• 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.17 no.9
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• pp.2199-2205
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• 2013

In modern society the image processing has been applied to various digital devices such as smartphone, digital camera, and digital TV. In the field of image processing the edge detection is one of the important parts in the image processing procedure. The image edge means point that the pixel value is changed between background and object rapidly, and includes the important information such as magnitude, location, and orientation. The performance of the existing edge detection method is insufficient for the image degraded by AWGN(additive white Gaussian noise) because it detects edges by using small weighted masks. Therefore, in this paper, to detect edge in AWGN environment effectively, we proposed an algorithm that detects edge as calculated gradient of sorting vector which is transformed by estimated mask from new pixel according to each region.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1315-1318
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• 2004

Based on fuzzy 2-mean classification and template matching method, we propose a new algorithm to detect the edges of an image. In the algorithm, fuzzy 2-mean classification can classify all pixels in the mask into two clusters whatever the mask in the dark or light region; and template matching not only determines the edge's direction, but also thins the detected edge by a set of inference rules and, by the way, reduces the impulse noises.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.921-923
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• 2015

Edge in the image includes the size, direction and location of objects. The existing detection methods for detecting this edge is a method using Sobel, Prewitt, Roberts and Laplacian, etc. These existing methods use a fixed weighted mask in order to detect the edge and have somewhat insufficient edge detection characteristics. Therefore in this paper, an algorithm that detects the edge by applying the grey level converting function according to the pixel distribution of local mask was proposed.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.100-103
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• 2014

Currently, edge detection is utilized in various areas. Edge detection is the preprocessing process for image processing in general, and this is a technology that is considered essential for image processing. According, research on this subject is carried out incessantly. Edge has important image related elements such as size, direction and location of the object of an image. Numerous methods were proposed for the detection. Among them, the representative methods are Sobel, Prewitt, Roberts, Laplacian. However, these existing methods are rather lacking when it comes to the edge detection characteristics in case of the image with mixed noise. Therefore, this study presented edge detection method that utilizes median and average values for the elements depending on the size and location of local mask.

• Journal of the korean academy of Pediatric Dentistry
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• v.28 no.4
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• pp.643-648
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• 2001

Class III malocclusion usually becomes manifested at a very early age, most typically evidenced clinically by the appearance of either an edge-to-edge incisor relationship or an anterior crossbite. Anterior crossbite, by it-self, retards growth of maxilla, and accelerates growth of mandible. So, treatment should be started as early as the patient cooperates, removing any factors or forces that inhibit growth and development in the same physiologic maxillary displacement direction. The facial mask is effective in most developing Class III patients, because the appliance system affects virtually all areas contributing to a Class III malocclusion. Thus, the facial mask can be applied to most developing Class If cases regardless of the specific etiology. In these cases, the results were followed. Anterior crossbite was corrected by anterior movement of maxilla and downward backward rotation of mandible and simultaneously, lower facial height was increased. So, it can be concluded that the facial mask is effective in treating growing patients with a deficient maxilla.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.3
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• pp.735-741
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• 2014

Edge in images appears when a great difference shows up in light and shade between pixels and includes data of the subject's size, location direction and etc. The edge is generally detected by the methods such as Sobel, Roberts, Laplacian, LoG(Laplacian of Gaussian) and etc. However, in AWGN(additive white Gaussian noise) added images, quality of the edge becomes slightly uncertain. Therefore, this paper proposed edge detection algorithm using modified mask of weighting to improve the quality of the existing methods. And in order to verify the performance efficiency of the proposed method, processed image and PFOM(Pratt's figure of merit) has been used as valuation standard for a comparison with the existing methods.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.11
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• pp.2779-2785
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• 2014

Edge Detection is a technique that obtains the particular information of the image using the brightness variation of pixel values and utilized for preprocessing in various image processing sectors. The conventional edge detection methods such as Sobel, Prewitt and Roberts are processed by applying the same weighted value to the entire pixels regardless of pixel distrbution and provides somewhat insufficient edge detection results. therefore, this paper has proposed an edge detection method considering the direction and magnitute of pixels by applying a modified directional mask.

• International Journal of Precision Engineering and Manufacturing
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• v.4 no.1
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• pp.23-29
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• 2003

Stencil is used normally as a mask for solder pasting on pad of a printed circuit board (PCB). The objective of this study is to develop a stencil cutting system and determine the optimal conditions to make good-quality stencil by using a Nd:YAG laser. The effects of process parameters such as laser power, type of mask, gas pressure, cutting speed and pulse duration on the cut edge quality were investigated. In order to analyze the cut surface characteristics (roughness, kerfwidth, dross) optical microscopy, SEM microscopy and roughness measurements were used. As a result, the optimal conditions of cutting process parameters were determined, and the practical feasibility of the proposed system was also examined by using a commercial Gerber file for PCB stencil manufacturing.

• Laser Solutions
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• v.4 no.2
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• pp.47-57
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• 2001

This study deals with the laser cutting of stencil for the PCB. The most important aim of this study is to determine optimal conditions which make good-qualify stencil in Nd:YAG laser cutting. We made an experiment according to various variables (power. type of mask. gas pressure, cutting speed, and pulse width) and analyzed the cutting characteristics (surface roughness, kerf width. dross) . Each variable has optimal value for good-qualify cut edge under fixed condition. And neural network after learning experimental data with a million time iteration could predict surface roughness of cut edge under arbitrary condition approximately.