• Journal of Biosystems Engineering
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• v.36 no.5
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• pp.377-383
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• 2011

This study proposed the new method of discerning the assembled parts and presuming the position of central point in a Cowl Cross Bar (CCB) using a Charge-Couple Device (CCD) camera attached to a robot in the auto assembly line. Three control points of an ellipse were decided by three reference points, which were equally distanced. The radii of these reference points were determined by the size of the object, and the repeated presumption secured the precise determination. The comparison of the central point of ellipse presumed by Randomized Hough Transform (RHT) with the part information stored in a database was used for determining the faulty part in an assembly. The method proposed in this study was applied for the real-time inspection of elliptical parts, such as bolt, nut hole and so on, connected to a CCB using a CCD camera. The findings of this study showed that the precise decision on whether the parts are inferior or not can be made irrespective of the lighting condition of industrial site and the noises of the surface of the part. In addition, the defect decision on the individual elliptic parts assembled in a CCB showed more than 98% accuracy within a 500-millisecond period at most.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.1
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• pp.31-43
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• 2015

This study had been aimed to conduct the camera calibration on VLBI antenna in the Space Geodetic Observation Center of Sejong City with a low-cost digital camera, which embedded in a mobile phone to determine the three-dimension position coordinates of the VLBI antenna, based on stereo images. The initial values for the camera calibration have been obtained by utilizing the Direct Linear Transformation algorithm and the commercial digital photogrammetry system, PhotoModeler $Scanner^{(R)}$ ver. 6.0, respectively. The accuracy of camera calibration results was compared with that the camera calibration results, acquired by a bundle adjustment with nonlinear collinearity condition equation. Although two methods showed significant differences in the initial value, the final calibration demonstrated the consistent results whichever methods had been performed for obtaining the initial value. Furthermore, those three-dimensional coordinates of feature points of the VLBI antenna were respectively calculated using the camera calibration by the two methods to be compared with the reference coordinates obtained from a total station. In fact, both methods have resulted out a same standard deviation of $X=0.004{\pm}0.010m$, $Y=0.001{\pm}0.015m$, $Z=0.009{\pm}0.017m$, that of showing a high degree of accuracy in centimeters. From the result, we can conclude that a mobile phone camera opens up the way for a variety of image processing studies, such as 3D reconstruction from images captured.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.29 no.5
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• pp.519-525
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• 2011

High-resolution earth-observing satellites acquire substantial amount of geospatial images. In addition to high image quality, high-resolution satellite images (HRSI) provide unprecedented direct georegistration accuracy, which have been enabled by accurate orbit determination technology. Direct georegistration is carried out by relating the determined position and attitude of camera to the ground target, i.e., projecting an image point to the earth ellipsoid using the collinearity equation. However, the apparent position of ground target is displaced due to the atmosphere and satellite velocity causing significant georegistration bias. In other words, optic ray from the earth surface to satellite cameras at 400~900km altitude refracts due to the thick atmosphere which is called atmospheric refraction. Velocity aberration is caused by high traveling speed of earth-observing satellites, approximately 7.7 km/s, relative to the earth surface. These effects should be compensated for accurate direct georegistration of HRSI. Therefore, this study presents the equation and the compensation procedure of atmospheric refraction and velocity aberration. Then, the effects are simulated at different image acquisition geometry to present how much bias is introduced. Finally, these effects are evaluated for Quickbird and WorldView-1 based on the physical sensor model.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.7
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• pp.83-91
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• 2004

The determination of camera position and orientation from known correspondences of 3D reference points and their images is known as pose estimation in computer vision or space resection in photogrammetry. This paper discusses estimation of transform parameters using the pattern matching method with 2D images only. In general, the 3D reference points or lines are needed to find out the 3D transform parameters, but this method is applied without the 3D reference points or lines. It uses only two images to find out the transform parameters between two image. The algorithm is simulated using Visual C＋＋ on Windows 98.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.2
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• pp.163-171
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• 2014

Based on the GPS/IMU integration, the car navigation has unstable conditions as well as drastically reduces accuracies in urban region. Nowadays, many cars mounted the camera to record driving states. If the ground coordinates of street furniture are known, the position and attitude of camera can be determined through SPR(Single Photo Resection). Therefore, an estimated position and attitude from SPR can be applied measurements in Kalman filter for updating errors of navigation solutions from GPS/IMU integration. In this study, the GPS/IMU/SPR integration algorithm was developed in loosely coupled modes through extended Kalman filters. Also, in order to analyze performances of GPS/IMU/SPR, simulation tests were conducted in GPS signal reception environments and the GCPs (Ground Control Points) distributions. In fact, the position and attitude gathered from GPS/IMU/SPR integration are more precise than the position and attitude from GPS/IMU integration. When IPs (image points), corresponded to GCPs, were concentrated in the center of image, the position error in the optical axis respectively increased. To understand effects from SPR, we plan to carry additional test on the magnitude of GCP, IP and initial exterior orientation errors.

