• Title/Summary/Keyword: 물표탐지

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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 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.

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.

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.

항해용 레이더 펄스변화와 파랑계측의 연관성

  • Yang, Yeong-Jun;Park, Dong-U;Gwon, Su-Yeon;Lee, Gyeong-Hun;Lee, Yeong-U
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • 2018.05a
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    • pp.175-177
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    • 2018
  • 항해용 X-band 레이더는 물표탐지를 통한 안전한 항해를 목적으로 널리 사용되고 있다. 해당 목적을 위해서는 노이즈로 간주되는 해면반사파(sea clutter)신호는 제거하여 사용하지만, 본 연구에서는 노이즈로 간주되는 해면반사파 신호를 활용하여 파랑에 대한 정보(파고, 파주기, 파향 등)를 파악하는데 활용하였다. 레이더에서 방출되는 전자기파는 펄스의 길이에 의해 탐지할 수 있는 영역이 제한되어 있다. 펄스의 길이가 짧을수록 짧은 주기의 파랑을 계측할 수 있다는 장점이 있지만, 거리의 제약으로 인하여 대형선박의 실 운항시에는 활용하기 어려운 현실적인 딜레마가 있다. 본 연구에서는 삼성중공업, 오션알앤디가 개발한 WaveFinder 시스템을 이용하여 기존 short pulse 모드 뿐만아니라 midium pulse 에서의 활용 가능성을 실제 시운전을 통해 확인하였다.

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A Study on the Development of YOLO-Based Maritime Object Detection System through Geometric Interpretation of Camera Images (카메라 영상의 기하학적 해석을 통한 YOLO 알고리즘 기반 해상물체탐지시스템 개발에 관한 연구)

  • Kang, Byung-Sun;Jung, Chang-Hyun
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.28 no.4
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    • pp.499-506
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    • 2022
  • For autonomous ships to be commercialized and be able to navigate in coastal water, they must be able to detect maritime obstacles. One of the most common obstacles seen in coastal area are the farm buoys. In this study, a maritime object detection system was developed that detects buoys using the YOLO algorithm and visualizes the distance and bearing between buoys and the ship through geometric interpretation of camera images. After training the maritime object detection model with 1,224 pictures of buoys, the precision of the model was 89.0%, the recall was 95.0%, and the F1-score was 92.0%. Camera calibration had been conducted to calculate the distance and bearing of an object away from the camera using the obtained image coordinates and Experiment A and B were designed to verify the performance of the maritime object detection system. As a result of verifying the performance of the maritime object detection system, it can be seen that the maritime object detection system is superior to radar in its short-distance detection capability, so that it can be used as a navigational aid along with the radar.

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.

레이더 영상 기반 딥러닝을 이용한 물체 인식

  • 이유경;이창민;양영준
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • 2022.06a
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    • pp.28-30
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    • 2022
  • 본 연구에서는 컴퓨터 비전 기반의 딥러닝 객체 인식 기술을 이용하여 속초해수욕장에서 수집한 레이더 이미지에서 선박, 섬 및 부유체에 대해 탐지(Detection), 인식(Recognition)하는 연구를 수행하였다. 2021년 8월에 수집한 레이더 영상을 이용하여 본 연구를 수행하였으며, 움직이는 물표와 섬 등을 구분하였다. 일부 환경적인 제약에 따라 에러 발생이 있었지만, 향후 현재까지 수집한 레이더 영상을 추가하여 정확도를 높일 예정이다.

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영상처리기법을 활용한 선박 입출항 관리시스템 개발에 관한 연구

  • 남희
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • 2022.06a
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    • pp.257-259
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    • 2022
  • 보조수단으로 운용중인 폐쇠회로는 고정된 위치에서 선박들의 이동경로가 파악 가능하여 입출항 관리 시스템 개발에 있어서 중요한 역할을 한다. 이 연구에서는 가우시안 혼합모델을 이용하여 물표를 탐지하고 이동벡터의 계산을 분석하여 매트랩에 적용 가능한 알고리즘을 진행하고자한다.

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연근해 소형 어선의 레이더 정보수록 및 해석 시스템 개발 - CFAR에 의한 레이더 잡음 억제-

  • 이대재;김광식;신형일;변덕수;강희영
    • Proceedings of the Korean Society of Fisheries Technology Conference
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    • 2003.10a
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    • pp.35-38
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    • 2003
  • 현재, 세계 여러나라에서 해상물표를 정확하게 탐지 및 검출하기 위한 방안으로 레이더 clutter 신호를 효과적으로 억제 및 제거하기 위한 연구가 활발하게 진행되고 있다. 일반적으로 레이더 반사파에 대한 envelope 신호의 진폭는 Rayleigh 분포에 따라 변동하는 특성을 나타내지만, clutter의 진폭분포의 파라 메터가 변동하여 분포형상이 변화하면, 오경보확률(false alarm probability)에도 변화가 발생하기 때문에 오경보확률을 충분히 낮은 일정치로써 억제시켜 일정오경보확률(constant false alarm rate, CFAR)을 유지하는 처리가 필요하다. (중략)

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