Abstract —Real-time performance is necessary inapplications involving on-line handwriting recognition.However, conventional approaches usually wait until the entirecurve is traced out before starting the analysis, inevitablycausing delays in the recognition process. In regards to theArabic script, the postponed analysis may be attributed to thecursive and unconstrained nature of the Arabic writing system,in both printed and handwritten forms. Nevertheless, thispaper proposes a real-time recognition-based segmentationtechnique of on-line Arabic script. It demonstrate thefeasibility of carrying out the most time consuming tasks,required for the segmentation process, during the course ofwriting. The system has been designed and tested using theADAB Database, and promising results were obtained. Keywords -Arabic script segmentation; handwriting recogni-tion; on-line text segmentation; I. I NTRODUCTION Handwriting remains the most commonly used meanof communication and recording of information in thedaily life, therefore, a growing interest in the handwritingcharacter recognition field has emerged in recent years.Handwriting recognition can be categorized into two mainareas: off-line and on-line. In the off-line case, a digitalimage containing text is fed to the computer, and the systemattempts to convert the spatial representation of the lettersinto digital symbols [1]. In contrast, the process of on-linehandwriting recognition is done on a digital representation ofthe text written on a special digitizer, tablet or smart-phonedevice, where sensors pick up the pen-tip movements.Research in this field has established two main ap-proaches; the analytic approach, which involves segmen-tation and classification of each part of the text [2], [3],[4], and the holistic approach, which considers the globalproperties of the written text and recognizes the input wordshape as a whole [5], [6]. While having many advantages, theholistic approach requires the classifier to be trained over theentire dictionary, which is impractical for large dictionaries(containing more than 20,000 words) [7].The cursiveness of the Arabic script, prima facie, requiresdelaying the launch of the recognition process until thecompletion of the word scribing. However, in this paper, wequestion the necessity of this requirement by demonstratingthe feasibility of approximating the position of the