Abstract
Complexity of Arabic writing language makes its handwritten recognition very complex in terms of computer algorithms. The Arabic handwritten recognition has high importance in modern applications. The contour analysis of word image can extract special contour features that discriminate one character from another by the mean of vector features. This paper implements a set of pre-processing functions over a handwritten Arabic characters, with contour analysis, to enter the contour vector to neural network to recognize it. The selection of this set of pre-processing algorithms was completed after hundreds of tests and validation. The feed forward neural network architecture was trained using many patterns regardless of the Arabic font style building a rigid recognition model. Because of the shortcomings in Arabic written databases or datasets, the testing was done by non-standard data set. The presented algorithm structure got recognition ratio about 97%.
Highlights
Human activities digitizing demands is accelerating and the computer era moving to internet of things (IoT) increases the demand of automatic user applications
The proposed algorithm in this paper is based on hundred days of testing, validation and evaluation to specify the best approach that can achieve more than 95% of recognition accuracy with less than 1% of falls acceptance ratio
The main goal of this study is to conduct the optimal model for Arabic handwritten recognition whose recognition process complexity is reduced
Summary
Human activities digitizing demands is accelerating and the computer era moving to internet of things (IoT) increases the demand of automatic user applications. The functionalities are convoying by collaborative technologies inventing and development between computer and human Such rising scheme increasing the demand and growth of researches that are focusing on handwritten recognition. Handwritten recognition is taken place and main role in modern computer systems It becomes very wide in smart mobile phones, archiving systems, scanning systems, etc. Arabic language has complex context style, writing methodology, font, and texture. This makes the mission of computer system not easy to solve. Writing English letters in upper and lower case makes different shapes of the same character, but the variety still restricted. Arabic had wide variety of writing styles for the same character, while the connected characters cursive style moves the character between completely different shapes with respect to its location in the word (Abdullah, Al-Harigy & AlFraidi, 2012). Arabic normally read from right to left but the numbers should be written from left to right (Boukerma & Farah, 2012; Bharath & Madhvanath, 2012)
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