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

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dc.contributor.advisorDe Jager, Gerharden_ZA
dc.contributor.authorHenry, Karen Janeen_ZA
dc.date.accessioned2014-11-05T17:35:24Z
dc.date.available2014-11-05T17:35:24Z
dc.date.issued1996en_ZA
dc.descriptionIncludes bibliographical references.en_ZA
dc.description.abstractBoth 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.en_ZA
dc.identifier.apacitationHenry, K. J. (1996). <i>An investigation of a pattern recognition system to analyse and classify dried fruit</i>. (Thesis). University of Cape Town ,Faculty of Engineering & the Built Environment ,Department of Mechanical Engineering. Retrieved from http://hdl.handle.net/11427/9249en_ZA
dc.identifier.chicagocitationHenry, Karen Jane. <i>"An investigation of a pattern recognition system to analyse and classify dried fruit."</i> Thesis., University of Cape Town ,Faculty of Engineering & the Built Environment ,Department of Mechanical Engineering, 1996. http://hdl.handle.net/11427/9249en_ZA
dc.identifier.citationHenry, K. 1996. An investigation of a pattern recognition system to analyse and classify dried fruit. University of Cape Town.en_ZA
dc.identifier.ris TY - Thesis / Dissertation AU - Henry, Karen Jane AB - 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. DA - 1996 DB - OpenUCT DP - University of Cape Town LK - https://open.uct.ac.za PB - University of Cape Town PY - 1996 T1 - An investigation of a pattern recognition system to analyse and classify dried fruit TI - An investigation of a pattern recognition system to analyse and classify dried fruit UR - http://hdl.handle.net/11427/9249 ER - en_ZA
dc.identifier.urihttp://hdl.handle.net/11427/9249
dc.identifier.vancouvercitationHenry KJ. An investigation of a pattern recognition system to analyse and classify dried fruit. [Thesis]. University of Cape Town ,Faculty of Engineering & the Built Environment ,Department of Mechanical Engineering, 1996 [cited yyyy month dd]. Available from: http://hdl.handle.net/11427/9249en_ZA
dc.language.isoengen_ZA
dc.publisher.departmentDepartment of Mechanical Engineeringen_ZA
dc.publisher.facultyFaculty of Engineering and the Built Environment
dc.publisher.institutionUniversity of Cape Town
dc.subject.otherApplied Scienceen_ZA
dc.titleAn investigation of a pattern recognition system to analyse and classify dried fruiten_ZA
dc.typeMaster Thesis
dc.type.qualificationlevelMasters
dc.type.qualificationnameMScen_ZA
uct.type.filetypeText
uct.type.filetypeImage
uct.type.publicationResearchen_ZA
uct.type.resourceThesisen_ZA
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