Automatic classification of Citrus Aurantifolia based on digital image processing and pattern recognition

Victor Tuesta-Monteza, Freddy Alcarazo, Heber I. Mejía-Cabrera, Manuel G. Forero

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

1 Cita (Scopus)


Citrus Aurantifolia swingle is grown on the northern coast of Peru for domestic consumption and export. This is an indispensable ingredient due to its high level of acidity for the preparation of fish ceviche, the traditional dish of Peruvian gastronomy. Lemons are classified according to their color in yellow, green and pinton (green lemons already showing a hint of yellow), since the yellow ones are for national consumption, while the other two types are for export. This selection is done manually. This process is time consuming and additionally lemons are frequently misclassified due to lack of concentration, exhaustion and experience of the worker, affecting the quality of the product sold in domestic and foreign markets. Therefore, this paper introduces a new method for the automatic classification of Citrus Aurantifolia, which comprises three stages: acquisition, image processing, feature extraction, and classification. A mechanical prototype for image acquisition in a controlled environment and a software for the classification of lemons were developed. A new segmentation method was implemented, which makes use only of the information obtained from the blue channel. From the segmented images we obtained the color characteristics, selecting the best descriptors in the RGB and CIELAB spaces, finding that the red channel allows the best accuracy. Two classification models were used, SVM and KNN, obtaining an accuracy of 99.04% with the K-NN.

Idioma originalInglés
Título de la publicación alojadaApplications of Digital Image Processing XLIII
EditoresAndrew G. Tescher, Touradj Ebrahimi
ISBN (versión digital)9781510638266
EstadoPublicada - 2020
Publicado de forma externa
EventoApplications of Digital Image Processing XLIII 2020 - Virtual, Online, Estados Unidos
Duración: 24 ago. 20204 set. 2020

Serie de la publicación

NombreProceedings of SPIE - The International Society for Optical Engineering
ISSN (versión impresa)0277-786X
ISSN (versión digital)1996-756X


ConferenciaApplications of Digital Image Processing XLIII 2020
País/TerritorioEstados Unidos
CiudadVirtual, Online

Nota bibliográfica

Publisher Copyright:
© 2020 SPIE


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