Computer vision system in real-time for color determination on flat surface food

Saldaña, Erick; Siché, Raúl; Huamán, Rosmer; Luján, Mariano; Castro, Wilson; Quevedo, Roberto

doi:10.17268/sci.agropecu.2013.01.06

Cited by 13 publications

(5 citation statements)

References 24 publications

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“…Por otro lado, el prototipo evaluado permite eliminar interferencias del medio en las mediciones y la posición del sensor de color puede ajustarse para lograr una mayor precisión en las lecturas. Saldaña et al (2013) realizaron mediciones de los parámetros de color L*, a* y b* a 30 cartulinas de colores con un sistema de visión computarizada (CVS), el cual consistía en una videocámara y una interfaz gráfica de usuario (GUIDE) de MATLAB. Estas mediciones se compararon con las determinaciones efectuadas para el mismo material con un colorímetro, y se observaron errores cercanos al 5 %.…”

Section: Resultados Y Discusiónunclassified

Desarrollo y evaluación de un prototipo de medición de color en vegetales frescos

2020

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El objetivo de este trabajo fue desarrollar y evaluar un prototipo de medición de color de vegetales frescos como alternativa económica frente a los equipos y técnicas comerciales. Se emplearon los sensores DHT11 para temperatura y TCS230-3200 para color, conectados a una tarjeta de adquisición de datos (Arduino Nano). La transferencia de información a un ordenador se estableció con los programas PXL-DAQ y Microsoft Excel ® 2013, y las mediciones se registraron en el modelo de color RGB para su conversión al sistema CIE L*a*b*. Se realizaron ensayos de comparación de medidas sobre la carta de color PANTONE con el prototipo, y colorímetro CR-400 Konica Minolta, determinándose el error medio entre las medidas. Se encontró un error medio promedio de 15,57 % y 27,45 % en las mediciones registradas por el prototipo de color y el colorímetro, respectivamente, lo cual evidenció que el uso del prototipo es una alternativa técnica apropiada de medición de color en vegetales frescos.

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Section: Resultados Y Discusiónunclassified

Desarrollo y evaluación de un prototipo de medición de color en vegetales frescos

2020

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“…According to Saldaña et al (2013), to convert the RGB colour space of an image obtained by a computer vision system, to the L* a* b* colour space, this must be done in two phases. The first phase involves the conversion from RGB to XYZ, and the second phase from XYZ to the CIELab colour space.…”

Section: Size and Volumementioning

confidence: 99%

Review: computer vision applied to the inspection and quality control of fruits and vegetables

Saldaña

Siché

Luján

et al. 2013

Braz. J. Food Technol.

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This is a review of the current existing literature concerning the inspection of fruits and vegetables with the application of computer vision, where the techniques most used to estimate various properties related to quality are analyzed. The objectives of the typical applications of such systems include the classification, quality estimation according to the internal and external characteristics, supervision of fruit processes during storage or the evaluation of experimental treatments. In general, computer vision systems do not only replace manual inspection, but can also improve their skills. In conclusion, computer vision systems are powerful tools for the automatic inspection of fruits and vegetables. In addition, the development of such systems adapted to the food industry is fundamental to achieve competitive advantages. ResumoEste trabalho apresenta uma revisão da literatura existente, mais recente, sobre visão computacional aplicada à inspeção de frutas e verduras. Foram analisadas as técnicas mais empregadas para estimar diversas propriedades relacionadas com a qualidade. Os objetivos das aplicações típicas de tais sistemas incluem a classificação, a estimativa da qualidade segundo características internas ou externas, o seguimento dos processos da fruta durante o armazenamento ou a avaliação de tratamentos experimentais. Em geral, um sistema de visão computacional não só pode substituir a inspeção manual, mas também melhorar suas capacidades. Conclui-se que os sistemas de visão computacional são potentes ferramentas para a inspeção automática da qualidade de frutas e verduras, e o desenvolvimento de sistemas deste tipo, adaptados à indústria de alimentos, é fundamental para adquirir vantagens competitivas. Campinas, v. 16, n. 4, p. 254-272, out./dez. 2013 Review: computer vision applied to the inspection and quality control of fruits and vegetables Revisão: visão computacional aplicada à inspeção e ao controle da qualidade de frutas e verduras

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“…The classical instrument is the colorimeter, which optically quantifies color by measuring XYZ tristimulus values. XYZ is a quantitative representation of the human eye color receptors—red, green, and blue (RGB; Saldaña et al, 2013). From these values, color differences can be analyzed using the CIELAB color space ( L * a * b *) defined by the International Commission on Illumination (CIE).…”

Section: Introductionmentioning

confidence: 99%

Novel apparatus for monitoring simultaneously color and °Brix of selected fruit juices through RGB image analysis

Ortiz

Oliveira

Venâncio

et al. 2023

J Food Process Engineering

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This work introduces a novel apparatus for monitoring both color and °Brix of selected fruit juices. These parameters are essential for quality and processing control at concentration and dilution operations. The proposed apparatus performs the red, green, and blue (RGB) image analysis of the fruit juice as it flows through a transparent cell equipped with a webcam and a light source. The viewing cell is inside a box for controlling temperature and for ensuring homogeneous lighting. This apparatus not only measures the RGB color space of the fruit juice online but also allows relating it to the °Brix. The relationship between RGB and °Brix was obtained by measuring the RGB color space of various fruit juice samples, of which the °Brix were previously determined using a digital refractometer. RGB image analysis showed an excellent relationship with °Brix (R2 > 0.99, using an exponential fit), allowing for monitoring reliably this parameter during continuous fruit juice concentration and dilution experiments. These results show the potential of this novel apparatus to substitute conventional instruments such as colorimeters and refractometers for online process monitoring. Furthermore, it has the advantage of not requiring sampling, which reduces measurement errors and saves time.Practical applicationsThis work introduces a novel apparatus based on RGB image analysis for monitoring simultaneously the color and the °Brix of fruit juices. These parameters are important to control the production and quality of fruit juices, especially at concentration and dilution operations. The apparatus proposed here is a viewing cell where the RGB color space is quantified using the software RGBview® as the fruit juice flows through it. The °Brix are determined from the RGB color space using a suitable fit obtained from a previous calibration with juice samples with known °Brix. This is an alternative to conventional analytical instruments such as colorimeters and refractometers but with the advantage of performing an online measurement. This configuration allows for the reduction of analytical errors associated with sampling and saves time. Moreover, this apparatus has the potential to monitor other physicochemical properties related to the color of fruit juices.

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Computer vision system in real-time for color determination on flat surface food

Cited by 13 publications

References 24 publications

Desarrollo y evaluación de un prototipo de medición de color en vegetales frescos

Desarrollo y evaluación de un prototipo de medición de color en vegetales frescos

Review: computer vision applied to the inspection and quality control of fruits and vegetables

Novel apparatus for monitoring simultaneously color and °Brix of selected fruit juices through RGB image analysis

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