THE POTENTIAL OF CONTOUR GROUPING FOR IMAGE CLASSIFICATION

Christoph Rasche

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.

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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