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Image analysis of seafloor photographs for estimation of deep-sea minerals

DRS at CSIR-National Institute of Oceanography

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Title Image analysis of seafloor photographs for estimation of deep-sea minerals
 
Creator Sharma, R.
Jaisankar, S.
Samanta, S.
Sardar, A.A.
Gracias, D.G.
 
Subject mineral resources
ocean floor
underwater photographs
image processing
ferromanganese nodules
imaging techniques
 
Description Factors such as non-uniform illumination of seafloor photographs and partial burial of polymetallic nodules and crusts under sediments have prevented the development of a fully automatic system for evaluating the distribution characteristics of these minerals, necessitating the involvement of a user input. A method has been developed whereby spectral signatures of different features are identified using a software ‘trained’ by a user, and the images are digitized for coverage estimation of nodules and crusts. Analysis of more than 20,000 seafloor photographs was carried out along five camera transects covering a total distance of 450 km at 5,100-5,300 m water depth in the Central Indian Ocean. The good positive correlation (R sup(2) greater than 0.98) recorded between visual and computed estimates shows that both methods of estimation are highly reliable. The digitally computed estimates were approx. 10% higher than the visual estimates of the same photographs; the latter have a conservative operator error, implying that computed estimates would more accurately predict a relatively high resource potential. The fact that nodules were present in grab samples from some locations where photographs had nil nodule coverage emphasises that nodules may not always be exposed on the seafloor and that buried nodules will also have to be accounted for during resource evaluation. When coupled with accurate positioning/depth data and grab sampling, photographic estimates can provide detailed information on the spatial distribution of mineral deposits, the associated substrates, and the topographic features that control their occurrences. Such information is critical for resource modelling, the selection of mine sites, the designing of mining systems and the planning of mining operations.
 
Date 2010-11-29T07:39:51Z
2010-11-29T07:39:51Z
2010
 
Type Journal Article
 
Identifier Geo-marine letters, vol.30(6); 617-626
no
http://drs.nio.org/drs/handle/2264/3745
 
Language en
 
Relation Geo-Mar_Lett_30_617.jpg
 
Rights An edited version of this paper was published by Springer. This paper is for R & D pupose and Copyright [2010] Springer.
 
Publisher Springer