Handwritten English Character Recognition using HMM, Baum-Welch and Genetic Algorithm

It is the problem of computer science that how we detect the handwritten character and word, so it is also the problem in the field of image processing and pattern recognition of computer science. The meaning of handwritten character and word recognition refers to the identification of the characters or word which is written by a human being. Our approach is this, how this problem solved correctly. In Handwritten character recognition, we have to assign each character into its (A-Z, a-z or 0-9). In this paper we use two approaches Hidden Markov Model (HMM) and Genetic Algorithm (GA) to identify features of each character and compare with its testing set of characters. In this paper we uses various stages of handwritten character recognition system that are: read a scanned image of hand written character, converting this matrix into binary form (0 and 1), resizing each character matrix into size of (n x m where n and m may be same), and thinning of an image to get a clear skeleton of each character. Then In this paper identify the each character using three algorithms namely: Forward Algorithm, Baum Welch and Genetic Algorithm. The results obtained from each of the algorithm are compared separately and at the end the accuracy of these algorithms are compared separately. Keyword: HMM (Hidden Markov Model), GA (Genetic Algorithm), Baum Welch Method (BWM), Handwritten Character Recognition (HC).