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Transactions: WSEAS TRANSACTIONS ON ACOUSTICS AND MUSIC
Transactions ID Number: 31-567
Full Name: Cristian Molder
Position: Lecturer
Age: ON
Sex: Male
Address: 81-83 George Cosbuc blvd., Bucharest
Country: ROMANIA
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E-mail address: cristianmolder@gmail.com
Other E-mails: cristianmolder@yahoo.fr
Title of the Paper: Automatic Sea Floor Characterization based on Underwater Acoustic Image Processing
Authors as they appear in the Paper: Cristian Molder, Mircea Boscoianu, Mihai I. Stanciu, Iulian C. Vizitiu
Email addresses of all the authors: cristianmolder@gmail.com, mircea_boscoianu@yahoo.co.uk, stanciu_mihai_ionut@yahoo.com, iulian_vizitiu@yahoo.com
Number of paper pages: 10
Abstract: Automatic sea floor characterization is mainly based on the signal or image processing of the data acquired using an active acoustic system called sediment sonar. Each processing method suits a specific type of sonar, such as the monobeam, the multibeam, or the side-scan sonar. Most types of sonar offer a two dimensional view of the sea floor surface. Therefore, a high resolution image results which can be further analyzed. The inconvenient is that the sonar cannot view inside of the sea floor for a deeper analysis. Therefore, lower frequency acoustic systems are used for in-depth sea floor penetration (boomer, sparker, airguns or sub-bottom profilers). In this case, a mono dimensional signal results. Previous studies on the low-frequency systems are mainly based on the visual inspection by a geological human expert. To automatize this process, we propose the use of feature sets based on the transposed expert fuzzy reasoning. Two features are extracted, the first !
based on the sea floor contour and the second based on the sub-bottom sediment texture.
Keywords: Sedimentology, Underwater acoustics, Pattern recognition, Image processing, Textures, Wavelets
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