ORBi: Kleynen Olivier - Development of a multi-spectral vision system for the detection of defects on apples

Reference : Development of a multi-spectral vision system for the detection of defects on apples


	Document type :	Scientific journals : Article
	Discipline(s) :	Life sciences : Food science Engineering, computing & technology : Chemical engineering
	To cite this reference:	http://hdl.handle.net/2268/72791

Title :	Development of a multi-spectral vision system for the detection of defects on apples
Language :	English
Author, co-author :	Kleynen, Olivier [> > > >]
	Leemans, Vincent [Université de Liège - ULg > Gembloux Agro-Bio Tech > Gembloux Agro-Bio Tech >]
	Destain, Marie-France [Université de Liège - ULg > Gembloux Agro-Bio Tech > Gembloux Agro-Bio Tech >]
Publication date :	2005
Journal title :	Journal of Food Engineering
Publisher :	Elsevier Science
Volume :	69
Issue/season :	1
Pages :	41-49
Audience :	International
ISSN :	0260-8774
City :	Oxford
Country :	United Kingdom
Keywords :	[en] bicolour fruit ; pattern matching ; segmentation ; Bayes' theorem ; classification ; sorting
Abstract :	[en] A method to sort 'Jonagold' apples based on the presence of defects was proposed. A multi-spectral vision system including four wavelength bands in the visible/NIR range was developed. Multi-spectral images of sound and defective fruits were acquired tending to cover the whole colour variability of this bicolour apple variety. Defects were grouped into four categories: slight defects, more serious defects, defects leading to the rejection of the fruit and recent bruises. Stem-ends/calyxes were detected using a correlation pattern matching algorithm. The efficiency of this method depended on the orientation of the stem-end/calyx according to the optical axis of the camera. Defect segmentation consisted in a pixel classification procedure based on the Bayes' theorem and non-parametric models of the sound and defective tissue. Fruit classification tests were performed in order to evaluate the efficiency of the proposed method. No error was made on rejected fruits and high classification rates were reached for apples presenting serious defects and recent bruises. Fruits with slight defects presented a more important misclassification rate but those errors fitted however the quality tolerances of the European standard. Considering an actual ratio of sound fruits of 90%, less than 2% of defective fruits were classified into the sound ones. (c) 2004 Elsevier Ltd. All rights reserved.
Permalink :	http://hdl.handle.net/2268/72791
	also: http://hdl.handle.net/2268/21014
DOI :	10.1016/j.jfoodeng.2004.07.008

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