A The State of the Art Handwritten Recognition of Arabic Script Using Simplified Fuzzy ARTMAP and Hidden Markov Models

In this paper, we present recognition of handwritten characters of Arabic script. Arabic is now the 6 most spoken language in the world and is spoken by more than 200 million people worldwide. The 7 Century A.D., Arabic started to spread to the Middle East as many people started to convert to Islam. During this time of religious conversions, Arabic replaced many South Arabian languages, most of which are no longer commonly spoken or understood languages. The challenges in Arabic handwritten character recognition wholly lie in the variation and disfigurement of Arabic handwritten characters, since different Arabic people may use a different style of handwriting, and direction to draw the same shape of the characters of their known Arabic script. Though various new propensity and technologies come out in these days, still handwriting is playing an important role. To recognize Arabic handwritten data there are different strategies like Simplified Fuzzy ARTMAP and Hidden Markov Models (HMM). In this paper, we are using Simplified Fuzzy ARTMAP, which is an updated version of Predictive Adaptive Resonance Theory. It also has a capacity to adjust clusters, as per the requirements Arabic script, which is remunerative to mitigate noise. We have tested our method on Arabic scripts and we have obtained encouraging results from our proposed technique.