Publicado:
2025-11-30Número:
Vol. 19 Núm. 2 (2025)Sección:
Visión InvestigadoraDevelopment of a color classification algorithm in processed milk using RGB image analysis with computer vision
Desarrollo de un algoritmo de clasificación de coloración en leche procesada: análisis de imágenes RGB usando visión computacional
Palabras clave:
Programming algorithm, quality, HSV, OpenCV, perception, Python, RGB, Streaming, Computer vision (en).Palabras clave:
HSV, OpenCV, Python, RGB, Algoritmo de programación, calidad, percepción, Streaming, Visión por computador (es).Descargas
Resumen (en)
This document presents the design and testing of an optical sensor based on computer vision to detect the ideal color quality of processed milk through the reflection of a white incident light source, with the aim of being used in industrial dairy production quality visual testing, the system is designed with the use of a digital camera acting as a photodetector and a Python programming algorithm using the OpenCv library, which allows the detection and identification of color and its translation from Red, Green, Blue (RGB) to Hue Saturation Value (HSV). To minimize human intervention in the process, the system detected the coloration of previously evaluated and recognized samples of good quality and took these color values to calculate a non-rejection range, then evaluated an individual sample and classified it as ideal or non-ideal color quality, and finally recorded the results obtained from the tests.
Resumen (es)
En este documento se presenta el diseño y pruebas de un sensor óptico basado en la visión computacional para detectar la coloración de calidad ideal de la leche procesada por medio de la reflexión de una fuente de luz blanca incidente, con la finalidad de ser utilizado en las pruebas de calidad visual de una cadena de producción industrial lechera. El sistema está diseñado con el uso de una cámara digital la cual actúa como fotodetector y un algoritmo de programación en lenguaje Python que utiliza la librería OpenCv la cual permite la detección e identificación del color y su traducción tipológica de Red, Green, Blue (RGB) a Hue Saturation Value (HSV). Para minimizar la intervención humana en el proceso, el sistema detectó la coloración de muestras previamente evaluadas y reconocidas como muestras de buena calidad y tomó estos valores de color con el fin de calcular un rango de no rechazo y posteriormente evaluar una muestra individual y clasificarla como una coloración de calidad ideal o no, para finalizar, se registraron los resultados obtenidos de las pruebas.
Referencias
. Dillon, J. J. . Seven Decades of Milk-A History of New York's Dairy Industry. Read Books Ltd (2019).
. Castilla-Pinedo, Y., Alvis-Estrada, L., & Alvis-Guzmán, N. Exposure to organochlorines by ingestion of pasteurized milk marketed in Cartagena, Colombia. Journal of Public Health, 12, 14-26 (2020).
. Valbuena, E., Castro, G., Lima, K., Acosta, W., Bríñez, W., & Tovar, A. Microbiological quality of the main pasteurized milk brands distributed in the city of Maracaibo, Venezuela. Revista Científica, 14(1) (2019).
. Carulla, J. E., & Ortega, E. . Dairy production systems in Colombia: challenges and opportunities. Archivos latinoamericanos de producción animal, 24(2), 83-87 (2016).
. Rodríguez-Magadán, H. M., Salinas-Rios, T., Aquino-Cleto, M., Ortiz-Muñoz, I. Y., Pérez- León, M. I., Jiménez-López, G., & Hernández-Bautista, J. Yield and organoleptic characteristics of fresh cheese made from alcohol-positive milk. Agro Productividad, 12 (2019).
. Rojas, G., & Jeannet, E. Neurobiology of visual perception. Editorial Universidad del Rosario (2021).
. Valencia, V. R., Larrea, N. L., Salazar, J. G., & Valencia, J. M. Prototype of a wireless sensor network for recreational water quality monitoring. Revista Ibérica de Sistemas e Tecnologias de Informação, (E32), 359-372 (2020).
. Revilla, Aurelio. "Milk technology: processing, manufacturing and analysis." (1982).
. Filoteo-Razo, J. D., Estudillo-Ayala, J. M., Hernández-García, J. C., Jáuregui-Vázquez, D., Rojas-Laguna, R., Valle-Atilano, F. J., & Sámano-Aguilar, L. F. (2020). RGB sensor to detect color changes in fruit skin. Acta Universitaria, 26(1), 24-29.
. Ningsih, L., & Cholidhazia, P. Classification Of Tomato Maturity Levels Based On RGB And HSV Colors Using KNN Algorithm. RIGGS: Journal of Artificial Intelligence and Digital Business, 1(1), 25-30. (2022).
. Demasi, M. D., & Vidal, L. Use of the OpenCV library for segmentation and classification of weather radar images.(2022).
. Acosta Morales, R. J. Vehicle license plate recognition applying digital image processing in Python-OpenCV (Doctoral dissertation) (2020).
