• Journal of the Korean Society for Precision Engineering
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• v.15 no.7
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• pp.167-174
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• 1998

This paper presents an unoccluded cylindrical object pose measurement using a slit beam laser in which a robot recognizes all of the unoccluded objects from the top of jumbled objects, and picks them up one by one. The elliptical equation parameters of a projected curve edge on a slice are calculated using LSM. The coefficients of standard elliptical equation are compared with these parameters to estimate the object pose. The hamming distances between the estimated coordinates and the calculated ones are extracted as measures to evaluate a local constraint and a smoothing surface curvature. The edges between slices are linked using error function based on the edge types and the hamming distances. The linked edges on slices are compared with the model object's length to recognize the unoccluded object. This proposed method may provide a solution to the automation of part handling in manufacturing environments such as punch press operation or part assembly.

• Proceedings of the KIEE Conference
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• 1990.11a
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• pp.23-27
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• 1990

Adaptive mesh refinement scheme is incorporated with the Boundary Element Method (BEM) in order to get accurate solution with relatively fewer unknowns for the case of magnetostatic field analysis and A new and simple posteriori local error estimation method is presented. The local error is defined as integration over the element of the difference between solutions acquired us ing second order and first order interpolation function and is used as the criterion for mesh refinement at given grid. Case study for two dimensional problems with singular point reveals that meshes are concentrated on the neighbor of singular point and the error is decreased gradually and the solutions calculated on the domain are converged to the analytic solution as the number of unknowns increases. The adaptive mesh gives much better rate of convergence in global errors than the uniform mesh.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.4
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• pp.87-92
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• 2004

Digital halftoning is to quantize a grayscale image to binary image. The error diffusion halftoning generates high quality bilevel image. But that also has some defects such as warms effect, sharpening and etc. To reduce these defects, Kite proposed the modified threshold modulation that has a parameter to control sharpening. Nevertheless some degradation left near edges with large luminance change. In this paver, we propose a method to control the parameter in proportional to local edge magnitude. The results of computer simulation show more reductions of the sharpening in the halftone image. Especially there are great improvement of quality near edges with large luminance change.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.24 no.1
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• pp.23-37
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• 2020

The quadratic error metric (QEM) algorithm has been frequently used for simplification of triangular surface models that utilize the vertex-pair algorithm. Simplified models obtained using such algorithms present the advantage of smaller storage capacity requirement compared to the original models. However, a number of cases exist where significant features are lost geometrically, and these features can generally be preserved by utilizing the advantages of the curvature-weighted algorithm. Based on the vertex-based geometric features, a method capable of preserving the geometric features better than the previous algorithms is proposed in this work. To validate the effectiveness of the proposed method, a simplification experiment is conducted using several models. The results of the experiment indicate that the geometrically important features are preserved well when a local feature is present and that the error is similar to those of the previous algorithms when no local features are present.

• The Journal of the Korea Contents Association
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• v.5 no.2
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• pp.221-228
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• 2005

The paper proposes the improved error diffusion halftoning system to enhance the edges using the spatial perceptual characteristics of the human visual system. The proposed method computes a spatial variation(SV), which is the difference between a pixel luminance and the average of its $3{\times}3$ neighborhood pixels' luminances weighted according to the spatial positioning. Information of edge enhancement(IEE) Is computed using the SV and the local average luminance. The IEE is added to the quantizer's input pixel and feeds into the halftoning quantizer. The quantizer produces the halftone image having the enhanced edge. The performance of the proposed method is compared with conventional methods by measuring the edge correlation. The halftone images by using the proposed method show better quality due to the enhanced edge. And the detailed edge is preserved in the halftone images by using the proposed method.

• Journal of the Korean Institute of Intelligent Systems
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• v.9 no.5
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• pp.490-495
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• 1999

In this paper. a learning method VoD-EBP for neural networks is proposed, which learn patterns by error back propagation. Based on Voronoi diagram, the method initializes the weights of the neural networks systematically, wh~ch results in faster learning speed and alleviated local optimum problem. The method also shows better the reliability of the design of neural network because proper number of hidden nodes are determined from the analysis of Voronoi diagram. For testing the performance, this paper shows the results of solving the XOR problem and the parity problem. The results were showed faster learning speed than ordinary error back propagation algorithm. In solving the problem, local optimum problems have not been observed.

