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Pregled bibliografske jedinice broj: 594149

A*-Search Image Segmentation Algorithm for Mine-like Objects Segmentation in SONAR Images


Aleksi, Ivan; Lehman, Benjamin; Fei, Tai; Kraus, Dieter; Hocenski, Željko
A*-Search Image Segmentation Algorithm for Mine-like Objects Segmentation in SONAR Images // ICoURS:International Conference on Underwater Remote Sensing
Brest, France, 2012. (poster, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)


Naslov
A*-Search Image Segmentation Algorithm for Mine-like Objects Segmentation in SONAR Images

Autori
Aleksi, Ivan ; Lehman, Benjamin ; Fei, Tai ; Kraus, Dieter ; Hocenski, Željko

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

Izvornik
ICoURS:International Conference on Underwater Remote Sensing / - Brest, France, 2012

Skup
ICoURS:International Conference on Underwater Remote Sensing

Mjesto i datum
Brest, France, 8-11.10.2012

Vrsta sudjelovanja
Poster

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
A*-Search; Image Segmentation; Path Finding

Sažetak
This paper addresses a SONAR image segmentation method employing a novel A*-Search Image Segmentation (ASSIS) algorithm. ASSIS is applied on Mine-Like Objects (MLO) in SONAR images, where an object is defined by highlight and shadow regions, i.e. regions of high and low pixel intensities in a SONAR image. Usually, the A*-Search is used in mobile robotics for finding the shortest path, where the environment map is predefined and the start/goal locations are known. The ASSIS algorithm represents the image segmentation problem as a path-finding problem. Main modification concerning the original A*-Search is in the cost function that takes pixel intensities in order to navigate the 2D segmentation contour. Firstly, the ASSIS algorithm uses a pixel intensity thresholding technique to build a goal distance map with the numerical navigation function (NNF). The NNF uses the L2 norm to estimate the Euclidean distance between the current pixel and a goal pixel. The estimated distance is then recalculated as predicted cost h to the goal. So far made cost g is calculated according to the current path length. Finally, the sum of g and h defines the cost function f that determines the next contour point around an MLO.

Izvorni jezik
Engleski

Znanstvena područja
Računarstvo



POVEZANOST RADA


Projekt / tema
165-0361621-2000 - Distribuirano računalno upravljanje u transportu i industrijskim pogonima (Željko Hocenski, )
165-0362980-2002 - Postupci raspoređivanja u samoodrživim raspodijeljenim računalnim sustavima (Goran Martinović, )

Ustanove
Fakultet elektrotehnike, računarstva i informacijskih tehnologija Osijek