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Computer vision application for improved product traceability in the granite manufacturing industry

  • Martínez, J. [1] ; Rigueira, X. [1] ; Araújo, M. [1] ; Giráldez, E. [1] ; Recamán, A. [2]
    1. [1] Universidade de Vigo

      Universidade de Vigo

      Vigo, España

    2. [2] Pavestone S.L.
  • Localización: Materiales de construcción, ISSN 0465-2746, Vol. 73, n 351, 2023
  • Idioma: inglés
  • DOI: 10.3989/mc.2023.308922
  • Títulos paralelos:
    • Visión artificial aplicada a la industria del granito para la mejora de la trazabilidad
  • Enlaces
  • Resumen
    • español

      La trazabilidad de los bloques de granito consiste en identificar cada bloque con un número finito de bandas de color, las cuales representan un código numérico. Dicho código tiene que ser leído varias veces durante el proceso de producción, pero la precisión de esta lectura se encuentra afectada por el factor humano, lo cual lleva a fallos en el sistema. Se presenta un sistema de visión artificial basado en la detección de colores y la decodificación de dichas bandas. El sistema hace uso de transformaciones entre espacios de color y varios intervalos para la selección de los mismos. Se implementan métodos de visión artificial, incluyendo la detección de contornos para la identificación de la posición de los colores. En último lugar, se analiza la geometría del patrón de colores para su decodificación. El algoritmo propuesto es entrenado en un set de 109 imágenes tomadas en diferentes condiciones medioambientales y validado en un set de 21 imágenes. Los resultados son prometedores, demostrando una eficacia del 75% en el proceso de validación. Por lo tanto, el sistema propuesto se considera de utilidad a la hora de incrementar la eficacia de la trazabilidad en la industria del granito.

    • English

      The traceability of granite blocks consists in identifying each block with a finite number of colour bands that represent a numerical code. This code has to be read several times throughout the manufacturing process, but its accuracy is subject to human errors, leading to cause faults in the traceability system. A computer vision system is presented to address this problem through colour detection and the decryption of the associated code. The system developed makes use of colour space transformations and various thresholds for the isolation of the colours. Computer vision methods are implemented, along with contour detection procedures for colour identification. Lastly, the analysis of geometrical features is used to decrypt the colour code captured. The proposed algorithm is trained on a set of 109 pictures taken in different environmental conditions and validated on a set of 21 images. The outcome shows promising results with an accuracy rate of 75.00% in the validation process. Therefore, the application presented can help employees reduce the number of mistakes in product tracking.

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