Title
Quantitative methods of evaluating image segmentation
Abstract
Two sets of measures are proposed in this paper for quantitatively evaluating segmentation results. The first set is designed for the situation where ground truth is available; while the second for the situation where ground truth is not available. Based on a test bank of more than 50 images for which ground truth is available, we computed both sets of evaluation measures and then correlated the two sets. Experimental results show that the first set of measures proposed agree with human (subjective) visual evaluation and the second set of measures correlates well with the first set, an indication of the usefulness of this set of measures in assessing the quality of image segmentation results even when ground truth is not available.
Year
DOI
Venue
1995
10.1109/ICIP.1995.537578
ICIP (3)
Keywords
Field
DocType
quantitative methods,polynomials,shape,robustness,computer vision,ground truth,testing,image segmentation,quantitative method,degradation
Image segmentation computer vision,Computer vision,Pattern recognition,Polynomial,Segmentation,Computer science,Image segmentation,Robustness (computer science),Ground truth,Artificial intelligence
Conference
Volume
ISBN
Citations 
3
0-8186-7310-9
71
PageRank 
References 
Authors
13.27
1
2
Name
Order
Citations
PageRank
Qian Huang17113.27
Byron Dom22600825.93