Multiscale segmentation of unstructured document pages using softdecision integration
Etemad, K.
Doermann, D.
Chellappa, R.
Center for Autom. Res., Maryland Univ., College Park, MD;
This paper appears in: Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publication Date: Jan 1997
Volume: 19,
Issue: 1
On page(s): 92-96
ISSN: 0162-8828
References Cited: 17
CODEN: ITPIDJ
INSPEC Accession Number: 5493205
Digital Object Identifier: 10.1109/34.566817
Current Version Published: 2002-08-06
Abstract
We present an algorithm for layout-independent document page
segmentation based on document texture using multiscale feature vectors
and fuzzy local decision information. Multiscale feature vectors are
classified locally using a neural network to allow soft/fuzzy
multi-class membership assignments. Segmentation is performed by
integrating soft local decision vectors to reduce their
“ambiguities”
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