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.
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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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Skrabanek, P., Majerík, F. (2016). Simplified Version of White Wine Grape Berries Detector Based on SVM and HOG Features. In: Silhavy, R., Senkerik, R., Oplatkova, Z., Silhavy, P., Prokopova, Z. (eds) Artificial Intelligence Perspectives in Intelligent Systems. Advances in Intelligent Systems and Computing, vol 464. Springer, Cham. https://doi.org/10.1007/978-3-319-33625-1_4
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DOI: https://doi.org/10.1007/978-3-319-33625-1_4
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