THE POTENTIAL OF CONTOUR GROUPING FOR IMAGE CLASSIFICATION

Christoph Rasche

2010

Abstract

An image classification system is introduced, that is predominantly based on a description of contours and their relations. A contour is described by geometric parameters characterizing its global aspects (arc or alternating) and its local aspects (degree of curvature, edginess, symmetry). To express the relation between contours, we use a multi-dimensional vector, whose parameters describe distances between contour points and the contours’ local aspects. This allows comparing for instance L features or parallel contours with a simple distance measure. The approach has been evaluated on two image collections (Caltech 101 and Corel) and shows a reasonable categorization performance, yet its future lies in exploiting the preprocessing to understand ’parts’ of the image.

Paper Citation

in Harvard Style

Rasche C. (2010). THE POTENTIAL OF CONTOUR GROUPING FOR IMAGE CLASSIFICATION . In Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2010) ISBN 978-989-674-029-0, pages 481-486. DOI: 10.5220/0002815904810486

in Bibtex Style

@conference{visapp10,
author={Christoph Rasche},
title={THE POTENTIAL OF CONTOUR GROUPING FOR IMAGE CLASSIFICATION},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2010)},
year={2010},
pages={481-486},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002815904810486},
isbn={978-989-674-029-0},
}

in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2010)
TI - THE POTENTIAL OF CONTOUR GROUPING FOR IMAGE CLASSIFICATION
SN - 978-989-674-029-0
AU - Rasche C.
PY - 2010
SP - 481
EP - 486
DO - 10.5220/0002815904810486