• Journal of the Korea Society of Computer and Information
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• v.14 no.1
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• pp.99-106
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• 2009

Though edge detection, an important stage that significantly affecting the performance of image recognition, has been given numerous researches on its execution methods, it still remains as difficult problem and it is one of the components for image recognition applications while it is not the only way to identify an object or track a specific area. This paper, unlike gradient operator using edge detection method, found out edge pixel by referring to 2 neighboring pixels information in binary image and comparing them with pre-defined 4 edge pixels pattern, and detected binary image edge by determining the direction of the next edge detection exploring pixel and proposed method to detect binary image edge by repeating step of edge detection to detect another area edge. When recognizing image, if edge is detected with the use of gradient operator, thinning process, the stage next to edge detection, can be omitted, and with the edge detection algorithm executing time reduced compared with existing area edge tracing method, the entire image recognizing time can be reduced by applying real-time image recognizing system.

• Journal of Welding and Joining
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• v.24 no.4
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• pp.32-38
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• 2006

The objective of present research works is to investigate the effects of process parameters, including the power of laser, cutting speed, material thickness, and the edge angle, on the melted area in the sharp edge of the cut material fur the case of cutting of a low carbon steel sheet using high-power CW Nd:YAG laser. In order to investigate the influence of edge angle and size of loop on the melted area in the sharp edge, angular cutting tests and loop cutting tests have been carried out. From the results of angular cutting tests, the relationship between the edge angle and the melted area has been obtained. The results of the experiments have been shown that the melted area is rapidly reduced from $120^{\circ}$ of the edge angle and the melted area is nearly zero at $150^{\circ}$ of the edge angle. Through the results of loop cutting experiments, the relationship between the cutting angle on the melted area in the edge according to the size of loop have been obtained. In addition, it has been shown that a proper size of loop is nearly 3 mm as the corner angle is greater than $90^{\circ}$ and 5 mm as the comer angle is less than $90^{\circ}$. The results of above experiments will be reflected on the knowledge base to generate optimal cutting path of the laser.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2092-2095
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• 2003

In this paper, we propose an algorithm to extract rectangular object area such 3s Data Matrix two-dimensional barcode using edge tracing-based linear feature detection. Hough transform is usually employed to detect lines of edge map. However, it requires parametric image space, and does not find the location of end points of the detected lines. Our algorithm detects end points of the detected lines using edge tracing and extracts object area using its shape information.

• Journal of Technologic Dentistry
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• v.18 no.1
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• pp.117-127
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• 1996

This study was aimed to help the construction of esthetic dental prosthesis by investigation of the factors affecting on the atterition position and attrition angle of maxillary lateral incisors. Therefore 197 complete cast of maxillary and mandibualar extracted form the student of K. college were subjected for this study, and result throught the study are as follows. 1. None attrite rate of the maxiilary right lateral incisors was about 16.2% and that of the maxillary left lateral incisors was about 32.4% of examined teeth. 2. Throught mesiodistal attrition area 1) It showed that right lateral incisors was the most frequence in attrition of mesial area of incisal edge, and left lateral incisors was the most frequence in attrition of mesial and mid area of incisal edge. 2) It showed that square type arch was more frequence in attrition of all incisal edge, and ovoid type arch was more frequence in the attrition of mid area of incisal edge, and ovoid type arch was more frequence in the attrition of mid area of incisal edge, and taper type arch was more frequence in the attrition of mesial area of incisal edge than it of average frequence of right lateral incisors, by dental arch type. 3) It showed that square type arch was more frequence in the attrition of all area and mid area of incisal edge, and ovoid type arch was more frequence in the attrition of mid area of incisal edge, and taper type arch was more frequence in the attrition of mesial and distal area of incisal edge than it of average frequence of left lateral incisal, by dental arch type. 4) Sex, vertical overlap, horizontal overlap, incisal guide angle, did not affect significantly to throughout mesiodistal attrition, statistically 3. Throughout labiolingual attrition quantity. 1) It showed that throughout labiolingual attrition quantity was more attrition in order of taper type arch < ovoid type arch < square type arch, by dental arch type. 2) It showed that throughout labiolingual attrition qauntity was more attrition when the length of horizontal overlap is shorter than it of other, by horizontal overlap. 3) Throughout labiolingual attrition quantity of right lateral incisors showed that male was more attrition than it of female. 4) Vertical overlap, incisal guide angle, sex on left lateral incisors did not affect significantly to throughout labiolingual attrition, statistically. 4. Attrition angle 1) It showed that average attrition anlge of right lateral incisors were $30{\pm}13.02$ degree, and it of left lateral incisors were $26{\pm}13.37$ degree. 2) It showed that taper type arch have a bigger attrition angle than it of average of lateral incisors, and square tape arch have a smaller attrition angle than it of average of lateral incisors, by dental arch type. 3) It showed that horizontal overlap of 2.1mm above have a bigger attrition angle than it of average, by horizontal overlap. 4) It showed that female have a bigger attrition angle it of male, by sex.

