Abstract
Efficient Analysis of Vertical Projection Histogram to Segment Arabic Handwritten Characters
Highlights
Writing recognition, a vast field of pattern recognition, is still a subject of intense research and experimentation
The segmentation step is an important step in the recognition process; this step is simple in the case of printed Latin text, but very difficult in the case of cursive writing (Arabic writing)
The results obtained show that 89.5% of the segmentation points were extracted correctly, which is a very appreciable rate compared to the state of the art
Summary
A vast field of pattern recognition, is still a subject of intense research and experimentation. Despite the number of people who speak Arabic, little research has been done on this language [Yasser (2013); Naz, Umar, Shirazi et al (2016)], mainly because of the difficulty of segmenting words into letters. The segmentation step is an important step in the recognition process; this step is simple in the case of printed Latin text, but very difficult in the case of cursive writing (Arabic writing). The complexity of the morphology of Arabic writing and its cursivity make it more difficult to segment words into characters. Several studies have been carried out by researchers based on the recognition of the entire word (global approach) without segmentation [Lawgali (2015)], and others assume that characters are already segmented to avoid the segmentation step [Lorigo and Govindaraju (2006); Khorsheed (2002)].
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