Digitální knihovnaUPCE
 

Detection of grapes in natural environment using HOG features in low resolution images

Konferenční objektpeer-reviewedpostprint
Náhled

Datum publikování

2017

Vedoucí práce

Oponent

Název časopisu

Název svazku

Vydavatel

Institute of Physics Publishing Ltd

Abstrakt

Detection of grapes in real-life images has importance in various viticulture applications. A grape detector based on an SVM classifier, in combination with a HOG descriptor, has proven to be very efficient in detection of white varieties in high-resolution images. Nevertheless, the high time complexity of such utilization was not suitable for its real-time applications, even when a detector of a simplified structure was used. Thus, we examined possibilities of the simplified version application on images of lower resolutions. For this purpose, we designed a method aimed at search for a detector’s setting which gives the best time complexity vs. performance ratio. In order to provide precise evaluation results, we formed new extended datasets. We discovered that even applied on low-resolution images, the simplified detector, with an appropriate setting of all tuneable parameters, was competitive with other state of the art solutions. We concluded that the detector is qualified for real-time detection of grapes in real-life images.

Rozsah stran

p. 1-8

ISSN

1742-6588

Trvalý odkaz na tento záznam

Projekt

SGS_2017_027/Moderní metody simulace, řízení a optimalizace

Zdrojový dokument

Journal of Physics: Conference Series

Vydavatelská verze

Přístup k e-verzi

open access

Název akce

2nd International Conference on Measurement Instrumentation and Electronics, ICMIE 2017 (09.06.2017 - 11.06.2017, Praha)

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Klíčová slova

grape detection, precision viticulture, real scene images, image processing, histogram of oriented gradients, support vector machine

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