드론 장착 카메라를 이용한 하천의 표면유속측정

류권규(Yu Kwonkyu),황정근(Hwang Jeong Geun) 한국방재학회 2017 한국방재학회논문집 Vol.17 No.2

본 연구의 목적은 드론에 장착된 카메라로 하천 수표면을 촬영하여 하천의 표면유속을 측정하는 방법을 개발하는 것이다. 표면영상유속계를 이용할 때, 폭이 넓은 하천의 경우 하천 양안이나 교량 등에서는 충분한 화각을 확보하기 어렵다. 드론을 이용하면 사람이 접근하기 힘든 지역도 쉽게 촬영이 가능하므로 원하는 하천 표면의 영상을 쉽게 촬영할 수 있다. 다만, 드론에 장착된 비디오 카메라는 야간에는 촬영이 어려우며, 아무리 정지비행을 잘 하더라도 영상에는 다소간의 흔들림이 항상 존재한다. 이를 해결하기 위해 본 연구에서는 열영상 카메라를 추가적으로 드론에 장착하고, 흔들린 영상에 대해서는 형태 정합법에 의해 보정을 하였다. 영상 보정 과정은 고정된 표정점을 영상에서 추적한 뒤, 기준 영상의 표정점과 보정 영상의 표정점이 일치하도록 보정하였다. 영상 보정 후 영상 처리와 분석프로그램을 통하여 유속을 도출한다. 실험 하천에 대해 적용한 결과 상당히 만족스런 결과를 얻었다. The present study aims to develop a drone-based surface image velocimeter to measure velocity fields of a river surface. When we measure water surface velocity using a surface image velocimeter, it is difficult to get a proper angle of view from bridges or river banks, especially for wide rivers. If we use a drone to take images of river surface, it is possible to access anywhere and get good angle of view. However, most video cameras installed by default on drones cannot take image in night time. And another problem is in most cases the images taken with a drone camera will have small and large sway due to drone stabilization. To solve the problems, we installed a far-infrared camera on a drone and corrected images using a pattern matching technique. In the image correction process, we tracked some reference points on images, and transformed the images to a reference image so that the locations of ground control points on transformed images match to those of the reference image. After the image correction, a surface image volocimeter software can calculates velocity fields from those images. The analyses showed fairly good results.

경기도 무인기(드론)영상 통합구축 및 활성화 방안

옥진아,정효진 경기연구원 2018 정책연구 Vol.- No.-

As the size of the drone market has grown rapidly, relevant policies have been proposed worldwide and reflecting these movements, aviation laws and regulations are being eased in Korea. Further, local governments are also establishing policies and support measures for introducing drones into business and developing and developing the drones industry. In the LH (Korea Land & Housing Corporation), LX (Korea Land and Geospatial Informatix Corporation) and Seoul city government, the drones were introduced to the whole business without being devoted to the utilization of one field, and recognized as efficient decision-making methods and constructed the image-based system. Gyeonggi-Do needs more precise spatial information due to the many developments compared to other attempts, and it is necessary to monitor through renewal. Therefore, in order to achieve the virtuous cycle of the drones industry in Gyeonggi-Do, it is necessary to present the effective utilization field that matches the characteristics of Gyeonggi-Do and to suggest the direction and strategy of human resource development for revitalizing the drone industry. Currently, Gyeonggi-Do owns a drone and produces photographic and orthophoto images using drones according to each department requests. In addition, a survey on the real estate status of the common property and the aerial photographing of the land surveyed were conducted. In addition, Gyeonggi-Do plans to provide the service called Drone Space as an internal policy support service within the real estate portal. Through this service, Gyeonggi-Do intends to provide the system for collecting, processing, and then managing the information of the drone image promoted by each department in Gyeonggi-Do. However, the images collected through the drones currently operating in Gyeonggi-Do have problems of budget and management because the system construction process has not been established yet. In order to establish a drones image construction process, it is necessary to select priorities in consideration of availability, urgency, safety, and sustainability for each department, and appropriate achievements should be presented. Internally, it should be improved to provide services that can systematically use and manage drone spatial information so that it can be used for work, as well as share it with the citizens. In order to improve the limited use of duties, it is necessary to find out projects that can actually use drones in the public service field of Gyeonggi-Do and expand them to pilot projects. And it is necessary to establish a utilization strategy leading to demonstration → application → expansion by promoting practical research. A drones application support center is established to activate the drones industry, and it should be operated as a systematic organization that supports the drones industry so as to provide customized image information for each department.

