax (Refund Policy)

In this paper, Particle Swarm Optimization (PSO) is applied for the problem of face sketch recognition. The novelty of this work originates from two-folds, i.e., formulating of face sketch problem as an optimization problem, and adopting PSO algorithm to solve the formulated problem. In particular, PSO is employed to perform localization of sketch facial components (e.g., eyes region, nose region, and mouth region), and then, these localized components are matched with database gallery photos to recognize the input sketch image. To evaluate the effectiveness of the proposed approach, two benchmark sketch images are used, i.e., CUHK database, and AR database. The reported results demonstrate the effectiveness of PSO algorithm in solving face sketch recognition problem as compared with other reported results in the literature.
No Reference information available - sign in for access.
No Citation information available - sign in for access.
No Supplementary Data.
No Article Media
No Metrics

Keywords: AR Database; CUHK Database; Face Sketch Recognition; Particle Swarm Optimization

Document Type: Research Article

Affiliations: School of Electrical and Electronic Engineering, Universiti Sains Malaysia, Malaysia

Publication date: November 1, 2017

More about this publication?
  • ADVANCED SCIENCE LETTERS is an international peer-reviewed journal with a very wide-ranging coverage, consolidates research activities in all areas of (1) Physical Sciences, (2) Biological Sciences, (3) Mathematical Sciences, (4) Engineering, (5) Computer and Information Sciences, and (6) Geosciences to publish original short communications, full research papers and timely brief (mini) reviews with authors photo and biography encompassing the basic and applied research and current developments in educational aspects of these scientific areas.
  • Editorial Board
  • Information for Authors
  • Subscribe to this Title
  • Ingenta Connect is not responsible for the content or availability of external websites
  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content
Cookie Policy
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more