Artificial Visualization System for Asparagus Classification in a Fresh Asparagus Processing and Exporting Company

León León R.A.; Castillo Alva N.D.; Soto Lozada X.A. · CICIC 2023 - Decima Tercera Conferencia Iberoamericana de Complejidad, Informatica y Cibernetica en el contexto de the 14th International Multi-Conference on Complexity, Informatics, and Cybernetics, IMCIC 2023 - Memorias (2023) · DOI: 10.54808/cicic2023.01.192

Resumen

This research project applies computer vision to the detection of specific characteristics of asparagus destined for the food industry. Using computer vision supported by a camera and the Python programming language, this research aims to simulate the classification of asparagus based on two criteria: color and tip type, with a focus on achieving precision in the analysis of each. Python is chosen as the programming language for its developer-friendly features, making it an ideal choice for this project. Additionally, computer vision is considered efficient, working with image analysis of asparagus from the reception area, gathered data, and a programming language, which relies heavily on continuous research for the application to function. The goal of this research is to be implemented as a solution for classifying asparagus according to the aforementioned criteria, achieving an efficiency rate of 95%.

Instituciones: Universidad Privada del Norte