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Automated stratigraphic classification and feature detection from images of borehole cores

Thesis (MScEng (Electrical and Electronic Engineering))--University of Stellenbosch, 2005.

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Bibliographic Details
Main Author: Van der Walt, Stefan Johann
Other Authors: Cloete, J. H.
Format: Thesis
Language:English
Published: Stellenbosch : University of Stellenbosch 2007
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access_status_str Open Access
author Van der Walt, Stefan Johann
author2 Cloete, J. H.
author_browse Cloete, J. H.
Van der Walt, Stefan Johann
author_facet Cloete, J. H.
Van der Walt, Stefan Johann
author_sort Van der Walt, Stefan Johann
collection Thesis
dc_rights_str_mv University of Stellenbosch
description Thesis (MScEng (Electrical and Electronic Engineering))--University of Stellenbosch, 2005.
format Thesis
id oai:scholar.sun.ac.za:10019.1/2045
institution Stellenbosch University (South Africa)
language English
last_indexed 2026-06-10T12:43:31.605Z
license_str Other — see source repository
provenance_str_mv Harvested via OAI-PMH from SUNScholar — Stellenbosch University Repository
publishDate 2007
publishDateRange 2007
publishDateSort 2007
publisher Stellenbosch : University of Stellenbosch
publisherStr Stellenbosch : University of Stellenbosch
record_format dspace
source_str SUNScholar — Stellenbosch University Repository
spelling oai:scholar.sun.ac.za:10019.1/2045 Automated stratigraphic classification and feature detection from images of borehole cores Van der Walt, Stefan Johann Cloete, J. H. Herbst, B. M. University of Stellenbosch. Faculty of Engineering. Dept. of Electrical and Electronic Engineering. Image processing Rocks -- Analysis Dissertations -- Electronic engineering Theses -- Electronic engineering Electrical and Electronic Engineering Thesis (MScEng (Electrical and Electronic Engineering))--University of Stellenbosch, 2005. This thesis describes techniques proposed for analysing images of borehole cores. We address two problems: firstly, the automated stratigraphic classification of cores based on texture and secondly, the location of thin chromitite layers hidden in pyroxenite cores. Texture features of different rock types are extracted using wavelets, the theory of which provides an intuitive and powerful tool for this purpose. A Bayesian classifier is trained and used to discriminate between different samples. Thin, planar chromitite layers are located using a shortest path algorithm. In order to estimate the physical orientation of any layer found, a sinusoidal curve is fitted. The proposed algorithms were implemented and tested on samples taken from photographed cores. A high success rate was obtained in rock classification, and thin planar layers were located and characterised. 2007-01-22T12:06:26Z 2010-06-01T08:39:28Z 2007-01-22T12:06:26Z 2010-06-01T08:39:28Z 2005-03 Thesis http://hdl.handle.net/10019.1/2045 en University of Stellenbosch 3775840 bytes application/pdf application/pdf Stellenbosch : University of Stellenbosch
spellingShingle Image processing
Rocks -- Analysis
Dissertations -- Electronic engineering
Theses -- Electronic engineering
Electrical and Electronic Engineering
Van der Walt, Stefan Johann
Automated stratigraphic classification and feature detection from images of borehole cores
title Automated stratigraphic classification and feature detection from images of borehole cores
title_full Automated stratigraphic classification and feature detection from images of borehole cores
title_fullStr Automated stratigraphic classification and feature detection from images of borehole cores
title_full_unstemmed Automated stratigraphic classification and feature detection from images of borehole cores
title_short Automated stratigraphic classification and feature detection from images of borehole cores
title_sort automated stratigraphic classification and feature detection from images of borehole cores
topic Image processing
Rocks -- Analysis
Dissertations -- Electronic engineering
Theses -- Electronic engineering
Electrical and Electronic Engineering
url http://hdl.handle.net/10019.1/2045
work_keys_str_mv AT vanderwaltstefanjohann automatedstratigraphicclassificationandfeaturedetectionfromimagesofboreholecores