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Simulation System of a Tomato Sorting Process Using Artificial Vision

Part of the Lecture Notes in Networks and Systems book series (LNNS,volume 405)

Abstract

This present research consists of a design of a virtual plant to simulate the automatization of a tomato sorting process by means of artificial vision. This sorting process starts with the entry of tomatoes on a conveyor belt, the fruits move at a constant speed until they are under the scope of the camera. An image processing system developed in LabVIEW software is in charge of detecting three main characteristics: green color, red color and defects on the surface of the fruit. The simulation was performed in Factory I/O software in conjunction with TIA Portal to obtain a real simulation environment.

Keywords

  • Machine vision
  • Tomatoes
  • Processing
  • Imaging

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  • DOI: 10.1007/978-3-030-96043-8_11
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References

  1. Padrón Pereira, C.A., Padrón León, G.M., Montes Hernández, A.I., Oropeza González, R.A.: Determinación del color en epicarpio de tomates (lycopersicum esculentum mill.) con sistema de visión computarizada durante la maduración, San Pedro (2012).www.cia.ucr.ac.cr. Accessed Mar 29 2021

  2. Soria, Á.: Modelo Analítico De Calidad De Fruto En Explotaciones Agrícolas Dedicadas Al Cultivo Del Tomate A Partir De Visión Artificial. Universidad de Alcalá Escuela Politécnica Superior, Alcalá (2020)

    Google Scholar 

  3. Vega, J.O.: Control de calidad Gestiopolis (2020). https://www.gestiopolis.com/control-de-calidad/. Accessed Mar 30 2021

  4. Ausay, E.: Respuesta de tomate riñón (lycopersicum esculentum mill) cv dominic bajo invernadero a dos relaciones nitrato/amonio mediante fertiriego por goteo. Escuela Superior Politécnica del Chimborazo, Riobamba (2015)

    Google Scholar 

  5. Bernal, R.: Enfermedades de tomate (lycopersicum esculentum mill.) en invernadero en las zonas de salto y bella unión. Montevideo: Unidad de Comunicación y Transferencia de Tecnología INIA (2010)

    Google Scholar 

  6. Bilbao, J.: Fotografía y emigración. 1era edici, Salamanca (2008)

    Google Scholar 

  7. Viera-Maza, G.: Procesamiento De Imágenes Usando Opencv Aplicado En Raspberry Pi Para La Clasificación Del Cacao. Universidad de Piura, Piura (2017)

    Google Scholar 

  8. Vélez, J., Moreno, A., Sánchez, Á.: Visión por computador, 2da Edición. Madrid (2015)

    Google Scholar 

  9. García, I.: Visión artificial y procesamiento digital de imágenes, Rev. Científica axioma, no. 3, pp. 40–41 (2007). http://axioma.pucesi.edu.ec/index.php/axioma/article/view/149. Accessed Mar 30 2021

  10. Molina, L., Vargas, C.: Estudio E Implementación De Un Sistema De Control De Calidad Para La Detección De Contaminantes Superficiales De Diferentes Tipos De Frutas Usando Visión Artificial. Universidad de las Fuerzas Armadas, Latacunga (2019)

    Google Scholar 

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Correspondence to Sandro Balarezo .

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Balarezo, S., Arias, X., Espín, K., Aquino, M., Novillo, G. (2022). Simulation System of a Tomato Sorting Process Using Artificial Vision. In: Botto-Tobar, M., Cruz, H., Díaz Cadena, A., Durakovic, B. (eds) Emerging Research in Intelligent Systems. CIT 2021. Lecture Notes in Networks and Systems, vol 405. Springer, Cham. https://doi.org/10.1007/978-3-030-96043-8_11

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