Vol 8, No 3 (2017) > Electrical, Electronics and Computer Engineering >

Designing Offline Arabic Handwritten Isolated Character Recognition System using Artificial Neural Network Approach

Ahmed Subhi Abdalkafor


Abstract: The Arabic language is one of
the major languages that has little attention in character recognition field
by Arab researchers in particular and foreign researchers in general. Due to
the highly cursive nature of handwritten Arabic language, Arabic character
recognition is considered one of the most challenging problems in contrast to
working with Latin, Japanese or Chinese character recognition. In this paper, we proposed
Arabic off-line handwritten isolated recognition system based on novel feature
extraction techniques, a back propagation
neural network as classification phase. The presented work is implemented and tested via the
CENPARMI database. Competitive recognition accuracy has been achieved 96.14%. This result motivates us and other researchers in this
field to employ the features extraction techniques that we have used in this
research with other Arabic character shapes.
Keywords: Directional features; Regional features; Universe of discourse; Zoning

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