• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.11a
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• pp.319-320
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• 2022

해무는 해면에 인접한 층에서 수증기가 응결하여 대기 중에 부유하는 현상으로 기상학적으로 수평 가시거리가 1km이하 일때로 정의되며 해무로 인해 항공기 이착륙 지연, 교통사고, 운항 통제, 인명 피해 등 사회적, 경제적 피해를 유발하고 있다. 본 연구에서는 기존의 해무 발생, 탐지, 예측과 관련한 연구를 비교 분석하여 향후 연구개발의 방향을 제시하고자 한다. 해무 발생, 예측과 관련하여 연구개발이 진행되어 왔으나 해무의 특성상 규칙성이 약하고 고정적인 측정법이나 이를 다루기 위한 네트워크가 부족하여 예측하기가 어렵다. 특히, 국내에서는 국립해양조사원과 기상청에서 해무 탐지 및 예측에 관한 연구개발 및 서비스가 진행되고 있으나 현업화가 이루어지지 않거나 특정지점에 대한 정보만 제공되고 있는 한계가 있다. 따라서, CCTV영상, 인공위성 영상, 시정계, 기상자료, 수치모형을 통해 수집된 정보를 통합하여 예측할 수 있는 인공지능기반의 해무 탐지 및 예측 기술개발이 진행되어야 할 것이다.

• Korean Journal of Remote Sensing
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• v.37 no.5_2
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• pp.1317-1328
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• 2021

This study analyzes the early satellite mission marine fog detection results from Geostationary Ocean Color Imager-II (GOCI-II). We investigate optical characteristics of the GOCI-II spectral bands for marine fog between October 2020 and March 2021 during the overlapping mission period of Geostationary Ocean Color Imager (GOCI) and GOCI-II. For Rayleigh-corrected reflection (R_rc) at 412 nm band available for the input of the GOCI-II marine fog algorithm, the inter-comparison between GOCI and GOCI-II data showed a small Root Mean Square Error (RMSE) value (0.01) with a high correlation coefficient (0.988). Another input variable, Normalized Localization Standard (NLSD), also shows a reasonable correlation (0.798) between the GOCI and GOCI-II data with a small RMSE value (0.007). We also found distinctive optical characteristics between marine fog and clouds by the GOCI-II observations, showing the narrower distribution of all bands' R_rc values centered at high values for cloud compared to marine fog. The GOCI-II marine fog detection distribution for actual cases is similar to the GOCI but more detailed due to the improved spatial resolution from 500 m to 250 m. The validation with the automated synoptic observing system (ASOS) visibility data confirms the initial reliability of the GOCI-II marine fog detection. Also, it is expected to improve the performance of the GOCI-II marine fog detection algorithm by adding sufficient samples to verify stable performance, improving the post-processing process by replacing real-time available cloud input data and reducing false alarm by adding aerosol information.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.11a
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• pp.214-216
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• 2022

본 논문에서는 시정계에 비해서 낮은 가격으로 개발이 가능한 카메라 시스템과 촬영한 사진으로 해무 강도를 측정하는 방안을 제안한다. 항로표지에 부착이 가능하고 360도 촬영이 가능한 카메라 시스템 구현 내용을 설명하고 해무의 강도를 측정하기 위해 안개 모델과 Dark Channel Prior(DCP)를 이용해 해무 강도를 측정하는 알고리즘을 개발하였다.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.11a
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• pp.177-179
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• 2023

항로표지에 설치된 카메라에서 촬영한 영상으로 해무 강도를 측정한다. 영상 이미지를 Dark Channel 값으로 바꾼 후에 특정 문턱값을 기준으로 전체 영상에서 해무가 존재하지 않은 픽셀 개수의 비율을 통해서 해무 강도를 추정하여 날씨로 인한 항로 표지 안전사고를 해결하는 것을 제안한다..

