Omnifont Character Recognition Based On Fast Feature Vectorization

H. C. Yung; I. M. Green

doi:10.1117/12.969007

25 October 1988 Omnifont Character Recognition Based On Fast Feature Vectorization

H. C. Yung, I. M. Green

Proceedings Volume 1001, Visual Communications and Image Processing '88: Third in a Series; (1988) https://doi.org/10.1117/12.969007
Event: Visual Communications and Image Processing III, 1988, Cambridge, MA, United States

Abstract

This paper presents major achievements made towards the development of a high-speed optical character recognition (OCR) workstation for characters of various fonts and sizes. The system is based upon an efficient feature extraction concept centred around an edge-vectorization technique. The resulting edges are mapped into a feature space from where a binary feature vector is built and subsequently fed to a standard statistical Bayesian classifier. The technique has been demonstrated on an IBM-PC/XT (without coprocessor) to operate at least 25 times the speed of conventional OCR techniques, achieving a 100% recognition rate with learned characters and 87% with unlearned.

Citation Download Citation

H. C. Yung and I. M. Green "Omnifont Character Recognition Based On Fast Feature Vectorization", Proc. SPIE 1001, Visual Communications and Image Processing '88: Third in a Series, (25 October 1988); https://doi.org/10.1117/12.969007

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