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)


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.
Number of pages5
ISBN (Print)081867282X, 9780818672828
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
ISSN (Print)1051-4651


Other13th International Conference on Pattern Recognition, ICPR 1996


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..