On feature extraction for fingerprinting grapevine leaves

Dominik L. Michels, Sven A. Giesselbach, Thomas Werner, Volker Steinhage

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

1 Scopus citations

Abstract

Within the scope of CROP.SENSe.net, an interdisciplinary research network of Bonn University and the Jülich Research Centre, we work on a new model-based approach to the phenotyping of grapevine. Our algorithm performs a robust extraction of different features from a given leaf image, like specific points of the vein network, the vein network itself, and different distances respectively angles between special features. For that we present robust methods, like a template based method to extract the peduncle point, a detection strategy to determine end points of leaf veins, and a Gabor filter-based directional edge tracing procedure to extract the network. The extracted features are fed into a support vector machine in order to realize a full automatic sufficient variety identification.

Original languageEnglish (US)
Title of host publicationProceedings of the 2013 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2013
EditorsHamid R. Arabnia, Leonidas Deligiannidis, Joan Lu, Fernando G. Tinetti, Jane You, George Jandieri, Gerald Schaefer, Ashu M. G. Solo, Vladimir Volkov
PublisherCSREA Press
Pages407-412
Number of pages6
ISBN (Electronic)1601322526, 9781601322524
StatePublished - 2013
Event2013 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2013, at WORLDCOMP 2013 - Las Vegas, United States
Duration: Jul 22 2013Jul 25 2013

Publication series

NameProceedings of the 2013 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2013
Volume1

Conference

Conference2013 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2013, at WORLDCOMP 2013
Country/TerritoryUnited States
CityLas Vegas
Period07/22/1307/25/13

Bibliographical note

Publisher Copyright:
© 2013 CSREA Press. All rights reserved.

Keywords

  • Cultivar classification
  • Feature detection
  • Gabor filters
  • Support vector machines
  • Vein extraction

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design
  • Computer Vision and Pattern Recognition

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