• Journal of the Korean Society for Precision Engineering
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• v.32 no.6
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• pp.537-542
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• 2015

The measurement of 3D shape is important in inspecting the quality of product. In this paper, we present a 3D shape measurement system of fastener using a camera and a slit laser. Calibration structure with slits is used in the extrinsic calibration of the camera and laser. The pose of the camera and laser is computed under the same world coordinate system in the calibration structure. Reflection of laser light on the metal surface causes many difficulties in the robust detection of them on image. We overcome this difficulty by using color and dynamic programming. Motor stage is used to rotate the fastener to recover the whole 3D shape of the surface of it.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.31 no.8
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• pp.44-49
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• 2003

In case of an extrinsic Fabry-Perot interferometric sensor, the phase compensating technique is particularly necessary in applying the interferometer to detecting acoustic emission signals because of signal-fading problems. The technique makes it possible to maintain the phase at the quadrature point. In this paper, we developed the stabilization control sensor system that is composed of a broadband light source, a tunable Fabry-Perot (F-P) filter and a control-circuit board. A tension test of a composite specimen was performed to verify if the developed system could compensate the phase change induced from the tension strain and keep the phase at the quadrature point.

• Proceedings of the Korean Society For Composite Materials Conference
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• 2002.10a
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• pp.161-164
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• 2002

Optical fiber vibrations sensors (OFVSs) and extrinsic Fabry-Perot interferometer (EFPI) were used in damage monitoring of fiber-metal laminates(FML). The optical fiber vibration sensor and EFPI were applied in order to detect and evaluate the strain, damage and failure of FML. Damages in composites, such as matrix cracks, delamination and fiber breakage may occur as a result of excessive load, fatigue and low-velocity impacts. Tensile test was performed with the measurement of optical signal and acoustic emission (AE). The signals of the optical fiber vibration sensor due to damages were quantitatively evaluated by wavelet transform. EFPI was less sensible to the damage signals compared with the optical fiber vibration sensor. It was found that damage information of comparable in quality to acoustic emission data could be obtained from the optical fiber vibration sensor signals.

• Proceedings of the KSME Conference
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• 2003.04a
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• pp.370-375
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• 2003

Optical fiber vibrations sensors (OFVSs) and extrinsic Fabry-Perot interferometer (EFPI) were used in damage monitoring of fiber-metal laminates(FML). The optical fiber vibration sensor and EFPI were applied in order to detect and evaluate the strain, damage and failure of FML. Damages in composites, such as matrix cracks, delamination and fiber breakage may occur as a result of excessive load, fatigue and low-velocity impacts. Tensile and indentation test was performed with the measurement of optical signal and acoustic emission (AE). The signals of the optical fiber vibration sensor due to damages were quantitatively evaluated by wavelet transform. It was found that damage information of comparable in quality to acoustic emission data could be obtained from the optical fiber vibration sensor signals.

• Proceedings of the Korean Society For Composite Materials Conference
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• 2003.04a
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• pp.42-45
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• 2003

Optical fiber vibrations sensors (OFVSs) and extrinsic Fabry-Perot interferometer (EFPI) were used in damage monitoring of fiber-metal laminates(FML). The optical fiber vibration sensor and EFPI were applied in order to detect and evaluate the strain, damage and failure of FML. Damages in composites, such as matrix cracks, delamination and fiber breakage may occur as a result of excessive load, fatigue and low-velocity impacts. Indentation test was performed with the measurement of optical signal and acoustic emission (AE). The signals of the optical fiber vibration sensor due to damages were quantitatively evaluated by wavelet transform. It was found that damage information of comparable in quality to acoustic emission data could be obtained from the optical fiber vibration sensor signals.

• Information and Communications Magazine
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• v.24 no.12
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• pp.14-21
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• 2007

This paper aims to improve the design of iterative detection and decoding(IDD) based on the soft interference cancellation with minimum mean squared error(SC-MMSE) detector, which shows low performance compared to the maximum a posteriori(MAP) detector. By means of extrinsic information transfer(EXIT) chart analysis, such low performance may be attributed to that the "pure"(original) turbo principle is not always best for IDD. Thus, we propose a new IDD architecture based on the SC-MMSE detector which uses new a priori information. Simulation results show that the performance of the proposed IDD is very close to that of IDD based on the MAP detector.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39A no.9
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• pp.528-534
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• 2014

In this paper, we propose an iterative detection and decoding scheme for the LDPC coded multiuser uplink massive-MIMO systems. We consider the simple maximal ratio combining (MRC) detector and LDPC decoder. We formulate the soft output of MRC detector and the relation between the extrinsic informations of the detector and decoder. The performance improvement of the proposed iterative detection and decoding scheme is shown by computer simulation.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.43 no.3 s.309
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• pp.8-15
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• 2006

Obstacle detection is an important task for many mobile robot applications. The methods using stereo vision and optical flow are computationally expensive. Therefore, this paper presents a vision-based obstacle detection method using only two view images. The method uses a single passive camera and odometry, performs in real-time. The proposed method is an obstacle detection method using 3D reconstruction from taro views. Processing begins with feature extraction for each input image using Dr. Lowe's SIFT(Scale Invariant Feature Transform) and establish the correspondence of features across input images. Using extrinsic camera rotation and translation matrix which is provided by odometry, we could calculate the 3D position of these corresponding points by triangulation. The results of triangulation are partial 3D reconstruction for obstacles. The proposed method has been tested successfully on an indoor mobile robot and is able to detect obstacles at 75msec.

• Journal of Electrical Engineering and Technology
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• v.13 no.6
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• pp.2530-2544
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• 2018

In this paper, we propose an enhanced LiDAR-camera calibration method that extracts the marker plane from 3D point cloud information. In previous work, we estimated the straight line of each board to obtain the vertex. However, the errors in the point information in relation to the z axis were not considered. These errors are caused by the effects of user selection on the board border. Because of the nature of LiDAR, the point information is separated in the horizontal direction, causing the approximated model of the straight line to be erroneous. In the proposed work, we obtain each vertex by estimating a rectangle from a plane rather than obtaining a point from each straight line in order to obtain a vertex more precisely than the previous study. The advantage of using planes is that it is easier to select the area, and the most point information on the board is available. We demonstrated through experiments that the proposed method could be used to obtain more accurate results compared to the performance of the previous method.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.55 no.4
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• pp.173-180
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• 2006

A key component of autonomous navigation of intelligent home robot is localization and map building with recognized features from the environment. To validate this, accurate measurement of relative location between robot and features is essential. In this paper, we proposed relative localization algorithm based on 3D reconstruction of scale invariant features of two images which are captured from two parallel cameras. We captured two images from parallel cameras which are attached in front of robot and detect scale invariant features in each image using SIFT(scale invariant feature transform). Then, we performed matching for the two image's feature points and got the relative location using 3D reconstruction for the matched points. Stereo camera needs high precision of two camera's extrinsic and matching pixels in two camera image. Because we used two cameras which are different from stereo camera and scale invariant feature point and it's easy to setup the extrinsic parameter. Furthermore, 3D reconstruction does not need any other sensor. And the results can be simultaneously used by obstacle avoidance, map building and localization. We set 20cm the distance between two camera and capture the 3frames per second. The experimental results show :t6cm maximum error in the range of less than 2m and ${\pm}15cm$ maximum error in the range of between 2m and 4m.