COGNITUS - Fast and Reliable Recognition of Handwritten Forms based on Vector Quantisation

Neschen, Martin and NĂ¼bel, Frank (1996) COGNITUS - Fast and Reliable Recognition of Handwritten Forms based on Vector Quantisation.
Published In: High performance computing and networking : international conference and exhibition, Brussels, Belgium, April 15 - 19, 1996 ; proceedings, Lecture notes in computer science. 1067 Springer 1996, pp. 333-339.

Abstract

We report on an efficient intelligent character recognition tool for the automatic treatment of handwritten bank transfer forms. The classification is based on nearest-neighbor algorithms and a novel binary clustering technique for the generation of large prototype sets. We introduce a new confidence measure which can be used on a decision tree structure to combine lowest error rates with a very high recognition speed. Likelihood vectors allow context correction by database queries based on dynamic programming techniques as well as an easy integration of different classifier approaches in a multi-agent environment. In this paper, we present all components of the prototype system and give details on its realization and on possible parallel implementations on embedded systems.


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Deposit Information:
ZAIK Number: zpr95-210
Depositing User: Archive Admin
Date Deposited: 02 Apr 2001 00:00
Last Modified: 19 Dec 2011 09:45
URI: http://e-archive.informatik.uni-koeln.de/id/eprint/210