Authors:
Anton Mazhurin
1
and
Nawwaf Kharma
2
Affiliations:
1
ALMAZ Technology, Canada
;
2
Concordia University, Canada
Keyword(s):
Image Segmentation, Quality Assessment, Software Tool, Pixel-based Measures, Region-based Measures.
Related
Ontology
Subjects/Areas/Topics:
Computer Vision, Visualization and Computer Graphics
;
Image and Video Analysis
;
Segmentation and Grouping
Abstract:
This paper presents algorithms and their software implementation, which assess the quality of segmentation of any image, given an ideal segmentation (or ground truth image) and a usually less-than-ideal segmentation result (or machine segmented image). The software first identifies every region in both the ground truth and machine segmented images, establishes as much correspondence as possible between the images, then computes two sets of measures of quality: one, region-based and the other, pixel-based. The paper describes the algorithms used to assess quality of segmentation and presents results of the application of the software to images from the Berkeley Segmentation Dataset. The software, which is freely available for download, facilitates R&D work in image segmentation, as it provides a tool for assessing the results of any image segmentation algorithm, allowing developers of such algorithms to focus their energies on solving the segmentation problem, and enabling them to tes
ts large sets of images, swiftly and reliably.
(More)