Abstract
The growing relevance of printed and digitalized hand-written characters has necessitated the need for convalescent automatic recognition of characters in Optical Character Recognition (OCR). Among the handwritten characters, Arabic is one of those with special attention due to its distinctive nature, and the inherent challenges in its recognition systems. This distinctiveness of Arabic characters, with the difference in personal writing styles and proficiency, are complicating the effectiveness of its online handwritten recognition systems. This research, based on limitations and scope of previous related studies, studied the recognition of Arabic isolated characters through the identification of its features and dots in view of producing an efficient online Arabic handwriting isolated character recognition system. It proposes a hybrid of decision tree and Artificial Neural Network (ANN), as against being combined with other algorithms as found in previous studies. The proposed recognition process has four main steps with associated sub-steps. The results showed that the proposed method achieved the highest performance at 96.7%, whereas the benchmark methods which are EDMS and Naeimizaghiani had 68.88% and 78.5 % respectively. Based on this, ANN has the best performance recognition rate at 98.8%, while the best rate for decision tree was obtained at 97.2%.
Highlights
IntroductionOptical character recognition (OCR) is one of the areas of applied studies of pattern recognition [1]
Optical character recognition (OCR) is one of the areas of applied studies of pattern recognition [1].Pattern recognition uses machine learning models and various mathematical, statistical and heuristic techniques for the detection of patterns, and provides a computational implementation framework for its recognition systems [1, 2]
This study proposes a hybrid of a decision tree and artificial neural network, as against being combined with other algorithms as found in previous studies, in view of improving the online Arabic character recognition
Summary
Optical character recognition (OCR) is one of the areas of applied studies of pattern recognition [1]. Hand-written character recognition is employed and needed in automated mail sorting and check processing, and improving their performance is important [3, 9]. This is applicable to all characters, and Arabic attracts special attention. An Arabic letter will have distinct shapes and forms when at the beginning, middle, and the end of a word [12, 13].The distinctiveness of Arabic characters, especially the difficulties associated with automated recognition, and complicated with its online hand-written characters, necessitated this study [14]. The fifth section, which is the last section, presents the results and discussion of this study
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