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Multiscale segmentation of unstructured document pages using soft decision integration

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3 Author(s)
Etemad, K. ; Center for Autom. Res., Maryland Univ., College Park, MD, USA ; Doermann, D. ; Chellappa, R.

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”

Published in:

Pattern Analysis and Machine Intelligence, IEEE Transactions on  (Volume:19 ,  Issue: 1 )

Date of Publication:

Jan 1997

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