Date fruit sorting using appearance-based information and neural network classifier

H. Bouchech, S. Foufou, L. Khriji

Research output: Chapter in Book/Report/Conference proceedingConference contribution


This paper presents a new two-step system for automatically sorting date fruit in four categories which are big 'Sukkari' dates, defective big 'Sukkari' dates, small 'Sukkari' dates and 'Khalas' dates. In the first step, we used the Principal Component Analysis tool for feature extraction and data dimensionality reduction. Then, the obtained features were injected in a modified Back-Propagation-based Neural Network to be classified. Four tests were made upon a locally made database of date images, and obtained results varied between 96 and 100% accuracy.

Original languageEnglish (US)
Title of host publicationInternational Conference on Agricultural Engineering
Subtitle of host publicationNew Technologies for Sustainable Agricultural Production and Food Security
EditorsH. Jayasuriya, Y.A. Al-Mulla, M. Ahmed
PublisherInternational Society for Horticultural Science
Number of pages8
ISBN (Electronic)9789462610453
StatePublished - Oct 22 2014

Publication series

NameActa Horticulturae
ISSN (Print)0567-7572


  • Date fruit
  • Neural network
  • Principal component analysis

ASJC Scopus subject areas

  • Horticulture


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