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Application of Particle Swarm Optimization in Face Sketch Recognition

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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.
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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

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  • 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.
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