Document image analysis using integrated image and neural processing

I
ICDAR
1995
Third International Conference on Document Analysis and Recognition (ICDAR'95) - Volume 1
Abstract - Document image analysis using integrated image and neural processing

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Third International Conference on Document Analysis and Recognition (ICDAR'95) - Volume 1

Montr?al, Canada

August 14-August 15

ISBN: 0-8186-7128-9

	ASCII Text	x
	D.X. Le, G.R. Thoma, H. Wechsler, "Document image analysis using integrated image and neural processing," Document Analysis and Recognition, International Conference on, vol. 1, pp. 327, Third International Conference on Document Analysis and Recognition (ICDAR'95) - Volume 1, 1995.

	BibTex	x
	@article{ 10.1109/ICDAR.1995.599005, author = {D.X. Le and G.R. Thoma and H. Wechsler}, title = {Document image analysis using integrated image and neural processing}, journal ={Document Analysis and Recognition, International Conference on}, volume = {1}, year = {1995}, isbn = {0-8186-7128-9}, pages = {327}, doi = {http://doi.ieeecomputersociety.org/10.1109/ICDAR.1995.599005}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Document Analysis and Recognition, International Conference on TI - Document image analysis using integrated image and neural processing SN - 0-8186-7128-9 SP EP A1 - D.X. Le, A1 - G.R. Thoma, A1 - H. Wechsler, PY - 1995 KW - document image processing; image classification; neural nets; document image analysis; robust algorithms; page orientation; degree of skew; binary document images; classification; neural network models; classification accuracy; training times; memory requirements; radial basis functions; integrated document analysis system; textual block classification VL - 1 JA - Document Analysis and Recognition, International Conference on ER -

D.X. Le, Nat. Libr. of Med., Bethesda, MD, USA

G.R. Thoma, Nat. Libr. of Med., Bethesda, MD, USA

H. Wechsler, Nat. Libr. of Med., Bethesda, MD, USA

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICDAR.1995.599005

In this paper we present robust algorithms for detecting the page orientation (portrait/landscape) and the degree of skew for binary document images, and a method for classification of binary document images into textual or non-textual data blocks using neural network models. The performance of four neural network models are compared in terms of training times, memory requirements, and classification accuracy, and it was found that the radial basis functions performed best. The experiments show the feasibility of building an integrated document analysis system for page orientation and skew angle detection, and textual block classification.

Index Terms:

document image processing; image classification; neural nets; document image analysis; robust algorithms; page orientation; degree of skew; binary document images; classification; neural network models; classification accuracy; training times; memory requirements; radial basis functions; integrated document analysis system; textual block classification

Citation:

D.X. Le, G.R. Thoma, H. Wechsler, "Document image analysis using integrated image and neural processing," icdar, vol. 1, pp.327, Third International Conference on Document Analysis and Recognition (ICDAR'95) - Volume 1, 1995

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