SIMULATION OF A CANNING JAR SORTING SYSTEM BY MACHINE VISION IN ENTERPRISES USING PYTHON
Read ArticleDate of Conference
December 6-7, 2022
Published In
“Exponential Technologies and Global Challenges: Moving toward a new culture of entrepreneurship and innovation for sustainable development”
Location of Conference
Virtual Edition
Authors
León León, Ryan Abraham
Guevara Jiménez, Nicole Del Milagro
Briceño Cabrera, Samuel
Espinoza Llanos, Álvaro
Gamboa Nolasco, Leyla
Marín Alzamora, Ángel
Paz Rodríguez, Paulina
Abstract
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.