Молимо вас користите овај идентификатор за цитирање или овај линк до ове ставке:
https://open.uns.ac.rs/handle/123456789/6744
Назив: | Image processing method for automatic discrimination of hoverfly species | Аутори: | Crnojević, Vladimir Panić, Marko Brkljač, Branko Ćulibrk, Dubravko Ačanski, Jelena Vujić, Ante |
Датум издавања: | дец-2014 | Часопис: | Mathematical Problems in Engineering | Сажетак: | © 2014 Vladimir Crnojević et al. An approach to automatic hoverfly species discrimination based on detection and extraction of vein junctions in wing venation patterns of insects is presented in the paper. The dataset used in our experiments consists of high resolution microscopic wing images of several hoverfly species collected over a relatively long period of time at different geographic locations. Junctions are detected using the combination of the well known HOG (histograms of oriented gradients) and the robust version of recently proposed CLBP (complete local binary pattern). These features are used to train an SVM classifier to detect junctions in wing images. Once the junctions are identified they are used to extract statistics characterizing the constellations of these points. Such simple features can be used to automatically discriminate four selected hoverfly species with polynomial kernel SVM and achieve high classification accuracy. | URI: | https://open.uns.ac.rs/handle/123456789/6744 | ISSN: | 1024-123X | DOI: | 10.1155/2014/986271 |
Налази се у колекцијама: | IBS Publikacije/Publications |
Приказати целокупан запис ставки
SCOPUSTM
Навођења
7
проверено 15.03.2024.
Преглед/и станица
49
Протекла недеља
0
0
Протекли месец
0
0
проверено 15.03.2024.
Google ScholarTM
Проверите
Алт метрика
Ставке на DSpace-у су заштићене ауторским правима, са свим правима задржаним, осим ако није другачије назначено.