A Metaheuristic Algorithm for OCR Baseline Detection of Arabic Languages

A Metaheuristic Algorithm for OCR Baseline Detection of Arabic Languages

F. Daneshfar, W. Fathy, B. Alaqeband
ISBN13: 9781522552048|ISBN10: 1522552049|EISBN13: 9781522552055
DOI: 10.4018/978-1-5225-5204-8.ch027
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MLA

Daneshfar, F., et al. "A Metaheuristic Algorithm for OCR Baseline Detection of Arabic Languages." Computer Vision: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, IGI Global, 2018, pp. 707-734. https://doi.org/10.4018/978-1-5225-5204-8.ch027

APA

Daneshfar, F., Fathy, W., & Alaqeband, B. (2018). A Metaheuristic Algorithm for OCR Baseline Detection of Arabic Languages. In I. Management Association (Ed.), Computer Vision: Concepts, Methodologies, Tools, and Applications (pp. 707-734). IGI Global. https://doi.org/10.4018/978-1-5225-5204-8.ch027

Chicago

Daneshfar, F., W. Fathy, and B. Alaqeband. "A Metaheuristic Algorithm for OCR Baseline Detection of Arabic Languages." In Computer Vision: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, 707-734. Hershey, PA: IGI Global, 2018. https://doi.org/10.4018/978-1-5225-5204-8.ch027

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Abstract

Preprocessing is a very important part of cursive languages Optical Character Recognition (OCR) systems. Thus, baseline detection, which is one of the main parts of the preprocessing operation, plays a basic role on OCR systems; improvement on baseline detection could be absolutely useful for decreasing errors in recognition words. In this chapter, a metaheuristic- and mathematical-based algorithm is recommended, which has improved the baseline detection process in relation to the well-known baseline detection algorithms. The most important advantages of the proposed method are simplicity, high speed processing, and reliability. To test this novel solution, IFN/ENIT database, which is a well-known and attending database, is utilized. However, the proposed solution is reliable to any standard database of cursive language's OCR.

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