• Journal of the Korean Society for Precision Engineering
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• v.16 no.12
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• pp.143-151
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• 1999

The shape of surface micro-crack is very irregular due to nonhomogeneous microstructure but is very important in respect to qualitative estimation of fatigue life. Fractal geomety can quantify the shape of surface mciro-crack. Fractal dimension is measured for surface micro-cracks with coast line and box counting method and estimates cycle ration in Al 2024-T3. The average fractal dimension $D_{favg}$ of surface micro-cracks has 3-parameter weibull distribution and location parameter is nearly constant but shape parameter decreases as cycle ration increases. The fractal dimension by coast line method is measured for individual surface micro-crack but the fractal dimension by box countin method is measured for all the surface micro-cracks under sampling area. Therefore, This paper shows fractal dimension $D_{fb}$ can predict cycle ratio $N/N_f$ more convenient than fractal dimension $D_{favg}$.

• The Journal of Natural Sciences
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• v.8 no.2
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• pp.17-20
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• 1996

We show Equivariant Serre Problem in real algebraic category is true when dimension of the fiber is one i.e., we show an equivariant line bundle over a real representation space is isomorphic to a product bundle of a real representation space and some G-module.

• The KIPS Transactions:PartB
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• v.10B no.7
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• pp.837-846
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• 2003

This paper deals with plain figures on the architectural drawings of apartment. This kind of architectural drawings consist of main walls represented by two parallel bold lines, symbols (door, window, $\cdots$), dimension line, extension line, and dimensions represent various numerical values and characters. This paper suggests a method for recognizing main wall which is a backbone of apartment in an architectural drawing. In this thesis, the following modules are realized : an efficient image barbarization, a removal of thin lines, a vectorization of detected lines, a region bounding for main walls, a calculation of extension lines, a finding main walls based on extension line, and a field expansion by searching other main walls which are linked with the detected main walls. Although the windows between main walls are not represented as main walls, a detection module for the windows is considered during the recognition period. So the windows are found as a part of main wall. An experimental result on 9 different architectural drawings shows 96.5% recognition of main walls and windows, which is about 5.8% higher than that of Karl Tombre.

• Progress in Superconductivity and Cryogenics
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• v.4 no.2
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• pp.11-15
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• 2002

High speed probe for measurement of sin91e flux quantum circuits is comprised of coaxial cables and microstrip lines in order to carry high speed signals without loss. For the impedance matching between coaxial cable and microstrip line, we have determined the dimension of the microstrip line with 50${\Omega}$ impedance by simulation and then have investigated the effect of line width and cross-sectional shape of signal line, dielectric material, thickness of soldering lead at the coaxial-to-microstrip transition Point, and the an91c between dielectric material and end part of the signal line on the characteristics of signal transmission of the microstrip line. From the simulation, we have found that these all parameter's had influenced on the characteristic of signal transmission on the microstrip line and should be reflected in fabricating high speed probe, We have also determined the dimension of coplanar waveguide to fabricate testing sample for performance test of high speed probe.

• Proceedings of the IEEK Conference
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• 2002.06e
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• pp.211-214
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• 2002

Under a continuous manufacturing process, two dimension inspection system causes problems as blurring effect and low resolution and requires position calibration between frames. One dimension inspection system is, therefore, being researched as a substitution. In this paper, we implement mechanism of switching memory and processing data for reasonable one dimension inspection system. Redundant weft image and noise was suggested to be reduced by new method using modified morphological process and masked erosion process. From resulting image, line data and possible error information were obtained and constructed as a structure. Finally, error detecting algorithm was performed with this data structure. Processing time of error detecting was 0.625ms per line in applied system and experiment showed 94.7% of error detecting ability. This method is 20% faster in speed and 2.7% higher in error detecting ability comparing with the present method.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.10
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• pp.822-831
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• 2003

A computer-vision based pipe-inspection algorithm is developed. The algorithm uses the modified Hough transformation and a line-scanning approach to identify the edge line and the radius of the pipe image, from which the eccentricity and dimension of the pipe-end is calculated. Line and circle detection was performed using Laplace operator with input image, which are acquired from the front and side cameras. In order to minimize the memory usage and the processing time, a clustering method with the modified Hough transformation is introduced for line detection. The dimension of inner and outer radius of pipe is calculated by the proposed line-scanning method. The method scans several lines along the X and Y axes, calculating the eccentricity of inner and outer circle, by which pipes with wrong end-shape can be classified and removed.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.99.1-99
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• 2002

In this paper, a computer-vision based pipe-inspection algorithm is developed. The algorithm uses the modified Hough transformation and a line-scanning approach to identify the edge line and radius of the pipe image, from which the eccentricity and dimension of the pipe-end is calculated. Line and circle detection was performed using Laplacian operator with input image which are acquired from the front and side cameras. In order to minimize the memory usage and the processing time, a clustering method with the modified Hough transformation for line detection. The dimension of inner and outer radius of pipe is calculated by proposed line-scanning method. The method scans several lines along t...

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.946-950
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• 2003

In this paper, a computer-vision based pipe shape inspection algorithm is developed. The algorithm uses the modified Hough transformation and a line-scanning approach to identify the edge line and radius of the pipe image, from which the eccentricity and dimension of the pipe-end is calculated. Line and circle detection was performed using Laplace operator with input image, which are acquired from the front and side cameras. In order to minimize the memory usage and the processing time, a clustering method with the modified Hough transformation for line detection. The dimension of inner and outer radius of pipe is calculated by proposed line-scanning method. The method scans several lines along the X and Y axes, calculating the eccentricity of inner and outer circle. by which pipes with wrong end-shape can be classified removed.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.10a
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• pp.521-525
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• 2002

In this paper, a computer-vision based pipe-inspection algorithm is developed. The algorithm uses the modified Hough transformation and a line-scanning approach to identify the edge line and radius of the pipe image, from which the eccentricity and dimension of the pipe-end is calculated. Line and circle detection was performed using Laplace operator with input image, which are acquired from the front and side cameras. In order to minimize the memory usage and the processing time, a clustering method with the modified Hough transformation for line detection. The dimension of inner and outer radius of pipe is calculated by proposed line-scanning method. The method scans several lines along the X and Y axes, calculating the eccentricity of inner and outer circle, by which pipes with wrong end-shape can be classified removed.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.11
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• pp.114-125
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• 1997

This paper presents a method that automatically recognizes dimension sets from the mechanical drawings, and that classifies 6 types dimension sets according to functional purpose. In the proposed method, the object and closed-loop symbols are separated from the character-free drawings. Then object lines and interpretation lines are vectorized. And, after recognizing dimension sets(consistings of arrowhead, shape line, tail lines, extension lines, text-string, and feature control frame), we classify recognized dimension sets as horizontal, vertical, angular, diametral, radial, and leader dimension sets. Finally the proposed method converts classified dimension sets into AutoCAD data by using AutoLisp language. By using the methods of geometric modeling, the proposed method readily recognized and classifies dimension sets from complex drawings. Experimetnal results are presented, which are obtained by applying the proposed method to drawings drawn in compliance with the KS drafting standard.