• Journal of the Institute of Electronics and Information Engineers
• /
• v.53 no.3
• /
• pp.91-98
• /
• 2016

Detection and classification of underwater objects in sonar imagery are challenging problems. This paper proposes a system that detects and identifies underwater objects at the sea floor level using a sonar image and image processing techniques. The identification process of underwater objects consists of two steps; detection of candidate regions and identification of underwater objects. The candidate regions of underwater objects are extracted by image registration through the detection of common feature points between the reference background image and the current scanning image. And then, underwater objects are identified as the closest pattern within the database using eigenvectors and eigenvalues as features. The proposed system is expected to be used in efficient securement of Q route in vessel navigation.

• Korean Journal of Remote Sensing
• /
• v.13 no.2
• /
• pp.133-150
• /
• 1997

The purpose of this paper is to develop an algorithm of classification and interpretation of seafloor based on side scan sonar data. The algorithm consists of mosaicking of sonar data using navigation data, correction and compensation of the acouctic amplitude data considering the charateristics of the side scan sonar system, and segmentation of the seafloor using digital image processing techniques. The correction and compensation process is essential because there is usually difference in acoustic amplitudes from the same distance of the port-side and the starboard-side and the amplitudes become attenuated as the distance is increasing. In this paper, proposed is an algorithm of compensating the side scan sonar data, and its result is compared with the mosaicking result without any compensation. The algorithm considers the amplitude characteristics according to the tow-fish's depth as well as the attenuation trend of the side scan sonar along the beam positions. This paper also proposes an image segmentation algorithm based on the texture, where the criterion is the maximum occurence related with gray level. The preliminary experiment has been carried out with the side scan sonar data and its result is demonstrated.

• Journal of the Korean Society of Fisheries and Ocean Technology
• /
• v.39 no.2
• /
• pp.92-98
• /
• 2003

The quantification of fish school abundance was carried out by using luminance of pixel on scanning sonar image, and compared with the indices of fish school abundance e.g. school number, school area and weighted school area. The survey was carried out in Funka Bay off southern Hokkaido, Japan using research vessel Ushio-Maru during December 1999. A 180-degree scanning sonar with a frequency of 164kHz was used. The school number was counted both left and right 40-degree radial lines from the center of own vessel mark on a scanning image. The school area was measured approximately as an ellipse from the school length and width. The weighted school area was calculated by multiplying school area and average value of inner pixel luminance. A quantification of pixel luminance was also measured to integrate squared pixel luminance value on these lines. Fish school and school bottom were discriminated by the produced sonar echogram using pixel luminance value on these lines. The relationships between the quantified luminance value and other abundance indices such as school area and weighted school area revealed a good correlation. Therefore, the quantified luminance is a useful method in estimating fish school abundance in the acoustic survey using sonar.

• Journal of Ocean Engineering and Technology
• /
• v.30 no.3
• /
• pp.227-233
• /
• 2016

This paper presents an underwater structure 3D reconstruction method using a 2D multibeam imaging sonar. Compared with other underwater environmental recognition sensors, the 2D multibeam imaging sonar offers high resolution images in water with a high turbidity level by showing the reflection intensity data in real-time. With such advantages, almost all underwater applications, including ROVs, have applied this 2D multibeam imaging sonar. However, the elevation data are missing in sonar images, which causes difficulties with correctly understanding the underwater topography. To solve this problem, this paper concentrates on the physical relationship between the sonar image and the scene topography to find the elevation information. First, the modeling of the sonar reflection intensity data is studied using the distances and angles of the sonar beams and underwater objects. Second, the elevation data are determined based on parameters like the reflection intensity and shadow length. Then, the elevation information is applied to the 3D underwater reconstruction. This paper evaluates the presented real-time 3D reconstruction method using real underwater environments. Experimental results are shown to appraise the performance of the method. Additionally, with the utilization of ROVs, the contour and texture image mapping results from the obtained 3D reconstruction results are presented as applications.

