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Range image segmentation using Zernike moment-based generalized edge detectorThe authors proposed a novel Zernike moment-based generalized step edge detection method which can be used for segmenting range and intensity images. A generalized step edge detector is developed to identify different kinds of edges in range images. These edge maps are thinned and linked to provide final segmentation. A generalized edge is modeled in terms of five parameters: orientation, two slopes, one step jump at the location of the edge, and the background gray level. Two complex and two real Zernike moment-based masks are required to determine all these parameters of the edge model. Theoretical noise analysis is performed to show that these operators are quite noise tolerant. Experimental results are included to demonstrate edge-based segmentation technique.
Document ID
19930051553
Acquisition Source
Legacy CDMS
Document Type
Conference Paper
Authors
Ghosal, S.
(NASA Langley Research Center Hampton, VA, United States)
Mehrotra, R.
(Kentucky Univ. Lexington, United States)
Date Acquired
August 16, 2013
Publication Date
January 1, 1992
Publication Information
Publication: In: 1992 IEEE International Conference on Robotics and Automation, 8th, Nice, France, May 12-14, 1992, Proceedings. Vol. 2 (A93-35501 13-63)
Publisher: IEEE Computer Society Press
Subject Category
Cybernetics
Accession Number
93A35550
Funding Number(s)
CONTRACT_GRANT: NAG1-1276
CONTRACT_GRANT: NIH-S07-RR-07114-21
Distribution Limits
Public
Copyright
Other

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