• Title/Summary/Keyword: 영상 기록 시스템

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Performance analysis of YOLOv5 and Faster R-CNN for real-time crosswalk pedestrian detection (심층 신경망을 이용한 실시간 횡단보도 보행자 검출 방법 분석)

  • Bang, Junho;Park, Min-Ki;Song, Chaeyong;Choi, Haechul
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2022.06a
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    • pp.1184-1186
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    • 2022
  • 횡단보도에서의 보행자 교통사고 방지를 위한 다양한 방법들이 연구되고 있다. 본 논문에서는 점멸 신호등 상황에서 보행자 교통사고를 감소시키기 위해 영상을 이용한 심층 신경망 기반 횡단보도 보행자 검출 방법을 소개한다. YOLOv5 와 Faster R-CNN 각각을 기반으로 다양한 버전의 횡단보도 보행자 검출기를 구현하고, 이번 실험에서 중점이 되는 이들의 수행 시간을 비교 평가하고 mAP@0.5 가 어느 정도인지 판단하여 가장 적합한 모델을 판단한다. 실험 결과 실시간 처리 측면에서 YOLOs 모델이 84 fps 를 달성함으로써 실시간 보행자 검출에 가장 좋은 성능을 보였다. 횡단보도의 상황은 상시 빠르게 변하므로 가장 빠른 처리 성능을 기록한 YOLOv5s 모델이 실시간 횡단보도 보행자 검출 시스템에 가장 적합한 것으로 판단된다.

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A Study of Korean Drone-security Education System (한국 드론시큐리티 교육훈련 시스템에 관한 연구)

  • YIn, Man-Sik
    • Proceedings of the Korean Society of Disaster Information Conference
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    • 2022.10a
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    • pp.373-374
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    • 2022
  • 본 연구는 민간 시큐리티 분야의 드론 도입 시 교육과목 중 드론의 기능을 적용할 수 있는 과목을 기준으로 절차 및 내용에 관하여 연구를 실시하였다. 연구 결과 경계감시, 순찰, 경보, 촬영 및 영상기록, 장비점검, 장비 운송, 사격등의 과목에 드론운영에 대한 교육 내용을 포함시켜야 할 것이다. 이처럼 드론 시큐리티 분야를 민간 시큐리티 산업에 적용하기 위해서는 드론의 기능과 더불어 각 업무분야에 고유한 특성을 반영하여 과목을 구성하여야 할 필요가 있다. 또한 현재의 기술로는 드론에 부착되는 장비에 따라 사용 용도가 다를 수 밖에 없으며, 비행시기와 장소에 따라 실내비행이나 야간비행이 필요한 추가적인 조종교육 및 운용교육이 요구된다고 할 것이다.

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A study on optical coherence tomography system using optical fiber (광섬유를 이용한 광영상 단층촬영기에 관한연구)

  • 양승국;박양하;장원석;오상기;김현덕;김기문
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • 2004.04a
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    • pp.5-9
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    • 2004
  • In this paper, we studied the OCT(Optical Coherence Tomography) system which it has been extensively studied because of having some advantages such as high resolution cross-sectional images, low cost, and small size configuration. A basic principle of OCT system is Michelson interferometer. The characteristics of light source determine the resolution and the transmission depth. As a results, the light source have a commercial SLD with a central wavelength of 1,285 nm and FWHM(Full Width at Half Maximum) of 35.3 nm. The optical delay line part is necessary to equal of the optical path length with scattered light or reflected light from sample. In order to equal the optical path length, the stage which is attached to reference mirror is moved linearly by step motor And the interferometer is configured with the Michelson interferometer using single mod fiber, the scanner can be focused of the sample by using the reference arm. Also, the 2-dimensional cross-sectional images were measured with scanning the transverse direction of the sample by using step motor. After detecting the internal signal of lateral direction at a paint of sample, scanner is moved to obtain the cross-sectional image of 2-demensional by using step motor. Photodiode has been used which has high detection sensitivity, excellent noise characteristic, and dynamic range from 800 nm to 1,700 nm. It is detected mixed small signal between noise and interference signal with high frequency After filtering and amplifying this signal, only envelope curve of interference signal is detected. And then, cross-sectional image is shown through converting this signal into digitalized signal using A/D converter. The resolution of the OCT system is about 30$\mu\textrm{m}$ which corresponds to the theoretical resolution. Also, the cross-sectional image of ping-pong ball is measured. The OCT system is configured with Michelson interferometer which has a low contrast because of reducing the power of feedback interference light. Such a problem is overcomed by using the improved inteferometer. Also, in order to obtain the cross-sectional image within a short time, it is necessary to reduce the measurement time for improving the optical delay line.

