State-of-the-art of Off-line Arabic Handwriting Segmentation

Abstract

Computer processing of off-line Arabic handwriting is very difficult. The cursiveness of the script and the almost variability of the handwritten symbols make the automatic recognition of Arabic a very challenging task. Character segmentation is an important pre-processing stage in any intelligent character recognition system. This paper surveys the field of off-line Arabic character segmentation. Four classes of segmentation approaches are identified based on the used features and on where segmentation points are located. Text curves analysis, outer contour detection and following, stroke scrutiny and singularities vs regularities are the most used techniques. Instructive examples of each category are described and some comments are given.