• Title/Summary/Keyword: Real-time Drone image

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Sensor Fusion Docking System of Drone and Ground Vehicles Using Image Object Detection (영상 객체 검출을 이용한 드론과 지상로봇의 센서 융합 도킹 시스템)

  • Beck, Jong-Hwan;Park, Hee-Su;Oh, Se-Ryeong;Shin, Ji-Hun;Kim, Sang-Hoon
    • KIPS Transactions on Software and Data Engineering
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    • v.6 no.4
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    • pp.217-222
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    • 2017
  • Recent studies for working robot in dangerous places have been carried out on large unmanned ground vehicles or 4-legged robots with the advantage of long working time, but it is difficult to apply in practical dangerous fields which require the real-time system with high locomotion and capability of delicate working. This research shows the collaborated docking system of drone and ground vehicles which combines image processing algorithm and laser sensors for effective detection of docking markers, and is finally capable of moving a long distance and doing very delicate works. We proposed the docking system of drone and ground vehicles with sensor fusion which also suggests two template matching methods appropriate for this application. The system showed 95% docking success rate in 50 docking attempts.

A Study on the Construction of Near-Real Time Drone Image Preprocessing System to use Drone Data in Disaster Monitoring (재난재해 분야 드론 자료 활용을 위한 준 실시간 드론 영상 전처리 시스템 구축에 관한 연구)

  • Joo, Young-Do
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.18 no.3
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    • pp.143-149
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    • 2018
  • Recently, due to the large-scale damage of natural disasters caused by global climate change, a monitoring system applying remote sensing technology is being constructed in disaster areas. Among remote sensing platforms, the drone has been actively used in the private sector due to recent technological developments, and has been applied in the disaster areas owing to advantages such as timeliness and economical efficiency. This paper deals with the development of a preprocessing system that can map the drone image data in a near-real time manner as a basis for constructing the disaster monitoring system using the drones. For the research purpose, our system is based on the SURF algorithm which is one of the computer vision technologies. This system aims to performs the desired correction through the feature point matching technique between reference images and shot images. The study area is selected as the lower part of the Gahwa River and the Daecheong dam basin. The former area has many characteristic points for matching whereas the latter area has a relatively low number of difference, so it is possible to effectively test whether the system can be applied in various environments. The results show that the accuracy of the geometric correction is 0.6m and 1.7m respectively, in both areas, and the processing time is about 30 seconds per 1 scene. This indicates that the applicability of this study may be high in disaster areas requiring timeliness. However, in case of no reference image or low-level accuracy, the results entail the limit of the decreased calibration.

Position Recognition and Indoor Autonomous Flight of a Small Quadcopter Using Distributed Image Matching (분산영상 매칭을 이용한 소형 쿼드콥터의 실내 비행 위치인식과 자율비행)

  • Jin, Taeseok
    • Journal of the Korean Society of Industry Convergence
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    • v.23 no.2_2
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    • pp.255-261
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    • 2020
  • We consider the problem of autonomously flying a quadcopter in indoor environments. Navigation in indoor settings poses two major issues. First, real time recognition of the marker captured by the camera. Second, The combination of the distributed images is used to determine the position and orientation of the quadcopter in an indoor environment. We autonomously fly a miniature RC quadcopter in small known environments using an on-board camera as the only sensor. We use an algorithm that combines data-driven image classification with image-combine techniques on the images captured by the camera to achieve real 3D localization and navigation.

Comparison of Deep-Learning Algorithms for the Detection of Railroad Pedestrians

  • Fang, Ziyu;Kim, Pyeoungkee
    • Journal of information and communication convergence engineering
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    • v.18 no.1
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    • pp.28-32
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    • 2020
  • Railway transportation is the main land-based transportation in most countries. Accordingly, railway-transportation safety has always been a key issue for many researchers. Railway pedestrian accidents are the main reasons of railway-transportation casualties. In this study, we conduct experiments to determine which of the latest convolutional neural network models and algorithms are appropriate to build pedestrian railroad accident prevention systems. When a drone cruises over a pre-specified path and altitude, the real-time status around the rail is recorded, following which the image information is transmitted back to the server in time. Subsequently, the images are analyzed to determine whether pedestrians are present around the railroads, and a speed-deceleration order is immediately sent to the train driver, resulting in a reduction of the instances of pedestrian railroad accidents. This is the first part of an envisioned drone-based intelligent security system. This system can effectively address the problem of insufficient manual police force.

A study on the creation of mission performance data using search drone images (수색용 드론 이미지를 활용한 임무수행 데이터 생성에 관한 연구)

  • Lee, Sang-Beom;Lim, Jin-Taek
    • Journal of the Institute of Convergence Signal Processing
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    • v.22 no.4
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    • pp.179-184
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    • 2021
  • Along with the development of the fourth industry, the public sector has increasingly paid more attention to search using drones and real-time monitoring, for various goals. The drones are used and researched to complete a variety of searching and monitoring missions, including search for missing persons, security, coastal patrol and monitoring, speed enforcement, highway and urban traffic monitoring, fire and wildfire monitoring, monitoring of illegal fishing in reservoirs and protest rally monitoring. Police stations, fire departments and military authorities, however, concentrate on the hardware part, so there are little research on efficient communication systems for the real-time monitoring of data collected from high-performance resolution and infrared thermal imagining cameras, and analysis programs suitable for special missions. In order to increase the efficiency of drones with the searching mission, this paper, therefore, attempts to propose an image analysis technique to increase the precision of search by producing image data suitable for searching missions, based on images obtained from drones and provide the foundation for improving relevant policies and establishing proper platforms, based on actual field cases and experiments.

