Artificial vision in pattern recognition for fruit classification in agrobusiness

Visión artificial en reconocimiento de patrones para clasificación de frutas en agronegocios

León Reynaldo Sucari, Yolanda Aroquipa Durán, Edgardo Quispe Yapo, Anibal Sucari León, Luz Delia Quina Quina and Fredy Abel Huanca Torres
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León Reynaldo Sucari: UNAH - Universidad Nacional Autónoma de Huanta
Yolanda Aroquipa Durán: UNAH - Universidad Nacional Autónoma de Huanta
Edgardo Quispe Yapo: UNAP - Universidad Nacional del Altiplano
Anibal Sucari León: UNAP - Universidad Nacional del Altiplano
Luz Delia Quina Quina: UNAJMA - Universidad Nacional José María Arguedas

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Abstract: 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.

Keywords: clasificación de frutas; reconocimiento de patrones; visión artificial; fruit classification; pattern recognition; artificial vision (search for similar items in EconPapers)
Date: 2020
Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-02554550
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Published in PURIQ, inPress, 2 (2), ⟨10.37073/puriq.2.2.76⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:halshs-02554550

DOI: 10.37073/puriq.2.2.76

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