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Simplified Version of White Wine Grape Berries Detector Based on SVM and HOG Features

  • Pavel SkrabanekEmail author
  • Filip Majerík
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 464)

Abstract

The detection of grapes in real scene images is a serious task solved by researches dealing with precision viticulture. Our research has shown that in the case of white wine varieties, grape berry detectors based on a support vector machine classifier in combination with a HOG descriptor are very efficient. In this paper, simplified versions of our original solutions are introduced. Our research showed that skipping contrast normalization by image preprocessing accelerates the detection process; however, the performance of the detectors is not negatively influenced by this modification.

Keywords

Computer vision Precision viticulture Grape detection Support vector machine HOG features 

Notes

Acknowledgments

The work has been supported by the Funds of University of Pardubice, Czech Republic. We would like to offer our special thanks to company Víno Sýkora s.r.o. which enabled us to perform experiments in its vineyards.

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Faculty of Electrical Engineering and InformaticsUniversity of PardubicePardubiceCzech Republic

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