• The Journal of Korean Institute of Communications and Information Sciences
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• v.13 no.5
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• pp.379-389
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• 1988

In this paper, an algorithm for obtaining 2-state switching failure function and a terminal pair reliability evaluation method in a communication network are proposed. The communication network is modeled by a graph. By using the sequence of matrix transformations for the graph, minimal cut-set matrix representing all minimal cut-sets which completely interrupt the communication path is determined and 2-state switching failure function is then obtained from the minimal cut-set matrix. The terminal pari reliability of the communication network is evaluated by corresponding the random variables to 2-state switching failure function. Illustrative examples are provided to demonstrate the algorithm. A computer program evaluating the terminal pair reliability in a complex and large network has also been developed.

• International Journal of Contents
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• v.9 no.1
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• pp.6-10
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• 2013

Foreground estimation in object segmentation has been an important issue for last few decades. In this paper we propose a GrabCut based automatic foreground estimation method using block clustering. GrabCut is one of popular algorithms for image segmentation in 2D image. However GrabCut is semi-automatic algorithm. So it requires the user input a rough boundary for foreground and background. Typically, the user draws a rectangle around the object of interest manually. The goal of proposed method is to generate an initial rectangle automatically. In order to create initial rectangle, we use Gabor filter and Saliency map and then we use 4 features (amount of area, variance, amount of class with boundary area, amount of class with saliency map) to categorize foreground and background. From the experimental results, our proposed algorithm can achieve satisfactory accuracy in object segmentation without any prior information by the user.

• Korean Journal of Computational Design and Engineering
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• v.2 no.1
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• pp.19-27
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• 1997

This paper presents rough cut tool path planning for the fewer-axis machine consisting of a three-axis CNC machine and a rotary indexing table. In the problem dealt with in this paper, the tool orientation is "intermediately" changed, distinguished from the conventional problem where the tool orientation is assumed to be fixed. The developed rough cut path planning algorithm tries to minimize the number of tool orientation (setup) changes together with tool changes and the machining time for the rough cut by the four procedures: a) decomposition of the machining area based on the possibility of tool interference (via convex hull operation), b) determination of the optimal tool size and orientation (via network graph theory and branch-and bound algorithm), c) generation of tool path for the tool and orientation (based on zig-zag pattern), and d) feedrate adjustment to maintain the cutting force at an operation level (based on average cutting force). The developed algorithms are validated via computer simulations, and can be also used in pure fiveaxis machining environment without modification.

• Proceedings of the KIEE Conference
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• 1979.08a
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• pp.138-141
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• 1979

The purpose of this paper is to develop an efficient model for the analysis of a John's Chopper Circuit. In the John's Chopper Circuit analysis, the open branches are removed from the associated graph to formulate the modified incidence matrix. An algorithm for the generation of a modified proper tree and fundamental cut set matrix from a network graph is developed, which utilizes much less computer storage space and computation time compared to the classical methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.6C
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• pp.593-603
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• 2009

In this paper, we propose a new integrated computer vision system designed to track multiple human beings and extract their silhouette with an active stereo camera. The proposed system consists of three modules: detection, tracking and silhouette extraction. Detection was performed by camera ego-motion compensation and disparity segmentation. For tracking, we present an efficient mean shift based tracking method in which the tracking objects are characterized as disparity weighted color histograms. The silhouette was obtained by two-step segmentation. A trimap is estimated in advance and then this was effectively incorporated into the graph cut framework for fine segmentation. The proposed system was evaluated with respect to ground truth data and it was shown to detect and track multiple people very well and also produce high quality silhouettes. The proposed system can assist in gesture and gait recognition in field of Human-Robot Interaction (HRI).

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.2
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• pp.335-341
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• 2017

This paper proposes an image-processing algorithm for inspecting double-cut defects in the motor shaft manufacturing process. The algorithm consists of extracting the outline using the brightness of the image, obtaining a binarized boundary graph using the extracted outline, and determining the defects from the graph. Defects in which two cut surfaces are separated are considered type 1 defects, and those in which two cut surfaces are connected are defined as type 2 defects. In an actual manufacturing process, 112 good samples and 44 defective samples (34 type 1 defects and 10 type 2 defects) were collected and used to verify the algorithm. The samples were judged with 100% accuracy for both type 1 and type 2 defects. The algorithm will be used in the field after securing reliability for various samples.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.8
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• pp.1974-1984
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• 1994

This paper presents a relative coordinate formulation for constrained mechanical systems. Relative coordinates are defined along degrees of freedom of a joint. Graph theoretic analyses are performed to identify topological paths in mechanical systems. Cut constraints are generated to handle closed loop systems. Equations of motion are derived in the Cartesian space and transformed to the joint space. Relative generalized coordinates are corrected to satisfy the cut constraints by a parametrizatiom method.

• Journal of the Korean Institute of Telematics and Electronics
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• v.23 no.2
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• pp.264-268
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• 1986

A thchnique has been studied for the measurement of the spectral loss and the cut-off wave length, at which the first high-order mode disappears. The near-field patterns of a fiber which is excited by a variable wavelength source are used for the measurement of cut-off wavelength. Because of the absorptive phenomenon of OH- molecular vibration, spectral loss of a single mode optical fiber sample is 5.6dB/km at 1380 nm wavelength and 1dB/km at 1240 nm wavelength. From the near field intensity patterns and the mode field diameter graph for the half power width, the cut-off wavelength of the fiber is measured to be 1120 nm.

• Journal of KIISE:Software and Applications
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• v.36 no.11
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• pp.936-946
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• 2009

A graph cuts method has recently attracted a lot of attentions for image segmentation, as it can globally minimize energy functions composed of data term that reflects how each pixel fits into prior information for each class and smoothness term that penalizes discontinuities between neighboring pixels. In previous approaches to graph cuts-based automatic image segmentation, GMM(Gaussian mixture models) is generally used, and means and covariance matrixes calculated by EM algorithm were used as prior information for each cluster. However, it is practicable only for clusters with a hyper-spherical or hyper-ellipsoidal shape, as the cluster was represented based on the covariance matrix centered on the mean. For arbitrary-shaped clusters, this paper proposes graph cuts-based image segmentation using mean shift analysis. As a prior information to estimate the data term, we use the set of mean trajectories toward each mode from initial means randomly selected in $L^*u^*{\upsilon}^*$ color space. Since the mean shift procedure requires many computational times, we transform features in continuous feature space into 3D discrete grid, and use 3D kernel based on the first moment in the grid, which are needed to move the means to modes. In the experiments, we investigate the problems of mean shift-based and normalized cuts-based image segmentation methods that are recently popular methods, and the proposed method showed better performance than previous two methods and graph cuts-based automatic image segmentation using GMM on Berkeley segmentation dataset.

• Journal of information and communication convergence engineering
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• v.9 no.2
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• pp.141-149
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• 2011

We consider the problem of assigning tasks to homogeneous nodes in the distributed system, so as to minimize the amount of communication, while balancing the processors' loads. This issue can be posed as the graph partitioning problem. Given an undirected graph G=(nodes, edges), where nodes represent task modules and edges represent communication, the goal is to divide n, the number of processors, as to balance the processors' loads, while minimizing the capacity of edges cut. Since these two optimization criteria conflict each other, one has to make a compromise between them according to the given task type. We propose a new cost function to evaluate static task assignments and a heuristic algorithm to solve the transformed problem, explicitly describing the tradeoff between the two goals. Simulation results show that our approach outperforms an existing representative approach for a variety of task and processing systems.