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Daytime Water Detection Based on Color VariationRobust water detection is a critical perception requirement for unmanned ground vehicle (UGV) autonomous navigation. This is particularly true in wide open areas where water can collect in naturally occurring terrain depressions during periods of heavy precipitation and form large water bodies (such as ponds). At far range, reflections of the sky provide a strong cue for water. But at close range, the color coming out of a water body dominates sky reflections and the water cue from sky reflections is of marginal use. We model this behavior by using water body intensity data from multiple frames of RGB imagery to estimate the total reflection coefficient contribution from surface reflections and the combination of all other factors. Then we describe an algorithm that uses one of the color cameras in a forward- looking, UGV-mounted stereo-vision perception system to detect water bodies in wide open areas. This detector exploits the knowledge that the change in saturation-to-brightness ratio across a water body from the leading to trailing edge is uniform and distinct from other terrain types. In test sequences approaching a pond under clear, overcast, and cloudy sky conditions, the true positive and false negative water detection rates were (95.76%, 96.71%, 98.77%) and (0.45%, 0.60%, 0.62%), respectively. This software has been integrated on an experimental unmanned vehicle and field tested at Ft. Indiantown Gap, PA.
Document ID
20150008529
Acquisition Source
Jet Propulsion Laboratory
Document Type
Conference Paper
External Source(s)
Authors
Rankin, Arturo L.
(Jet Propulsion Lab., California Inst. of Tech. Pasadena, CA, United States)
Matthies, Larry H.
(Jet Propulsion Lab., California Inst. of Tech. Pasadena, CA, United States)
Date Acquired
May 20, 2015
Publication Date
October 18, 2010
Subject Category
Earth Resources And Remote Sensing
Instrumentation And Photography
Meeting Information
Meeting: IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2010)
Location: Taipei
Country: Taiwan, Province of China
Start Date: October 18, 2010
End Date: October 22, 2010
Sponsors: Robotics Society of Japan, Institute of Electrical and Electronics Engineers
Distribution Limits
Public
Copyright
Other
Keywords
reflection coefficient
water detection
water segmentation

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