Towards an Automatic Classification of Persian Lime

Ellen M Giacometti, Gabriel Araujo, Thiago Prego, Amaro de Lima, Cristiano de Carvalho, Fabrício Silva

DOI: 10.14209/sbrt.2022.1570823756

Evento: XL Simpósio Brasileiro de Telecomunicações e Processamento de Sinais (SBrT2022)

Keywords: Random Forest Classification Persian lime Data Augmentation

Abstract

Persian Lime (Citrus × latifolia) is a citrus fruit commonly called Tahiti lime in Brazil, a major exporter of it. In this work, we propose a computer vision-based system to automatically classify Persian lime according to color, size, and defect. We designed a dataset composed of images from hundreds limes in several conditions to train and validate the proposed system. Data augmentation was employed to increase the data variability in the training stage. The results are competitive in terms of hit rate achieving over than 80% of accuracy in both maturity and defect classifications.

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