Development of an artificial vision model to detect the degree of maturity of the Arca type pepper

León León R.A.; Reyes Vidal R.Y.; Sifuentes Ruiz A.B. · CISCI - Conferencia Iberoamericana en Sistemas, Cibernetica e Informatica (2024) · DOI: 10.54808/cisci2024.01.335

Resumen

The present research aims to develop a computer vision algorithm for the detection of the maturity level of Ark-type peppers. The programming language Python was employed for the development of the computer vision algorithm; furthermore, the outlined methodology is non-experimental, applied, and quantitatively error-proof. The developed software successfully achieves a maturity detection accuracy of 98% with a 2% error margin. Ultimately, it is concluded that the application of this technology has a significant impact on the export-oriented industrial sector. Moreover, our focus revolves around type-based classification, an aspect not thoroughly addressed in other studies within this domain, thereby providing a unique and valuable contribution to the scientific literature in this field. © CISCI - Simposium Iberoamericano en Educacion, Cibernetica e Informatica 2024.

Instituciones: Universidad Privada del Norte