• The Journal of Korea Robotics Society
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• v.9 no.4
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• pp.197-205
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• 2014

As computer vision algorithms are developed on a continuous basis, the visual information from vision sensors has been widely used in the context of simultaneous localization and mapping (SLAM), called visual SLAM, which utilizes relative motion information between images. This research addresses a visual SLAM framework for online localization and mapping in an unstructured seabed environment that can be applied to a low-cost unmanned underwater vehicle equipped with a single monocular camera as a major measurement sensor. Typically, an image motion model with a predefined dimensionality can be corrupted by errors due to the violation of the model assumptions, which may lead to performance degradation of the visual SLAM estimation. To deal with the erroneous image motion model, this study employs a local bundle optimization (LBO) scheme when a closed loop is detected. The results of comparison between visual SLAM estimation with LBO and the other case are presented to validate the effectiveness of the proposed methodology.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.4
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• pp.845-850
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• 2018

In this paper, we propose a method to estimate the number of biofouling attached to the surface of marine structures. This method estimates the number of biofouling by calculating the region maxima using images taken in underwater. To do this, we analyze the correlation between the region maxima and the number of biofouling. The analysis showed that there is a significant correlation between the number of region maxima and the number of biofouling. By using the results of this analysis, the experiments were conducted on images taken in the underwater. Experimental results show that the higher the region maxima of the image, is greater than the number of biofouling in the image. The proposed method can be used as an important technology in computer vision for underwater images.

• The Journal of the Acoustical Society of Korea
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• v.26 no.7
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• pp.366-374
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• 2007

In underwater wireless communication, needs for long distance communication using the high frequency are surpassing ones of short range communication by ultrasonic wave, and demands for transmitting and receiving various data such as voice or high resolution image data are increasing as well. In this work, we studied the effects on the real underwater communication depending on the difference of digital modulation methods. Simulation shows that only the performance of GMSK among many other PSK based modulation schemes(BPSK, QPSK, MSK, GMSK) is significant. Test condition simulates the oceanographic conditions along the 207-survey line, 15Km south of Busan and SNR is maintained 35dB or below. Simulated tests are composed of both transmitting image data($3{\times}10^5$ pixel, 4 bit per pixel) and voice communication($10^{-2}$BER, channel capacity of 1Kbps). Test results show that there are gain of about 7 seconds in transmission time in image transmission case, where channel capacity for BPSK, QPSK, and MSK and for GMSK were 65 Kbps and 45 Kbps, respectively and gain of about 8Km in distances in voice communication case.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.883-884
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• 2008

This paper presents a method for classification of underwater transient signals using, which employs a binary image pattern of the mel-frequency cepstral coefficients(MFCC) as a feature vector and a neural network as a classifier. A feature vector is obtained by taking DCT and 1-bit quantization for the square matrix of the MFCC sequences. The classifier is a feed-forward neural network having one hidden layer and one output layer, and a back propagation algorithm is used to update the weighting vector of each layer. Experimental results with some underwater transient signals demonstrate that the proposed method is very promising for classification of underwater transient signals.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.9
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• pp.830-836
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• 2012

According to increasing the importance of underwater environments, the needs of UUV are growing. This paper represents the mechanism and algorithm of UUV docking system with 21-inch torpedo tubes for military submarines as a docking station. To improve the reliability of the docking, torpedo tubes launch a wired ROV and next the ROV combined with UUV is retrieved. For estimating the relative position between the ROV and UUV, in this paper, combining RF sensors and vision system is proposed. The RSSI method of RF sensors is used to estimate the distance and the optical image is combined for the directional information.

• The Journal of Korea Robotics Society
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• v.7 no.4
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• pp.259-266
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• 2012

