Using a viewing window and the Hausdorff-Voronoi Network (HAVNET) neural network for the recognition of words within a document

David L. Enke; Cihan H. Dagli

doi:10.1117/12.205172

6 April 1995 Using a viewing window and the Hausdorff-Voronoi Network (HAVNET) neural network for the recognition of words within a document

David L. Enke, Cihan H. Dagli

Author Affiliations +

Proceedings Volume 2492, Applications and Science of Artificial Neural Networks; (1995) https://doi.org/10.1117/12.205172
Event: SPIE's 1995 Symposium on OE/Aerospace Sensing and Dual Use Photonics, 1995, Orlando, FL, United States

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%.

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David L. Enke and Cihan H. Dagli "Using a viewing window and the Hausdorff-Voronoi Network (HAVNET) neural network for the recognition of words within a document", Proc. SPIE 2492, Applications and Science of Artificial Neural Networks, (6 April 1995); https://doi.org/10.1117/12.205172

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