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Fuzzy set methods for object recognition in space applicationsProgress on the following tasks is reported: (1) fuzzy set-based decision making methodologies; (2) feature calculation; (3) clustering for curve and surface fitting; and (4) acquisition of images. The general structure for networks based on fuzzy set connectives which are being used for information fusion and decision making in space applications is described. The structure and training techniques for such networks consisting of generalized means and gamma-operators are described. The use of other hybrid operators in multicriteria decision making is currently being examined. Numerous classical features on image regions such as gray level statistics, edge and curve primitives, texture measures from cooccurrance matrix, and size and shape parameters were implemented. Several fractal geometric features which may have a considerable impact on characterizing cluttered background, such as clouds, dense star patterns, or some planetary surfaces, were used. A new approach to a fuzzy C-shell algorithm is addressed. NASA personnel are in the process of acquiring suitable simulation data and hopefully videotaped actual shuttle imagery. Photographs have been digitized to use in the algorithms. Also, a model of the shuttle was assembled and a mechanism to orient this model in 3-D to digitize for experiments on pose estimation is being constructed.
Document ID
19930007370
Acquisition Source
Legacy CDMS
Document Type
Contractor Report (CR)
Authors
Keller, James M.
(Missouri Univ. Columbia., United States)
Date Acquired
September 6, 2013
Publication Date
September 30, 1991
Subject Category
Computer Programming And Software
Report/Patent Number
NASA-CR-191778
NAS 1.26:191778
Accession Number
93N16559
Funding Number(s)
PROJECT: RICIS PROJ. SE-42
CONTRACT_GRANT: NCC9-16
Distribution Limits
Public
Copyright
Work of the US Gov. Public Use Permitted.
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