• Proceedings of the KIEE Conference
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• 1999.11d
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• pp.1117-1119
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• 1999

An edge finite element method is applied to calculate the field distribution of a coupled waveguide structure. We compares a node based finite element method with the edge element one. For 2-d eigenvalue problems of waveguide structures, the former generates spurious eigenmodes, but the latter dose not. Using an simple rectangular waveguide, we implement both methods to obtain some results of field computation in waveguide. The paper shows that the finite element method using edge elements succeeds in suppressing spurious solutions.

• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.3
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• pp.105-112
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• 1989

A new simple edge-based segmentation method composed of edge tracing, region filling, and post processing is proposed. Solving so called the small gap problem common to most of edge-based methods, this method segments images so completely as to be suitable for image coding. Experimental results show that our methods has much less (1/3) computation time than Perkins' one, and its reconstructed images is good on visual perception.

• 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 KIISE:Software and Applications
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• v.32 no.2
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• pp.85-98
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• 2005

Recently, a lot of researches about mobile vision using Personal Digital Assistant(PDA) has been attempted. Many CPUs for PDA are integer CPUs, which have no floating-computation component. It results in slow computation of the algorithms peformed by vision system or image processing, which have much floating-computation. In this paper, in order to resolve this weakness, we propose the Client(PDA)/server(PC) architecture which is connected to each other with a wireless LAN, and we construct the system with pipelining processing using two CPUs of the Client(PDA) and the Server(PC) in image sequence. The Client(PDA) extracts tentative text regions using Edge Density(ED). The Server(PC) uses both the Multi-1.aver Perceptron(MLP)-based texture classifier and Connected Component(CC)-based filtering for a definite text extraction based on the Client(PDA)'s tentativel99-y extracted results. The proposed method leads to not only efficient text extraction by using both the MLP and the CC, but also fast running time using Client(PDA)/server(PC) architecture with the pipelining processing.

• 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.

• Journal of Information Processing Systems
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• v.20 no.2
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• pp.226-238
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• 2024

Recently, multi-access edge computing (MEC) has emerged as a promising technology to alleviate the computing burden of vehicular terminals and efficiently facilitate vehicular applications. The vehicle can improve the quality of experience of applications by offloading their tasks to MEC servers. However, channel conditions are time-varying due to channel interference among vehicles, and path loss is time-varying due to the mobility of vehicles. The task arrival of vehicles is also stochastic. Therefore, it is difficult to determine an optimal offloading with resource allocation decision in the dynamic MEC system because offloading is affected by wireless data transmission. In this paper, we study computation offloading with resource allocation in the dynamic MEC system. The objective is to minimize power consumption and maximize throughput while meeting the delay constraints of tasks. Therefore, it allocates resources for local execution and transmission power for offloading. We define the problem as a Markov decision process, and propose an offloading method using deep reinforcement learning named deep deterministic policy gradient. Simulation shows that, compared with existing methods, the proposed method outperforms in terms of throughput and satisfaction of delay constraints.

• Journal of Adhesion and Interface
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• v.6 no.1
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• pp.1-6
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• 2005

The high accurate simulation of very thin glue layers based on the finite element method is still connected to many problems which result from the necessity to construct a complicated mesh of essentially different sizes of elements. This can lead to a loss of accuracy, unstable calculations and even loss of convergence. However, the implementation of special transmission elements along the glue ling and special edge-elements in the near-edge region would lead to a dramatic decrease of number of finite elements in the mesh and thus, prevent unsatisfactory phenomena in numerical analysis and extensive computation time. The theoretical basis for such special elements is the knowledge about appropriate transmission conditions and the edge effects near the free boundary of the adhesive layer. Therefore, recently proposed so-called non-classical transmission conditions and the behavior near the free edge are investigated in the context of the single-lap tensile-shear test of adhesive technology.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.5 no.2
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• pp.57-62
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• 1996

Basically, the idea underlying most edge-detection technique is the computation of a local derivative operator used for edge detection in gray level image. This concept can be easily illustrated with the aid of object which shows an image of a simple lilght on a dark background, Using the gray level profile along a horizontal scan line of the image. the first and second derivatives of it were acquired. This study is to develop an automatic measuring system based on the digital image processing which can be applied to the real time measurement of the characteristics of the ultra-thin thickness. The experimental results indicate that the developed automatic inspection can be applied in real situation.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.05a
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• pp.842-847
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• 2005

Although there are many applications of Euclidean Voronoi diagram for spheres in a 3D space in various disciplines from sciences and engineering, it has not been studied as much as it deserves. In this paper, we present an edge-tracing algorithm to compute the Euclidean Voronoi diagram of 3-dimensional spheres in O(mn) in the worst-case, where m is the number of edges of Voronoi diagram and n is the number of spheres. After building blocks for the algorithm, we show an example of Voronoi diagram for atoms using actual protein data and discuss its applications for protein analysis.

• Electrical & Electronic Materials
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• v.9 no.8
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• pp.783-788
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• 1996

In this paper, the high-$T_c$ , superconductor (HTS) microstrip patch antenna which is directly coupled to a microstrip transmission line is designed and the numerical solution which evaluate near electromagnetic field of HTS antenna is presented. This solution uses the interpolation function with the vector edge triangular element. The advantage of this element is the elimination of spurious solutions attributed to the lack of enforcement of the divergence condition. The results of this method have a good agreement with $TM_10$ mode in HTS microstrip patch antenna and show that the computation of resonant length considering the fringing capacitance effect at radiating edge are proper.