A New Textual/Non-Textual Classifier for Document Skew Correction

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16th International Conference on Pattern Recognition (ICPR'02) - Volume 1

Quebec City, QC, Canada

August 11-August 15

ISBN: 0-7695-1695-X

	ASCII Text	x
	Xiaoyan Zhu, Xiaoxin Yin, "A New Textual/Non-Textual Classifier for Document Skew Correction," Pattern Recognition, International Conference on, vol. 1, pp. 10480, 16th International Conference on Pattern Recognition (ICPR'02) - Volume 1, 2002.

	BibTex	x
	@article{ 10.1109/ICPR.2002.1044768, author = {Xiaoyan Zhu and Xiaoxin Yin}, title = {A New Textual/Non-Textual Classifier for Document Skew Correction}, journal ={Pattern Recognition, International Conference on}, volume = {1}, year = {2002}, issn = {1051-4651}, pages = {10480}, doi = {http://doi.ieeecomputersociety.org/10.1109/ICPR.2002.1044768}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Pattern Recognition, International Conference on TI - A New Textual/Non-Textual Classifier for Document Skew Correction SN - 1051-4651 SP EP A1 - Xiaoyan Zhu, A1 - Xiaoxin Yin, PY - 2002 KW - null VL - 1 JA - Pattern Recognition, International Conference on ER -

Xiaoyan Zhu, Tsinghua University

Xiaoxin Yin, Tsinghua University

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICPR.2002.1044768

A robust approach is proposed for document skew detection. We use Fourier analysis and SVM to classify textual areas from non-textual areas of documents. We also propose a robust method to determine the skew angle from textual areas. Our approach achieves good performance on documents with large area of non-textual contents.

Citation:

Xiaoyan Zhu, Xiaoxin Yin, "A New Textual/Non-Textual Classifier for Document Skew Correction," icpr, vol. 1, pp.10480, 16th International Conference on Pattern Recognition (ICPR'02) - Volume 1, 2002

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