Automatic Classification of Persian Gulf Bottom Based on Acoustic Images
- سال انتشار: 1383
- محل انتشار: ششمین همایش بین المللی سواحل، بنادر و سازه های دریایی
- کد COI اختصاصی: ICOPMAS06_123
- زبان مقاله: انگلیسی
- تعداد مشاهده: 2731
نویسندگان
Malek-Ashtar University
Shiraz University
چکیده
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.کلیدواژه ها
اطلاعات بیشتر در مورد COI
COI مخفف عبارت CIVILICA Object Identifier به معنی شناسه سیویلیکا برای اسناد است. COI کدی است که مطابق محل انتشار، به مقالات کنفرانسها و ژورنالهای داخل کشور به هنگام نمایه سازی بر روی پایگاه استنادی سیویلیکا اختصاص می یابد.
کد COI به مفهوم کد ملی اسناد نمایه شده در سیویلیکا است و کدی یکتا و ثابت است و به همین دلیل همواره قابلیت استناد و پیگیری دارد.