Detection of grapes in natural environment using support vector machine classifier
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25530%2F15%3A39899510" target="_blank" >RIV/00216275:25530/15:39899510 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Detection of grapes in natural environment using support vector machine classifier
Original language description
The detection of grapes in real scene images is a serious task solved by researches dealing with precision viticulture. The detection of wine grapes of red varieties is a well mastered problem; however, the detection of white varieties still poses challenges. In this paper, four detectors for white wine grapes detection are introduced and evaluated. The detectors are based on support vector machines and they differ in kernels and features used for image representation. Namely, the pixel intensities and histogram of oriented gradients (HOG) are used for the representation of images. Radial basis functions and linear kernels are applied. The detectors based on the HOG feature have proven to be very efficient. Their average recognition accuracy by cross-validation was 98.23% and 98.96%, respectively. Furthermore, they show very good performance for other cross-validation metrics. Their average precision is 0.978 and 0.985, respectively; their average recall is 0.987 and 0.994, respectively. The detectors were also verified on test sets with positive samples affected by rotation distortion, and moreover on image sections of a real scene photo, in both cases with good results. Moreover, the detectors do not require any artificial lighting and they can work under different light conditions.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
JD - Use of computers, robotics and its application
OECD FORD branch
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Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2015
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Mendel 2015: 21st International Conference on Soft Computing
ISBN
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ISSN
1803-3814
e-ISSN
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Number of pages
8
Pages from-to
143-150
Publisher name
Vysoké učení technické v Brně
Place of publication
Brno
Event location
Brno
Event date
Jun 23, 2015
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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