Bibliographic citations
This is an automatically generated citacion. Modify it if you see fit
Gonzales, G., (2020). Automated classification system of giant white corn using image processing and supervised techniques [Universidad de Lima]. https://hdl.handle.net/20.500.12724/12722
Gonzales, G., Automated classification system of giant white corn using image processing and supervised techniques []. PE: Universidad de Lima; 2020. https://hdl.handle.net/20.500.12724/12722
@misc{renati/1442454,
title = "Automated classification system of giant white corn using image processing and supervised techniques",
author = "Gonzales Asto, Gabriela",
publisher = "Universidad de Lima",
year = "2020"
}
Title: Automated classification system of giant white corn using image processing and supervised techniques
Authors(s): Gonzales Asto, Gabriela
Advisor(s): Gutiérrez Cárdenas, Juan Manuel
Keywords: Maíz; Algoritmos computacionales; Proceso de imágenes; Corn; Computer algorithms; Image processing
OCDE field: https://purl.org/pe-repo/ocde/ford#2.02.04
Issue Date: 2020
Institution: Universidad de Lima
Abstract: Nowadays, the use of artificial vision for classification in agricultural products has
proven to have a great impact on this field. The exportation of agricultural goods has
risen all over the world, consequently, that is the reason why exporting companies are
looking to automate their processes and artificial vision techniques seems a great niche.
This automation will allow an improvement in their production performance by
diminishing the time and cost of their processes. While having a sound quality product
in less time, improved precision and with no extensive manipulation of the product. In
this article, we aim to offer a low cost alternative to this procedure oriented to the
classification of Peruvian white corn by proposing an algorithm for the segmentation
and recognition of images using computer vision techniques.
Link to repository: https://hdl.handle.net/20.500.12724/12722
Discipline: Ingeniería de sistemas
Grade or title grantor: Universidad de Lima. Facultad de Ingeniería y Arquitectura
Grade or title: Ingeniero de sistemas
Juror: Guzman-Jimenez, Rosario-Marybel; Ayma-Quirita, Victor-Hugo; Ramos-Ponce, Oscar-Efrain
Register date: 17-Mar-2021
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.