• Title/Summary/Keyword: 물표 추출

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Robust Object Extraction Algorithm in the Sea Environment (해양환경에서 강건한 물표 추적 알고리즘)

  • Park, Jiwon;Jeong, Jongmyeon
    • Journal of the Korean Institute of Intelligent Systems
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    • v.24 no.3
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    • pp.298-303
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    • 2014
  • In this paper, we proposed a robust object extraction and tracking algorithm in the IR image sequence acquired in the sea environment. In order to extract size-invariant object, we detect horizontal and vertical edges by using DWT and combine it to generate saliency map. To extract object region, binarization technique is applied to saliency map. The correspondences between objects in consecutive frames are defined by the calculating minimum weighted Euclidean distance as a matching measure. Finally, object trajectories are determined by considering false correspondences such as entering object, vanishing objects and false object and so on. The proposed algorithm can find trajectories robustly, which has shown by experimental results.

Object Detection Algorithm Using Edge Information on the Sea Environment (해양 환경에서 에지 정보를 이용한 물표 추출 알고리즘)

  • Jeong, Jong-Myeon;Park, Gyei-Kark
    • Journal of the Korea Society of Computer and Information
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    • v.16 no.9
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    • pp.69-76
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    • 2011
  • According to the related reports, about 60 percents of ship collisions have resulted from operating mistake caused by human factor. Specially, the report said that negligence of observation caused 66.8 percents of the accidents due to a human factor. Hence automatic detection and tracking of an object from an IR images are crucial for safety navigation because it can relieve officer's burden and remedies imperfections of human visual system. In this paper, we present a method to detect an object such as ship, rock and buoy from a sea IR image. Most edge directions of the sea image are horizontal and most vertical edges come out from the object areas. The presented method uses them as a characteristic for the object detection. Vertical edges are extracted from the input image and isolated edges are eliminated. Then morphological closing operation is performed on the vertical edges. This caused vertical edges that actually compose an object be connected and become an object candidate region. Next, reference object regions are extracted using horizontal edges, which appear on the boundaries between surface of the sea and the objects. Finally, object regions are acquired by sequentially integrating reference region and object candidate regions.

A Study on Target Extraction Using Radar-based Ship Collision Accident Data (레이더 기반 선박충돌사고 데이터를 이용한 물표 추출에 관한 연구)

  • Kee-Seok Lee;Bong-Hak Kim;Heon-Jei Park;Nam-Sun Son;Han-Sol Park
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • 2022.11a
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    • pp.178-180
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    • 2022
  • 선박충돌사고를 재현하고 분석하기 위해서는 레이더 기반 선박충돌사고 데이터에서 물표 정보를 정확하게 확보하는 것이 매우 중요한 역할을 한다. 이 연구에서는 HSV 색공간과 OpenCV 라이브러리를 이용하여 물표 정보를 추출하는 방법을 분석하였고, 실제 상황에 적용한 프로그램도 개발하였다.

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A Scale Invariant Object Detection Algorithm Using Wavelet Transform in Sea Environment (해양 환경에서 웨이블렛 변환을 이용한 크기 변화에 무관한 물표 탐지 알고리즘)

  • Bazarvaani, Badamtseren;Park, Ki Tae;Jeong, Jongmyeon
    • Journal of the Korean Institute of Intelligent Systems
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    • v.23 no.3
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    • pp.249-255
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    • 2013
  • In this paper, we propose an algorithm to detect scale invariant object from IR image obtained in the sea environment. We create horizontal edge (HL), vertical edge (LH), diagonal edge (HH) of images through 2-D discrete Haar wavelet transform (DHWT) technique after noise reduction using morphology operations. Considering the sea environment, Gaussian blurring to the horizontal and vertical edge images at each level of wavelet is performed and then saliency map is generated by multiplying the blurred horizontal and vertical edges and combining into one image. Then we extract object candidate region by performing a binarization to saliency map. A small area in the object candidate region are removed to produce final result. Experiment results show the feasibility of the proposed algorithm.

Extraction of the ship movement information by a radar target extractor (Radar Target Extractor에 의한 선박운동정보의 추출에 관한 연구)

  • Lee, Dae-Jae;Kim, Kwang-Sik;Byun, Duck-Soo
    • Journal of the Korean Society of Fisheries and Ocean Technology
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    • v.38 no.3
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    • pp.249-255
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    • 2002
  • This paper describes on the extraction of ship's real-time movement information using a combination full-function ARPA radar and ECS system that displays radar images and an electronic chart together on a single PC screen. The radar target extractor(RTX) board, developed by Marine Electronics Corporation of Korea, receives radar video, trigger, antenna bearing pulse and heading pulse signals from a radar unit and processes these signals to extract target information. The target data extracted from each pulse repetition interval in DSPs of RTX that installed in 16 bit ISA slot of a IBM PC compatible computer is formatted into a series of radar target messages. These messages are then transmitted to the host PC and displayed on a single screen. The position data of target in range and azimuth direction are stored and used for determining the center of the distributed target by arithmetic averaging after the detection of the target end. In this system, the electronic chart or radar screens can be displayed separately or simulaneously and in radar mode all information of radar targets can be recorded and replayed In spite of a PC based radar system, all essential information required for safe and efficient navigation of ship can be provided.

