Improving the Segmentation of Arabic Handwriting Using Ligature Detection Technique  

作　　者：Husam Ahmad Al Hamad Mohammad Shehab 

机构地区：[1]College of Computer Sciences and Informatics,Amman Arab University,Amman,11953,Jordan

出　　处：《Computers, Materials & Continua》2024年第5期2015-2034,共20页计算机、材料和连续体（英文）

摘　　要：Recognizing handwritten characters remains a critical and formidable challenge within the realm of computervision. Although considerable strides have been made in enhancing English handwritten character recognitionthrough various techniques, deciphering Arabic handwritten characters is particularly intricate. This complexityarises from the diverse array of writing styles among individuals, coupled with the various shapes that a singlecharacter can take when positioned differently within document images, rendering the task more perplexing. Inthis study, a novel segmentation method for Arabic handwritten scripts is suggested. This work aims to locatethe local minima of the vertical and diagonal word image densities to precisely identify the segmentation pointsbetween the cursive letters. The proposed method starts with pre-processing the word image without affectingits main features, then calculates the directions pixel density of the word image by scanning it vertically and fromangles 30° to 90° to count the pixel density fromall directions and address the problem of overlapping letters, whichis a commonly attitude in writing Arabic texts by many people. Local minima and thresholds are also determinedto identify the ideal segmentation area. The proposed technique is tested on samples obtained fromtwo datasets: Aself-curated image dataset and the IFN/ENIT dataset. The results demonstrate that the proposed method achievesa significant improvement in the proportions of cursive segmentation of 92.96% on our dataset, as well as 89.37%on the IFN/ENIT dataset.

关 键 词：Arabic handwritten SEGMENTATION image processing ligature detection technique intelligent recognition 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]