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Artificial vision in pattern recognition for fruit classification in agrobusiness
[Visión artificial en reconocimiento de patrones para clasificación de frutas en agronegocios]

Author

Listed:
  • León Reynaldo Sucari

    (Universidad Nacional Autónoma de Huanta)

  • Yolanda Aroquipa Durán

    (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)

  • Fredy Abel Huanca Torres

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.

Suggested Citation

  • León Reynaldo Sucari & Yolanda Aroquipa Durán & Edgardo Quispe Yapo & Anibal Sucari León & Luz Delia Quina Quina & Fredy Abel Huanca Torres, 2020. "Artificial vision in pattern recognition for fruit classification in agrobusiness [Visión artificial en reconocimiento de patrones para clasificación de frutas en agronegocios]," Post-Print halshs-02554550, HAL.
    • Handle: RePEc:hal:journl:halshs-02554550
    DOI: 10.37073/puriq.2.2.76
    Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-02554550
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