Automatic Classification of Persian Gulf Bottom Based on Acoustic Images

سال انتشار: 1383
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 2,390

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شناسه ملی سند علمی:

ICOPMAS06_123

تاریخ نمایه سازی: 5 آذر 1384

چکیده مقاله:

The technology of underwater geo-acoustic detection has been progressed from the topographic and seabed mapping to the new stage of seabed qualitative detection and geological classification. Knowledge of the seafloor play an important role in understanding the undersea environment including geological survey, geophysical exploration, ocean engineering (autonomous underwater vehicles, surveillance of pipelines and cables, etc), sound propagation simulation, physical parameters estimation, navigation, explosive mine counter measurement, data communication and classification of buried objects lying on seafloors. On the other hand, high-resolution sonar systems and optical sensors play an important role in underwater sensing for automatic segmentation and classification of the sea bottom. The segmentation of seafloor sonar images aims to partition the acoustic image into homogeneous regions with respect to certain physical properties or geological characteristics. The goal of the classification task is to assign these different geo-acoustic regions to seafloor types as rocks, sand, pebbles, etc. Due to highly textured appearance of sonar images, texture analysis techniques become a common choice for seafloor acoustic images. It was shown that different transforms like Fourier transform and wavelet transform are valuable tools for texture analysis. In recent years, many automatic classification systems such as RoxAnn and QTC-View were developed; but because of different classification methods, they produce different results for the same region. Some of these systems are susceptible to noise and ship speed. In a large extent, taking good result from a system depends on the skill and experience of the user and the intended use of the system. In addition, usually sea bottoms having similar acoustic signatures for a particular classification system are not necessarily geologically similar. Therefore, most of acoustic seabed classification systems are essentially empirical devices, which may work well for some bottoms but not others. In this paper, the problem of seafloor segmentation and classification of Persian Gulf using acoustic images will be addressed. Different techniques and instruments in this area will be introduced. The advantages and drawbacks of each one will be discussed. Then, the feasibility study of doing such a work in Persian Gulf region will be expressed and finally, practical results will be outlined.

نویسندگان

Reza Javidan

Malek-Ashtar University

Hasan J. Eghbali

Shiraz University

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  • JI Wenyun, Lin Yijun, and Zhang Shuying, ،Pattern Recognition of ...
  • Mignotte M. and Collet C., ،Markov Random Field and Fuzzy ...
  • Javidan Reza, Jones Ian S. F., *High Resolution Acoustic Imaging ...
  • and sonar image classification: wavelet packet transforms Vs Optical؛ [4] ...
  • Eghbali Hasan J., *Adaptive Digital Image filtering in Wavelet Domain?, ...
  • Kociolek M., Materka1 A., Strzelecki M., and Szczypiski P., ،discrete ...
  • Hamilton, L. J. and Mulhearn P. J. and Poeckert R., ...
  • Kinsler L. E. & others, ،#Fundamental of acoustics?, John Wiley ...
  • Sonar: a directional filter of Sidescan؟، [10] Bell J. M., ...
  • Duda Richard O., Hart Peter E., and Stork David G., ...
  • نمایش کامل مراجع