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Features for neural net based region identification of newspaper documents
Andersen, T. Wei Zhang
Comput. Sci. Dept., Boise State Univ., ID, USA;

This paper appears in: Document Analysis and Recognition, 2003. Proceedings. Seventh International Conference on
Publication Date: 3-6 Aug. 2003
On page(s): 403- 407 vol.1
ISSN:
ISBN: 0-7695-1960-1
INSPEC Accession Number: 7839364
Digital Object Identifier: 10.1109/ICDAR.2003.1227698
Current Version Published: 2003-09-08

Abstract
Several features for neural network based document region identification are tested. Specifically, this paper examines features for non-text region identification. The neural network based region identification algorithm is a key component of a document recognition system that segments a document into regions, classifies them into text, graphic, photo, and other region types, and then uses this classification to guide the processing and analysis of the image. The input data are unusually challenging: low quality images of newspaper documents obtained from microfilmed archives. The results compare favorably with other results reported in the literature.

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