영상처리와 센서를 이용한 드론의 실내 장애물 인식 알고리즘 연구

정보성,김혜린,이정훈 한국기계기술학회 2022 한국기계기술학회지 Vol.24 No.6

In this paper, we proposed and tested an indoor obstacle recognition and avoidance algorithm using vision and ultrasonic sensors for effective operation of drone with low-power. In this paper, the indoor flight of a drone is mainly composed of two algorithms. First, for the indoor flight of the drone, the vanishing point and the center point of the image were extracted through Hough transform of the input image of the vision sensor. The drone moves along the extracted vanishing point. Second, we set an area of interest so that the drone can avoid obstacles. The area of interest is a space where the drone can fly after recognizing an obstacle at a distance from the ultrasonic sensor. When an obstacle is recognized in the drone's area of ​​interest, the drone performs an obstacle avoidance action. To verify the algorithm proposed in this paper, a simple obstacle was installed in an indoor environment and the drone was flown. From the experimental results, the proposed algorithm confirmed the indoor flight and obstacle avoidance behavior of the drone according to the vanishing point.

선형과 특징점을 이용한 연속적인 드론영상의 자동기하보정

최한승,김의명 한국측량학회 2019 한국측량학회지 Vol.37 No.1

Images captured by drone have the advantage of quickly constructing spatial information in small areas and are applied to fields that require quick decision making. If an image registration technique that can automatically register the drone image on the ortho-image with the ground coordinate system is applied, it can be used for various analyses. In this study, a methodology for geo-referencing of a single image and sequential images using drones was proposed even if they differ in spatio-temporal resolution using linear features and distinct points. Through the method using linear features, projective transformation parameters for the initial geo-referencing between images were determined, and then finally the geo-referencing of the image was performed through the template matching for distinct points that can be extracted from the images. Experimental results showed that the accuracy of the geo-referencing was high in an area where relief displacement of the terrain was not large. On the other hand, there were some errors in the quantitative aspect of the area where the change of the terrain was large. However, it was considered that the results of geo-referencing of the sequential images could be fully utilized for the qualitative analysis. 드론영상은 소규모 지역의 공간정보를 신속하게 구축할 수 있는 장점을 가지고 있어 빠른 의사결정이 필요한 분야에 적용되고 있다. 이러한 드론영상을 지상좌표계가 설정되어 있는 정사영상에 자동으로 영상등록할 수 있는 기하보정 기법이 적용된다면 다양한 분석에 활용될 수 있다. 이에 본 연구에서는 선형정보와 특징점 정보를 이용하여 시·공간해상도에 차이가 있더라도 드론을 이용하여 촬영된 단일 영상 및 연속영상을 기하보정할 수 있는 방법론을 제안하였다. 선형정보를 이용하는 방법을 통해서 영상간의 초기 기하보정을 위한 투영변환 매개변수를 결정한 후 영상에서 다수 추출할 수 있는 특징점에 대한 템플릿 정합을 통해서 최종적으로 영상의 기하보정을 수행하였다. 실험을 통하여 지형의 기복이 많이 있지 않은 지역에서는 기하보정의 정확도가 높게 나타났다. 이에 반해 지형의 변화가 많은 지역에서는 정량적인 측면에서 다소 오차가 크게 나타났으나 정성적인 분석에는 연속영상의 기하보정 결과를 충분히 활용가능한 것으로 판단된다.

