Ice Floe Identification in Satellite Images Using Mathematical Morphology and Clustering about Principal Curves
Identification of ice floes and their outlines in satellite images is important for understanding physical processes in the polar regions, for transportation in ice-covered seas and for the design of offshore structures intended to survive in the presence of ice. At present this is done manually, a...
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ftdtic:ADA213854 2023-05-15T16:37:24+02:00 Ice Floe Identification in Satellite Images Using Mathematical Morphology and Clustering about Principal Curves Banfield, Jeffrey D. Raftery, Adrian E. WASHINGTON UNIV SEATTLE DEPT OF STATISTICS 1989-08 text/html http://www.dtic.mil/docs/citations/ADA213854 http://oai.dtic.mil/oai/oai?&verb=getRecord&metadataPrefix=html&identifier=ADA213854 en eng http://www.dtic.mil/docs/citations/ADA213854 Approved for public release; distribution is unlimited. DTIC AND NTIS Cartography and Aerial Photography Snow Ice and Permafrost Statistics and Probability *SEA ICE *SATELLITE PHOTOGRAPHY *REMOTE DETECTORS ENVIRONMENTS EDGES COMPUTER PROGRAMMING MORPHOLOGY ACCURACY ICE FORMATION ESTIMATES IDENTIFICATION EROSION CLUSTERING ICE IMAGES ARTIFICIAL SATELLITES MATHEMATICS COVERINGS AUTOMATIC OFFSHORE STRUCTURES VOLUME PROPAGATION ALGORITHMS POLAR REGIONS WUNR661003 Text 1989 ftdtic 2016-02-23T04:33:44Z Identification of ice floes and their outlines in satellite images is important for understanding physical processes in the polar regions, for transportation in ice-covered seas and for the design of offshore structures intended to survive in the presence of ice. At present this is done manually, a long and tedious process which precluded full use of the great volume of relevant images now available. We describe an automatic and accurate method for identifying ice floes and their outlines. Floe outlines are modeled as closed principal curves (Hastie and Stuetzle, 1989), a flexible class of smooth non- parametric curves. We propose a robust method of estimating closed principal curves which reduces both bias and variance. Initial estimates of floe outlines come from the erosion-propagation (EP) algorithm, which combines erosion from mathematical morphology with local propagation of information about floe edges. The edge pixel from the EP algorithm are grouped into floe outlines using a new clustering algorithm. This extends existing clustering methods by allowing groups to be centered about principal curves rather than points or lines. This may open the way to efficient feature extraction using cluster analysis in images more generally. The method is implemented in an object-oriented programming environment for which it is well suited, and is quite computationally efficient. Keywords: Erosion; Feature extraction; LANDSAT; Non- parametric curves. Text Ice permafrost Sea ice Defense Technical Information Center: DTIC Technical Reports database |
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Open Polar |
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Defense Technical Information Center: DTIC Technical Reports database |
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language |
English |
topic |
Cartography and Aerial Photography Snow Ice and Permafrost Statistics and Probability *SEA ICE *SATELLITE PHOTOGRAPHY *REMOTE DETECTORS ENVIRONMENTS EDGES COMPUTER PROGRAMMING MORPHOLOGY ACCURACY ICE FORMATION ESTIMATES IDENTIFICATION EROSION CLUSTERING ICE IMAGES ARTIFICIAL SATELLITES MATHEMATICS COVERINGS AUTOMATIC OFFSHORE STRUCTURES VOLUME PROPAGATION ALGORITHMS POLAR REGIONS WUNR661003 |
spellingShingle |
Cartography and Aerial Photography Snow Ice and Permafrost Statistics and Probability *SEA ICE *SATELLITE PHOTOGRAPHY *REMOTE DETECTORS ENVIRONMENTS EDGES COMPUTER PROGRAMMING MORPHOLOGY ACCURACY ICE FORMATION ESTIMATES IDENTIFICATION EROSION CLUSTERING ICE IMAGES ARTIFICIAL SATELLITES MATHEMATICS COVERINGS AUTOMATIC OFFSHORE STRUCTURES VOLUME PROPAGATION ALGORITHMS POLAR REGIONS WUNR661003 Banfield, Jeffrey D. Raftery, Adrian E. Ice Floe Identification in Satellite Images Using Mathematical Morphology and Clustering about Principal Curves |
topic_facet |
Cartography and Aerial Photography Snow Ice and Permafrost Statistics and Probability *SEA ICE *SATELLITE PHOTOGRAPHY *REMOTE DETECTORS ENVIRONMENTS EDGES COMPUTER PROGRAMMING MORPHOLOGY ACCURACY ICE FORMATION ESTIMATES IDENTIFICATION EROSION CLUSTERING ICE IMAGES ARTIFICIAL SATELLITES MATHEMATICS COVERINGS AUTOMATIC OFFSHORE STRUCTURES VOLUME PROPAGATION ALGORITHMS POLAR REGIONS WUNR661003 |
description |
Identification of ice floes and their outlines in satellite images is important for understanding physical processes in the polar regions, for transportation in ice-covered seas and for the design of offshore structures intended to survive in the presence of ice. At present this is done manually, a long and tedious process which precluded full use of the great volume of relevant images now available. We describe an automatic and accurate method for identifying ice floes and their outlines. Floe outlines are modeled as closed principal curves (Hastie and Stuetzle, 1989), a flexible class of smooth non- parametric curves. We propose a robust method of estimating closed principal curves which reduces both bias and variance. Initial estimates of floe outlines come from the erosion-propagation (EP) algorithm, which combines erosion from mathematical morphology with local propagation of information about floe edges. The edge pixel from the EP algorithm are grouped into floe outlines using a new clustering algorithm. This extends existing clustering methods by allowing groups to be centered about principal curves rather than points or lines. This may open the way to efficient feature extraction using cluster analysis in images more generally. The method is implemented in an object-oriented programming environment for which it is well suited, and is quite computationally efficient. Keywords: Erosion; Feature extraction; LANDSAT; Non- parametric curves. |
author2 |
WASHINGTON UNIV SEATTLE DEPT OF STATISTICS |
format |
Text |
author |
Banfield, Jeffrey D. Raftery, Adrian E. |
author_facet |
Banfield, Jeffrey D. Raftery, Adrian E. |
author_sort |
Banfield, Jeffrey D. |
title |
Ice Floe Identification in Satellite Images Using Mathematical Morphology and Clustering about Principal Curves |
title_short |
Ice Floe Identification in Satellite Images Using Mathematical Morphology and Clustering about Principal Curves |
title_full |
Ice Floe Identification in Satellite Images Using Mathematical Morphology and Clustering about Principal Curves |
title_fullStr |
Ice Floe Identification in Satellite Images Using Mathematical Morphology and Clustering about Principal Curves |
title_full_unstemmed |
Ice Floe Identification in Satellite Images Using Mathematical Morphology and Clustering about Principal Curves |
title_sort |
ice floe identification in satellite images using mathematical morphology and clustering about principal curves |
publishDate |
1989 |
url |
http://www.dtic.mil/docs/citations/ADA213854 http://oai.dtic.mil/oai/oai?&verb=getRecord&metadataPrefix=html&identifier=ADA213854 |
genre |
Ice permafrost Sea ice |
genre_facet |
Ice permafrost Sea ice |
op_source |
DTIC AND NTIS |
op_relation |
http://www.dtic.mil/docs/citations/ADA213854 |
op_rights |
Approved for public release; distribution is unlimited. |
_version_ |
1766027690461102080 |