Title :
Scalable discrepancy measures for segmentation evaluation
Author :
Odet, C. ; Belaroussi, B. ; Benoit-Cattin, H.
Author_Institution :
CREATIS, CNRS, Villeurbanne, France
Abstract :
We propose a set of scalable discrepancy measures that may be applied for segmentation evaluation when a reference is known. The proposed measures take into account under and over detected points within an adjustable area. They give the intensity of the discrepancy and its relative position. Furthermore a scale parameter allows the accuracy of the measures to be adjusted.
Keywords :
computer vision; error analysis; image segmentation; computer vision; image analysis; image segmentation evaluation; over detected points; scalable discrepancy measures; scale parameter; under detected points; Area measurement; Computer vision; Detectors; Equations; Feature extraction; Humans; Image edge detection; Image quality; Image segmentation; Position measurement;
Conference_Titel :
Image Processing. 2002. Proceedings. 2002 International Conference on
Print_ISBN :
0-7803-7622-6
DOI :
10.1109/ICIP.2002.1038142
