References of "Magein, Hugo"
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See detailOn-line fruit grading according to their external quality using machine vision
Leemans, Vincent ULg; Magein, Hugo ULg; Destain, Marie-France ULg

in Biosystems Engineering (2002), 83(4), 397-404

This paper presents apple grading into four classes according to European standards. Two varieties were tested: Golden Delicious and Jonagold. The image database included more than a 1000 images of fruits ... [more ▼]

This paper presents apple grading into four classes according to European standards. Two varieties were tested: Golden Delicious and Jonagold. The image database included more than a 1000 images of fruits (528 Golden Delicious, 642 Jonagold) belonging to the three acceptable categories-Extra, I and II-and the reject (each class represents, respectively, about 60, 10 and 20% of the sample size). The image grading was achieved in six steps: image acquisition; ground colour classification; defect segmentation; calyx and stem recognition; defects characterisation and finally the fruit classification into quality classes. The proposed method for apple external quality grading showed correct classification rates of 78 and 72%, for Golden Delicious and Jonagold apples, respectively. Taking into account that the healthy fruit were far better graded and considering that this class was under represented in the sample compared with the fruit population, the results of the proposed method (an error rate which drops to 5 and 10%, respectively) are compatible with the requirements of European standards. (C) 2002 Silsoe Research Institute. Published by Elsevier Science Ltd. All rights reserved. [less ▲]

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See detailDéveloppement de méthodes pour apprécier 'en ligne' la qualité externe de pommes par vision artificielle
Leemans, Vincent ULg; Destain, Marie-France ULg; Magein, Hugo ULg

Book published by Ministère des Classes moyennes et de l'Agriculture - DG6 -Service Recherche subventionnée (2001)

L'ouvrage présente les résultats des recherches effectuées pour mettre au point un système de tri automatisé pour pommes, en fonction des critères de qualité externe, la couleur, la forme et la présence ... [more ▼]

L'ouvrage présente les résultats des recherches effectuées pour mettre au point un système de tri automatisé pour pommes, en fonction des critères de qualité externe, la couleur, la forme et la présence de défauts. [less ▲]

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See detailOn-line fruit grading according to external quality using machine vision.
Leemans, Vincent ULg; Magein, Hugo ULg; Destain, Marie-France ULg

in AgEng Warwick 2000 - Abstract part 1 - Agricultural engineering into the third millennium (2000, July)

This paper presents apple grading into four classes according to European standards. Two varieties were tested, the Golden delicious and the Jonagold. The image database included more than thousand images ... [more ▼]

This paper presents apple grading into four classes according to European standards. Two varieties were tested, the Golden delicious and the Jonagold. The image database included more than thousand images of fruits (528 Golden, 642 Jonagold) belonging to three categories Extra, I, II and to reject. The image grading was achieved in six steps : the image acquisition, the ground colour classification, the defect segmentation, the calyx and stem recognition, the defects characterisation and finally the fruit classification in quality classes. The proposed method for apple external quality grading showed correct classification rates of 78 and 72% respectively for Golden delicious and for Jonagold apples. Taking into account that the healthy fruits were far better graded and considering that this class was under represented, the results of the proposed method (an error rate reaching respectively 5 and 10%) are compatible with the requirements of the European standards. [less ▲]

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See detailQuality fruit grading by colour machine vision: defect recognition.
Leemans, Vincent ULg; Destain, Marie-France ULg; Magein, Hugo ULg

in Acta Horticulturae (2000), (517), 405-412

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See detailDefect segmentation on 'Jonagold' apples using colour vision and a Bayesian classification method
Leemans, Vincent ULg; Magein, Hugo ULg; Destain, Marie-France ULg

in Computers & Electronics in Agriculture (1999), 23(1), 43-53

This paper shows how the information enclosed in a colour image of a bi-colour apple can be used to segment defects. A method to segment pixels, based on a Bayesian classification process, is proposed ... [more ▼]

This paper shows how the information enclosed in a colour image of a bi-colour apple can be used to segment defects. A method to segment pixels, based on a Bayesian classification process, is proposed. The colour frequency distributions of the healthy tissue and of the defects were used to estimate the probability distribution of each class. The results showed that most defects, namely bitter pit, fungi attack, scar tissue, frost damages, bruises, insect attack and scab, are segmented. However, russet was sometimes confused with the transition area between ground and blush colour. (C) 1999 Elsevier Science B.V. All rights reserved. [less ▲]

