• Title/Summary/Keyword: HD camera

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Operational Improvement of Hemire ROV for Deep-sea Survey and Application to Exploration of Ferromanganese Crusts of Western Pacific Seamount (해미래의 심해탐사 운용기법 개선 및 서태평양 해저산 망간각 탐사에 적용)

  • Baek, Hyuk;Park, Jin-Yeong;Shim, Hyungwon;Jun, Bong-Huan;Lee, Pan-Mook
    • Journal of Ocean Engineering and Technology
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    • v.32 no.4
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    • pp.287-295
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    • 2018
  • This paper presents the results of an exploration of the ferromanganese crusts of Western Pacific Seamount registered by the Korean government. This area has been surveyed with a deep-sea camera and crust samples have been acquired by deep-sea dredging since 2013. On October 18-19, 2017, a united research team from KIOST and KRISO explored two blocks, OSM11 and OSM07, on the seamount using Hemire ROV. A precise survey was conducted on the ferromanganese crusts and sediments covering the slope/top of OSM11 and the middle flat area of OSM07. Rock samples were collected with precise positioning, and HD videos were recorded for 7 hours. This paper discusses the technical issues of this exploration in terms of (1) how to deal with an emergency situation during an electric power blackout, (2) the improvement of the thruster power by adding cooling plugs to the housings of the thruster amplifiers, (3) the relative motion of the depressor by changing the fixing method of the cable terminator, which affects the service life of the cable, (4) a sampling technique for the steep slope of the seamount, (5) integrated navigation under a USBL blackout, and (6) a 3-dimensional image mosaic for visualizing the distribution state of the crusts.

Vehicle Tracking using Euclidean Distance (유클리디안 척도를 이용한 차량 추적)

  • Kim, Gyu-Yeong;Kim, Jae-Ho;Park, Jang-Sik;Kim, Hyun-Tae;Yu, Yun-Sik
    • The Journal of the Korea institute of electronic communication sciences
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    • v.7 no.6
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    • pp.1293-1299
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    • 2012
  • In this paper, a real-time vehicle detection and tracking algorithms is proposed. The vehicle detection could be processed using GMM (Gaussian Mixture Model) algorithm and mathematical morphological processing with HD CCTV camera images. The vehicle tracking based on separated vehicle object was performed using Euclidean distance between detected object. In more detail, background could be estimated using GMM from CCTV input image signal and then object could be separated from difference image of the input image and background image. At the next stage, candidated objects were reformed by using mathematical morphological processing. Finally, vehicle object could be detected using vehicle size informations dependent on distance and vehicle type in tunnel. The vehicle tracking performed using Euclidean distance between the objects in the video frames. Through computer simulation using recoded real video signal in tunnel, it is shown that the proposed system works well.

Tillage boundary detection based on RGB imagery classification for an autonomous tractor

  • Kim, Gookhwan;Seo, Dasom;Kim, Kyoung-Chul;Hong, Youngki;Lee, Meonghun;Lee, Siyoung;Kim, Hyunjong;Ryu, Hee-Seok;Kim, Yong-Joo;Chung, Sun-Ok;Lee, Dae-Hyun
    • Korean Journal of Agricultural Science
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    • v.47 no.2
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    • pp.205-217
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    • 2020
  • In this study, a deep learning-based tillage boundary detection method for autonomous tillage by a tractor was developed, which consisted of image cropping, object classification, area segmentation, and boundary detection methods. Full HD (1920 × 1080) images were obtained using a RGB camera installed on the hood of a tractor and were cropped to 112 × 112 size images to generate a dataset for training the classification model. The classification model was constructed based on convolutional neural networks, and the path boundary was detected using a probability map, which was generated by the integration of softmax outputs. The results show that the F1-score of the classification was approximately 0.91, and it had a similar performance as the deep learning-based classification task in the agriculture field. The path boundary was determined with edge detection and the Hough transform, and it was compared to the actual path boundary. The average lateral error was approximately 11.4 cm, and the average angle error was approximately 8.9°. The proposed technique can perform as well as other approaches; however, it only needs low cost memory to execute the process unlike other deep learning-based approaches. It is possible that an autonomous farm robot can be easily developed with this proposed technique using a simple hardware configuration.

