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Proceedings Paper

Regression approach to combination of decisions by multiple character recognition algorithms
Author(s): Tin Kam Ho; Jonathan J. Hull; Sargur N. Srihari
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Paper Abstract

A regression method is proposed to combine decisions of multiple character recognition algorithms. The method computes a weighted sum of the rank scores produced by the individual classifiers and derive a consensus ranking. The weights are estimated by a logistic regression analysis. Two experiments are discussed where the method was applied to recognize degraded machine-printed characters and handwritten digits. The results show that the combination outperforms each of the individual classifiers.

Paper Details

Date Published: 1 August 1992
PDF: 9 pages
Proc. SPIE 1661, Machine Vision Applications in Character Recognition and Industrial Inspection, (1 August 1992); doi: 10.1117/12.130282
Show Author Affiliations
Tin Kam Ho, SUNY/Buffalo (United States)
Jonathan J. Hull, SUNY/Buffalo (United States)
Sargur N. Srihari, SUNY/Buffalo (United States)

Published in SPIE Proceedings Vol. 1661:
Machine Vision Applications in Character Recognition and Industrial Inspection
Donald P. D'Amato; Wolf-Ekkehard Blanz; Byron E. Dom; Sargur N. Srihari, Editor(s)

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