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See detailDefects segmentation on 'Golden Delicious' apples by using colour machine vision
Leemans, Vincent ULg; Magein, Hugo ULg; Destain, Marie-France ULg

in Computers & Electronics in Agriculture (1998), 20(2), 117-130

A method based on colour information is proposed to detect defects on 'Golden Delicious' apples. In a first step, a colour model based on the variability of the normal colour is described. To segment the ... [more ▼]

A method based on colour information is proposed to detect defects on 'Golden Delicious' apples. In a first step, a colour model based on the variability of the normal colour is described. To segment the defects, each pixel of ail apple image is compared with the model. If it matches the pixel, it is considered as belonging to healthy tissue, otherwise as a defect. Two other steps refine the segmentation, using either parameters computed on the whole fruit, or values computed locally. Some results are shown and discussed. The algorithm is able to segment a wide range of defects. (C) 1998 Elsevier Science B.V. All rights reserved. [less ▲]

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See detailContrôle de la qualité des pommes par vision artificielle.
Leemans, Vincent ULg; Magein, Hugo ULg; Destain, Marie-France ULg

in Fruit Belge (1998), 66(471),

Article de vulgarisation à destination des profesionnels du secteur fruitier, présentant les possibilités de l'analyse d'images numériques pour le tri des fruits suivant leur qualité externe

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See detailApple Shape Inspection with Computer Vision
Leemans, Vincent ULg; Magein, Hugo ULg; Destain, Marie-France ULg

in Sensors for Nondestructive Testing - Measuring the Quality of Fresh Fruits and Vegetables (1997, February)

Two shape separation methods were compared for shape grading of 'Golden Delicious' apples using machine vision. The first one was based on moments and other geometric parameters while the second implied ... [more ▼]

Two shape separation methods were compared for shape grading of 'Golden Delicious' apples using machine vision. The first one was based on moments and other geometric parameters while the second implied the computation of Fourier descriptors.Both methods required that one stem view and six cheek views of the fruit were presented to the camera. The Fourier descriptors were found the most efficient method since they allowed an accuracy in classification reaching 96% and can be made invariant to translation, rotation and scale. Furthermore, they are obtained from boundary information and do not need to examine the whole area of the apple. They permit the reconstruction of the apple shape from the harmonics. [less ▲]

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See detailVision artificielle et quantification de la forme de pommes
Leemans, Vincent ULg; Magein, Hugo ULg; Destain, Marie-France ULg

in Cahiers Agricultures (1997), 6

Golden delicious apples were characterised automatically by machine vision, taking into account six view of the cheeks and one of the stem end. The Fourier transform of the fruit boundaries were computed ... [more ▼]

Golden delicious apples were characterised automatically by machine vision, taking into account six view of the cheeks and one of the stem end. The Fourier transform of the fruit boundaries were computed and normalised. All the relevant information about the shape was included in the first fifteen harmonics. Moreover, particular harmonics were found to characterise the shape of the Golden delicious variety. By using the amplitude of particular harmonics in a discriminant analysis, apple were sorted into categories defined by EU, with a precision around 96%. The proposed method may also be used to compare varieties objectively, in order to identify relation between physiology and shape. [less ▲]

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See detailThe quality of 'Golden delicious' apples by colour computer vision
Leemans, Vincent ULg; Magein, Hugo ULg; Destain, Marie-France ULg

in Munack, A.; Tantau, H.-J. (Eds.) Mathematical and control application in agriculture and horticulture (1997)

A colour machine vision system was developed to form a basis for colour grading and defect inspection of 'Golden delicious' apples. The criteria were based on European Union standards and took into ... [more ▼]

A colour machine vision system was developed to form a basis for colour grading and defect inspection of 'Golden delicious' apples. The criteria were based on European Union standards and took into account commercial practices which add subclasses to the basic categories. The system was able to grade correctly more than 90% of the apple for colour (94% by using three colorimetric parameter R, G, B or H,S,I and 91% by using the single canonical variate) and ensured good defect detection (russet, scab, fungi attack, tec.). [less ▲]

Detailed reference viewed: 39 (4 ULg)