In these days, researches about underwater robots have been actively in progress for the purposes of ocean detection and resource exploration. Unlike general underwater robots such as ROV(Remotely Operated Vehicle) and AUV(Autonomous Underwater Vehicle) which have propellers, an articulated underwater robot which is called Crabster has been being developed in KORDI(Korea Ocean Research & Development Institute) with many cooperation organizations since 2010. The robot is expected to be able to walk and swim under the sea with its legs. Among many researching fields of this project, we are focusing on a swimming section. In order to find effective swimming locomotion for the robot, we approached this subject in terms of Biomimetics. As a model of optimized swimming organism in nature, diving beetles were chosen. In the paper, swimming motions of diving beetles were analyzed in viewpoint of robotics for applying them into the swimming motion of the robot. After modeling the kinematics of diving beetle through robotics engineering technique, we obtained swimming patterns of the one of living diving beetles, and then compared them with calculated optimal swimming patterns of a robot leg. As the first trial to compare the locomotion data of legs of the diving beetle with a robot leg, we have sorted two representative swimming patterns such as forwarding and turning. Experimental environment has been set up to get the motion data of diving beetles. The experimental equipment consists of a transparent aquarium and a high speed camera. Various swimming motions of diving beetles were recorded with the camera. After classifying swimming patterns of the diving beetle, we can get angular data of each joint on hind legs by image processing software, Image J. The data were applied to an optimized algorithm for swimming of a robot leg which was designed by robotics engineering technique. Through this procedure, simulated results which show trajectories of a robot leg were compared with trajectories of a leg of a diving beetle in desired directions. As a result, we confirmed considerable similarity in the result of trajectory and joint angles comparison.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.9
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• pp.4507-4513
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• 2013

The developing unmanned underwater equipment can be used for underwater construction site such as underwater leveling works. If a optical camera is applied to the unmanned underwater equipment, recognition in underwater can be gone to low due to high turbidity in working field. To overcome this problem, a sonar will be installed to the unmanned underwater equipment. In this study, the resolution of the sonar and the quality test of the sonar image under high turbidity environment were conducted. And the method to indicate the boundary of the underwater construction site was proposed. By these results, the basic performance of the sonar was evaluated.

• Journal of the Korean Society of Marine Environment & Safety
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• v.30 no.5
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• pp.373-386
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• 2024

The aim of this study is to establish a system for the early detection of high-density harmful marine organisms. Considering its accuracy and processing speed, YOLOv8m (You Only Look Once version 8 medium) is selected as a suitable model for real-time underwater image-based object detection. Applying the detection algorithm allows one to detect numerous fish and the occasional occurrence of jellyfish. The average precision, recall rate, and mAP (mean Average Precision) of the trained model are 0.931, 0.881, and 0.948 for the validation data, respectively. Also, the mAP for each class is 0.97 for fish, 0.97 for jellyfish and 0.91 for salpa, all of which exceed 0.9 (90%) for classes demonstrating the excellent performance of the model. A scientific sonar system is used to address the object-detection range and validate the detection results. Additionally, integrating and grid averaging the echo strength allows the detection results to be smoothed in space and time. Mean-volume back-scattering strength values are obtained to reflect the detection variability within the analysis domain. Furthermore, an underwater image-based object (marine lives) detection algorithm, an image-correction technique based on the underwater environmental conditions (including nights), and quantified detection results based on a scientific sonar system are presented, which demonstrate the utility of the detection system in various applications.

• The Journal of the Acoustical Society of Korea
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• v.23 no.2
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• pp.117-124
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• 2004

In this paper, we have been implemented the QPSK-based underwater transmission systems using DSP in order to transmit the underwater image data. We have adopted a BDPA (Block Data Parallel Architecture) to control multiple DSPs used in the transmitter and receiver in order to transmit the image data in real-time. We also have developed GUI software in order to drive and to debug the implemanted system in real-time. We have executed open sea tests in order to analyze the performance of the implemented system at East Sea near Kosung in Kangwon-Do. As a result of these experiments, it has been demonstrated that 10 kbps image data can be received without errors at 30m and 80m depth points, while the distance between the transmitter and the receiver is up to 20m.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.47 no.3
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• pp.56-62
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• 2010

Weakly electric fish uses active sensing to detect the distortion of self-generated electric field in the underwater environments. The active electrolocation makes it possible to identify target objects from the surroundings without vision in the dark sea. Weakly electric fish have many electroreceptors over the whole body surface of electric fish, and sensor readings from a collection of electroreceptors are represented as an electric image. Many researchers have worked on finding features in the electric image to know how the weakly electric fish identify the target object. In this paper, we suggest a new mechanism of how the electrolocation can recognize a given target object among object plants. This approach is based on the differential components of the electric image, and has a potential to be applied to the underwater robotic system for object localization.