Intelligent tool for Malayalam cursive handwritten character recognition using artificial neural network and Hidden Markov Model

Abstract

This paper represents an attractive method for the conversion of the image into an editable text as it is written by Optical Character Recognition (OCR). With this offline handwritten character recognition method, it shows the ability of a computer to receive and recognize handwritten input. Computers may find some difficulty in deciphering the exact handwritten characters with different fonts and styles. This paper mainly focuses on the recognition of handwritten Malayalam (a South Indian Language) characters. Thus cursive Malayalam characters can be recognized by Hidden Markov Model (HMM). The classification is done with Artificial Neural Network (ANN). Handwritten character recognition with high accuracy and efficient method to recognize the cursive letters are included in the proposed system.