• Journal of Sensor Science and Technology
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• v.11 no.4
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• pp.239-246
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• 2002

In this paper a new design of multi-layer perceptron(MLP) for camera calibration is proposed. Most existing techniques determine a transformation from 3D spatial points to their image points and camera parameters are tried to be estimated from the transformation. The technique proposed here, on the other hand, determines rays of sight uniquely from image points and parameters are estimated from the relationship using an MLP. By this approach projection and back-projection can be done more straightforwardly. Being based on a geometric model, a network design process becomes less ambiguous, which is a clear merit compared to other neural net based techniques. An MLP designed according to the technique proposed showed fast and stable learning in tests under various conditions.

• Proceedings of the KSRS Conference
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• v.1
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• pp.372-375
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• 2006

The MSC is a high resolution multi-spectral camera system which is mounted on the KOMPSAT-II satellite. The electro-optic camera system has a refocusing mechanism which can be used in-orbit by ground commands. By adjusting locations of some elements in optics, the system can be focused precisely. The focus mechanism in MSC is implemented with stepper motor and potentiometer. By reading the value of the potentiometer, rough position of the motor can be understood. The exact location of the motor can not be acquired because the information from the potentiometer can not be so accurate. However, before and after certain events of the satellite, like a satellite launch, the direction of the movement or order of the magnitude of the movement can be understood. In this paper, the trend analysis of the focus motor position during the ground test phase is introduced. This result can be used as basic information for the focus calibration after launch. By studying the long term trend, deviation from the best focal point can be understood. The positions of the focus motors after launch are also compared.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.37 no.12
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• pp.1209-1216
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• 2009

This paper presents the pose estimation of a small UAV utilizing visual information from low cost cameras installed indoor. To overcome the limitation of the outside flight experiment, the indoor flight test environment based on multi-camera systems is proposed. Computer vision algorithms for the proposed system include camera calibration, color marker detection, and pose estimation. The well-known extended Kalman filter is used to obtain an accurate position and pose estimation for the small UAV. This paper finishes with several experiment results illustrating the performance and properties of the proposed vision-based indoor flight test environment.

• Proceedings of the Korean Society of Computer Information Conference
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• 2012.07a
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• pp.429-432
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• 2012

In this paper, we proposed the algorithm computes the waste volume periodically for the way of waste repository standard. For the construction of safe and clear urban environment, it is necessary that we identify the rubbish waste volume and we know the accuracy volume. After camera calibration, we obtained the point cloud on the surface of the object and took this as the input of the calculation algorithm of the object volume. We proposed the two volume calculation algorithms based on the triangularmeshing methods and verified the validity of the algorithm through simulation and real experiments. The proposed algorithm can be used not only as the volume calculation of the waste repository but also as the general volume calculation of a three dimensional object.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.530-532
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• 2007

Multi-Spectral Camera(MSC) is a main payload on the KOMPSAT-2 satellite to perform the earth remote sensing. The MSC instrument has one(1) channel for panchromatic imaging and four(4) channel for multi-spectral imaging covering the spectral range from 450nm to 900nm using TDI CCD Focal Plane Array (FPA). The compression method on KOMPSAT-2 MSC was selected and used to match EOS input rate and PDTS output data rate on MSC image data chain. At once the MSC performance was carefully handled to minimize any degradation so that it was analyzed and restored in KGS(KOMPSAT Ground Station) during LEOP and Cal./Val.(Calibration and Validation) phase. In this paper, on-orbit image data chain in MSC and image data processing on KGS including general MSC description is briefly described. The influences on image performance between on-board compression algorithms and between performance restoration methods in ground station are analyzed and discussed.

• Journal of Biosystems Engineering
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• v.23 no.4
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• pp.381-390
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• 1998

An algorithm to extract the 3-D geometric information of a static object was developed using a set of 2-D computer vision system and a laser structured lighting device. As a structured light pattern, multi-parallel lines were used in the study. The proposed algorithm was composed of three stages. The camera calibration, which determined a coordinate transformation between the image plane and the real 3-D world, was performed using known 6 pairs of points at the first stage. Then, utilizing the shifting phenomena of the projected laser beam on an object, the height of the object was computed at the second stage. Finally, using the height information of the 2-D image point, the corresponding 3-D information was computed using results of the camera calibration. For arbitrary geometric objects, the maximum error of the extracted 3-D feature using the proposed algorithm was less than 1~2mm. The results showed that the proposed algorithm was accurate for 3-D geometric feature detection of an object.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.1907-1910
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• 2003

This paper describes a method of stereo image composition for mixed reality without camera calibration or complicate tracking algorithm. The proposed system tracks the panel which has blob makers, and composes virtual objects naturally using the method of texture mapping which is often used in geological computer graphics mapping when we do mapping 2D computer graphic data or man-made 2D images. The proposed algorithm makes it possible for us to compose virtual data even in the case that the panel is bent. For composing 3D object, the system uses depth information obtained from stereo image so that we do not need cumbersome procedure of camera calibration.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.504-507
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• 2007

The KOMPSAT-2 satellite is a push-broom system with MSC (Multi Spectral Camera) which contains a panchromatic band and four multi-spectral bands covering the spectral range from 450nm to 900nm. The PAN band is composed of six CCD array with 2528 pixels. And the MS band has one CCD array with 3792 pixels. Raw imagery generated from a push-broom sensor contains vertical streaks caused by variability in detector response, variability in lens falloff, pixel area, output amplifiers and especially electrical gain and offset. Relative radiometric calibration is necessary to account for the detector-to-detector non-uniformity in this raw imagery. Non-uniformity correction (NUC) is that the process of performing on-board relative correction of gain and offset for each pixel to improve data compressibility and to reduce banding and streaking from aggregation or re-sampling in the imagery. A relative gain and offset are calculated for each detector using scenes from uniform target area such as a large desert, forest, sea. In the NUC of KOMPSAT-2, The NUC table for each pixel are divided as HF NUC (high frequency NUC) and LF NUC (low frequency NUC) to apply to few restricted facts in the operating system ofKOMPSAT-2. This work presents the algorithm and process of NUC table generation and shows the imagery to compare with and without calibration.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.6
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• pp.637-643
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• 2010

In this study, we developed a Portable Multi-sensor System, which consists of a video camera, a GPS/MEMS IMU and a UMPC to acquire video images and position/attitude data. We performed image georeferencing based on the bundle adjustment without ground control points using the acquired data and then evaluated the effectiveness of our system through the accuracy verification. The experimental results showed that the RMSE of relative coordinates on the ground point coordinates obtained from our system was several centimeters. Our system can be efficiently utilized to obtain the 3D model of object and their relative coordinates. In future, we plan to improve the accuracy of absolute coordinates through the rigorous calibration of the system and camera.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.8
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• pp.309-314
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• 2014

To generate a complete 3D model from depth images of multiple RGB-D cameras, it is necessary to find 3D transformations between RGB-D cameras. This paper proposes a convenient view calibration technique using a spherical object. Conventional view calibration methods use either planar checkerboards or 3D objects with coded-pattern. In these conventional methods, detection and matching of pattern features and codes takes a significant time. In this paper, we propose a convenient view calibration method using both 3D depth and 2D texture images of a spherical object simultaneously. First, while moving the spherical object freely in the modeling space, depth and texture images of the object are acquired from all RGB-D camera simultaneously. Then, the external parameters of each RGB-D camera is calibrated so that the coordinates of the sphere center coincide in the world coordinate system.