Zone classification using texture features

Dmitry Chetverikov, Jisheng Liang, Jozsef Komuves, Robert M. Haralick

Research output: Chapter in Book/Report/Conference proceedingConference contribution

29 Citations (Scopus)

Abstract

We consider the problem of zone classification in document image processing. Document blocks are labelled as text or nontext using texture features derived from a feature based interaction map (FBIM), a recently introduced general tool for texture analysis. The zone classification procedure proposed is tested on the comprehensive document image database UW-I created at the University of Washington in Seattle. Different classification procedures are considered. The performance ranges from 96% to 98% using 6 FBIM texture features only.

Original languageEnglish
Title of host publicationTrack C
Subtitle of host publicationApplications and Robotic Systems
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages676-680
Number of pages5
ISBN (Print)081867282X, 9780818672828
DOIs
Publication statusPublished - Jan 1 1996
Event13th International Conference on Pattern Recognition, ICPR 1996 - Vienna, Austria
Duration: Aug 25 1996Aug 29 1996

Publication series

NameProceedings - International Conference on Pattern Recognition
Volume3
ISSN (Print)1051-4651

Other

Other13th International Conference on Pattern Recognition, ICPR 1996
CountryAustria
CityVienna
Period8/25/968/29/96

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ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

Cite this

Chetverikov, D., Liang, J., Komuves, J., & Haralick, R. M. (1996). Zone classification using texture features. In Track C: Applications and Robotic Systems (pp. 676-680). [547031] (Proceedings - International Conference on Pattern Recognition; Vol. 3). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICPR.1996.547031