Horizon extraction in an optical collision avoidance sensor

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DOIResolve DOI: http://doi.org/10.1109/CCECE.2011.6030440
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TypeArticle
Proceedings titleCanadian Conference on Electrical and Computer Engineering
Conference2011 Canadian Conference on Electrical and Computer Engineering, CCECE 2011, 8 May 2011 through 11 May 2011, Niagara Falls, ON
ISSN0840-7789
ISBN9781424497898
Article number6030440
Pages210214; # of pages: 5
Subjectclustering; Distributed networks; Feature descriptors; Feature space; Horizon extraction; Morphological operations; Pre-selected; Prior measurement; Region of interest; Spurious cluster; Collision avoidance; Mathematical morphology; Unmanned vehicles; Distributed computer systems
AbstractExtraction and utilization of the horizon contour is presented within the context of an optical collision avoidance instrument, comprised of individual nodes configured in a fixed-topology distributed network. The algorithm iterates between learning and application stages. Pixel neighbourhoods were classified into ground and sky regions using a vector of feature descriptors. The clusters in feature space were separated by a learnt minimal-error threshold, which was subsequently applied to the entire image, or a pre-selected region-of-interest aided by scenario-dependent constraints. Morphological operations reduced spurious clusters. The resultant contour was parametrically fitted to a polynomial for comparison to ground-truth. Adaptive operation allows inputs from prior measurements and external attitude information. © 2011 IEEE.
Publication date
LanguageEnglish
AffiliationNational Research Council Canada (NRC-CNRC); Aerospace (AERO-AERO)
Peer reviewedYes
NPARC number21271254
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Record identifier6ebd57bd-461a-4664-b56f-9edad40b2c11
Record created2014-03-24
Record modified2016-05-09
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