• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.22 no.12
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• pp.1084-1088
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• 2009

The measurement of dynamic stagger in electric railways is one of the key test parameters to increase speed and maintain safety in electric railways. This paper is introduces a non-contact optical-based measuring instrument of a catenary system in electric railways. The instrument is implemented by utilizing a CCD (Charge Coupled Device) camera installed on the roof of a vehicle for vision acquisition and image processing techniques including the Canny edge detector and the Hough transform to detect contact wires and calculate dynamic stagger. To check the validity of our approach for the intended application, we measured stagger of a overhead wire of a Korea Tilting Train (TTX). The non-contact optical-based measurement system proposed in this paper performs real-time stagger measurement of an activated high-voltage contact wire. By results of this paper, the instrument should be applied to assess performance and reliability of newly developed electric railway vehicles.

• Progress in Superconductivity
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• v.4 no.2
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• pp.109-113
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• 2003

We have developed a planar-type single layer second-order $high-T_{c}$ SQUID gradiometer, which can detect the $d^2$$B_{z/}$dxdy of the second-order field gradient. This SQUID gradiometer consists of four-way 'clover-leaf' pick-up loops and is coupled directly to a 4-junction dc SQUID in such a way that the coupling polarity of the two diagonal loops is opposite to that of the other two loops. The pickup loops are intrinsically balanced for both uniform field and the 1 st-order field gradient. The $YBa_2$$Cu_3$$O_{7}$ thin film was made by pulsed laser deposition method on $SrTiO_3$ single crystal substrate and patterned by photolithography with Ar ion milling technique. Response of this gradiometer was tested for both uniform field and the 2nd-order field gradient. Details of the design, fabrication, and results will be discussed.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.11
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• pp.1879-1886
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• 2016

In this paper, we propose a real-time recognition algorithm of lanes, stop lines and speed bumps on roads for autonomous vehicles. First, we generate a top-view using the image transmitted from a camera that is installed to see the front of a vehicle. To speed up the processing, we simplify the mapping algorithm in constructing a top-view wherein the region of interest (ROI) is concerned. The features of lanes, stop lines and speed bumps, which are composed of lines, are searched in the edge image of the top-view, then followed by labeling and clustering specialized to detect straight lines. The width of lines, distances from the center of a vehicle, and curvature of each cluster are considered to select final candidates. We verify the proposed algorithm on real roads using the commercial car (KIA K7) which is converted into an autonomous vehicle.

• Proceedings of the KOSOMBE Conference
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• v.1990 no.05
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• pp.43-46
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• 1990

Modern society is prevailed a lot of allergies. So, the allergy test is very important. There are many kinds of allergy test. A doctor usually uses skin allergy test among many allergy tests. However, little standadization and objectivity of grading-standard has been established in the skin allergy test. A measurement of the reaction area has been a major objective to perform skin allergy test. Recently, a doctor's method is to measure the reaction area after drawing a line that represents the reaction area on the skin. But this method differs slightly from the real reaction area and individual doctor's measurement is different, because the edge of the reaction area is obscure. In this paper, we propose a algorithm which is able to detect vague edges using the fuzzy set. The algorithm that detects the line and curve is proposed first. Here, the maximum value is calculated by comparing the membership function of the line and curve seperately. We also encode the direction of the line and curve by using 8-direction code. Then, we calculate the reaction area by measuring the pixels which are inside the reaction area. And finally the Allergy grade is decided by grading-standard, and we accomplish faster, the 80re accurate and objective allergy grade decision.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.1
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• pp.127-135
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• 1995

The diffusion neural network forms a Gaussian distribution by transferring an excitation to the surround. A DOG(difference of two Gaussians) is obtained by the diffusion neural network. This type of the DOG, which can detect the intensity changes of an image, has the same shape as a LOG(Laplacian of a Gaussian:${\Delta}^2$G) and narrow band pass characteristics. In this paper we show that another type of the DOG which has a very narrow Gaussian for the excitatory and a very wide Gaussian for the inhibitory, can be formed by the diffusion process of this network, This type of the DOG has a wide band width in spatial frequency domain and can be used efficiently in detecting special type of edges.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.04a
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• pp.132-139
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• 2008

The blade vibration problem of bladed disk is the most critical subject to consider since it directly affects the stable performance of the engine as well as life of the engine. Especially, due to complicated vibration pattern of the bladed disk, more effort was required for vibration analysis and test. The research of measuring the vibration of the bladed disk, using NSMS(Non-intrusive stress measurement) instead of Aeromechanics testing method requiring slip ring or telemetry system with strain gauge, was successful. These testing can report the actual stresses seen on the blades; detect synchronous resonances that are the source of high cycle fatigue (HCF) in blades; measure individual blade mis-tuning and coupled resonances in bladed disks. In order to minimize the error being created due to heat expansion, the tip timing sensor is installed parallel to the blade trailing edge, yielding optimal result. Also, when working on finite element analysis, the whole bladed disk has gone through three-dimensional analysis, evaluating the family mode. The result of the analysis matched well with the test result.

