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

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations


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.

Original languageEnglish
Title of host publicationApplications of Digital Image Processing XLIII
EditorsAndrew G. Tescher, Touradj Ebrahimi
ISBN (Electronic)9781510638266
StatePublished - 2020
Externally publishedYes
EventApplications of Digital Image Processing XLIII 2020 - Virtual, Online, United States
Duration: 24 Aug 20204 Sep 2020

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X


ConferenceApplications of Digital Image Processing XLIII 2020
Country/TerritoryUnited States
CityVirtual, Online

Bibliographical note

Publisher Copyright:
© 2020 SPIE


  • Citrus Aurantifolia
  • Color classification
  • Color features
  • Feature extraction
  • Fruit classification
  • KNN
  • Lemon classification
  • SVM


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