드론 영상 기반 시설물 점검 - 기준 영상을 활용한 자동 처리 중심으로

김휘영(Kim, Hwi Young),최경아(Choi, Kyoung Ah),이임평(Lee, Im Pyeong) 대한공간정보학회 2018 대한공간정보학회지 Vol.26 No.2

교량, 댐, 도로와 같은 시설물의 노후화와 점검 대상 시설물의 증가로 인해 시설물 점검을 위한 보다 효율적이고 경제적인 방법이 필요하다. 현재의 시설물 점검은 육안 검사와 같이 사람이 접근하는 방식으로 수행되고 있다. 이는 시간과 비용이 많이 소요되고, 점검자에 따라 결과에 대한 신뢰도 차이가 발생한다. 본 연구는 육안 검사 기반시설물 점검의 효율성과 객관성을 높이기 위해, 기준 영상을 활용한 자동 처리 중심의 드론 영상 기반 시설물 점검을 제안한다. 시설물 점검 체계의 구성과 방식을 확인하고, 드론 영상 기반 시설물 점검의 활용 방안을 파악한다. 영상을 처리하기 위해 먼저 시설물의 드론 영상을 정밀하게 처리하여 기준 영상 데이터베이스를 구축한다. 구축된 기준 영상을 기반으로, 새롭게 취득한 드론 영상을 자동으로 처리하여 시설물의 대상면에 기하보정된 영상을 생성한다. 제시한 드론 영상 자동 처리 방법의 정확도를 검증하기 위하여, 시설물의 영상을 기준 영상을 기반으로 처리하였다. 영상의 외부표정요소의 정확도는 0.6cm, 0.01º이었고, 영상에서 추정한 시설물의 위치 정확도는 7.8cm이었다. 본 연구의 방법을 통해 시설물 점검의 비용 절감과 객관성 향상에 기여할 수 있을 것으로 기대한다. As many facilities such as bridges, dams and roads become deteriorated and the number of facilities to be inspected is increased, we require more efficient and economic methods for facility inspection. The current facility inspection relies on human intervention such as visual inspection, which is usually time consuming and requires a high cost. As it depends on the inspector, the inspection results may not be reliable and objective. This study thus proposes a drone image-based facility inspection focusing automatic processing using reference images to improve the efficiency and objectivity of a visual inspection-based facility inspection. We checked components and methods of the facility inspection system, identified applications of the drone image-based facility inspection. In order to process the images, first, the reference image database is constructed by precisely processing drone images of the facility. Based on the constructed reference images, the newly acquired drone image is automatically processed to generate ortho-images on the target plane of the facility. In order to verify the accuracy of the proposed method, the image of the facility was processed based on reference images. The accuracy of the exterior orientation parameters of images was 0.6cm and 0.01º, and the positional accuracy of target points of the facility estimated from the image was 7.8cm. It is expected that this method will reduce the cost and improve the objectivity of facility inspection.

