Grapes Visual Segmentation for Harvesting Robots Using Local Texture Descriptors

  • Eftichia Badeka
  • Theofanis Kalabokas
  • Konstantinos Tziridis
  • Alexander Nicolaou
  • Eleni Vrochidou
  • Efthimia Mavridou
  • George A. PapakostasEmail author
  • Theodore Pachidis
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11754)


This paper investigates the performance of Local Binary Patterns variants in grape segmentation for autonomous agricultural robots, namely Agrobots, applied to viniculture and winery. Robust fruit detection is challenging and needs to be accurate to enable the Agrobot to execute demanding tasks of precise farming. Segmentation task is handled by classification with the supervised machine learning model k-Nearest Neighbor (\( k \)-NN), including extracted features from Local Binary Patterns (LBP) and their variants in combination of color components. LBP variants are tested for both varieties of red and white grapes, subject to performance measures of accuracy, recall and precision. The results for red grapes indicate an approximate intended accuracy of 94% of detection, while the results relating to white grapes confirm the concerns of complex indiscreet visual cues providing accuracies of 83%.


Visual computing Computer vision Grapes detection Image segmentation Local binary patterns 



This research has been co‐financed by the European Union and Greek national funds through the Operational Program Competitiveness, Entrepreneurship and Innovation, under the call RESEARCH – CREATE – INNOVATE (project code: T1EDK-00300).


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Eftichia Badeka
    • 1
  • Theofanis Kalabokas
    • 1
  • Konstantinos Tziridis
    • 1
  • Alexander Nicolaou
    • 1
  • Eleni Vrochidou
    • 1
  • Efthimia Mavridou
    • 1
  • George A. Papakostas
    • 1
    Email author
  • Theodore Pachidis
    • 1
  1. 1.HUman-MAchines INteraction Laboratory (HUMAIN-Lab), Department of Computer ScienceInternational Hellenic UniversityKavalaGreece

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