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Proceedings Paper

Benchtop methodology for evaluating the automatic segmentation of ladar images
Author(s): Gregory J. Power
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Paper Abstract

Numerous approaches to segmentation exist requiring an evaluation technique to determine the most appropriate technique to use for a specific ladar design. A benchtop evaluation methodology that uses multiple measures is used to evaluate ladar-specific image segmentation algorithms. The method uses multiple measures along with an inter-algorithmic approach that was recently introduced for evaluating Synthetic Aperture Radar (SAR) imagery. Ladar imagery is considered to be easier to segment than SAR since it generally contains less speckle and has both a range and intensity map to assist in segmentation. A system of multiple measures focuses on area, shape and edge closeness to judge the segmentation. The judgement is made on the benchtop by comparing the segmentation to supervised hand-segmented images. To demonstrate the approach, a ladar image is segmented using several segmentation approaches introduced in literature. The system of multiple measures is then demonstrated on the segmented ladar images. An interpretation of the results is given. This paper demonstrates that the original evaluation approach designed for evaluating SAR imagery can be generalized across differing sensor modalities even though the segmentation and sensor acquisition approaches are different.

Paper Details

Date Published: 22 October 2001
PDF: 8 pages
Proc. SPIE 4379, Automatic Target Recognition XI, (22 October 2001); doi: 10.1117/12.445355
Show Author Affiliations
Gregory J. Power, Air Force Research Lab. (United States)

Published in SPIE Proceedings Vol. 4379:
Automatic Target Recognition XI
Firooz A. Sadjadi, Editor(s)

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