Colour measurements by computer vision for food quality control – A review

Wu, Di; Sun, Da‐Wen

doi:10.1016/j.tifs.2012.08.004

Cited by 508 publications

(298 citation statements)

References 66 publications

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“…The assessment of color quality and consistency itself is a well-addressed topic and is employed in many very different fields of research [14,13,12]. The CIE calibrated color spaces are a convenient way of obtaining device independent color measurements [9].…”

Section: Related Workmentioning

confidence: 99%

An Image-Based Method for Objectively Assessing Injection Moulded Plastic Quality

et al. 2017

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Abstract. In high volume productions based on casting processes, like high-pressure die casting (HPDC) or injection moulding, there is a wide range of variables that affect the end quality of produced parts. These variables include production parameters (temperature, pressure, mixture), and external factors (humidity, temperature, etc.). With this many variables it is a challenge to maintain a stable output quality, wherefore massive amounts of resources are spent on quality assurance (QA) of produced parts. Currently, this QA is done manually through visual inspection. We demonstrate how a multispectral imaging system can be used to automatically rate the quality of a produced part using an autocorrelation and a Fourier-based method. These methods are compared with human rankings and achieve good correlations on a variety of samples.

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Section: Related Workmentioning

confidence: 99%

An Image-Based Method for Objectively Assessing Injection Moulded Plastic Quality

et al. 2017

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“…In target-based approach, an image of a reference colour card with a number of colour samples is acquired by the CVS to obtain their mean RGB values, while the correspondent XYZ values are measured by a spectrophotometer. Different methods can be applied to derive the RGB-XYZ transform: look up tables with interpolation, polynomial regressions and neural network among all (Hong et al, 2001;Wu and Sun, 2013). CIELab colour coordinates are then calculated applying the following standard transformation:…”

Section: Devices Colour Characterizationmentioning

confidence: 99%

“…Therefore, a colour space transform that maps RGB values of a digital image onto a device-independent colorimetric colour space, such as CIELab, has to be defined for accurate colour measurements (Hong et al, 2001;Westland and Ripamonti, 2004;K. León et al, 2006;Wu and Sun, 2013). This procedure is usually called device colour characterization.…”

Section: Introductionmentioning

confidence: 99%

Application of Computer Vision for quality control in frozen mixed berries production: colour calibration issues

Aimonino¹,

Gay²,

Comba³

2013

J Agricult Engineer

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Computer vision is becoming increasingly important in quality control of many food processes. The appearance properties of food products (colour, texture, shape and size) are, in fact, correlated with organoleptic characteristics and/or the presence of defects. Quality control based on image processing eliminates the subjectivity of human visual inspection, allowing rapid and non-destructive analysis. However, most food matrices show a wide variability in appearance features, therefore robust and customized image elaboration algorithms have to be implemented for each specific product. For this reason, quality control by visual inspection is still rather diffused in several food processes. The case study inspiring this paper concerns the production of frozen mixed berries. Once frozen, different kinds of berries are mixed together, in different amounts, according to a recipe. The correct quantity of each kind of fruit, within a certain tolerance, has to be ensured by producers. Quality control relies on bringing few samples for each production lot (samples of the same weight) and, manually, counting the amount of each species. This operation is tedious, subject to errors, and time consuming, while a computer vision system (CVS) could determine the amount of each kind of berries in a few seconds. This paper discusses the problem of colour calibration of the CVS used for frozen berries mixture evaluation. Images are acquired by a digital camera coupled with a dome lighting system, which gives a homogeneous illumination on the entire visible surface of the berries, and a flat bed scanner. RBG device dependent data are then mapped onto CIELab colorimetric colour space using different transformation operators. The obtained results show that the proposed calibration procedure leads to colour discrepancies comparable or even below the human eyes sensibility.

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“…It is the fi rst quality attribute of food evaluated by consumers, and is therefore an important component of food quality relevant to market acceptance (Wu & Sun, 2013). Minimizing loss of pigment during processing is a primary concern for the processing industry -continuous monitoring of color change during industrial processing is necessary to ensure product quality (Shao-qian et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

EFFECTS OF THE ADDITION OF SUGARS ON THE THERMOSTABILITY OF BETANIN FROM Beta vulgaris L.

Izaguirres

Rodrigues

Silva

et al. 2018

BCEPPA

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O impacto da adição de açúcares na estabilidade das betaninas de Beta vulgaris L. (beterraba) durante o tratamento térmico entre 50 e 80°C e pH 5 foi investigado. A degradação das betaninas pura e adicionada de 10% de sacarose e 40% de frutose seguiu modelo de cinética de primeira ordem e conforme aumento da temperatura, houve aumento dos valores da constante de degradação térmica (Kd), redução na meia-vida e nos valores do tempo de redução decimal (D). Termodinamicamente, apresentando valores de variação de entalpia (ΔH) mais altos (entre 99,66 e 99,41 kJ mol -1 ) que o extrato com a adição de sacarose (entre 85,27 e 85,03 kJ mol -1 ) e controle (entre 78,85 e 78,61 kJ mol -1 ), a incorporação de frutose foi mais promissora no aumento da estabilidade do extrato de betaninas. Os valores positivos para a variação da energia livre de Gibbs (ΔG) indicaram que a reação de degradação das betaninas foi não-espontânea e os baixos valores da variação de entropia (ΔS) para o extrato com frutose (entre 0,02 e 0,03 J mol -1 K -1 ) indicaram que o estado do material estava próximo ao seu equilíbrio termodinâmico.

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Colour measurements by computer vision for food quality control – A review

Cited by 508 publications

References 66 publications

An Image-Based Method for Objectively Assessing Injection Moulded Plastic Quality

An Image-Based Method for Objectively Assessing Injection Moulded Plastic Quality

Application of Computer Vision for quality control in frozen mixed berries production: colour calibration issues

EFFECTS OF THE ADDITION OF SUGARS ON THE THERMOSTABILITY OF BETANIN FROM Beta vulgaris L.

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