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Design and Implementation of Picture Archiving and Communication System Component using the RFID for Mobile Web Environments (모바일 웹 환경을 위한 의료영상저장전송시스템 컴포넌트의 설계 및 구현)

  • Kim Chang-Soo;Yim Jae-Hong
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.10 no.6
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    • pp.1124-1131
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    • 2006
  • The recent medical treatment guidelines and the development of information technology make hospitals reduce the expense in surrounding environment and it requires improving the quality of medical treatment of the hospital. Moreover, MIS, PACS(Picture Archiving and Communication System), OCS, EMR are also developing. Medical Information System is evolved toward integration of medical IT and situation is changing with increasing high speed in the ICT convergence. Mobile component refers to construct wireless system of hospital which has constructed in existing environment. Through RFID development in existing system, anyone can log on easily to internet whenever and wherever. It is the core technology to implement automatic medical processing system. This paper provides a basic review of RFID model, PACS application component services. In addition, designed and implemented database server's component program and client program of mobile application that recognized RFID tag and patient data in the ubiquitous environments. This system implemented mobile PACS that performed patient data based db environments, and so reduced delay time of requisition, medical treatment, lab.

A Study on the Vehicle Black Box with Accident Prevention (사고예방이 가능한 차량용 블랙박스 시스템에 관한 연구)

  • Kim, Kang Hyo;Moon, Hae Min;Shin, Ju Hyun;Pan, Sung Bum
    • Smart Media Journal
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    • v.4 no.1
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    • pp.39-43
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    • 2015
  • A vehicle black box helps to investigate the cause of accident by recording time, and videos as wells as shock information of the time of accident Lately, intelligent black box with accident prevention as well as existing functions is being studied. This paper proposes an applicable algorithm for vehicle black boxes that prevent any accident likely to occur while a car is parked, like robbery, theft or hit-and-run. Proposed algorithm provides object recognition, face detection and alarm as the object approaches car. Tests on the algorithm prove that it can recognize an approaching object, identify and set alarm if needed, depending on each risk level.

Development of Left Turn Response System Based on LiDAR for Traffic Signal Control

  • Park, Jeong-In
    • Journal of the Korea Society of Computer and Information
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    • v.27 no.11
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    • pp.181-190
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    • 2022
  • In this paper, we use a LiDAR sensor and an image camera to detect a left-turning waiting vehicle in two ways, unlike the existing image-type or loop-type left-turn detection system, and a left-turn traffic signal corresponding to the waiting length of the left-turning lane. A system that can efficiently assign a system is introduced. For the LiDAR signal transmitted and received by the LiDAR sensor, the left-turn waiting vehicle is detected in real time, and the image by the video camera is analyzed in real time or at regular intervals, thereby reducing unnecessary computational processing and enabling real-time sensitive processing. As a result of performing a performance test for 5 hours every day for one week with an intersection simulation using an actual signal processor, a detection rate of 99.9%, which was improved by 3% to 5% compared to the existing method, was recorded. The advantage is that 99.9% of vehicles waiting to turn left are detected by the LiDAR sensor, and even if an intentional omission of detection occurs, an immediate response is possible through self-correction using the video, so the excessive waiting time of vehicles waiting to turn left is controlled by all lanes in the intersection. was able to guide the flow of traffic smoothly. In addition, when applied to an intersection in the outskirts of which left-turning vehicles are rare, service reliability and efficiency can be improved by reducing unnecessary signal costs.