• Journal of the Korean Physical Society
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• v.73 no.11
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• pp.1644-1649
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• 2018

Aiming at infrared thermal images with different buried depth defects, we study a variety of image segmentation algorithms based on the threshold to develop global search ability and the ability to find the defect area accurately. Firstly, the iterative thresholding method, the maximum entropy method, the minimum error method, the Ostu method and the minimum skewness method are applied to image segmentation of the same infrared thermal image. The study shows that the maximum entropy method and the minimum error method have strong global search capability and can simultaneously extract defects at different depths. However none of these five methods can accurately calculate the defect area at different depths. In order to solve this problem, we put forward a strategy of "divide and conquer". The infrared thermal image is divided into several local thermal maps, with each map containing only one defect, and the defect area is calculated after local image processing of the different buried defects one by one. The results show that, under the "divide and conquer" strategy, the iterative threshold method and the Ostu method have the advantage of high precision and can accurately extract the area of different defects at different depths, with an error of less than 5%.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.5
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• pp.409-415
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• 2013

In this paper, we propose a correlation function using newly designed local signals for cosine-phased binary offset carrier (BOC) signal tracking. First, we divide a sub-carrier pulse over one pseudo random noise code period into multiple rectangular pulses, and subsequently, design novel local signals. Then, we obtain a correlation function with no side-peak based on a combination of correlations between the newly generated local signals and received cosine-phased BOC signal. From numerical results, it is confirmed that the proposed correlation function provides a tracking performance improvement over the conventional correlation functions in terms of the tracking error standard deviation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.2
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• pp.536-564
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• 2019

Soft faults are inherent in wireless sensor networks (WSNs) due to external and internal errors. The failure of processes in a protocol stack are caused by errors on various layers. In this work, impact of errors and channel misbehavior on process execution is investigated to provide an error classification mechanism. Considering implementation of WSN protocol stack, inter-process correlations of stacked and peer layer processes are modeled. The proposed model is realized through local and global decision trees for fault diagnosis. A hybrid framework is proposed to implement local decision tree on sensor nodes and global decision tree on diagnostic cluster head. Local decision tree is employed to diagnose critical failures due to errors in stacked processes at node level. Global decision tree, diagnoses critical failures due to errors in peer layer processes at network level. The proposed model has been analyzed using fault tree analysis. The framework implementation has been done in Castalia. Simulation results validate the inter-process correlation model-based fault diagnosis. The hybrid framework distributes processing load on sensor nodes and diagnostic cluster head in a decentralized way, reducing communication overhead.

• Journal of Environmental Impact Assessment
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• v.16 no.6
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• pp.495-502
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• 2007

In Korea, military authorities have neglected to consider impacts of military projects on local communities and natural environment. Moreover, local communities have had difficulties in dealing with the Ministry of National Defense (MND), which was stubborn enough not to implement environmental assessment on their projects. In this situation, recent case, "EIA of Baekgol Division's Howitzer Fire Training Site" in the Supreme Court-in which judges upheld the Higher Court's decision that the division violated the Environmental Impact Assessment law by ignoring to implement EIA-reveals that military projects can no longer forgo environmental assessment. The decision has serious ramifications on the future of Environmental Impact Assessment in military-led projects. This paper examines the proper scope of EIA in military-led projects and, more specifically, fire training site and searches for how to improve it through 'probable error,' a military training method that is applied to real 'howitzer' fire training. Probable error of the artillery field manual is nothing more than an error that exceeded as often as it is not exceeded and its scientific method was demonstrated through real fire tests in the US. Army. If it is applied to improve assessment methods about the proper scope of EIA in military 'howitzer' fire training site, 'probable error' will improve effect prediction, mitigation and reliability.