• Title/Summary/Keyword: Sonar Image

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Study on Development of Side Scan Sonar Using Multi-beam Sensors (다중 빔 센서를 이용한 측면주사음탐기에 관한 연구)

  • Chang, Y.S.;Keh, J.E.;Park, S.S.;Lee, M.H.
    • Proceedings of the Korean Society of Marine Engineers Conference
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    • 2006.06a
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    • pp.317-318
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    • 2006
  • The towfish oi a side scan sonar is an equipment that search images of the bottom surface of the sea in real time. It is a typical equipment that is related to a sea investigation such as a geological survey, seabed communication cable and power line cable placing repair investigation, fish breeding ground investigation, sea purification, relic and mineral investigation, and mine and submarine search. It used to find objects and Investigate on the seabed surface. But, recently, it is used to sea purification and geological survey that require information of the correct surface of the seabed. So, it needs various filtering technique and image processing techniques development to acquire high resolution image. Therefore, this research develops a side scan sonar using multi-beam sensors that supply various information with the fast scan speed and correct high resolution that is not a simple underwater investigation equipment.

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Development of Algorithms for Correcting and Mapping High-Resolution Side Scan Sonar Imagery (고해상도 사이드 스캔 소나 영상의 보정 및 매핑 알고리즘의 개발)

  • 이동진;박요섭;김학일
    • Korean Journal of Remote Sensing
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    • v.17 no.1
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    • pp.45-56
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    • 2001
  • To acquire seabed information, the mosaic images of the seabed were generated using Side Scan Sonar. Short time energy function which is needed for slant range correction is proposed to get the height of Tow-Fish to the reflected acoustic amplitudes of each ping, and that leads to a mosaic image without water column. While generating mosaic image, maximum value, last value and average value are used for the measure of a pixel in the mosaic image and 3-D information was kept by using acoustic amplitudes which were heading for specific direction. As a generating method of mosaic image, low resolution mosaic image which is over 1m/pixel resolution was generated for whole survey area first, and then high resolution mosaic image which is generated under 0.1m/pixel resolution was generated for the selected area. Rocks, ripple mark, sand wave, tidal flat and artificial fish reef are found in the mosaic image.

Bundle Adjustment and 3D Reconstruction Method for Underwater Sonar Image (수중 영상 소나의 번들 조정과 3차원 복원을 위한 운동 추정의 모호성에 관한 연구)

  • Shin, Young-Sik;Lee, Yeong-jun;Cho, Hyun-Taek;Kim, Ayoung
    • The Journal of Korea Robotics Society
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    • v.11 no.2
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    • pp.51-59
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    • 2016
  • In this paper we present (1) analysis of imaging sonar measurement for two-view relative pose estimation of an autonomous vehicle and (2) bundle adjustment and 3D reconstruction method using imaging sonar. Sonar has been a popular sensor for underwater application due to its robustness to water turbidity and visibility in water medium. While vision based motion estimation has been applied to many ground vehicles for motion estimation and 3D reconstruction, imaging sonar addresses challenges in relative sensor frame motion. We focus on the fact that the sonar measurement inherently poses ambiguity in its measurement. This paper illustrates the source of the ambiguity in sonar measurements and summarizes assumptions for sonar based robot navigation. For validation, we synthetically generated underwater seafloor with varying complexity to analyze the error in the motion estimation.

Processing of Side Scan Sonar and SBP Data for the Artificial Reef Area (인공어초지역에 대한 사이드스캔소나와 SBP 탐사 자료처리)

  • Shin, Sung-Ryul;Lim, Min-Hyuk;Jang, Won-Il;Lim, Jong-Se;Yoon, Ji-Ho;Lee, Seong-Min
    • Geophysics and Geophysical Exploration
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    • v.12 no.2
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    • pp.192-198
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    • 2009
  • Side scan sonar and SBP (sub-bottom profiler) play a very important role in the survey for seafloor imaging and sub-bottom profiling. In this study, we have acquired side scan sonar and SBP data from the artificial reef area. We applied digital image processing techniques to side scan sonar data in order to improve an image quality. For the enhancement of data quality and image resolution, we applied the typical seismic data processing sequence including gain recovery, muting, spectrum analysis, predictive deconvolution, migration to SBP data. We could easily estimate if artificial reef structures were settled properly and their distribution on the seafloor from the integrated interpretation of side scan sonar and SBP data. From the sampling analysis of seabed sediments, texture filtering of side scan sonar data and SBP data interpretation, we could evaluate the sediment type, distribution and thickness of seafloor sediments in detail.