• Journal of Korean Society for Geospatial Information Science
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• v.25 no.2
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• pp.21-29
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• 2017

For the efficient and stable operation of autonomous vehicles or advanced driver assistance systems being actively studied nowadays, it is important to determine the positions of the vehicle accurately and economically. A satellite based navigation system is mainly used for positioning, but it has a limitation in signal blockage areas. To overcome this limitation, sensor fusion methods including additional sensors such as an inertial navigation system have been mainly proposed but the high sensor cost has been a problem. In this work, we develop a vehicle position estimation algorithm using in-vehicle sensors and a low-cost imaging sensor without any expensive additional sensor. We determine the vehicle positions using the velocity and yaw-rate of a car from the in-vehicle sensors and the position and attitude of the camera based on the single photo resection process. For the evaluation, we built a prototype system, acquired test data using the system, and estimated the trajectory. The proposed algorithm shows the accuracy of about 40% higher than an in-vehicle sensor only method.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.7
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• pp.52-61
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• 1992

An iterative scheme for computing the three-dimensional position and the surface orientation of an opaque object from a singel shaded image is proposed. This method demonstrates that calculating the depth(distance) between the camera and the object from one shaded video image is possible. Most previous research works on $'Shape from Shading$' problem, even in the $'Photometric Stereo Method$', invoved the determination of surface orientation only. To measure the depth of an object, depth of the object, and the reflectance properties of the surface. Assuming that the object surface is uniform Lambertian the measured intensity level at a given image pixel*x,y0becomes a function of surface orientation and depth component of the object. Derived Image Irradiance Equation can`t be solved without further informations since three unknown variables(p,q and D) are in one nonlinear equation. As an additional constraints we assume that surface satisfy smoothness conditions. Then equation can be solved relaxatively using standard methods of TEX>$'Calculus of VariationTEX>$'. After checking the sensitivity of the algorithm to the errors ininput parameters, the theoretical results is tested by experiments. Three objects (plane, cylinder, and sphere)are used. Thees initial results are very encouraging since they match the theoretical calculations within 20$\%$ error in simple experiments.> error in simple experiments.

• Journal of Sensor Science and Technology
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• v.8 no.1
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• pp.80-88
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• 1999

This paper deals with the position determination problem of stereo camera systems used as a sensor for 3D robotic manipulation. Stereo cameras having parallel rays of sight and been set up on the same baseline are assumed. The distance between the sensor and the space measured is determined so as to get insensitive parameters to the uncertainty of control points used for calibration and to satisfy the error condition set by considering the repeatability of the robot. The baseline width is determined by minimizing the mutual effect of 3D positional error and stereo image coordinate error. Unlike existing techniques, the technique proposed here is developed without complicated constraints and modelling process of the object to be observed. Thus, the technique of this paper is more general and its effectiveness is proved by simulation.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.14 no.1
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• pp.89-95
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• 1996

As an attempt to apply GPS technique to aerial photogrammetry, an effort is exerted to replace the ground control points that were necessary in the traditional aerial photogrammetry with the aerial control by measuring the position of the camera exposure. In this study, various situations are simulated to test the conditions that affect the positioning of the points in aerial photogrammetry for the use of GPS data. From the result of the simulations, the necessary conditions and the applicable values to produce a 1:1, 000 topographical map were suggested. In the case of a photo block consists of 104 photos, we found a minimum of six ground control points make acceptable accuracy under the condition of below $10\mu{m}$ image positional error and with the ground observations.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.10 no.2
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• pp.101-106
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• 2010

We propose an approach to estimate the real-time moving trajectory of an object in this paper. The object's position is obtained from the image data of a CCD camera, while a state estimator predicts the linear and angular velocities of the moving object. To overcome the uncertainties and noises residing in the input data, a Extended Kalman Filter(EKF) and neural networks are utilized cooperatively. Since the EKF needs to approximate a nonlinear system into a linear model in order to estimate the states, there still exist errors as well as uncertainties. To resolve this problem, in this approach the Kohonen networks, which have a high adaptability to the memory of the inputoutput relationship, are utilized for the nonlinear region. In addition to this, the Kohonen network, as a sort of neural network, can effectively adapt to the dynamic variations and become robust against noises. This approach is derived from the observation that the Kohonen network is a type of self-organized map and is spatially oriented, which makes it suitable for determining the trajectories of moving objects. The superiority of the proposed algorithm compared with the EKF is demonstrated through real experiments.