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https://doi.org/10.17559/TV-20150319092835

Ragweed detection based on SURF features

Ádám Schiffer ; University of Pécs, H-7624, Pécs, Rókus 2., Hungary
Zoltán Sari ; University of Pécs, H-7624, Pécs, Rókus 2., Hungary
Péter Müller orcid id orcid.org/0000-0002-2283-1791 ; University of Pécs, H-7624, Pécs, Rókus 2., Hungary
Ildikó Jancskar ; University of Pécs, H-7624, Pécs, Rókus 2., Hungary
Géza Varady ; University of Pécs, H-7624, Pécs, Rókus 2., Hungary
Zsolt Ercsey orcid id orcid.org/0000-0001-5427-913X ; University of Pecs, H-7630, Pécs, Boszorkany 2., Hungary


Puni tekst: hrvatski pdf 2.452 Kb

str. 1519-1524

preuzimanja: 358

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Puni tekst: engleski pdf 2.452 Kb

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preuzimanja: 464

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Sažetak

The paper describes a parameter study corresponding to automatic detection of ragweed based on SURF features. The basic idea behind the method is to build a feature database from very simple ragweed samples containing characteristic features of the leaves of the plant, and compare the feature database to features extracted from natural images which contain or lack ragweed. The results of the study clearly show that the approach is promising and has value as a standalone method, or as a potential training basis for a classification expert system.

Ključne riječi

feature detection; parameter study; ragweed

Hrčak ID:

188249

URI

https://hrcak.srce.hr/188249

Datum izdavanja:

25.10.2017.

Podaci na drugim jezicima: hrvatski

Posjeta: 1.588 *