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Classification of cured tobacco leaves by colour and plant position by means of computer processing of digital images
Bibliography: pages 174-182.
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| Main Author: | |
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| Other Authors: | |
| Format: | Thesis |
| Language: | English |
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Department of Electrical Engineering
2016
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| _version_ | 1867613278897700865 |
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| access_status_str | Open Access |
| author | Tattersfield, George Metcalf |
| author2 | De Jager, Gerhard |
| author_browse | De Jager, Gerhard Tattersfield, George Metcalf |
| author_facet | De Jager, Gerhard Tattersfield, George Metcalf |
| author_sort | Tattersfield, George Metcalf |
| collection | Thesis |
| description | Bibliography: pages 174-182. |
| format | Thesis |
| id | oai:open.uct.ac.za:11427/21167 |
| institution | University of Cape Town (South Africa) |
| language | eng |
| last_indexed | 2026-06-10T12:33:35.758Z |
| license_str | Not specified — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UCTD — University of Cape Town Open Access Repository |
| publishDate | 2016 |
| publishDateRange | 2016 |
| publishDateSort | 2016 |
| publisher | Department of Electrical Engineering |
| publisherStr | Department of Electrical Engineering |
| record_format | dspace |
| source_str | UCTD — University of Cape Town Open Access Repository |
| spelling | oai:open.uct.ac.za:11427/21167 Classification of cured tobacco leaves by colour and plant position by means of computer processing of digital images Tattersfield, George Metcalf De Jager, Gerhard Electrical Engineering Image processing Bibliography: pages 174-182. This dissertation investigates the machine vision grading of flue-cured Virginia tobacco by means of digital processing of tobacco leaf images. With reference to international grading standards and to modem image processing techniques, two classifiers are designed. The colour classifier uses seven features extracted from each leaf image to grade the leaf into one of five official colour classes. It does this with an expected correct classification rate of 93.5%. The plant position classifier identifies the position on the stalk from which a leaf was reaped, using ten size and shape features to classify the leaf into one of six plant position categories. It has a correct classification rate of 70%. Average colours for each colour class and archetypal shapes for each plant position category are derived from the digital leaf data. These should be of value to tobacco graders as objective representations of typical leaves within each class. 2016-08-11T09:45:59Z 2016-08-11T09:45:59Z 1999 Master Thesis Masters MSc http://hdl.handle.net/11427/21167 eng application/pdf Department of Electrical Engineering Faculty of Engineering and the Built Environment University of Cape Town |
| spellingShingle | Electrical Engineering Image processing Tattersfield, George Metcalf Classification of cured tobacco leaves by colour and plant position by means of computer processing of digital images |
| thesis_degree_str | Master's |
| title | Classification of cured tobacco leaves by colour and plant position by means of computer processing of digital images |
| title_full | Classification of cured tobacco leaves by colour and plant position by means of computer processing of digital images |
| title_fullStr | Classification of cured tobacco leaves by colour and plant position by means of computer processing of digital images |
| title_full_unstemmed | Classification of cured tobacco leaves by colour and plant position by means of computer processing of digital images |
| title_short | Classification of cured tobacco leaves by colour and plant position by means of computer processing of digital images |
| title_sort | classification of cured tobacco leaves by colour and plant position by means of computer processing of digital images |
| topic | Electrical Engineering Image processing |
| url | http://hdl.handle.net/11427/21167 |
| work_keys_str_mv | AT tattersfieldgeorgemetcalf classificationofcuredtobaccoleavesbycolourandplantpositionbymeansofcomputerprocessingofdigitalimages |