Share Email Print

Proceedings Paper

Application of scalable discrepancy measures for computer vision image segmentation tasks
Author(s): B. Belaroussi; Christophe Odet; Hugues Benoit-Cattin
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper Abstract

In this paper, a set of scalable discrepancy measures is applied in the context of computer vision. These measures allow tuning of edge detectors and segmentation evaluation when a reference is known. Thanks to a scale parameter in an adjustable area the proposed measures allows to weight the importance of over-detection as well as under-detection. They give the intensity of the discrepancy and its relative position.

Paper Details

Date Published: 1 May 2003
PDF: 7 pages
Proc. SPIE 5132, Sixth International Conference on Quality Control by Artificial Vision, (1 May 2003); doi: 10.1117/12.514938
Show Author Affiliations
B. Belaroussi, INSA of Lyon (France)
Christophe Odet, INSA of Lyon (France)
Hugues Benoit-Cattin, INSA of Lyon (France)

Published in SPIE Proceedings Vol. 5132:
Sixth International Conference on Quality Control by Artificial Vision
Kenneth W. Tobin; Fabrice Meriaudeau, Editor(s)

© SPIE. Terms of Use
Back to Top