Publication detail

RGB Images Driven Recognition of Grapevine Varieties

ŠKRABÁNEK, P. DOLEŽEL, P. MATOUŠEK, R. JUNEK, P.

Original Title

RGB Images Driven Recognition of Grapevine Varieties

Type

conference paper

Language

English

Original Abstract

We present a grapevine variety recognition system based on a densely connected convolutional network. The proposed solution is aimed as a data processing part of an affordable sensor for selective harvesters. The system classifies size normalized RGB images according to varieties of grapes captured in the images. We train and evaluate the system on in-field images of ripe grapes captured without any artificial lighting, in a direction of sunshine likewise in the opposite direction. A dataset created for this purpose consists of 7200 images classified into 8 categories. The system distinguishes among seven grapevine varieties and background, where four and three varieties have red and green grapes, respectively. Its average per-class classification accuracy is at 98.10 % and 97.47 % for red and green grapes, respectively. The system also well differentiates grapes from background. Its overall average per-class accuracy is over 98 %. The evaluation results show that conventional cameras in combination with the proposed system allow construction of affordable automatic selective harvesters.

Keywords

Recognition of grapevine varieties; Densely connected convolutional network; In-field images; Agriculture mechanization

Authors

ŠKRABÁNEK, P.; DOLEŽEL, P.; MATOUŠEK, R.; JUNEK, P.

Released

29. 9. 2020

Publisher

Springer International Publishing

Location

Cham

ISBN

978-3-030-57802-2

Book

15th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2020)

ISBN

2194-5365

Periodical

Advances in Intelligent Systems and Computing

Year of study

1268

State

Swiss Confederation

Pages from

216

Pages to

225

Pages count

10

BibTex

@inproceedings{BUT165498,
  author="Pavel {Škrabánek} and Petr {Doležel} and Radomil {Matoušek} and Petr {Junek}",
  title="RGB Images Driven Recognition of Grapevine Varieties",
  booktitle="15th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2020)",
  year="2020",
  journal="Advances in Intelligent Systems and Computing",
  volume="1268",
  pages="216--225",
  publisher="Springer International Publishing",
  address="Cham",
  doi="10.1007/978-3-030-57802-2\{_}21",
  isbn="978-3-030-57802-2",
  issn="2194-5365"
}