Mosa, QO, Alfoudi, AS, Brisam, AA, Otebolaku, AM and Lee, GM (2022) Driving Active Contours to Concave Regions. Webology, 19 (1). pp. 5131-5140. ISSN 1735-188X

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Abstract

Broken characters restoration represents the major challenge of optical character recognition (OCR). Active contours, which have been used successfully to restore ancient documents with high degradations have drawback in restoring characters with deep concavity boundaries. Deep concavity problem represents the main obstacle, which has prevented Gradient Vector Flow active contour in converge to objects with complex concavity boundaries. In this paper, we proposed a technique to enhance (GVF) active contour using particle swarm optimization (PSO) through directing snake points (snaxels) toward correct positions into deep concavity boundaries of broken characters by comparing with genetic algorithms as an optimization method. Our experimental results showed that particle swarm optimization outperform on genetic algorithm to correct capturing the converged areas and save spent time in optimization process.

Item Type:	Article
Uncontrolled Keywords:	0805 Distributed Computing; 0807 Library and Information Studies; Information & Library Sciences
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:	Computer Science and Mathematics
Publisher:	NeuroQuantology Journal
SWORD Depositor:	A Symplectic
Date Deposited:	06 Jan 2025 14:40
Last Modified:	06 Jan 2025 14:40
DOI or ID number:	10.14704/web/v19i1/web19345
URI:	https://researchonline.ljmu.ac.uk/id/eprint/25182

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