Volume 19, No. 1, 2022

Driving Active Contours to Concave Regions


Qusay O. Mosa, Ali Saeed Alfoudi, Ahmed A. Brisam, Abayomi M. Otebolaku and Gyu Myoung Lee

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.


Pages: 5131-5140

DOI: 10.14704/WEB/V19I1/WEB19345

Keywords: GVF, Particle Swarm Optimizer, Deep Concavity

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