Regression approach to combination of decisions by multiple character recognition algorithms

Tin Kam Ho; Jonathan J. Hull; Sargur N. Srihari

doi:10.1117/12.130282

1 August 1992 Regression approach to combination of decisions by multiple character recognition algorithms

Tin Kam Ho, Jonathan J. Hull, Sargur N. Srihari

Proceedings Volume 1661, Machine Vision Applications in Character Recognition and Industrial Inspection; (1992) https://doi.org/10.1117/12.130282
Event: SPIE/IS&T 1992 Symposium on Electronic Imaging: Science and Technology, 1992, San Jose, CA, United States

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.

Citation Download Citation

Tin Kam Ho, Jonathan J. Hull, and Sargur N. Srihari "Regression approach to combination of decisions by multiple character recognition algorithms", Proc. SPIE 1661, Machine Vision Applications in Character Recognition and Industrial Inspection, (1 August 1992); https://doi.org/10.1117/12.130282

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