• The Bulletin of The Korean Astronomical Society
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• v.37 no.1
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• pp.40.1-40.1
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• 2012

In the hierarchical universe, galaxy merger is predicted to be frequent, and thus it is an important element for understanding galaxy evolution. In particular, star formation is greatly enhanced during the merger. The aim of this study is to understand the position and rate change of star formation caused by equal-mass edge-on mergers. We use the GADGET2- N-body/SPH code, and fully consider gas cooling, star formation, and supernova feedback. We show the star formation rate (SFR), and the magnitude and color evolution of the merger remnants for 18 different configurations varying orbit elements and inclinations of host galaxies against orbit planes. Then we construct the mock images of the remnants and investigate on how equal-mass galaxy merger affects the SFR and color/magnitude evolution while considering dust reddening. We conclude that over 90% mass of SF in equal-mass merger is in the central region. SF in tidal feature involves a small fraction of new stars and thus is difficult to detect unless deep imaging is performed. Around 55 ${\pm}$ 5 percent of gas turns into stars until the final coalescence which typically corresponds to 0.8, 1.2, and 2.5 Gyr for direct, parabolic, and elliptical orbit, respectively. This result is roughly consistent with Cox et al. 2000. We plan to implement this result into semi-analytic model of galaxy formation. Caveats and future work on merging conditions are discussed.

• IEMEK Journal of Embedded Systems and Applications
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• v.11 no.3
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• pp.163-171
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• 2016

Lane detection is a widely researched topic. Although simple road detection is easily achieved by previous methods, lane detection becomes very difficult in several complex cases involving noisy edges. To address this, we use a Convolution neural network (CNN) for image enhancement. CNN is a deep learning method that has been very successfully applied in object detection and recognition. In this paper, we introduce a robust lane detection method based on a CNN combined with random sample consensus (RANSAC) algorithm. Initially, we calculate edges in an image using a hat shaped kernel, then we detect lanes using the CNN combined with the RANSAC. In the training process of the CNN, input data consists of edge images and target data is images that have real white color lanes on an otherwise black background. The CNN structure consists of 8 layers with 3 convolutional layers, 2 subsampling layers and multi-layer perceptron (MLP) of 3 fully-connected layers. Convolutional and subsampling layers are hierarchically arranged to form a deep structure. Our proposed lane detection algorithm successfully eliminates noise lines and was found to perform better than other formal line detection algorithms such as RANSAC

• Korean Journal of Optics and Photonics
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• v.14 no.1
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• pp.44-50
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• 2003

This paper describes the thermal effect at Nd:YAG using a laser-diode side-pumping. To detect the depolarization loss and the retardation caused by the thermal effect, a λ/4 plate is inserted between the polarizer and the Nd:YAG laser material. Using a CCD has allowed detection of the variation of the beam pattern that could analyze the change of the refractive index of the Nd:YAG laser material by the thermal effect. Through the change of the probe beam power, we know that 21% of the pumping power was converted into heat in the material. The depolarization loss was 24.7% under a temperature of $25^{\circ}C$ of the laser material and a pumping power of 15 W. The inhomogeneous distribution showed that the retardation angle was 7$^{\circ}$ in the center of the material and 19$^{\circ}$ on the edge of it. It is confirmed that the thermal effect is analyzed at the each point of the laser material and it suggests an effective method to reduce the thermal effect on the LD side-pumped laser material.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.12
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• pp.5073-5086
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• 2015

The rock fracture detection by image analysis is significant for fracture measurement and assessment engineering. The paper proposes a novel image segmentation algorithm for the centerline tracing of a rock fracture based on Hessian Matrix at Multi-scales and Steger algorithm. A traditional fracture detection method, which does edge detection first, then makes image binarization, and finally performs noise removal and fracture gap linking, is difficult for images of rough rock surfaces. To overcome the problem, the new algorithm extracts the centerlines directly from a gray level image. It includes three steps: (1) Hessian Matrix and Frangi filter are adopted to enhance the curvilinear structures, then after image binarization, the spurious-fractures and noise are removed by synthesizing the area, circularity and rectangularity; (2) On the binary image, Steger algorithm is used to detect fracture centerline points, then the centerline points or segments are linked according to the gap distance and the angle differences; and (3) Based on the above centerline detection roughly, the centerline points are searched in the original image in a local window along the direction perpendicular to the normal of the centerline, then these points are linked. A number of rock fracture images have been tested, and the testing results show that compared to other traditional algorithms, the proposed algorithm can extract rock fracture centerlines accurately.