Segmentation techniques for Arabic handwritten: a review

Abstract

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.