ARTIFICIAL NEURAL NETWORK BASED CHARACTER RECOGNITION USING BACKPROPAGAT

Abstract

Optical Character Recognition, or OCR, is a technology that enables you to convert different types of documents, such as scanned paper documents, PDF files or images captured by a digital camera into editable and searchable data format. OCR is the translation of optically scanned bitmap of printed or written text character into the character codes, such as ASCII. This is an efficient way to turn hard copy material into digital data files that can be edited or manipulated. The optical character recognition refers to the branch of computer science that involves reading text from paper and translating the images into a form that the computer can manipulate. The potential of this technology is typically used for general character recognition which includes the transformation of anything humanly readable to machine manipulatable representation. OCR systems are enormous because they enable users to harness the power of computers to access printed documents.

The aim of this paper is to find a means by which the database entry from handwritten forms can be automated. Firstly the paper deals with the technology scanning hard copy data. Secondly describes machine learning process for training the system for converting hard copy into soft copy