Driving Active Contours to Concave Regions

Driving Active Contours to Concave Regions

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 rep...

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Veröffentlicht in:Webology 2022-01, Vol.19 (1), p.6079-6088
Hauptverfasser: Mosa, Qusay O, Alfoudi, Ali Saeed, Brisam, Ahmed A, Otebolaku, Abayomi M, Lee, Gyu Myoung
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Energy
Genetic algorithms
OCR
Optimization
Velocity
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container_issue 1
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container_title Webology
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creator Mosa, Qusay O
Alfoudi, Ali Saeed
Brisam, Ahmed A
Otebolaku, Abayomi M
Lee, Gyu Myoung
description 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.
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subjects Energy
Genetic algorithms
OCR
Optimization
Velocity
title Driving Active Contours to Concave Regions
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