• Journal of Korean Society of Rural Planning
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• v.21 no.4
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• pp.27-33
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• 2015

Forest ecosystem is considered as an important stepping stone to minimize the impact of climate change. However, the rapid urbanization has caused fragmentation of forest ecosystem. The fragmentation of forest patch results in edge effect which brings about adverse impacts on forest function and structure. Degradation of forest ecosystem decreases carbon sequestration because edge effect reduces productivity. Therefore, we analyzed the impact of forest edge effect on forest ecosystem carbon stock change in Seongnam-si, Gyeonggi-do. We used connectivity analysis to determine forest edge and core area. The field study sites were selected with considering forest age, density, class and soil type. Secondly, forest carbon stock was calculated with allometric equation. The soil carbon stock was derived from Walkely-Black method. Lastly, Mann-Whitney test was conducted to validate differences between carbon stock in edge and core area. As a result of study, the connectivity analysis was effective to determine forest edge and core. The core and edge of forest patch showed different composition of tree species and soil properties. Carbon stock per tree in the edge area was lower than that in the core area. However, the difference of soil organic carbon content between the edge and core were relatively small. This assessment can be applied for the conservation of forest patch as well as quantitative assessment on the forest carbon stock change caused by fragmentation.

• IEMEK Journal of Embedded Systems and Applications
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• v.17 no.2
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• pp.77-83
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• 2022

In this paper, the two-stage object detection approach is proposed to implement a deep learning-based label inspection system on edge computing environments. Since the label printed on the products during the production process contains important information related to the product, it is significantly to check the label information is correct. The proposed system uses the lightweight deep learning model that able to employ in the low-performance edge computing devices, and the two-stage object detection approach is applied to compensate for the low accuracy relatively. The proposed Two-Stage object detection approach consists of two object detection networks, Label Area Detection Network and Character Detection Network. Label Area Detection Network finds the label area in the product image, and Character Detection Network detects the words in the label area. Using this approach, we can detect characters precise even with a lightweight deep learning models. The SF-YOLO model applied in the proposed system is the YOLO-based lightweight object detection network designed for edge computing devices. This model showed up to 2 times faster processing time and a considerable improvement in accuracy, compared to other YOLO-based lightweight models such as YOLOv3-tiny and YOLOv4-tiny. Also since the amount of computation is low, it can be easily applied in edge computing environments.

• The Korean Journal of Applied Statistics
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• v.25 no.6
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• pp.1019-1026
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• 2012

This paper presents a method for the identification of "edge observations" located on a boundary area constructed by a truncation variable as well as for the identification of outliers and the after fit of multivariate skew $t$-distribution(MST) to asymmetric data. The detection of edge observation is important in data analysis because it provides information on a certain critical area in observation space. The proposed method is applied to an Australian Institute of Sport(AIS) dataset that is well known for asymmetry in data space.

• Journal of the Korea Society of Computer and Information
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• v.22 no.7
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• pp.47-54
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• 2017

Recently, correlation filter based trackers have shown excellent tracking performance and computational efficiency. In order to enhance tracking performance in the correlation filter based tracker, search area which is image patch for finding target must include target. In this paper, two methods to discriminatively represent target in the search area are proposed. Firstly, search area location is estimated using pyramidal Lucas-Kanade algorithm. By estimating search area location before filtering, fast motion target can be included in the search area. Secondly, we investigate multi-channel Local Edge Pattern(LEP) which is insensitive to illumination and noise variation. Qualitative and quantitative experiments are performed with eight dataset, which includes ground truth. In comparison with method without search area estimation, our approach retain tracking for the fast motion target. Additionally, the proposed multi-channel LEP improves discriminative performance compare to existing features.

• Proceedings of the Korean Society For Composite Materials Conference
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• 2001.05a
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• pp.78-82
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• 2001

Impact behaviors of Aluminum Honeycombs Sandwich Panel(AHSP) by drop weight test were investigated. Two types of specimens with 1/2" and 1/4" cell size were tested by two impactors which are weight of $5.25\textrm{kg}_{\textrm{f}}$ and $11.9\textrm{kg}_{\textrm{f}}$. Parametric studies were achieved including the impactor weight and impact sites which consist face, long-edge, short-edge, and point of the specimen. Face one of impact sites was the strongest and short-edge one of impact sites was the weakest. The damaged area of AHSP was enlarged with the increase of impactor weight that is equal to impact energy. After 3 point bending test, fracture modes of AHSP were analyzed with AE counts. Lower facesheet was fractured in the long-edge direction and then separated between facesheet and core. In the short-edge direction after core wrinkled, lower facesheet tear occurred. Impact behavior by FE analysis were increased localized damage in fast velocity because the faster velocity of the impact was, the smaller the stress of core was. Consequently, impactor weight had an effect on widely damaged area, while the impact velocity was caused on the localized damaged area.aged area.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.10
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• pp.2541-2551
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• 1996

Human visual systems are sensitive to noise on the flat intensity area. But it becomes less sensitive on the edge area. Recently, many types of spatially adaptive image restoration methods have been proposed, which employ the above mentioned huan visual characteristics. The present paper presents an adaptive image restoration method, which increases sharpness of the edge region, and smooths noise on the flat intensity area. For edge detection, the proposed method uses the visibility function based on the local variance on each pixel. And it adaptively changes the regularization parameter. More specifically, the image to be restored is divided into a number of steps from the flat area to the edge regio, and then restored by using the finite impulse response constrained least squares filter.