Pregled bibliografske jedinice broj: 928380
TIRAMISU Methodology for Semi-Automated Interpretation of Digital Multisensor Images
TIRAMISU Methodology for Semi-Automated Interpretation of Digital Multisensor Images // Book of Papers 2016 (International Symposium “Mine Action”) / Jakopec, Dražen (ur.).
Zagreb: Hrvatski centar za razminiranje - Centar za testiranje, razvoj i obuku (HCR-CTRO), 2016. str. 191-194 (predavanje, nije recenziran, cjeloviti rad (in extenso), znanstveni)
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Naslov
TIRAMISU Methodology for Semi-Automated
Interpretation of Digital Multisensor Images
Autori
Racetin, Ivan ; Krtalić, Andrija
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
Book of Papers 2016 (International Symposium “Mine Action”)
/ Jakopec, Dražen - Zagreb : Hrvatski centar za razminiranje - Centar za testiranje, razvoj i obuku (HCR-CTRO), 2016, 191-194
Skup
The 13th International Symposium “MINE ACTION 2016”
Mjesto i datum
Biograd na Moru, Hrvatska, 26.04.2016. - 29.04.2016
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Nije recenziran
Ključne riječi
color spaces, interpretation, methodology, statistical analysis,
Sažetak
In the scope of the EU FP7 TIRAMISU project a novel methodology for semi-automatic interpretation of digital multisensor images for the purpose of detection and extraction of unexploded ordnances was developed. Image interpretation is usually being executed by a professional human interpreter, which is highly reliable but simultaneously labor intensive and time consuming procedure. Experience showed that a human interpreter can’t be replaced by automatic methods of digital image processing, while some methods of digital image processing can reduce the workload of the interpreter. Methodology is based on combination of pixel and object based image analysis where lessons and rules learned on test dataset are then applied on other images of the same scene but different locations. Pixel based image analysis like transformations to various color spaces (IHS, CIELAB), Principal Component Analysis (PCA), Independent Component Analysis (ICA) and basic raster math were used. By executing these processing new datasets with different statistical properties are created. Now we have series of artificial layers which serve as input for statistical analysis and enables us better delineation of targeted objects. Object based image analysis offered additional geometrical parameters and reduced the human error in the process of manual vectorization of identified objects. Achieved results of methodology implementation on aerial images of exploded ammunition depot in Padjene (Croatia) are presented. Validation procedure was executed on randomly selected spatial subsets of 25 images and the outputs are shown in the form of confussion matrix.
Izvorni jezik
Engleski
Znanstvena područja
Geodezija
POVEZANOST RADA
Ustanove:
Fakultet građevinarstva, arhitekture i geodezije, Split