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Pregled bibliografske jedinice broj: 641388

Augmented Reality Based Segmentation of Outdoor Landscape Images


Bugarić, Marin; Braović, Maja; Stipaničev, Darko
Augmented Reality Based Segmentation of Outdoor Landscape Images // Proceedings of ISPA 2013, 8th International Symposium on Image and Signal Processing and Analysis / Ramponi Giovanni, Lončarić Sven, Carini Alberto, Egiazarian Karen (ur.).
Trieste: University of Zagreb, Croatia & University of Trieste, Italy, 2013. str. 43-48 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)


Naslov
Augmented Reality Based Segmentation of Outdoor Landscape Images

Autori
Bugarić, Marin ; Braović, Maja ; Stipaničev, Darko

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
Proceedings of ISPA 2013, 8th International Symposium on Image and Signal Processing and Analysis / Ramponi Giovanni, Lončarić Sven, Carini Alberto, Egiazarian Karen - Trieste : University of Zagreb, Croatia & University of Trieste, Italy, 2013, 43-48

ISBN
978-953-184-187-0

Skup
8th International Symposium on Image and Signal Processing and Analysis

Mjesto i datum
Trst, Italija, 4-6.09.2013

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
Segmentacija slike; Proširena stvarnost; slike otvorenog prostora
(Image segmentation Image classification Augmented reality Outdoor landscape images)

Sažetak
The segmentation and classification of image regions are very important tasks in the field of computer vision, and yet they remain one of its greatest challenges. These challenges arise from the fact that the same objects can come in different colors, shapes and sizes, and can appear in different contexts and under different illumination. In an attempt to overcome these obstacles, in this paper we propose a system for segmentation and classification of image regions on outdoor landscape images based on augmented reality and CORINE land cover (CLC) classification. We compare the results obtained by the proposed system with the results obtained by the k-NN algorithm, and show that the proposed algorithm outperforms the k-NN one, and generally gives favorable segmentation and classification results.

Izvorni jezik
Engleski

Znanstvena područja
Računarstvo



POVEZANOST RADA


Projekt / tema
023-0232005-2003 - AgISEco - Agentski orijentirani inteligentni sustavi nadzora i zaštite okoliša (Darko Stipaničev, )

Ustanove
Fakultet elektrotehnike, strojarstva i brodogradnje, Split