영상 드론의 운동성과 보기 양식에 관한 소고

임종수(Jongsoo Lim) 한국언론학회 2017 커뮤니케이션 이론 Vol.13 No.3

드론은 3차원 입체 공간에서 활동하는 증강현실 기계다. 이 글은 문화기술의 재매개적 논의와 경험적 자료에 입각해 영상 드론을 기계론과 운동론으로 검토하고 이를 영상 드론의 시각적 보기 양식의 관점에서 설명한다. 드론에서 기계성은 드론이 스스로 움직임을 조정해 가는 자동력으로, 운동성은 전통적인 카메라 축(axis)의 제거를 통한 3차원 입체 공간에서의 다양한 공간적 운동으로 정의된다. 따라서 드론은 드론 내 기계적 배치와 대상물과의 공간적 배치를 통해 운용된다. 그렇게 볼 때, 카메라를 단 영상 드론은 이용자로부터 분리되어 입체 공간상의 물리적 운동 과정을 통해 영상을 채취한다. 드론의 물리적 운동은 사물을 다시점적으로 보고자 했던 입체파적 관점에서 한 걸음 더 나아가 사태를 촘촘하게 들여다봄으로서 현장성과 역동성을 표현하는 힘이다. 이로 인해 영상 드론의 보기는 ‘전방위적 가시성(omni-viewpoint visibility)’이라는 공간적 보기 양식으로 개념화될 수 있다. 전방위적 가시성은 드론 특유의 운동성으로 인해 매끈한 운동성의 영상을 표현한다. 이 영상은 어느 방향에서도 볼 수 있기 때문에 전후좌우, 상하구분이 사라진 운동ᐨ이미지이다. 이 같은 드론 영상에 대한 창의적 제작 활동과 학술적 논의를 통해 드론 미디어학의 지평이 열리기를 기대한다. Drones are augmented reality machines operating in 3-dimensional space. Based on the discussion of remediation in cultural technology and experiential data, this paper examines the visual drones with mechanics and kinetics, then remarked it in terms of the visionary mode of seeing. Mechanism refers to the motility of the drones adjusting its movement, then kinetics refers to the various spatial movement in the aerial space due to the elimination of traditional camera axes. Therefore, drones are operated through the mechanical arrangement within the drone and spatial arrangement with the objects. In that point, visual drones equipped with camera separate from the controller, then gather the image through the physical exercise in 3-dimensional space. Physical movements of drones are a power expressing the vividness and dynamics as seeing the states in detail stepping forward from Cubism trying to see the object with multi-viewing point. As a result, the mode of seeing in visual drone can be conceptualized as spatial seeing called omni-viewpoint visibility. Omni-viewpoint visibility expresses seamless kinetic image due to the drone’s unique mobility. This image can be seen in any direction, so it is movement-image disappeared division of back and forth, left and right, even up and down. We hope that the new horizon of drone medialogy will be opened through the creative production activities and academic discussions on drone images.

Button Filtering for Converting Image to Coordinates of Swarming Drones

Inhwan Wee,Dasol Lee,David Hyunchul Shim 제어로봇시스템학회 2018 제어로봇시스템학회 국제학술대회 논문집 Vol.2018 No.10

In this paper, we propose Button Filtering which is a method of non-linear filtering that creates a set of points from an image. This set of points can be used as coordinates of drones. Button filtering is considered nonlinear filtering because it is not applied as convolution, which is used on typical filtering. Nevertheless, it is easy and fast owing to use of a simple button mask, and it has the advantage of immense extendibility. To date, it is only available for the 8-bit grayscale image, which is generally the edge of the original image or masked image. However, it can be applied to a color image, two-dimensional images in a 3D space, and even three-dimensional objects. In this paper, we present the use of button filtering for any object in any image. To this end, we must perform pre-processing before button filtering. We thus present six methods that can handle almost every image type and identify the specific methods that are effective for certain image types.

Deep learning–based drone detection with SWIR cameras

박호민,박경수,김유린,김정근,김재훈,이성대 한국마린엔지니어링학회 2020 한국마린엔지니어링학회지 Vol.44 No.6

Small unmanned aerial vehicles, commonly known as drones, and their related industries are improving in leaps and bounds. The global drone industry began with a military focus and subsequently progressed into commercial applications. Consequently, abuse cases linked to drone technology are gradually increasing. Following the technical advancement in drone technology, studies on drone detection and prevention are actively ongoing. This is one such study. Radar-based drone detection that combines various existing sensors or equipment has shortcomings, including high costs and specialist operations. Thus, this paper proposes a drone-detection system that uses only thermal images from short-wavelength infrared (SWIR) cameras. The YOLO model, which is widely used for object recognition, was used for the drone-detection algorithm. Labels were attached to 22,921 thermal images to test the constructed system; 16,121 images were used for training and the remainder for testing. The test results showed 98.17% precision and 98.65% recall. Learning through drone-image shooting in various environments, after removing static from clouds and other noise, is expected to improve detection performance in the future.

