A new watershed model based system for character segmentation in degraded text lines

Kavitha, A.; Shivakumara, Palaiahnakote; Kumar, G. Hemantha; Lü, Tong

doi:10.1016/j.aeue.2016.11.007

Cited by 20 publications

(5 citation statements)

References 11 publications

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“…One of the main useful features of the proposed scheme is automatic and enhanced word identification. Beside the Chinese language, there are studies which applied word segmentation for Urdu [26], Russian [40], Arabic [13], Vietnamese [52], Akkadian [55], Indian [59] and South Indian [59]. However, other studies [22] [44] and [32] applied sentence segmentation to analyze Arabic, Greek, and Malay languages accordingly.…”

Section: Resultsmentioning

confidence: 99%

Text Segmentation Techniques: A Critical Review

Pak

Teh

2017

Innovative Computing, Optimization and Its Applications

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Text segmentation is widely used for processing text. It is a method of splitting a document into smaller parts, which is usually called segments. Each segment has its relevant meaning. Those segments categorized as word, sentence, topic, phrase or any information unit depending on the task of the text analysis. This study presents various reasons of usage of text segmentation for different analyzing approaches. We categorized the types of documents and languages used. The main contribution of this study includes a summarization of 50 research papers and an illustration of past decade (January 2007-January 2017)'s of research that applied text segmentation as their main approach for analysing text. Results revealed the popularity of using text segmentation in different languages. Besides that, the "word" seems to be the most practical and usable segment, as it is the smaller unit than the phrase, sentence or line.

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Section: Resultsmentioning

confidence: 99%

Text Segmentation Techniques: A Critical Review

Pak

Teh

2017

Innovative Computing, Optimization and Its Applications

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“…An experiment by Shiekh et al [17] employed a region-based technique for diacritics segmentation and produced a promising result. The Watershed transform, which represents ridges dividing areas drained by distinct river systems [18], is instrumental in defining boundaries for image region separation [19], also aiding in detecting non-linear spacing between characters [20]. Contour tracing initiates from a source point and traces the character boundary to the point of contact [21].…”

Section: Categorization Of Present Segmentation Methodsmentioning

confidence: 99%

Segmentation techniques for Arabic handwritten: a review

Abdalla Sheikh,

Sanusi Azmi,

Abdel Karim Abuain

et al. 2024

IJECE

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Image segmentation refers to the process of partitioning a page into distinct sections. This technique aims to improve and transform the image's representation into a more coherent and user-friendly format. Its common application involves identifying objects and boundaries (such as lines and curves) within images. However, this paper focuses on discussing segmentation methods specifically tailored for Arabic handwritten content. Dealing with the segmentation of Arabic handwritten material poses a significant challenge due to the diverse handwriting styles and the interconnection between Arabic letters. The paper will also touch on the classification of segmentation algorithms originally designed for modern documents, illustrating their adaptation in document processing. Furthermore, the paper will address the difficulties associated with segmenting Arabic handwritten content, including variations in writing style, the connected nature of Arabic characters, the complexity of Arabic cursive writing and as well as the diacritics challenges. Lastly, a concise overview of previously widely used segmentation techniques in various research endeavors will be provided.

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“…The third strategy is a hybrid of the first two, using dissection together with recombination rules to define potential segments. After that, rule-based methods such as the connected domain method [11] and the watershed segmentation method [12] were gradually proposed. The latest rule-based method was proposed by Inkeaw et al in 2018.…”

Section: Rule-based Methodsmentioning

confidence: 99%

Multiscale fully convolutional network‐based approach for multilingual character segmentation

Liu

2021

IET Computer Vision

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Character segmentation is a challenging task for optical character recognition systems. Traditional methods usually utilize rule-based algorithms but most of them are not applicable in modern intelligent recognition applications that require high accuracy. It is especially the case for text containing Eastern Asian language characters with complex pictograph structures, such as Chinese. To alleviate this problem, this study proposes an encoder-decoder structure-based multiscale fully convolutional network (MSFCN) model for optical character segmentation. Comparing with other methods, MSFCN can not only effectively extract semantic details from images but also exploit boundary information of intervals between characters, thereby distinguishing characters from a background in pixel level. Extensive experiments have been conducted on two benchmark data sets of ICDAR2013 and MLCS. Obtained results prove that MSFCN achieves state-of-the-art segmentation performance and indicated its practical application value.This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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A new watershed model based system for character segmentation in degraded text lines

Cited by 20 publications

References 11 publications

Text Segmentation Techniques: A Critical Review

Text Segmentation Techniques: A Critical Review

Segmentation techniques for Arabic handwritten: a review

Multiscale fully convolutional network‐based approach for multilingual character segmentation

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