Seam carving-based Arabic handwritten sub-word segmentation

Berriche, Lamia; Al-Mutairy, Abeer

doi:10.1080/23311916.2020.1769315

Cited by 5 publications

(2 citation statements)

References 19 publications

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“…In Lamia Berriche (2020) [24] the technique used is Seam carving-based and Datasets are IESK-ArDB and IFN/ENIT this method leads to Result of 95.67% clear remark for this research is that small characters could be considered secondary components.…”

Section: Related Workmentioning

confidence: 90%

The Trend of Segmentation for Arabic Handwritten Touching Characters

Algaradi¹,

Azmi²,

Jalil³

et al. 2022

IJACSA

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The paper is a comprehensive study of existing research trends in the sector of Arabic language, with a focus on state-of-the-art methods to illustrate the existing condition of various theory in that sector, with the goal of facilitating the adaptation and extension of prior ones into new systems and applications. In the Arabic alphabet, there are 28 letters. Depending on its place in the word, every Arabic letter has over one shape; a single character may have from one to four shapes. The Touching between character and the Overlapping occurred in the handwritten. Historical documents contained a massive knowledge and culture. There are many old books that need to be converted into readable format. Which would take a long time if humans converted it. However, the main problem is the lack of research in Arabic Handwritten especially for segmentation of touching characters. Thus, current trends of the segmentation techniques are investigated to identify the current state-of-the art of segmenting touching characters in other domains for constructing enhance techniques for Arabic touching characters. In this paper, it reviewed approaches for the segmentation of the touching characters. This paper presents the trend of approaches for the recognition process and segmentation of Arabic handwritten touching characters. In this paper, it highlighted the strength of each technique, the method used, and the drawback of the techniques. Based on the outcome, this will provide a good foundation for constructing a better technique for segmentation of Arabic touching characters, especially from the degraded documents.

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Section: Related Workmentioning

confidence: 90%

The Trend of Segmentation for Arabic Handwritten Touching Characters

Algaradi¹,

Azmi²,

Jalil³

et al. 2022

IJACSA

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“…Resolving these issues intensive investigated research needs to be done in this area by improving more pre-processing filters to connect long gaps. As a suggestion to improve the proposed model can be integrated using the seam carving algorithm in [42]to resolve the touching problem. In addition to that, resolving ligature can apply the techniques using [43] and [44].…”

Section: Discussionmentioning

confidence: 99%

Off-Line Arabic Handwritten Words Segmentation using Morphological Operators

AbdAllah¹,

Viriri²

2020

SIPIJ

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The main aim of this study is the assessment and discussion of a model for hand-written Arabic through segmentation. The framework is proposed based on three steps: pre-processing, segmentation, and evaluation. In the pre-processing step, morphological operators are applied for Connecting Gaps (CGs) in written words. Gaps happen when pen lifting-off during writing, scanning documents, or while converting images to binary type. In the segmentation step, first removed the small diacritics then bounded a connected component to segment offline words. Huge data was utilized in the proposed model for applying a variety of handwriting styles so that to be more compatible with real-life applications. Consequently, on the automatic evaluation stage, selected randomly 1,131 images from the IESK-ArDB database, and then segmented into sub-words. After small gaps been connected, the model performance evaluation had been reached 88% against the standard ground truth of the database. The proposed model achieved the highest accuracy when compared with the related works.

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