드론촬영 기법을 활용한 영상합성 특성연구

김동조 차세대컨버전스정보서비스학회 2021 차세대컨버전스정보서비스기술논문지 Vol.10 No.4

In Drones used at imaging, sites are replacing existing photography techniques, requiring specialized production techniques along with continuous development of equipment. Due to the development of technology, various flight methods of drones and photography techniques using drone-mounted cameras are making great use of video content in all directions. And the image synthesis production environment has brought many changes in the image production process with the development of digital technology. Analysis data on the production method using camera tracking data using match moving while synthesizing graphics using natural camera movement is likely to be used as a video content production guide. Camera walking, which is free to move in space during the image synthesis process, consumes a lot of time and carries a lot of economic burdens. Image synthesis that combines drone photography can invest more time in planning images of various graphics than in order to obtain tracking data of cameras. Therefore, it is expected that video synthesis work using drone filming images will be able to expand the application area of video content production in various genres as well as VFX. 영상촬영 현장에서 사용되고 있는 드론은 기존 촬영 기법을 대체하고 있어 장비의 지속적인 발전과 함께 특화된 연출기법 연구가 필요한 실정이다. 기술의 발전으로 드론의 다양한 비행 방법과 드론에 장착된 카메라를 활용한 촬영 기법은 전방위적으로 영상 콘텐츠 제작에 있어서 매우 높은 활용을 하고 있다. 그리고 영상합성 제작환경은 디지털 기술의 발전과 함께 영상제작 과정에 있어 많은 변화를 가져왔다. 공간이동이 자유로운 카메라의 움직임을 이용한 컴퓨터 그래픽 오브젝트의 합성작업 중 매치 무브를 이용하여 카메라 트래킹 포인트 위치 데이터를 활용한 제작 방식에 대한 분석자료는 영상 콘텐츠 제작 가이드로 활용될 가능성이 높다. 영상합성 과정에서 공간의 이동이 자유로운 카메라 워킹은 장비의 이동에 따른 시간적 소모와 인력배치를 위한 경제적인 부담이 있다. 반면에 드론촬영을 병행한 영상합성은 카메라의 트래킹 포인트 위치 데이터를 추출하기 위한 작업보다 컴퓨터 그래픽의 이미지를 기획하는 것에 시간적 소모를 높게 투자할 수 있는 장점이 있다. 따라서 드론 촬영 영상을 활용한 영상합성 작업은 VFX 뿐만 아니라 다양한 분야에서 영상 콘텐츠 제작 응용 영역을 확대할 것으로 기대한다.

Drone 영상을 이용한 논 필지 볏짚 환원-동계 재배 확인 및 CH₄ 배출량 산정

장성주 ( Jang Seongju ),박진석 ( Park Jinseok ),홍록기 ( Hong Rokgi ),홍주표 ( Hong Joopyo ),권채린 ( Kwon Chaelyn ),송인홍 ( Song Inhong ) 한국농촌계획학회 2021 농촌계획 Vol.27 No.3

Rice straw management and winter crop cultivation are crucial components for the accurate estimation of paddy methane emissions. Field-based extensive investigation of paddy organic matter management requires enormous efforts however it becomes more feasible as drone technology advances. The objectives of this study were to identify paddy fields of straw application and winter crop cultivation using drone images and to apply for the estimation of yearly methane emission. Total 35 sites of over 150ha in area were selected nationwide as the study areas. Drone images of the study sites were taken twice during summer and winter in 2018 through 2019: Summer images were used to identify paddy cultivation areas, while winter images for straw and winter crop practices. Drone-image-based identification results were used to estimate paddy methane emission and compared with conventional method. As the result, mean areas for paddy, straw application and winter crop cultivation were 118.9ha, 12.0ha, and 11.3ha, respectively. Overall rice straw application rate were greater in Gyeonggi-do(20%) and Chungcheongnam-do(12%), while winter crop cultivation was greatest in Gyeongsangnam-do(30%) and Jeolla-do(27%). Yearly mean methane emission was estimated to be 226.2kg CH₄/ha/yr in this study and about 32% less when compared to 331.8kg CH₄/ha/yr estimated with the conventional method. This was primarily because of the lower rice straw application rate observed in this study, which was less than quarter the rate of 55.62% used for the conventional method. This indicates the necessity to use more accurate statistics of rice straw application as well as winter crop practices into paddy methane emission estimation. Thus it is recommended to further study to link drone technology with satellite image analysis in order to identify organic management practices at a paddy field level over extensive agricultural area.