Artificial vision in pattern recognition for fruit classification in agrobusiness

• Autores: Sucari León, Reynaldo, Aroquipa Durán, Yolanda, Quina Quina , Luz Delia, Quispe Yapo, Edgardo, Sucari León, Anibal, Huanca Torres, Fredy Abel s
• Formato: artículo
• Fecha de Publicación: 2020
• Institución: Universidad Nacional Autónoma de Huanta
• Repositorio: Revista UNAH - Puriq
• Lenguaje: español
• OAI Identifier: oai:ojs2.www.revistas.unah.edu.pe:article/76
• Enlace del recurso: https://www.revistas.unah.edu.pe/index.php/puriq/article/view/76
• Nivel de acceso: acceso abierto
• Materia: clasificación de frutas; reconocimiento de patrones; visión artificial; fruit classification; pattern recognition; artificial vision

The purpose of this research was to determine the effectivity of applying artificial vision on patterns recognition for the fruits classification in agrobusiness, for this purpose we has used a database with 50 records of 6 fruit varieties with 4 characteristics that are considered for each fruit and a sample of 20 fruits, likewise has been used the automatic pattern recognition technique through the Bayesian classifier implemented in Octave, in the experiment it was recognized to the fruits up to 93.33% and erring in other cases 6.67%. Concluding that is effective to apply artificial vision in the pattern recognition classify fruits.