• Journal of Internet Computing and Services
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• v.22 no.6
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• pp.25-32
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• 2021

In line with future changes in the marine environment, Aids to Navigation has been used in various fields and their use is increasing. The term "Aids to Navigation" means an aid to navigation prescribed by Ordinance of the Ministry of Oceans and Fisheries which shows navigating ships the position and direction of the ships, position of obstacles, etc. through lights, shapes, colors, sound, radio waves, etc. Also now the use of Aids to Navigation is transforming into a means of identifying and recording the marine weather environment by mounting various sensors and cameras. However, Aids to Navigation are mainly lost due to collisions with ships, and in particular, safety accidents occur because of poor observation visibility due to sea fog. The inflow of sea fog poses risks to ports and sea transportation, and it is not easy to predict sea fog because of the large difference in the possibility of occurrence depending on time and region. In addition, it is difficult to manage individually due to the features of Aids to Navigation distributed throughout the sea. To solve this problem, this paper aims to identify the marine weather environment by estimating sea fog level approximately with images taken by cameras mounted on Aids to Navigation and to resolve safety accidents caused by weather. Instead of optical and temperature sensors that are difficult to install and expensive to measure sea fog level, sea fog level is measured through the use of general images of cameras mounted on Aids to Navigation. Furthermore, as a prior study for real-time sea fog level estimation in various seas, the sea fog level criteria are presented using the Haze Model and Dark Channel Prior. A specific threshold value is set in the image through Dark Channel Prior(DCP), and based on this, the number of pixels without sea fog is found in the entire image to estimate the sea fog level. Experimental results demonstrate the possibility of estimating the sea fog level using synthetic haze image dataset and real haze image dataset.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.06a
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• pp.103-105
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• 2022

인공지능을 기반으로 한 안개를 제거하는 기술은 많은 연구가 있다. 하지만 대부분의 연구가 육상을 타겟으로 하고 있기 때문에 해상에 발생하는 해무를 제거하기 위한 데이터 셋은 현저히 부족하다. 이를 해결하기 위해 가상의 해무를 생성하여 데이터 셋을 생성하고 유효성 검증을 하는 방법에 대하여 연구하였다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2000.10a
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• pp.597-601
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• 2000

Sea fog/stratus is very difficult to detect because of the characteristics of air-sea interaction and locality, and the scantiness of the observed data from the oceans such as ships or ocean buoys. The aim of our study develops new algorism for sea fog detection by using Geostational Meteorological Satellite-5(CMS-5) and suggests the technics of its continuous detection.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.12
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• pp.2355-2362
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• 2016

Seg fog removal is an important issue concerned by both computer vision and image processing. Sea fog or haze removal is widely used in lots of fields, such as automatic control system, CCTV, and image recognition. Color image dehazing techniques have been extensively studied, and expecially the dark channel prior(DCP) technique has been widely used. This paper propose a fast and efficient image prior - dark channel prior to remove seg-fog from a single digital image based on the GPU. We implement the basic parallel program and then optimize it to obtain performance acceleration with more than 250 times. While paralleling and the optimizing the algorithm, we improve some parts of the original serial program or basic parallel program according to the characteristics of several steps. The proposed GPU programming algorithm and implementation results may be used with advantages as pre-processing in many systems, such as safe navigation for ship, topographical survey, intelligent vehicles, etc.

• Journal of Advanced Navigation Technology
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• v.24 no.6
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• pp.485-490
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• 2020

Recently, amid active research on domestic shipbuilding industry and IT convergence technology, with the development of satellite detection technology for ship safety operation, ships monitored the movement of ships with the mandatory long-range identification & tracking of vessels and automatic identification system. It is possible to help safe navigation, but it is necessary to develop safety device that alert the marine officer who rely on radar to correct conditions in case of weightlessness. Therefore, an ocean fog alarm system was developed to detect and inform using photo sensors. The fabricated ocean fog detect and alarm system consists of a small, low-power optical sensor transceiver and data sensing processing module. Through experiment, it is confirmed that the fabricated ocean fog detect and alarm system measure the corresponding concentration of ocean fog for fogless circumstance and fogbound circumstance, respectively. Furthermore, the fabricated system can control RPM of ship engine according to the concentration of ocean fog, and consequently, the fabricated system can be applied to assistant device for ship safety operation.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2021.11a
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• pp.39-40
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• 2021

선박과 항로표지 간 충돌에 의한 항로표지(buoy) 소실 및 사고를 줄이고자 영상을 기반으로 선박 접근 여부를 판단한다. 또한, 해양 기상환경을 파악해 운항 안전사고를 방지하기 위해 카메라로 촬영한 영상을 이용해 해무 강도를 측정하고자 한다.