Design of Navigation Algorithm for Mobile Robot using Sensor fusion (센서 합성을 이용한 자율이동로봇의 주행 알고리즘 설계)

  • Kim Jung-Hoon;Kim young-Joong;Lim Myo-Teag
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.53 no.10
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    • pp.703-713
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    • 2004
  • This paper presents the new obstacle avoidance method that is composed of vision and sonar sensors, also a navigation algorithm is proposed. Sonar sensors provide poor information because the angular resolution of each sonar sensor is not exact. So they are not suitable to detect relative direction of obstacles. In addition, it is not easy to detect the obstacle by vision sensors because of an image disturbance. In This paper, the new obstacle direction measurement method that is composed of sonar sensors for exact distance information and vision sensors for abundance information. The modified splitting/merging algorithm is proposed, and it is robuster for an image disturbance than the edge detecting algorithm, and it is efficient for grouping of the obstacle. In order to verify our proposed algorithm, we compare the proposed algorithm with the edge detecting algorithm via experiments. The direction of obstacle and the relative distance are used for the inputs of the fuzzy controller. We design the angular velocity controllers for obstacle avoidance and for navigation to center in corridor, respectively. In order to verify stability and effectiveness of our proposed method, it is apply to a vision and sonar based mobile robot navigation system.

Research on Segmentation for Sidescan Sonar Image by Morphological Method (사이드스캔소나 이미지의 모폴로지 기법을 이용한 세그먼테이션에 관한 연구)

  • Lee, Ji-Eun;Shim, Tae-Bo
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.49 no.2
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    • pp.143-148
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    • 2012
  • There are many researches on segmentation of sidescan sonar image to recognize or classify the underwater objects. Although existing algorithms's performance is good in detecting object's shadow and reducing the underwater noise, the computing time is very low. In this paper we try to separate shadow from background and segment the underwater image by using morphological method using background's noise distribution characteristics and object's shadow charateristics. This algorithm is useful when the average of background is lower than the average of the shadow, because this is adjusted from the background's chracteristics. Results shows that the algorithm works fine in multiple object environments and the computing time is reduced to 1 second.

Sea-bottom Sediments and Seafloor Acoustic Image by Side Scan Sonar on Sindu-ri Offshore (신두리 해안 Side Scan Sonar 해저면 음향영상과 해저퇴적물)

  • Woo, Han-Jun;Lee, Yong-Kuk;Jeong, Kap-Sik;Je, Jong-Geel;Park, Gun-Tae;Jung, Baek-Hun;Cho, Jin-Hyung;Kim, Seong-Ryul
    • Journal of the Korean earth science society
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    • v.23 no.8
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    • pp.707-721
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    • 2002
  • Seafloor acoustic image data using the side scan sonar system were gathered on the Sindu-ri offshore near the Taean peninsula, middle western Korea. The relationship between the back-scattering acoustic intensity and the sea-bottom sediment properties was studied. And these two data sets were compared and interpreted with the water depth, respectively. Most of sediment properties were correlated well to the acoustic intensity, however the distribution patterns of the sea-bottom sediment and the seafloor acoustic image were not similar to each other except the rocky bottom area. The water depth was not only influential on the distribution pattern of seafloor acoustic image but also showed a linear relation with the sediment properties distribution.

Submarine Terrain Exploration for the Coast Using Side Scan Sonar (측면주사음탐기를 이용한 연안지역 해저지형탐사)

  • 이종출;문두열;김대현;서동주
    • Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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    • 2004.11a
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    • pp.539-544
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    • 2004
  • In this study, locational information data acquisited by using the side scan sonar which is more precise than traditional submarine terrain' survey equipment. And the result of exploration through the object area(the East sea), accurate submarine terrain could be deciphered by sounded image. Also, in the future, side scan sonar's application will be maximized for the submarine terrain's sediment investigation to design or construction of ocean facilities.

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수동 소나 배열을 이용한 수중 음향 영상에 관한 연구

  • 김형균
    • Proceedings of the Acoustical Society of Korea Conference
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    • 1984.12a
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    • pp.96-99
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    • 1984
  • In this study, the underwater acoustic images were obtained by ultrasonicwave. The experiment was performed in the anechoic watertank, using a passive sonar array for one and two sound source respectively by X-Y scanning technique. The receiving array was consist of 8 disc type transducers with 1.5cm diameter at 25KHz resonance frequency. The scanned data were processed by the FORTRAN IV algorithm for the reconstruction of image, and the image had some noise due to the surface reflected waves. As the result, it was found that the acoustic imaging by electrical deflection and dynamic focusing technique is applicable to SONAR with the suppression of surface reflected wave.

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Active Sonar Target/Non-target Classification using Convolutional Neural Networks (CNN을 이용한 능동 소나 표적/비표적 분류)

  • Kim, Dongwook;Seok, Jongwon;Bae, Keunsung
    • Journal of Korea Multimedia Society
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    • v.21 no.9
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    • pp.1062-1067
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    • 2018
  • Conventional active sonar technology has relied heavily on the hearing of sonar operator, but recently, many techniques for automatic detection and classification have been studied. In this paper, we extract the image data from the spectrogram of the active sonar signal and classify the extracted data using CNN(convolutional neural networks), which has recently presented excellent performance improvement in the field of pattern recognition. First, we divided entire data set into eight classes depending on the ratio containing the target. Then, experiments were conducted to classify the eight classes data using proposed CNN structure, and the results were analyzed.