Design and Development of Underwater Drone for Fish Farm Growth Environment Management (양식장 생육 환경관리를 위한 수중 드론 설계 및 개발)

  • Yoo, Seung-Hyeok;Ju, Yeong-Tae;Kim, Jong-Sil;Kim, Eung-Kon
    • The Journal of the Korea institute of electronic communication sciences
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    • v.15 no.5
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    • pp.959-966
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    • 2020
  • With the growing importance of the fishery industry and the rapid growth of the aquaculture industry, research on smart farms through ICT convergence in the aquaculture field is in progress. To enable monitoring of the growing environment at the farm site, an underwater drone drive unit, an image collection device, an integrated controller for posture stabilization, and a remote control device capable of controlling and controlling drones through real-time underwater images were proposed, and design, development, and tests were conducted. By utilizing underwater drones, it is possible to replace the supply and demand of manpower and high-cost work in the aquaculture industry, and to manage fish farms in a stable manner by reducing the probability of farming deaths.

A Scheme of Security Drone Convergence Service using Cam-Shift Algorithm (Cam-Shift 알고리즘을 이용한 경비드론 융합서비스 기법)

  • Lee, Jeong-Pil;Lee, Jae-Wook;Lee, Keun-Ho
    • Journal of the Korea Convergence Society
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    • v.7 no.5
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    • pp.29-34
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    • 2016
  • Recently, with the development of high-tech industry, the use of the drones in various aspects of daily life is rapidly advancing. With technical and functional advancements, drones have an advantage of being easy to be utilized in the areas of use according to various lifestyles. In addition, through the diversification of the drone service converged with image processing medium such as camera and CCTV, an automated security system that can replace humans is expected to be introduced. By designing these unmanned security technology, a new convergence security drone service techniques that can strengthen the previous drone application technology will be proposed. In the proposed techniques, a biometric authentication technology will be designed as additional authentication methods that can determine the safety incorporated with security by selecting the search and areas of an object focusing on the objects in the initial windows and search windows through OpenCV technology and CAM-Shift algorithm which are an object tracking algorithm. Through such, a highly efficient security drone convergence service model will be proposed for performing unmanned security by using the drones that can continuously increase the analysis of technology on the mobility and real-time image processing.

A Real Time Quadrotor Autonomous Navigation and Remote Control Method (실시간 쿼드로터 자율주행과 원격제어 기법)

  • Son, Byung-Rak;Kang, Seok-Min;Lee, Hyun;Lee, Dong-Ha
    • IEMEK Journal of Embedded Systems and Applications
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    • v.8 no.4
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    • pp.205-212
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    • 2013
  • In recent, the demand of Unmanned Aerial Vehicles (UAVs) that can autonomous navigation and remote control has been increased in military, civil and commercial field. Particularly, existing researches focused on autonomous navigation method based on vanish point and remote control method based on event processing in indoor environments. However, the existing methods have some problems. For instance, a detected vanish point in intersection point has too much detection errors. In addition, the delay is increased in existing remote control system for processing images in real time. Thus, we propose improved vanish point algorithm by removing detection errors in intersection point. We also develop a remote control system with android platform by separating flying control and image process. Finally, we compare the proposed methods with existing methods to show the improvement of our approaches.

Histogram Learning-based Solar Power Plant Failure Reading System (히스토그램 학습 기반 태양광발전소 고장 판독 시스템)

  • Youm, SungKwan;Shin, Kwang-Seong
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2021.10a
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    • pp.572-573
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    • 2021
  • By optimizing the development of IoT-type thermal image-based photovoltaic fault detection equipment and interworking with drones using a drone with an intelligent path movement function, real-time analysis of the acquired image data facilitates fault reading of solar power plants. , design a system that can read out the failure of a solar panel using the image subtraction analysis technique and the presentation of the basic technology that can improve the power generation rate of the solar power plant and make an efficient maintenance model.

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Real-time traffic situation analysis and fire type artificial intelligence application study when 119 fire trucks are dispatched Intelligence research (119 소방차 출동 시 실시간 교통상황 분석 및 화재유형 인공지능 적용 연구)

  • Lee, Han-young;Park, Dea-woo
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2022.05a
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    • pp.222-224
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    • 2022
  • Korea has more than 2,000 fires and more than 2,000 casualties every year. This study takes measures to facilitate the incorporation of 119 fire trucks by judging vehicles or standing signs using real-time image reading YOLO5 before the fire trucks arrive at the fire site. It is possible to shorten the time to extinguish a fire by photographing a fire site, transmitting the situation of the site, and analyzing the components of smoke to determine the type of fire. As a result, it is expected that it will be able to minimize casualties by keeping the golden time.

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