Text line segmentation of offline malayalam handwritten document

Automatic handwriting recognition systems rely on text line segmentation. Text line segmentation faces a number of obstacles, such as irregular text line gaps, slanted text lines, cursive handwriting, and other similar problems. Furthermore, line segmentation is worse when dealing with noisy and unc...

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Main Authors: Anju, A. T., Chacko, Binu P., Basheer, K. P. Mohammad
Format: Conference Proceeding
Language:English
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Documents
Handwriting recognition
Segmentation
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Chacko, Binu P.
Basheer, K. P. Mohammad
description Automatic handwriting recognition systems rely on text line segmentation. Text line segmentation faces a number of obstacles, such as irregular text line gaps, slanted text lines, cursive handwriting, and other similar problems. Furthermore, line segmentation is worse when dealing with noisy and uncontrolled scanned handwritten manuscripts; dealing with Malayalam handwriting, which has a complicated style and character set, makes the process slightly more challenging. For the purpose of text line segmentation in unconstrained Malayalam handwritten scanned documents, this script independent technique primarily used morphological operations and contour extraction. More than that, the Hough line transform was used to fix the skewness of the scanned document picture. There were successful trials of the approach on ten other scripts, including Bengali, Devanagari, Gujarati, Gurumukhi, Kannada, Oriya, Roman, Tamil, Telugu, and Urdu.
doi_str_mv 10.1063/5.0211999
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source American Institute of Physics:Jisc Collections:Transitional Journals Agreement 2021-23 (Reading list)
subjects Documents
Handwriting recognition
Segmentation
title Text line segmentation of offline malayalam handwritten document
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