The Trend of Segmentation for Arabic Handwritten Touching Characters

Abstract

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 Historical documents contained a massive knowledge and culture.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.

Segmentation techniques for Arabic handwritten: a review

“…Despite this, a reliable solution to this challenging issue has yet to emerge [22]. Additionally, even though handwritten text varies from person to person, the segmentation of such text into words, lines, and characters remains a complex endeavor [23]. Handling non-Latin scripts like Arabic presents even greater challenges; aside from writing variations, the presence of diacritical marks and the abundance of ascender and descender characters further complicate the segmentation process.…”