• The Journal of Korea Robotics Society
• /
• v.14 no.1
• /
• pp.14-21
• /
• 2019

In the ground environment, mobile robot research uses sensors such as GPS and optical cameras to localize surrounding landmarks and to estimate the position of the robot. However, an underwater environment restricts the use of sensors such as optical cameras and GPS. Also, unlike the ground environment, it is difficult to make a continuous observation of landmarks for location estimation. So, in underwater research, artificial markers are installed to generate a strong and lasting landmark. When artificial markers are acquired with an underwater sonar sensor, different types of noise are caused in the underwater sonar image. This noise is one of the factors that reduces object detection performance. This paper aims to improve object detection performance through distortion and rotation augmentation of training data. Object detection is detected using a Faster R-CNN.

• The Journal of the Acoustical Society of Korea
• /
• v.40 no.4
• /
• pp.382-390
• /
• 2021

Synthetic aperture sonars as well as side scan sonars or multibeam echo sounders have been commercialized and are widely used for seafloor imaging. In Korea related research such as the development of a towed synthetic aperture sonar system is underway. In order to obtain high-resolution synthetic aperture sonar images, it is necessary to accurately estimate the platform motion on which it is installed, and a precise underwater navigation system is required. In this paper we are going to provide reference data for determining the required navigation accuracy and precision of navigation sensors by quantitatively analyzing how much distortion of the sonar images occurs according to motion characteristics of the platform equipped with the synthetic aperture sonar. Five types of motions are considered and normalized root mean square error is defined for quantitative analysis. Simulation for error analysis with parameter variation of motion characteristics results in that yaw and sway motion causes the largest image distortion whereas the effect of pitch and heave motion is not significant.

• The Journal of Korea Robotics Society
• /
• v.12 no.4
• /
• pp.385-394
• /
• 2017

Side scanning sonar (SSS) provides valuable information for robot navigation. However using the side scanning sonar images in the navigation was not fully studied. In this paper, we use range data, and side scanning sonar images from UnderWater Simulator (UWSim) and propose measurement models in a feature based simultaneous localization and mapping (SLAM) framework. The range data is obtained by echosounder and sidescanning sonar images from side scan sonar module for UWSim. For the feature, we used the A-KAZE feature for the SSS image matching and adjusting the relative robot pose by SSS bundle adjustment (BA) with Ceres solver. We use BA for the loop closure constraint of pose-graph SLAM. We used the Incremental Smoothing and Mapping (iSAM) to optimize the graph. The optimized trajectory was compared against the dead reckoning (DR).

• The Journal of the Acoustical Society of Korea
• /
• v.37 no.2
• /
• pp.118-128
• /
• 2018

In this paper, we have studied how to search an underwater object by learning the image generated by the side scan sonar in the convolution neural network. In the method of human side analysis of the side scan image or the image, the convolution neural network algorithm can enhance the efficiency of the analysis. The image data of the side scan sonar used in the experiment is the public data of NSWC (Naval Surface Warfare Center) and consists of four kinds of synthetic underwater objects. The convolutional neural network algorithm is based on Faster R-CNN (Region based Convolutional Neural Networks) learning based on region of interest and the details of the neural network are self-organized to fit the data we have. The results of the study were compared with a precision-recall curve, and we investigated the applicability of underwater object detection in convolution neural networks by examining the effect of change of region of interest assigned to sonar image data on detection performance.

• Proceedings of the Korean Society of Marine Engineers Conference
• /
• 2006.06a
• /
• pp.199-200
• /
• 2006

This paper describes how to generate stereoscopic sonar images by using multibeam data. Both parallel and crossing methods were used to create stereoscopic vision of the seafloor. Stereoscopic sonar images might provide reality and more detailed information of the target and the seafloor topography.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2004.10a
• /
• pp.696-699
• /
• 2004

A side scan sonar system uses the towfish installed sonars, It 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 fined 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.