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Pregled bibliografske jedinice broj: 1065456

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


Aleksi, Ivan; Matić, Tomislav; Lehmann, Benjamin; Kraus, Dieter
Robust A*-Search Image Segmentation Algorithm for Mine-like Objects Segmentation in SONAR Images // International journal of electrical and computer engineering systems (2020) doi:.org/10.32985/ijeces.11.2.1 (znanstveni, prihvaćen)


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

Autori
Aleksi, Ivan ; Matić, Tomislav ; Lehmann, Benjamin ; Kraus, Dieter

Vrsta, podvrsta
Radovi u časopisima, znanstveni

Izvornik
International journal of electrical and computer engineering systems (2020)

Status rada
Prihvaćen

Ključne riječi
A*-search ; image segmentation ; path planning ; synthetic aperture sonar

Sažetak
This paper addresses a sonar image segmentation method employing a Robust A*-Search Image Segmentation (RASIS) algorithm. RASIS 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 side-scan sonar image. RASIS uses a modified A*-Search method, which is usually used in mobile robotics for finding the shortest path where the environment map is predefined, and the start/goal locations are known. RASIS 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 and contour curvature in order to navigate the 2D segmentation contour. The proposed method is implemented in Matlab and tested on real MLO images. MLO image dataset consist of 70 MLO images with manta mine present, and 70 MLO images with cylinder mine present. Segmentation success rate is obtained by comparing the ground truth data given by the human technician who is detecting MLOs. Measured overall success rate (highlight and shadow regions) is 91% for manta mines and 81% for cylinder mines.

Izvorni jezik
Engleski

Znanstvena područja
Elektrotehnika, Računarstvo



POVEZANOST RADA


Ustanove
Fakultet elektrotehnike, računarstva i informacijskih tehnologija Osijek

Profili:

Avatar Url Tomislav Matić (autor)

Avatar Url Ivan Aleksi (autor)

Citiraj ovu publikaciju

Aleksi, Ivan; Matić, Tomislav; Lehmann, Benjamin; Kraus, Dieter
Robust A*-Search Image Segmentation Algorithm for Mine-like Objects Segmentation in SONAR Images // International journal of electrical and computer engineering systems (2020) doi:.org/10.32985/ijeces.11.2.1 (znanstveni, prihvaćen)
Aleksi, I., Matić, T., Lehmann, B. & Kraus, D. (2020) Robust A*-Search Image Segmentation Algorithm for Mine-like Objects Segmentation in SONAR Images. Prihvaćen za objavljivanje u International journal of electrical and computer engineering systems. [Preprint] doi:.org/10.32985/ijeces.11.2.1.
@unknown{unknown, year = {2020}, DOI = {doi.org/10.32985/ijeces.11.2.1}, keywords = {A\ast-search, image segmentation, path planning, synthetic aperture sonar}, journal = {International journal of electrical and computer engineering systems}, doi = {doi.org/10.32985/ijeces.11.2.1}, title = {Robust A\ast-Search Image Segmentation Algorithm for Mine-like Objects Segmentation in SONAR Images}, keyword = {A\ast-search, image segmentation, path planning, synthetic aperture sonar} }

Časopis indeksira:


  • Web of Science Core Collection (WoSCC)
    • Emerging Sources Citation Index (ESCI)
  • Scopus


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