An investigation of a pattern recognition system to analyse and classify dried fruit

Includes bibliographical references. === Both the declining cost and increasing capabilities of specialised computer hardware for image processing have enabled computer vision systems to become a viable alternative to human visual inspection in industrial applications. In this thesis a vision system...

Full description

Bibliographic Details
Main Author: Henry, Karen Jane
Other Authors: De Jager, Gerhard
Format: Dissertation
Language:English
Published: University of Cape Town 2014
Subjects:
Online Access:http://hdl.handle.net/11427/9249
id ndltd-netd.ac.za-oai-union.ndltd.org-uct-oai-localhost-11427-9249
record_format oai_dc
spelling ndltd-netd.ac.za-oai-union.ndltd.org-uct-oai-localhost-11427-92492020-12-10T05:11:11Z An investigation of a pattern recognition system to analyse and classify dried fruit Henry, Karen Jane De Jager, Gerhard Applied Science Includes bibliographical references. Both the declining cost and increasing capabilities of specialised computer hardware for image processing have enabled computer vision systems to become a viable alternative to human visual inspection in industrial applications. In this thesis a vision system that will analyse and classify dried fruit is investigated. In human visual inspection of dried fruit, the colour of the fruit is often the main determinant of its grade; in specific cases the presence of blemishes and geometrical fault are also incorporated in order to determine the fruit grade. A colour model that would successfully represent the colour variations within dried fruit grades, was investigated. The selected colour feature space formed the basis of a classification system which automatically allocated a sample unit of dried fruit to one specific grade. Various classification methods were investigated, and that which suited the system data and parameters was selected and evaluated using test sets of three types of dried fruit. In order to successfully grade dried fruit, a number of additional problems had to be catered for: the red/brown coloured central core area of dried peaches had to be removed from the colour analysis, and Black blemishes upon dried pears had to be isolated and sized in order to supplement the colour classifier in the final classification of the pear. The core area of a dried peach was isolated using the Morphological Top-Hat transform, and Black blemishes upon pears were isolated using colour histogram thresholding techniques. The test results indicated that although colour classification was the major determinant in the grading of dried fruit, other characteristics of the fruit had to be incorporated to achieve successful final classification results; these characteristics may be different for different types of dried fruit, but in the case of dried apricots, dried peaches and dried pears, they include the: peach core area removal, fruit geometry validation, and dried pear blemish isolation and sizing. 2014-11-05T17:35:24Z 2014-11-05T17:35:24Z 1996 Master Thesis Masters MSc http://hdl.handle.net/11427/9249 eng application/pdf University of Cape Town Faculty of Engineering and the Built Environment Department of Mechanical Engineering
collection NDLTD
language English
format Dissertation
sources NDLTD
topic Applied Science
spellingShingle Applied Science
Henry, Karen Jane
An investigation of a pattern recognition system to analyse and classify dried fruit
description Includes bibliographical references. === Both the declining cost and increasing capabilities of specialised computer hardware for image processing have enabled computer vision systems to become a viable alternative to human visual inspection in industrial applications. In this thesis a vision system that will analyse and classify dried fruit is investigated. In human visual inspection of dried fruit, the colour of the fruit is often the main determinant of its grade; in specific cases the presence of blemishes and geometrical fault are also incorporated in order to determine the fruit grade. A colour model that would successfully represent the colour variations within dried fruit grades, was investigated. The selected colour feature space formed the basis of a classification system which automatically allocated a sample unit of dried fruit to one specific grade. Various classification methods were investigated, and that which suited the system data and parameters was selected and evaluated using test sets of three types of dried fruit. In order to successfully grade dried fruit, a number of additional problems had to be catered for: the red/brown coloured central core area of dried peaches had to be removed from the colour analysis, and Black blemishes upon dried pears had to be isolated and sized in order to supplement the colour classifier in the final classification of the pear. The core area of a dried peach was isolated using the Morphological Top-Hat transform, and Black blemishes upon pears were isolated using colour histogram thresholding techniques. The test results indicated that although colour classification was the major determinant in the grading of dried fruit, other characteristics of the fruit had to be incorporated to achieve successful final classification results; these characteristics may be different for different types of dried fruit, but in the case of dried apricots, dried peaches and dried pears, they include the: peach core area removal, fruit geometry validation, and dried pear blemish isolation and sizing.
author2 De Jager, Gerhard
author_facet De Jager, Gerhard
Henry, Karen Jane
author Henry, Karen Jane
author_sort Henry, Karen Jane
title An investigation of a pattern recognition system to analyse and classify dried fruit
title_short An investigation of a pattern recognition system to analyse and classify dried fruit
title_full An investigation of a pattern recognition system to analyse and classify dried fruit
title_fullStr An investigation of a pattern recognition system to analyse and classify dried fruit
title_full_unstemmed An investigation of a pattern recognition system to analyse and classify dried fruit
title_sort investigation of a pattern recognition system to analyse and classify dried fruit
publisher University of Cape Town
publishDate 2014
url http://hdl.handle.net/11427/9249
work_keys_str_mv AT henrykarenjane aninvestigationofapatternrecognitionsystemtoanalyseandclassifydriedfruit
AT henrykarenjane investigationofapatternrecognitionsystemtoanalyseandclassifydriedfruit
_version_ 1719369958169772032