The Design and Implementation of Internet Broadcasting Solution applied to FLV (FLV를 적용한 인터넷 방송 솔루션의 설계 및 구현)

  • Kwon, O-Byoung;Shin, Hyun-Cheul
    • Convergence Security Journal
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    • v.12 no.3
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    • pp.93-97
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    • 2012
  • In this paper, we apply the next generation Internet TV solution, FLV has been designed and implemented. Currently being broadcast in the field to compress HD video in real time, as well as live Internet VOD services are available through the online system, the Internet LIVE broadcast and VOD service easy to operate and UCC services that support the solution. VOD video cameras and in real time using H264 CORECODEC to compress MPEC4, WMV, and real-time video streaming on the Internet, and phone system that supports the first, real-time recording of camera images featured nation's first real-time encoder system (Real time encoder system) is, Web and smart environment suitable for supporting the latest CORECODEC technology and software products. Second, the video can be played in MP4 player and customize your chat, and Custer (customizing) is a possible two-way Internet Broadcasting System. Third, CMS (Contents Management System) feature video content and course management content in real time via the Android phone and iPhone streaming service is available.

Study on Identification Procedure for Unidentified Underwater Targets Using Small ROV Based on IDEF Method (소형 ROV를 이용한 IDEF0 기반의 수중 미확인 물체 식별절차에 관한 연구)

  • Baek, Hyuk;Jun, Bong-Huan;Yoon, Suk-Min;Noh, Myounggyu
    • Journal of Ocean Engineering and Technology
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    • v.33 no.3
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    • pp.289-299
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    • 2019
  • Various sizes of ROVs are being utilized in offshore industrial, scientific, and military applications all around the world. Because of innovative developments in science and technology, image acquisition devices such as sonar devices and cameras have been reduced in size and their performance has been improved. Thus, we can expect better accuracy and higher resolution even in the case of exploration using a small ROV. The purpose of this paper is to prepare a standard procedure for the identification of unidentified hazardous materials found during the National Oceanographic Survey. In this paper, we propose an IDEF (Integrated DEFinition) method modeling technique to identify unidentified targets using a small ROV. In accordance with the proposed procedure, an ROV survey was carried out on target No.16 with a four-ton-class fishing boat as a support vessel on September 18th of 2018 in the sea near Daebu Island. Unidentified targets, which were not known by the multi-beam data obtained from the ship, could be identified as concrete pipes by analyzing the HD camera and high-resolution sonar images acquired by the ROV. The whole proposed procedure could be verified, and the survey with the small ROV required about 10 days to identify the target in one place.

Intermediate Depth Image Generation using Disparity Increment of Stereo Depth Images (스테레오 깊이영상의 변위증분을 이용한 중간시점 깊이영상 생성)

  • Koo, Ja-Myung;Seo, Young-Ho;Choi, Hyun-Jun;Yoo, Ji-Sang;Kim, Dong-Wook
    • Journal of Broadcast Engineering
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    • v.17 no.2
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    • pp.363-373
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    • 2012
  • This paper proposes a method to generate a depth image at an arbitrary intermediate view-point, which is targeting a video service for free-view, auto-stereoscopy, holography, etc. It assumes that the leftmost and the rightmost depth images are given and they both have been camera-calibrated and image-rectified. This method calculates and uses a disparity increment per depth value. In this paper, it is obtained by stereo matching for the given two depth image by considering more general cases. The disparity increment is used to find the location in the intermediate view-point depth image (IVPD) for each depth in the given images. Thus, this paper finds two IVPDs, from left image and from right image. Noises are removed and holes are filled in each IVPDs and the two results are combined to get the final IVPD. The proposed method was implemented and applied to several test sequences. The results revealed that the quality of the generated IVPD corresponds to 33.84dB of PSNR in average and it takes about 1 second to generate a HD IVPD. We evaluate that this image quality is quite good by considering the low correspondency among the left images, intermediate images, and the right images in the test sequences. If the execution speed is improved, the proposed method can be a very useful method to generate an IVPD at an arbitrary view-point, we believe.