Character recognition—a review
Pattern Recognition
One-Pass Parallel Thinning: Analysis, Properties, and Quantitative Evaluation
IEEE Transactions on Pattern Analysis and Machine Intelligence
C4.5: programs for machine learning
C4.5: programs for machine learning
Neural Networks in Computer Intelligence
Neural Networks in Computer Intelligence
Segmentation of Arabic Characters: A Comprehensive Survey
International Journal of Technology Diffusion
Hi-index | 0.00 |
Character recognition systems can contribute tremendously to the advancement of the automation process and can improve the interaction between man and machine in many applications, including office automation, cheque verification and a large variety of banking, business and data entry applications. The main theme of this paper is the automatic recognition of hand-printed Arabic characters using machine learning. Conventional methods have relied on hand-constructed dictionaries which are tedious to construct and difficult to make tolerant to variation in writing styles. The advantages of machine learning are that it can generalize over the large degree of variation between writing styles and recognition rules can be constructed by example.The system was tested on a sample of handwritten characters from several individuals whose writing ranged from acceptable to poor in quality and the correct average recognition rate obtained using cross-validation was 87.23%.