A Study on the Development of Ultrasonography Guide using Motion Tracking System (이미지 가이드 시스템 기반 초음파 검사 교육 기법 개발: 예비 연구)

  • Jung Young-Jin;Kim Eun-Hye;Choi Hye-Rin;Lee Chae-Jeong;Kim Seo-Hyeon;Choi Yu-Jin;Hong Dong-Hee
    • Journal of the Korean Society of Radiology
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    • v.17 no.7
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    • pp.1067-1073
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    • 2023
  • Breast cancer is one of the top three most common cancers in modern women, and the incidence rate is increasing rapidly. Breast cancer has a high family history and a mortality rate of about 15%, making it a high-risk group. Therefore, breast cancer needs constant management after an early examination. Among the various equipment that can diagnose cancer, ultrasound has the advantage of low risk and being able to diagnose in real time. In addition, breast ultrasound will be more useful because Asian women's breasts are denser and less sensitive. However, the results of ultrasound examinations vary greatly depending on the technology of the examiner. To compensate for this, we intend to incorporate motion tracking technology. Motion tracking is a technology that specifies and analyzes a location according to the movement of an object in a three-dimensional space. Therefore, real-time control is possible, and complex and fast movements can be recorded in real time. We would like to present the production of an ultrasound examination guide using these advantages.

Fingerprint Liveness Detection Using Patch-Based Convolutional Neural Networks (패치기반 컨볼루션 뉴럴 네트워크 특징을 이용한 위조지문 검출)

  • Park, Eunsoo;Kim, Weonjin;Li, Qiongxiu;Kim, Jungmin;Kim, Hakil
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.27 no.1
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    • pp.39-47
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    • 2017
  • Nowadays, there have been an increasing number of illegal use cases where people try to fabricate the working hours by using fake fingerprints. So, the fingerprint liveness detection techniques have been actively studied and widely demanded in various applications. This paper proposes a new method to detect fake fingerprints using CNN (Convolutional Neural Ntworks) based on the patches of fingerprint images. Fingerprint image is divided into small square sized patches and each patch is classified as live, fake, or background by the CNN. Finally, the fingerprint image is classified into either live or fake based on the voting result between the numbers of fake and live patches. The proposed method does not need preprocessing steps such as segmentation because it includes the background class in the patch classification. This method shows promising results of 3.06% average classification errors on LivDet2011, LivDet2013 and LivDet2015 dataset.

Implementation of AESA Radar Integration Analysis System by using Heterogeneous Media

  • Min-Jung Kang
    • Journal of the Korea Society of Computer and Information
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    • v.29 no.3
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    • pp.117-125
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    • 2024
  • In this paper, implement and propose an Active Electronically Scanned Array (AESA) radar integration analysis system which specialized for radar development by using heterogeneous media. Most analysis systems are used to analyze and improve the cause of defects, so they help the test easier. However, previous log analysis systems that operate only based on text are not intuitive and difficult to find the information user want at once if there is a lot of log information. so when an equipment defect occurs, there are limitations in analyzing the cause of defect. Therefore, the analysis system in this paper utilizes heterogeneous media. The media defined in this paper refers to recording text-based data, displaying data as image or video and visualizing data. The proposed analysis system classifies and stores data that transmitted and received between radar devices, radar target detection and Tracking algorithm data, etc. also displays and visualizes radar operation results and equipment defect information in real time. With this analysis system, it can quickly provide information what user want and assistance in developing high quality radar.

Detection of video editing points using facial keypoints (얼굴 특징점을 활용한 영상 편집점 탐지)

  • Joshep Na;Jinho Kim;Jonghyuk Park
    • Journal of Intelligence and Information Systems
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    • v.29 no.4
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    • pp.15-30
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    • 2023
  • Recently, various services using artificial intelligence(AI) are emerging in the media field as well However, most of the video editing, which involves finding an editing point and attaching the video, is carried out in a passive manner, requiring a lot of time and human resources. Therefore, this study proposes a methodology that can detect the edit points of video according to whether person in video are spoken by using Video Swin Transformer. First, facial keypoints are detected through face alignment. To this end, the proposed structure first detects facial keypoints through face alignment. Through this process, the temporal and spatial changes of the face are reflected from the input video data. And, through the Video Swin Transformer-based model proposed in this study, the behavior of the person in the video is classified. Specifically, after combining the feature map generated through Video Swin Transformer from video data and the facial keypoints detected through Face Alignment, utterance is classified through convolution layers. In conclusion, the performance of the image editing point detection model using facial keypoints proposed in this paper improved from 87.46% to 89.17% compared to the model without facial keypoints.