Classificação Automática de Ovos por Translucência: Uma Contribuição para a Indústria 4.0

Patrik L Peres, Marcio H Costa, Alvaro Burin, Ton Kramer, Lucas Rodrigues

DOI: 10.14209/sbrt.2025.1571144737

Evento: XLIII Simpósio Brasileiro de Telecomunicações e Processamento de Sinais (SBrT2025)

Keywords:

Abstract

This paper presents an automated classifier for translucency images of fertile and commercial eggs, based on machine learning methods. Translucency analysis is utilized for the evaluation of shell quality, which can be correlated with nutritional, sanitary, and management aspects. A comparison among different machine learning strategies, on the largest database reported in the literature to date, reveals evidence that the support vector machine method, fed by the ResNet512 network, yields performance comparable to that of human specialists, enabling the automation of the aforementioned process in commercial systems.

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