• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.5
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• pp.851-856
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• 2017

Research on the edge isolation process of typical polycrystalline silicon solar cells was carried out using laser scribing equipment. The voltage-current characteristics of the solar cell before and after laser scribing were analyzed using a solar simulator. Current density and efficiency increased as the fill factor of the solar cell remained constant after the laser scribing process. The efficiency of the solar cell can be increased in a short time by the edge isolation process performed via a laser scribing process. The polycrystalline silicon solar cell was made into a series electrode, and the efficiency of the solar cell increased because the width of the solar cell was narrowed and the active region was widened by the laser scribing process.

• Proceedings of the KOSOMBE Conference
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• v.1992 no.05
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• pp.98-101
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• 1992

A new algorithm using entropy operater with variable threshold for edge detection from 2D short axis echocardiogram is proposed. This algorithm is based on brightness, mean value of entropy, and variance value of entropy in local window. This algorithm is effective to process complex echocardiographic images due to the speckle noises, echo dropouts and characteristics of 2D echocardiographic constituents. Results of computer simulation of the proposed algorithm show excellent edge detection performance comparing wi th other edge operators which have been applied to 2D echocardiograms.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1995.10a
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• pp.60-63
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• 1995

The behavior of the work materials in the chip-tool interface in extremely high strain rates and temperatures is more that of viscous liquids than that of normal solid metals. In these circumstances the principles of fluid mechanics can be invoked to describe the metal flow in the neighborhood of the cutting edge. In the present paper an Eulerian finite element model is presented that simulates metal flow in the vicinity of the cutting edge when machining a low carbon steel with carbide cutting tool. The work material is assumed to obey visco-plastic (Bingham solid) constitutive law and Von Mises criterion. Heat generation is included in the model, assuming adiabatic conditions within each element. the mechanical and thermal properties of the work material are accepted to vary with the temperature. The model is based on the virtual work-stream function formulation, emphasis is given on analyzing the formation of the stagnant metal zone ahead of the cutting edge. The model predicts flow field characteristics such as material velocity effective stress and strain-rate distributions as well as built-up layer configuration

• Progress in Superconductivity
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• v.3 no.1
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• pp.65-69
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• 2001

We measured the transport properties of$ YBa_2$$Cu_3$$O_{x}$ ramp-edge junction fabricated with interface-engineered barrier. The current-voltage characteristics show a typical resistively-shunted junction like behavior Voltage noise measurement revealed that the main source of the 1/f noise is the critical current and resistance fluctuations. The analysis of the noise data showed that the critical current fluctuations increase with temperature, whereas the resistance fluctuations are almost constant, and both fluctuations are almost correlated. The smaller magnitude of the critical current and resistance fluctuations seems to result from the columnar-deflects.s.

• Journal of Sensor Science and Technology
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• v.14 no.3
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• pp.191-197
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• 2005

When fabricating a vision chip, we should consider the noise problem, such as the fixed pattern noise(FPN) due to the process variation. In this paper, we propose an edge-detection circuit based on biological retina using the offset-free column readout circuit to reduce the FPN occurring in the photo-detector. The offset-free column readout circuit consists of one source follower, one capacitor and five transmission gates. As a result, it is simpler and smaller than a general correlated double sampling(CDS) circuit. A vision chip for edge detection has been designed and fabricated using $0.35\;{\mu}m$ 2-poly 4-metal CMOS technology, and its output characteristics have been investigated.

• Journal of the Korea Furniture Society
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• v.11 no.1
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• pp.61-68
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• 2000

This study was carried out to investigate the effect of grain and veneer thickness on drying rate, required energy consumption, and drying defects such as checking, end waving, and burning during a far-infrared radiation drying process of decorative veneers of hard maple and beech. Most of the veneer could be dried from green to in-use moisture content within 30 to 360 seconds. The drying rates were significantly affected by veneer thickness, but there was little difference between edge-and flat-sliced veneers. The formation of checking during drying test was none or very slight. The percentages of the veneers defected by checks were higher in the flat-sliced veneers than in the edge-sliced veneers. The maximum end wavinesses in the flat-sliced veneers were almost 1.6 to 3 times larger than that in the edge-sliced veneers. All veneers were fee from burned marks during drying test.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.11
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• pp.1424-1433
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• 1995

The edge detection process serves to simplify the analysis of images by drastically reducing the amount of data to be processed, while preserving useful structural informations about object boundaries. At first, this paper proposes an edge detection algorithm to reduce the amount of computation. The gradients of pixels are calculated by using first order differential equations on the pixels with even rows and even columns or odd rows and odd columns, and they are compared with a threshold to decide edges. As a result, the computational complexity is reduced to one third or one forth compared with the provious ones. To enhance the accuracy of edge detection, a method with the adaptive threshold for each pixel window which is calculated by using characteristic values is proposed. In this case, the performance can be improved since the threshold is calculated properly for each window according to the local characteristics of corresponding window.

• Journal of Advanced Marine Engineering and Technology
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• v.29 no.2
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• pp.217-224
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• 2005

A new roof edge detection method based on multi level scales of wavelet function is proposed in this paper roof edge and its direction are obtained in this new methods at one time. Besides. scale characteristics of detecting roof edge is analyzed. And a few new methods on fingerprint image pre-processing are described. A method segmenting foreground/background of fingerprint images is proposed, in which Prior estimation of direction field is not required any more. A segmentation method based on multi-scale roof edges is implemented. and the valid scale range of the method is defined. too. And the method is used to segment ridges and valleys in fingerprint images simultaneously The exact direction fields made up of the direction of each point in ridges can be obtained when detecting ridges exactly based on the roof edge detector, in comparison with the traditional coarse estimation of direction fields. Obviously. it will establish a solid foundation for the sequent fingerprint identification.

• Transactions on Control, Automation and Systems Engineering
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• v.3 no.4
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• pp.283-288
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• 2001

In this paper, we proposed a method for extracting facial characteristics of human being in an image. Given a pair of gray level sample images taken with and without human being, the face of human being is segmented from the image. Noise in the input images is removed with the help of Gaussian filters. Edge maps are found of the two input images. The binary edge differential image is obtained from the difference of the two input edge maps. A mask for face detection is made from the process of erosion followed by dilation on the resulting binary edge differential image. This mask is used to extract the human being from the two input image sequences. Features of face are extracted from the segmented image. An effective recognition system using the discrete wave let transform (DWT) is used for recognition. For extracting the facial features, such as eyebrows, eyes, nose and mouth, edge detector is applied on the segmented face image. The area of eye and the center of face are found from horizontal and vertical components of the edge map of the segmented image. other facial features are obtained from edge information of the image. The characteristic vectors are extrated from DWT of the segmented face image. These characteristic vectors are normalized between +1 and -1, and are used as input vectors for the neural network. Simulation results show recognition rate of 100% on the learned system, and about 92% on the test images.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.8
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• pp.1867-1873
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• 2015

Edge detection is one of image processing techniques applied for a variety of purposes in a number of areas and it is used as a necessary pretreatment process in most applications. In the conventional edge detection methods, there are Sobel, Prewitt, Roberts and LoG, etc using a fixed weights mask. Since conventional edge detection methods apply the images to the fixed weights mask, the edge detection characteristics appear somewhat insufficient. Therefore in this study, an algorithm for detecting the edge is proposed by applying the cross mask based on the center pixel and up, down, left and right mask based on the surrounding pixels of center pixel in order to solve these problems. And in order to assess the performance of proposed algorithm, it was compared with a conventional Sobel, Roberts, Prewitt and LoG edge detection methods.