• Journal of the Korean Society for Aviation and Aeronautics
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• v.18 no.2
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• pp.16-22
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• 2010

This paper proposes the real-time moving object tracking system UAV using color information. Case of object tracking, it have studied to recognizing the moving object or moving multiple objects on the fixed camera. And it has recognized the object in the complex background environment. But, this paper implements the moving object tracking system using the pan/tilt function of the camera after the object's region extraction. To do this tracking system, firstly, it detects the moving object of RGB/HSI color model and obtains the object coordination in acquired image using the compact boundary box. Secondly, the camera origin coordination aligns to object's top&left coordination in compact boundary box. And it tracks the moving object using the pan/tilt function of camera. It is implemented by the Labview 8.6 and NI Vision Builder AI of National Instrument co. It shows the good performance of camera trace in laboratory environment.

• Korean Journal of Remote Sensing
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• v.35 no.1
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• pp.1-13
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• 2019

The advent of a fourth industrial revolution, built on advances in digital technology, has coincided with studies using various unmanned aerial vehicles (UAVs) being performed worldwide. However, the accuracy of different sensors and their suitability for particular research studies are factors that need to be carefully evaluated. In this study, we evaluated UAV photogrammetry using smart technology. To assess the performance of digital photogrammetry, the accuracy of common procedures for generating orthomosaic images and digital surface models (DSMs) using terrestrial laser scanning (TLS) techniques was measured. Two different type of non-surveying camera(Smartphone camera, fisheye camera) were attached to UAV platform. For fisheye camera, lens distortion was corrected by considering characteristics of lens. Accuracy of orthoimage and DSM generated were comparatively analyzed using aerial and TLS data. Accuracy comparison analysis proceeded as follows. First, we used Ortho mosaic image to compare the check point with a certain area. In addition, vertical errors of camera DSM were compared and analyzed based on TLS. In this study, we propose and evaluate the feasibility of UAV photogrammetry which can acquire 3 - D spatial information at low cost in a construction site.

• International Journal of Aeronautical and Space Sciences
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• v.9 no.1
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• pp.76-84
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• 2008

This paper is mainly concerned with the vision-based attitude stabilization of a quad-rotor UAV. The methods for attitude control rely on computing the roll and pitch angles of the vehicle from a two-camera vision system. One camera is attached to the body-fixed x-axis and the other to the body-fixed y-axis. The attitude computation for the quad-rotor UAV is performed by image processing consisting of Canny edge and Hough line detection. A proportional and integral controller is employed for the attitude hold autopilot. In this paper, the quad-rotor UAV is modeled by 6-DOF nonlinear equations of motion that includes rotor aerodynamics with blade element theory. The performance of the proposed method is evaluated through 3D environmental numerical simulations.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.5
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• pp.444-450
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• 2015

The accuracy of small and low cost CCD camera is insufficient to provide data for precisely tracking unmanned aerial vehicles(UAVs). This study shows how UAV can hover on a human targeted tracking object by using CCD camera rather than imprecise GPS data. To realize this, UAVs need to recognize their attitude and position in known environment as well as unknown environment. Moreover, it is necessary for their localization to occur naturally. It is desirable for an UAV to estimate of his attitude by environment recognition for UAV hovering, as one of the best important problems. In this paper, we describe a method for the attitude of an UAV using image information of a maker on the floor. This method combines the observed position from GPS sensors and the estimated attitude from the images captured by a fixed camera to estimate an UAV. Using the a priori known path of an UAV in the world coordinates and a perspective camera model, we derive the geometric constraint equations which represent the relation between image frame coordinates for a marker on the floor and the estimated UAV's attitude. Since the equations are based on the estimated position, the measurement error may exist all the time. The proposed method utilizes the error between the observed and estimated image coordinates to localize the UAV. The Kalman filter scheme is applied for this method. its performance is verified by the image processing results and the experiment.

