6 April 1995 Using a viewing window and the Hausdorff-Voronoi Network (HAVNET) neural network for the recognition of words within a document
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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%.
© (1995) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
David L. Enke, David L. Enke, Cihan H. Dagli, 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); doi: 10.1117/12.205172; https://doi.org/10.1117/12.205172
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