TY - GEN
T1 - SIMULACIÓN DE UN SISTEMA DE CLASIFICACIÓN DE FRASCOS DE CONSERVAS MEDIANTE VISIÓN ARTIFICIAL EN LAS EMPRESAS USANDO PYTHON
AU - Leon, Ryan León
AU - Jiménez, Nicole Guevara
AU - Cabrera, Samuel Briceño
AU - Llanos, Álvaro Espinoza
AU - Nolasco, Leyla Gamboa
AU - Alzamora, Angel Marín
AU - Rodriguez, Paulina Paz
N1 - Publisher Copyright:
© 2022 Latin American and Caribbean Consortium of Engineering Institutions. All rights reserved.
PY - 2022
Y1 - 2022
N2 - The project proposes a system that performs the classification of glass jars with preserves using a machine vision program in python loaded on a computer which extracts the characteristics of the jars through their exterior colour of the piquillo pepper product, The algorithm that we developed was able to detect jars in good condition and give an alarm signal when foreign material is present inside the jars due to the difference in colour using a high resolution Logitech camera that captures images of the jars that are in a stable and illuminated environment. These jars have previously been subjected to industrial sterilisation in autoclaves so, when the automated system is implemented, it classifies the jars in the canning companies and according to the corresponding colour, the programme differentiates the jars that are in good condition from those that have foreign material with a reliability of 98% according to the design tests, saving costs and using fewer resources within the company.
AB - The project proposes a system that performs the classification of glass jars with preserves using a machine vision program in python loaded on a computer which extracts the characteristics of the jars through their exterior colour of the piquillo pepper product, The algorithm that we developed was able to detect jars in good condition and give an alarm signal when foreign material is present inside the jars due to the difference in colour using a high resolution Logitech camera that captures images of the jars that are in a stable and illuminated environment. These jars have previously been subjected to industrial sterilisation in autoclaves so, when the automated system is implemented, it classifies the jars in the canning companies and according to the corresponding colour, the programme differentiates the jars that are in good condition from those that have foreign material with a reliability of 98% according to the design tests, saving costs and using fewer resources within the company.
KW - Canning jars
KW - Machine vision
KW - Quality control
KW - Quality control
KW - Sorting
KW - Sorting
UR - https://www.scopus.com/pages/publications/85150737552
U2 - 10.18687/LEIRD2022.1.1.181
DO - 10.18687/LEIRD2022.1.1.181
M3 - Contribución a la conferencia
AN - SCOPUS:85150737552
T3 - Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology
BT - Proceedings of the 2nd LACCEI International Multiconference on Entrepreneurship, Innovation and Regional Development
A2 - Larrondo Petrie, Maria M.
A2 - Texier, Jose
A2 - Matta, Rodolfo Andres Rivas
T2 - 2nd LACCEI International Multiconference on Entrepreneurship, Innovation and Regional Development, LEIRD 2022
Y2 - 6 December 2022 through 7 December 2022
ER -