Recognition of Handwritten Sheba Character using Artificial Neural Network

From the Last twenty years, the computer-based mechanism has an essential process in daily life and research-oriented applications, the whole world be attracted by computers and approximately all the main processing is being completed automatically. Recognition of handwriting now it is an eye-catching and tough study analysis in image processing and pattern identification field in the today’s world. To beat this problem Optical Character Recognition system (OCR) is practice and concentrated research has been carrying on OCR. Numerous OCR systems are existing in the market other than mainly of this system working for Japanese, English, Chinese, Roman letters. There is no adequate work on Arabic language particularly Sheba characters. In proposed paper, an OCR system for Sheba recognition of character depend on neural network is presented. After analysing various method for segmentation and pre-processing A and B which are used for image pre-processing and segmentation respectively to enhance performance for projected framework. All the issues and challenges for OCR system and relevancy or accuracy of proposed method are discussed and analysed briefly