A study of handwritten text character recognition using neural network

Hassan, Nur Maisarah (2020) A study of handwritten text character recognition using neural network. Project Report. Universiti Teknikal Malaysia Melaka, Melaka, Malaysia. (Submitted)

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Abstract

This title project uses Neural Network as a method to develop recognition systems for handwritten text characters. The handwriting recognition systems frequently fail or unable to give sufficient results on different types of handwriting due to massive inconsistency styles of handwriting. Handwriting recognition systems comprise of Preprocessing, Segmentation, Feature Extraction and Classification. The main goal of this project is to propose a framework of text character recognition algorithm using Neural Network. The classification comprises 52 classes of English handwritten characters with 26 characters for capital letters and 26 characters for small letters. The handwritten character recognition will be using MATLAB software with Image Processing and Neural Network Toolbox. This project serves to recognize all characters (English) provided as input image. If the character image input is given to the proposed program, the input character given in the image will be recognized. Neural Network does recognition and classification of characters.

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