loading
Documents

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Daniel Keysers 1 ; Faisal Shafait 1 and Thomas M. Breuel 2

Affiliations: 1 German Research Center for Artificial Intelligence (DFKI) GmbH, Germany ; 2 Technical University of Kaiserslautern, Germany

ISBN: 978-972-8865-74-0

ISSN: 2184-4321

Keyword(s): Document Image Analysis, Zone Classification.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Biomedical Engineering ; Biomedical Signal Processing ; Computer Vision, Visualization and Computer Graphics ; Data Manipulation ; Feature Extraction ; Features Extraction ; Health Engineering and Technology Applications ; Human-Computer Interaction ; Image and Video Analysis ; Informatics in Control, Automation and Robotics ; Methodologies and Methods ; Neurocomputing ; Neurotechnology, Electronics and Informatics ; Pattern Recognition ; Physiological Computing Systems ; Sensor Networks ; Signal Processing, Sensors, Systems Modeling and Control ; Soft Computing

Abstract: We describe a simple, fast, and accurate system for document image zone classification — an important sub-problem of document image analysis — that results from a detailed analysis of different features. Using a novel combination of known algorithms, we achieve a very competitive error rate of 1.46% (n = 13811) in comparison to (Wang et al., 2006) who report an error rate of 1.55% (n = 24177) using more complicated techniques. The experiments were performed on zones extracted from the widely used UW-III database, which is representative of images of scanned journal pages and contains ground-truthed real-world data.

PDF ImageFull Text

Download
CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 3.237.94.109

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Keysers D.; Shafait F.; M. Breuel T. and (2007). DOCUMENT IMAGE ZONE CLASSIFICATION - A Simple High-Performance Approach.In Proceedings of the Second International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, ISBN 978-972-8865-74-0, pages 44-51. DOI: 10.5220/0002052900440051

@conference{visapp07,
author={Daniel Keysers and Faisal Shafait and Thomas {M. Breuel}},
title={DOCUMENT IMAGE ZONE CLASSIFICATION - A Simple High-Performance Approach},
booktitle={Proceedings of the Second International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP,},
year={2007},
pages={44-51},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002052900440051},
isbn={978-972-8865-74-0},
}

TY - CONF

JO - Proceedings of the Second International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP,
TI - DOCUMENT IMAGE ZONE CLASSIFICATION - A Simple High-Performance Approach
SN - 978-972-8865-74-0
AU - Keysers, D.
AU - Shafait, F.
AU - M. Breuel, T.
PY - 2007
SP - 44
EP - 51
DO - 10.5220/0002052900440051

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.