Application of scalable discrepancy measures for computer vision image segmentation tasks

B. Belaroussi; Christophe Odet; Hugues Benoit-Cattin

doi:10.1117/12.514938

1 May 2003 Application of scalable discrepancy measures for computer vision image segmentation tasks

B. Belaroussi, Christophe Odet, Hugues Benoit-Cattin

Proceedings Volume 5132, Sixth International Conference on Quality Control by Artificial Vision; (2003) https://doi.org/10.1117/12.514938
Event: Quality Control by Artificial Vision, 2003, Gatlinburg, TE, United States

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.

Citation Download Citation

B. Belaroussi, Christophe Odet, and Hugues Benoit-Cattin "Application of scalable discrepancy measures for computer vision image segmentation tasks", Proc. SPIE 5132, Sixth International Conference on Quality Control by Artificial Vision, (1 May 2003); https://doi.org/10.1117/12.514938

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