On Hand-Printed Character Recognition

Abstract

Handwritten digit and alphabetic character recognition has been an active area of research for many years. Character recognition techniques associate a symbolic identity with the image of a character. The problem of replication of human functions by machines involves the recognition of both machine and hand-printed or cursive-written characters. Character recognition is better known as Optical Character Recognition (OCR) since it deals with recognition of optically processed characters rather than, for example, magnetically processed ones. The origin of character recognition can be found as early as in 1870, though the modern version of OCR appeared in the middle of the 1940s with the development of digital computers. Its main area of interest was data processing with application to the business world. The principal motivation for development of OCR system is the need to cope with the enormous flood of paper such as bank cheques, commercial forms, government records, mail sorting generated by the expanding society and international partnerships. Since the origin of OCR systems extensive research has been carried out and a large number of technical papers have been published by researchers in this area. Many techniques and experimental results have been published in the literature. In recent years, new classification approaches, such as neural networks, and design methodologies, such as classifier combination and parallel feature networks extraction, have renewed interests in this fields. As OCR technology seeks applications in more complicated, real time environments, the criterion for successful algorithm becomes more rigorous. New feature extraction and classification techniques are developed with parallel hardware implementation in mind. Several recognition methodologies are combined in order to improve the recognition quality. State of the art reports on character recognition research have been presented by Nagy [1968], Harmon [1972], Suen et al. [1980], Mori et al. [1984], Mantas [1986], Davis and Yall [1986], Govindan and Shivaprasad [1990], Lee and Srihari [1993].