• Proceedings of the Korean Information Science Society Conference
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• 2012.06b
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• pp.483-485
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• 2012

본 논문에서는 수중 영상 환경에 특화된 자동 수중 영상 보정 시스템을 제안한다. 수중 영상은 빛 희석(light attenuation)을 인한 가시거리 제한, 낮은 영상 대비(low contrast) 그리고 부유물질과 같은 영상의 노이즈 등의 특수한 환경적 제약이 따른다. 기존의 수중 영상 보정 알고리즘은 색 및 대비(contrast) 보정, 가시거리 확장 및 노이즈 제거 기법등을 이용한 부분적으로 보정 연구가 진행되어 왔는데, 부분적 영상 보정 기법으로는 선명한 영상의 결과를 얻기 힘들다. 제안한 통합 수중 영상 보정 시스템은 색 및 대비 보정, 부유물질 제거를 위한 노이즈 필터링, 객체 윤곽선 강화를 위한 기법들을 통합하여 수중 영상에 특화하였다. 실험을 통하여 제안된 수중 영상 보정 시스템의 효율성을 확인하였다.

• Journal of the Korean Association of Geographic Information Studies
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• v.11 no.4
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• pp.150-160
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• 2008

The present domestic underwater and ocean facilities management depends on analysis with the naked eye. This study performs quantitative analysis to improve conventional methods, analyze spatial situation of underwater facilities. This research is divided into two steps; underwater image distortion correction and image mosaic step. First, underwater image distortion correction step is for the production of underwater target, calculates the correction parameters, and then developed the method that convert the original image point to whose distortion is corrected. Second step is for the obtaining pipe images installed in the underwater, corrects the distortion, and then transforms a coordinates of the correction pipe image. After coordinate transformation, we make the mosaic image using the singularities. As a result, when we measure the distance between pipe and underwater ground and compare with calculation value on mosaic image, it is showed that RMSE is 0.3cm.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.5
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• pp.330-335
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• 2017

This study applied SONAR(Sound Navigation And Ranging) to the inspection and evaluation of underwater structures. Anactual river bridge was chosen for inspection and evaluation. SONAR and an optical camera were operated together to analyze the underwater image of the bridge. SONAR images were obtained by various methods to remove the environmental variables from the field experiment, and it was confirmed that the reliability of detecting damaged areas on piers was decreased when using SONAR alone. The SONAR equipment and the optical camera can be used simultaneously to overcome the limitations of SONAR in inspecting underwater structures.These results can be used as basic data for the development of similar technologies for underwater structure inspection.

• The Journal of the Acoustical Society of Korea
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• v.42 no.4
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• pp.370-376
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• 2023

In the underwater image, it is not clear to distinguish the shape of the target due to underwater noise and low resolution. In addition, as an input of deep learning, underwater images require pre-processing and segmentation must be preceded. Even after pre-processing, the target is not clear, and the performance of detection and identification by deep learning may not be high. Therefore, it is necessary to distinguish and clarify the target. In this study, the importance of target shadows is confirmed in underwater images, object detection and target area acquisition by shadows, and data containing only the shape of targets and shadows without underwater background are generated. We present the process of converting the shadow image into a 3-mode image in which the target is white, the shadow is black, and the background is gray. Through this, it is possible to provide an image that is clearly pre-processed and easily discriminated as an input of deep learning. In addition, if the image processing code using Open Source Computer Vision (OpenCV)Library was used for processing, the processing speed was also suitable for real-time processing.

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

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.5
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• pp.645-652
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• 2015

In underwater, such as fish farm and sea, turbidity is increased by water droplets and various suspended, therefore light attenuation occurs depending on the depth also caused by the scattering effect of light float. In this paper, in order to improve the visibility of underwater images obtained from these aquatic environment, we propose a visibility enhancement method using a haze removal method based on dark channel prior and a trained color transform model. In order to train a color transform model, we used underwater pattern images captured from Pohang and Yeosu, and to measure the performance of the proposed method, we carried out experiment of visibility enhancement using underwater images collected from Yeosu, Geomundo and Philippines. The results show that the proposed method can improve the visibility of underwater images of various locations.

• Journal of the Korean Society of Marine Environment & Safety
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• v.23 no.7
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• pp.926-932
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• 2017

Image distortion can occur when photographing deep sea targets with an optical camera. This problem arises because sunlight is not sufficiently transmitted due to seawater and various floating particles of dust. Particularly, color distortion takes place, causing green and blue color channels to be over emphasized due to water depth, while distortion of boundaries also occurs due to light refraction by seawater and floating particles of dust. These distortions degrade the overall quality of underwater images. In this paper, we analyze underwater images of the bottom of vessels. Based on the results, we propose a technique for color correction and edge enhancement. Experimental results show that the proposed method increases edge clarity by 3.39 % compared to the effective edges of the original underwater image. In addition, a quantitative evaluation and subjective image quality evaluation were concurrently performed. As a result, it was confirmed that object boundaries became clear with color correction. The color correction and contour enhancement method proposed in this paper can be applied in various fields requiring underwater imaging in the future.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.475-476
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• 2018

In this paper, we propose a method to measure the number of biofouling attached to underwater structures. This method measures the number of biofouling based on digital images captured in underwater. The number of biofouling was measured after correcting the image quality of underwater images for accurate population counting. In order to measure the number of biofouling, Maxima value in the image was found.

• Journal of Broadcast Engineering
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• v.17 no.4
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• pp.684-694
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• 2012

In the underwater environment, light is absorbed and scattered by water and floating particles, which makes the underwater images suffer from color degradation and limited visibility. Physically, the amount of the scattered light transmitted to the image is proportional to the distance between the camera and the object. In this paper, the proposed visibility enhancement. method utilizes depth images to estimate the light transmission and the degradation factor by the scattered light. To recover the scatter-free images without unnatural artifacts, the proposed method normalizes the degradation factor based on the value of each pixel of the image. Finally, the scatter-free images are obtained by removing the scattered components on the image according to the estimated transmission. The proposed method also considers the color discrepancies of underwater stereo images so that the stereo images have the same color appearance after the visibility enhancement. The experimental results show that the proposed method improves the color contrast more than 5% to 14% depending on the experimental images.

• 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.