Applications of computer vision techniques in the agriculture and food industry: a review

Gomes, Jefferson de Oliveira; Leta, Fabiana Rodrigues

doi:10.1007/s00217-012-1844-2

Cited by 144 publications

(71 citation statements)

References 57 publications

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“…(Morales-Salazar et al, 1997) The reason for the use of texture as the main feature for detection is the possibility for detecting the physical appearance of mango leaves by naked eye, the change in color can be distinguished easily. (Gomes & Leta, 2012) However, this cannot be done by layman due to their limitation. Proving empirically on results subsequent research (Prasetyo, 2013;Prasetyo, 2016), the detection system has a better accuracy that is 88.89%.…”

Section: Current Research On Mangomentioning

confidence: 99%

Detection of Mango Tree Varieties Based on Image Processing

Prasetyo

2016

IJOST

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Mango is one of the most favourite fruits in the world. Therefore, this type of fruit has been researched deeply to enrich the variety. Here, the purpose of this study was to find the easiest method to determine the type and the variety of mango. In short of the experimental method, we analyzed the leaf using an image processing method. To confirm our result, several analyses were also conducted: leaves process digital image acquisition, and preprocessing, as well as feature extraction and classification. The result showed that our image processing method was effective to detect the variation of up to 78%. We believe that further study using this method will be effective for other types of fruits.

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Section: Current Research On Mangomentioning

confidence: 99%

Detection of Mango Tree Varieties Based on Image Processing

Prasetyo

2016

IJOST

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“…Banana images were acquired simultaneously with the spectral colorimetric measurements for analysis and determination of color, and subsequent characterization of the ripening subclass [1,2].…”

Section: Image Color Analysis Of the Banana Peelmentioning

confidence: 99%

“…Chromaticity coordinate values were calculated according to [6] and [7], after correction of the camera sensor's response using Equation set (1).…”

Section: System Calibrationmentioning

confidence: 99%

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Colorimetry and Computer Vision for Color Characterization by Image, Applied to Integrated Fruit Production

Gomes

Baldner

Costa

et al. 2015

17th International Congress of Metrology

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Résumé. L'utilisation de contrôles automatisés dans l'industrie agricole et alimentaire est désormais une solution commune pour l'analyse finale de la qualité du produit. Les caractéristiques évaluées incluent les aspects dimensionnels, mais aussi ses caractéristiques de couleur, de texture et de forme. De nombreux de pays utilisent des normes pour la classification, l'étiquetage et l'emballage afin de standardiser la qualité des produits commercialisés et de répondre aux demandes des consommateurs. La classification de fruits englobe différents paramètres tels que l'état de maturité, la quantité, la taille, etc. Ainsi, le but de cet article est de présenter une méthodologie de test utilisant des techniques non destructives de colorimétrie et de visualisation par ordinateur pour caractériser les couleurs par l'image, appliquée à la production fruitière intégrée. Afin d'atteindre l'objectif proposé, la banane (Musa sapientum) a été choisie comme étude de cas pour le développement de cette recherche. En conséquence, une nouvelle méthodologie a été développée pour caractériser les étapes de maturation de la banane à partir de l'analyse colorimétrique et proposer une norme pour le secteur. Cette norme comprend la classification des stades de maturation, la définition d'un système d'éclairage plus efficace et de la meilleure couleur de fond à utiliser, et une proposition pour l'étalonnage du système.

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“…And it is the area of engineering which deals with the study and application of methods which enable the computer to understand the content of an image, and this interpretation involves the extraction of certain characteristics which are important for a given aim ( Gomes & Leta, 2012) [12]. Over the past few years the development of information science, image processing and pattern recognition technology has been rapid.…”

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confidence: 99%

Quality Inspection of Fruits and Vegetables using Colour Sorting in Machine Vision System: A review

Anish¹

2017

IJETED

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ABSTRACT:Quality is an important aspect in the trading and business of vegetable and fruits. The customer satisfaction and acceptance depends greatly on the external appearance of these food items. The qualities assessed include the size, shape, colour and texture. At present only manual inspection is being done to brand the quality of the product. Manual inspection is challenging in terms of the speed of inspection and the reliability of the output. Machine vision systems may be used as an object of quality evaluation. Various methods such as colour sorting and pattern recognition can be used to evaluate the quality of the fruit or vegetable. Machine vision systems provide a nondestructive, reliable, accurate and fast results regarding the external appearance of the fruit or vegetable. The application of lighting, cameras and image processing are being discussed here with an eye on the future developments possible.

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Applications of computer vision techniques in the agriculture and food industry: a review

Cited by 144 publications

References 57 publications

Detection of Mango Tree Varieties Based on Image Processing

Detection of Mango Tree Varieties Based on Image Processing

Colorimetry and Computer Vision for Color Characterization by Image, Applied to Integrated Fruit Production

Quality Inspection of Fruits and Vegetables using Colour Sorting in Machine Vision System: A review

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