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Proceedings Paper

Using a viewing window and the Hausdorff-Voronoi Network (HAVNET) neural network for the recognition of words within a document
Author(s): David L. Enke; Cihan H. Dagli
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Paper Abstract

A substantial portion of research and applications for visual image recognition have been limited to the recognition of large, isolated, non-variant images. Performing a visual search for focusing on, locating, and recognizing smaller details within the context of a larger image has proven more difficult. This paper presents a system that is capable of learning words of various lengths, and then locating and recognizing a previously trained word within a noisy document. This system utilizes a fitness function, search routine and viewing window to identify possible word candidates, and then employs the Hausdorff-Voronoi network (HAVNET) for word recognition. After 330 searches of 30 different words, with document noise ranging from 0 - 20%, the system recognition and location accuracy were 97.3%.

Paper Details

Date Published: 6 April 1995
PDF: 8 pages
Proc. SPIE 2492, Applications and Science of Artificial Neural Networks, (6 April 1995); doi: 10.1117/12.205172
Show Author Affiliations
David L. Enke, Univ. of Missouri/Rolla (United States)
Cihan H. Dagli, Univ. of Missouri/Rolla (United States)

Published in SPIE Proceedings Vol. 2492:
Applications and Science of Artificial Neural Networks
Steven K. Rogers; Dennis W. Ruck, Editor(s)

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