@inproceedings{2eb8a716263446289d8f7b074da3b4f3,
title = "On feature extraction for fingerprinting grapevine leaves",
abstract = "Within the scope of CROP.SENSe.net, an interdisciplinary research network of Bonn University and the J{\"u}lich 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.",
keywords = "Cultivar classification, Feature detection, Gabor filters, Support vector machines, Vein extraction",
author = "Michels, {Dominik L.} and Giesselbach, {Sven A.} and Thomas Werner and Volker Steinhage",
note = "Publisher Copyright: {\textcopyright} 2013 CSREA Press. All rights reserved.; 2013 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2013, at WORLDCOMP 2013 ; Conference date: 22-07-2013 Through 25-07-2013",
year = "2013",
language = "English (US)",
series = "Proceedings of the 2013 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2013",
publisher = "CSREA Press",
pages = "407--412",
editor = "Arabnia, {Hamid R.} and Leonidas Deligiannidis and Joan Lu and Tinetti, {Fernando G.} and Jane You and George Jandieri and Gerald Schaefer and Solo, {Ashu M. G.} and Vladimir Volkov",
booktitle = "Proceedings of the 2013 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2013",
}