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Proceedings Paper

Enhancement Of Reading Accuracy By Multiple Data Integration
Author(s): Kangsuk Lee
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Paper Abstract

In this paper, a multiple sensor integration technique with neural network learning algorithms is presented which can enhance the reading accuracy of the hand-written numerals. Many document reading applications involve hand-written numerals in a predetermined location on a form, and in many cases, critical data is redundantly described. The amount of a personal check is one such case which is written redundantly in numerals and in alphabetical form. Information from two optical character recognition modules, one specialized for digits and one for words, is combined to yield an enhanced recognition of the amount. The combination can be accomplished by a decision tree with "if-then" rules, but by simply fusing two or more sets of sensor data in a single expanded neural net, the same functionality can be expected with a much reduced system cost. Experimental results of fusing two neural nets to enhance overall recognition performance using a controlled data set are presented.

Paper Details

Date Published: 24 July 1989
PDF: 8 pages
Proc. SPIE 1074, Imaging Workstations, (24 July 1989); doi: 10.1117/12.952615
Show Author Affiliations
Kangsuk Lee, Siemens Corporate Research (United States)

Published in SPIE Proceedings Vol. 1074:
Imaging Workstations
Roger R. A. Morton, Editor(s)

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