Development Of Handwritten Character Recognition By Using Artificial Neural Network

Lisa Umami, Abdul Khalik (2015) Development Of Handwritten Character Recognition By Using Artificial Neural Network. Project Report. UTeM, Melaka, Malaysia. (Submitted)

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Abstract

The constant development of computer tools leads to a requirement of easier interfaces between the man and the computer one of the example is handwritten character recognition. Handwritten character recognition is the ability of computer to receive and interpret the handwritten input images from sources such as document, photograph or touch-screen and transform it to machine readable and editable format. In this project the system implemented using the MATLAB software which using tool of Graphic User Interface (GUI). There are several steps involved in this system. The first step is preprocessing. The input image which consists of the handwritten text will be loaded and will go through some process like conversion to grayscale and binary image and image filtering. Next, the image will be segmented to individual character bounding plotting the bounding block and then it will be extracted according to respective to their feature vector. Finally, the classification process will take place and the extracted character will be classified by using the Artificial Neural Network. The GUI is created to uses windows, icons, and menus to bring out commands, such as opening, deleting, and moving files and to complete each steps.

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