Open AccessSide-scan sonar image processing: Seabed classification based on acoustic backscattering
Author(s) -
Subarsyah,
Henry M. Manik,
Ali Albab
Publication year - 2021
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.179
H-Index - 26
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/944/1/012001
Subject(s) - seabed , side scan sonar , sonar , geology , port (circuit theory) , silt , pixel , remote sensing , computer science , marine engineering , artificial intelligence , engineering , oceanography , electronic engineering , paleontology
The smoothness of vessel traffic flow is the most important thing in the shipping industry of port. Traffic problems are commonly solved by development and maintenance programs. Seabed conditions in the port-channel should be known to be considered in port development and maintenance programs related to port efficiency, safety navigation, and berthing. The objective of this paper is to characterize seabed into several classes of geological features. The Seabed condition and characteristics are classified based on image processing of side scan sonar data. The image processing will extract pixel value parameters; intensity, entropy, and standard deviation. Classification use combination of these pixel view parameter to define each class. Seabed classification has been successfully carried out in Teluk Bayur Port and classified into five classes, sandy silt, silty sand, fine sand, coarse sand, and rocks or reefs. Indication of crack or shallow structure was also identified. These results of classification are necessary to verify by sediment sampling and visual inspection, and then it should be reclassified to become a valid classification.