. Revilla, A. (1982). Tecnologia de la Leche-Processing, manufacturing and analysis. https://www.academia.edu/36652945/TECNOLOGIA_DE_LA_LECHE_REVILLA
. Arévalo-Vázquez, E. E., Zúñiga-López, A., Villegas-Cortez, J., & Avilés-Cruz, C. (2015). Implementation of object recognition by color and shape in a mobile robot. Research in Computing Science, 91(1), 21-31. https://doi.org/10.13053/rcs-91-1-2. https://doi.org/10.13053/rcs-91-1-2
. Bryan Manuel, V. Z. (n.d.). Evaluation of the quality and safety of milk in the dairy collection center san isidro del canton sucre [PROYECTO DE INVESTIGACIÓN, ESCUELA SUPERIOR POLITÉCNICA AGROPECUARIA DE MANABÍ MANUEL FÉLIX LÓPEZ]. https://repositorio.espam.edu.ec/bitstream/42000/1886/1/TIC_MV12D.pdf
. Chagua Aduviri, I. L., Quispe-Barra, M. A., & Ortega Achata, O. A. (2022). Design and construction of a prototype quinoa color sorting machine using IR sensors. Revista De Investigaciones Altoandinas - Journal of High Andean Research, 24(1), 45-52. https://doi.org/10.18271/ria.2022.272. https://doi.org/10.18271/ria.2022.272.
. Contrero, R. (2008). Milk quality: A challenge in Ecuador. La Granja: Journal of Science from the Vida. https://lagranja.ups.edu.ec/index.php/granja/article/view/7.2008.05
. Dussán-Sarria, S., Garzón-García, A. M., & Melo-Sevilla, R. E. (2020). Development and evaluation of a prototype for color measurement in fresh vegetables. Technological Information, 31(1), 253-260. https://doi.org/10.4067/s0718-07642020000100253.
. Padrón Pereira, C. A., Padrón León, G. M., Montes Hernández, A. I., & Oropeza González, R. (2012). Determination of color in epicarp of tomatoes (Lycopersicum esculentum mill.) with computer vision system during ripening. Agronomía Costarricense. https://doi.org/10.15517/rac.v36i1.9969.
. Rege, S., Memane, R., Phatak, M., & Agarwal, P. (2013). 2d geometric shape and color recognition using digital image processing. International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering, https://www.matlabi.ir/wp-content/uploads/bank_papers/gpaper/g517- www.Matlabi.ir.pdf
. Shreya, D. S. (2021). Digital image processing and recognition using python. International Journal of Engineering Applied Sciences and Technology. https://doi.org/10.33564/ijeast.2021.v05i10.046. https://doi.org/10.33564/ijeast.2021.v05i10.046
. Tafur Garzón, M. A. (2009). Food safety and international trade. Colombian JournalFrom Ciencias Pecuarias. https://revistas.udea.edu.co/index.php/rccp/article/view/324460/20781634
. Valdivia Avila, A. L., Rubio Fontanills, Y., & Beruvides Rodríguez, A. (n.d.). Hygienic-sanitary quality of milk, a priority for producers. Salud Animal. http://scielo.sld.cu/pdf/rpa/v33n2/2224-7920-rpa-33-02-1.pdf
. Vargas, T. (n.d.). Milk quality: Vision of the dairy industry. INLACA Foundation; Faculty of Ciencias Veterinarias. http://avpa.ula.ve/docuPDFs/xcongreso/P297_CalidadLeche.pdf
. Zuluaga, N. (2017). Food sensory analysis as a tool for the characterization and quality control of dairy derivatives [Extended abstract of Master's Thesis in Food Science and Technology, Universidad Nacional de Colombia]. https://repositorio.unal.edu.co/handle/unal/62784
. Zumbado Gutiérrez, L., & Romero Zuñiga, J. J. (2016). Concepts on safety in primary milk production. Revista Ciencias Veterinarias, 33(2), 51. https://doi.org/10.15359/rcv.33-2.1. https://doi.org/10.15359/rcv.33-2.1
. Zurita, J., & Perez, L. (n.d.). Design and implementation of an automatic machine to classify objects according to their color detected by a color sensor and classified by a robotic arm". Electrical and Electronics Department of the University of the Armed Forces.Armed Forces University ESPE Extension Latacunga. https://repositorio.espe.edu.ec/bitstream/21000/7343/1/AC-ESPEL-ENI-0313.pdf
Images or figures
Productos Naturales De La Sabana S.A.S. Nutritional Information Table (2022). https://alqueria.com.co/productos/leche/4-leche-deslactosada
Cómo citar
APA
ACM
ACS
ABNT
Chicago
Harvard
IEEE
MLA
Turabian
Vancouver
Descargar cita
Visitas
Descargas
Licencia

Esta obra está bajo una licencia internacional Creative Commons Atribución-NoComercial 4.0.
.png)
atribución- no comercial 4.0 International




.jpg)