• Journal of Cadastre & Land InformatiX
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• v.51 no.2
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• pp.185-198
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• 2021

Researches using UAVs are being actively conducted in the field of quickly constructing 3D spatial information in small areas. In this study, without using ground control points, a stereo camera was mounted on a UAV to collect images and quickly construct three-dimensional positions through image matching, bundle adjustment, and the determination of a scale factor. Through the experiment, when bundle adjustment was performed using stereo constraints, the root mean square error was 1.475m, and when absolute orientation was performed in consideration of a scale, it was found to be 0.029m. Through this, it was found that when using the data processing method of a UAV equipped with a stereo camera proposed in this study, high-accuracy 3D spatial information can be constructed without using ground control points.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.6
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• pp.475-483
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• 2015

This study examined the feasibility of using an automatic lens distortion correction (ALDC) camera as the payload for a photogrammetric unmanned aerial vehicle (UAV) system. First, lens distortion for the interior orientation (IO) parameters was estimated. Although previous studies have largely ignored decentering distortion, this study revealed that more than 50% of the distortion of the ALDC camera was caused by decentering distortion. Second, we compared the accuracy of bundle adjustment for camera calibration using three image types: raw imagery without the ALDC option; imagery corrected using lens profiles; and imagery with the ALDC option. The results of image triangulation, the digital terrain model (DTM), and the orthoimage using the IO parameters for the ALDC camera were similar to or slightly better than the results using self-calibration. These results confirm that the ALDC camera can be used in a photogrammetric UAV system using only self-calibration.

• Journal of the Korean Association of Geographic Information Studies
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• v.19 no.4
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• pp.106-117
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• 2016

Recently, solar power plants have spread widely as part of the transition to greater environmental protection and renewable energy. Therefore, regular solar plant inspection is necessary to efficiently manage solar-light modules. This study implemented a test that can detect solar-light module faults using an UAV based thermal infrared camera and GIS spatial analysis. First, images were taken using fixed UAV and an RGB camera, then orthomosaic images were created using Pix4D SW. We constructed solar-light module layers from the orthomosaic images and inputted the module layer code. Rubber covers were installed in the solar-light module to detect solar-light module faults. The mean temperature of each solar-light module can be calculated using the Zonalmean function based on temperature information from the UAV thermal camera and solar-light module layer. Finally, locations of solar-light modules of more than $37^{\circ}C$ and those with rubber covers can be extracted automatically using GIS spatial analysis and analyzed specifically using the solar-light module's identifying code.

• Korean Journal of Remote Sensing
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• v.32 no.3
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• pp.275-285
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• 2016

This study analyzes the accuracy of ortho imagery based on whether camera calibration performed or not, using an unmanned aerial vehicle which equipped smart camera. Photgrammetric UAV system application was developed and smart camera performed image triangulation, and then created image as ortho imagery. Image triangulation was performed depending on whether interior orientation (IO) parameters were considered or not, which determined at the camera calibration phase. As a result of the camera calibration, RMS error appeared 0.57 pixel, which is more accurate compared to the result of the previous study using non-metric camera. When IO parameters were considered in static experiment, the triangulation resulted in 2 pixel or less (RMSE), which is at least 200 % higher than when IO parameters were not considered. After generate ortho imagery, the accuracy is 89% higher when camera calibration are considered than when they are not considered. Therefore, smart camera has high potential to use as a payload for UAV system and is expected to be equipped on the current UAV system to function directly or indirectly.

• Aerospace Engineering and Technology
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• v.6 no.2
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• pp.245-249
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• 2007

The objective of the UAV removes the life loss of the pilot who is the maximum weak point of the manned reconnaissance aircraft, accomplishes the reconnaissance it is an aircraft for. The camera which will confirm the pilot substitution reconnaissance result which stands is necessary, we should confirm; the target which this camera probably is what. The report which described like this demand condition against the consideration fact which is necessary to the selection of the image sensory device which is a camera which with character will be applied in UAV.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.1
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• pp.24-30
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• 2016

The accuracy of small and low-cost CCD cameras is insufficient to provide data for precisely tracking unmanned aerial vehicles (UAVs). This study shows how a quad rotor UAV can hover on a human targeted tracking object by using data from a CCD camera rather than imprecise GPS data. To realize this, quadcopter UAVs need to recognize their position and posture in known environments as well as unknown environments. Moreover, it is necessary for their localization to occur naturally. It is desirable for UAVs to estimate their position by solving uncertainty for quadcopter UAV hovering, as this is one of the most important problems. In this paper, we describe a method for determining the altitude of a quadcopter UAV using image information of a moving object like a walking human. This method combines the observed position from GPS sensors and the estimated position from images captured by a fixed camera to localize a UAV. Using the a priori known path of a quadcopter UAV in the world coordinates and a perspective camera model, we derive the geometric constraint equations that represent the relation between image frame coordinates for a moving object and the estimated quadcopter UAV's altitude. Since the equations are based on the geometric constraint equation, measurement error may exist all the time. The proposed method utilizes the error between the observed and estimated image coordinates to localize the quadcopter UAV. The Kalman filter scheme is applied for this method. Its performance is verified by a computer simulation and experiments.