Object Detection Algorithm in Sea Environment Based on Frequency Domain (주파수 도메인에 기반한 해양 물표 검출 알고리즘)

  • Park, Ki-Tae;Jeong, Jong-Myeon
    • Journal of the Korean Institute of Intelligent Systems
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    • v.22 no.4
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    • pp.494-499
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    • 2012
  • In this paper, a new method for detecting various objects that can be risks to safety navigation in sea environment is proposed. By analysing Infrared(IR) images obtained from various sea environments, we could find out that object regions include both horizontal and vertical direction edges while background regions of sea surface mainly include vertical direction edges. Therefore, we present an approach to detecting object regions considering horizontal and vertical edges. To this end, in the first step, image enhancement is performed by suppressing noises such as sea glint and complex clutters using a statistical filter. In the second step, a horizontal edge map and a vertical edge map are generated by 1-D Discrete Cosine Transform technique. Then, a combined map integrating the horizontal and the vertical edge maps is generated. In the third step, candidate object regions are detected by a adaptive thresholding method. Finally, exact object regions are extracted by eliminating background and clutter regions based on morphological operation.

Object Detection Method in Sea Environment Using Fast Region Merge Algorithm (해양환경에서 고속 영역 병합 알고리즘을 이용한 물표 탐지 기법)

  • Jeong, Jong-Myeon;Park, Gyei-Kark
    • Journal of the Korean Institute of Intelligent Systems
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    • v.22 no.5
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    • pp.610-616
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    • 2012
  • In this paper, we present a method to detect an object such as ship, rock and buoy from sea IR image for the safety navigation. To this end, we do the image smoothing first and the apply watershed algorithm to segment image into subregions. Since watershed algorithm almost always produces over-segmented regions, it requires posterior merging process to get meaningful segmented regions. We propose an efficient merger algorithm that requires only two times of direct access to the pixels regardless of the number of regions. Also by analyzing IR image obtained from sea environments, we could find out that most horizontal edge come out from object regions. For the given input IR image we extract horizontal edge and eliminate isolated edges produced from background and noises by adopting morphological operator. Among the segmented regions, the regions that have horizontal edges are extracted as final results. Experimental results show the adequacy of the proposed method.

Radar Target Extractor에 의한 선박운동정보의 추출에 관한 연구

  • 이대재;김광식;변덕수;현윤기;강희영
    • Proceedings of the Korean Society of Fisheries Technology Conference
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    • 2001.10a
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    • pp.71-72
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    • 2001
  • 최근 연근해 어선에서는 소형 레이더 장치를 항해 및 어로장치와 함께 탑재하고 있으나, 소형 레이더에 있어서는 타선의 진운동정보(진침로, 진속력)나 충돌회피정보(CPA, TCPA), 또한, 주위의 상황변화에 대한 다양한 물표정보(진운동벡터표시, 실시간 추적정보)를 제공할 수 없는 문제가 있다. (중략)

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Manufacture of a Small RTE for Real-Time Extraction of Radar Signal (레이더 신호의 실시간 추출을 위한 소형 레이더 목표 추출기 개발)

  • Sung Tae-Kyung;Kim Dong-Seek;Cho Hyung-Rae
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.15 no.9
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    • pp.835-840
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    • 2004
  • Using of small Radar device can not supply the real exercise information of ellipse circumference or CPA, TCPA and the changing of surroundings fur various target information. Therefore, for the above problem, we develop RTE that is able to and of for each information from ARPA Radar which supply analog video signal, trigger bearing and heading pulse from low-cost small Radar device is equiped with general small fishing boat. The small fishing is equipped with small Radar device, so it is able to collect and apply sailing information such as real exercise information and TCPA.

A Study on Extracting Boundary Data of Marine Fish Farms Based on Satellite Images (위성영상 기반 해양수산 양식장의 경계 데이터 추출)

  • Seong-hoon Jeong
    • Journal of Advanced Navigation Technology
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    • v.27 no.6
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    • pp.877-883
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    • 2023
  • For safe operation of ships and management of marine fisheries farms, the data set that extracts the boundaries of marine fisheries farms can provide information on obstacles in the vessel's navigation path in advance by examining whether it matches the fishing ground permit area. In addition, it can be used to determine whether fish farms are operating to compensate for damage caused by marine accidents, and the relevant local government can use it to manage fishing grounds. It is also highly utilized as basic data to identify obstacles for safe navigation of ships. In this study, Sentinel-2 satellite image data from the European Space Agency (ESA) was used to extract the boundaries of fish farms. From the video image, the fish farm's status data by cycle was divided into five zones: Busan-Ulsan area, Geoje-Changwon area, Goseong-Tongyeong area, and Namhae-Sacheon area. Through the image highlighting process, the farm boundary data and meta data were processed and extracted.