• Journal of the Semiconductor & Display Technology
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• v.19 no.3
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• pp.7-11
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• 2020

Enormous methods have been proposed for the detection and segmentation of blur and non-blur regions of the images. Due to the limited available information about the blur type, scenario and the level of blurriness, detection and segmentation is a challenging task. Hence, the performance of the blur measure operators is an essential factor and needs improvement to attain perfection. In this paper, we propose an effective blur measure based on the local binary pattern (LBP) with the adaptive threshold for blur detection. The sharpness metric developed based on LBP uses a fixed threshold irrespective of the blur type and level which may not be suitable for images with large variations in imaging conditions and blur type and level. Contradictory, the proposed measure uses an adaptive threshold for each image based on the image and the blur properties to generate an improved sharpness metric. The adaptive threshold is computed based on the model learned through the support vector machine (SVM). The performance of the proposed method is evaluated using a well-known dataset and compared with five state-of-the-art methods. The comparative analysis reveals that the proposed method performs significantly better qualitatively and quantitatively against all the methods.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.11
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• pp.2453-2458
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• 2012

In this paper, we propose an adaptive thresholding method to binarize two-dimensional barcode images. Adaptive thresholding methods that minimize light effects convert an original image into a binary image. The methods are applied to document image binarization. The methods, however, have problems of determining box size used in adaptive thresholding. thus, they inappropriate to use in recognition of two-dimensional barcode images. To overcome the problem, we analysis the problem and propose a new adaptive threshold method using the integral image. To show the effectiveness of our method, we compared our method with the well-known existing methods in terms of visual quality and processing time. The experimental result indicates that the proposed method is superior to the existing method.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.12
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• pp.820-826
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• 2004

In this paper, studied error of various signal interpolation methods in vibration signal analysis with digital order tracking. Because, interpolation errors are related with sampling rate and amount of calculation. Appled Signal interpolation methods are Lagrange, Newton and Cubic-spline. This paper proposed more proper interpolation method. Also, we suggest guideline for adaptive application of signal interpolation methods with Calculated results.

• Journal of the Semiconductor & Display Technology
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• v.18 no.4
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• pp.110-115
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• 2019

Blur detection and segmentation play vital role in many computer vision applications. Among various methods, local binary pattern based methods provide reasonable blur detection results. However, in conventional local binary pattern based methods, the blur map is computed by using a fixed threshold irrespective of the type and level of blur. It may not be suitable for images with variations in imaging conditions and blur. In this paper we propose an effective method based on local binary pattern with adaptive threshold for blur detection. The adaptive threshold is computed based on the model learned through the multinomial logistic regression. The performance of the proposed method is evaluated using different datasets. The comparative analysis not only demonstrates the effectiveness of the proposed method but also exhibits it superiority over the existing methods.

• The KIPS Transactions:PartC
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• v.9C no.3
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• pp.399-406
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• 2002

We consider design of multiservice network link, in which connections of constant- and adaptive-rate services arrive and leave dynamically. We propose performance analysis and design methods of these dynamic multiservice networks. A multiservice network link is modeled by a Markov chain, and data rates for adaptive-rate connections are derived using QBD (Quasi-Birth-Death) processes and matrix-geometric equations. We estimate average number of adaptive-rate connections, average data rate and average connection delay. The performance of constant-rate connections is determined from the blocking probability of the connections. Based on the performance of constant-and adaptive- rate connections, we propose a design methods of a network link to satisfy performance requirements of constant- and adaptive-rate connections (data rates, delay, blocking probability). Our methods can be used for the analysis and design of network switch supporting dynamic data and voice (video) traffic simultaneously.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.25 no.12
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• pp.1895-1902
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• 2001

This paper gives an overview of the relationships between methods of loaming and adaptive control. It is the objective of this paper to develop adaptive learning control algorithms that combine the advantages of adaptive control with those of leaning control to the extent possible for the type of system model used. The robustness of this adaptive loaming control with respect to reinitialization errors and fluctuation of dynamics from disturbance is analyzed extensively. Simulation results have shown to verify the effectiveness of the proposed control algorithm.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.5
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• pp.556-566
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• 2001

This paper proposes a motion-adaptive de-interlacing algorithm based on EBMF(Edge Based Median Filter) and AMPDF(Adaptive Minimum Pixel Difference Fillet). To compensate 'motion missing'error, which is an important factor in motion-adaptive methods, we used AMPDF which estimates an accurate value using different thresholds after classifying the input image to 4 classes. To efficiently interpolate the moving diagonal edge, we also used EBMF which selects a candidate pixel according to the edge information. Finally, we, to increase the performance, adopted an adaptive interpolation after classifying the input image to moving region, stationary region, and boundary region. Simulation results showed that the proposed method provides better performance than the existing methods.

• Journal of Advanced Marine Engineering and Technology
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• v.19 no.3
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• pp.77-83
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• 1995

Recently, in the field of industrial servo-systems, several methods have been proposed for tracking the reference input fastly and finely without overshoot. These methods, however, are established under hypothesis that structure and parameters of the plant are known accurately and they are time invariant. In practice, it is difficult to obtain the values of plant's parameters accurately and usually plants change with time and operation conditions. In this paper a method to construct the nominal model tracking adaptive control system is proposed. The system is composed of the nomial model which produces a ideal response and the model tracking system with the fuzzy adaptive controller. If the actual plant is equal to the controlled object in the nominal model, the output of the plant is the same as that of the nominal model and the fuzzy adaptive controller becomes idle. However, when the plant changes, the fuzzy adaptive controller of the tracking system operates in order for the output of the plant to track the ideal response. Through the computer simulations under various conditions, it is confirmed that the proposed model tracking system is very effective.

• Journal of Advanced Marine Engineering and Technology
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• v.30 no.7
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• pp.791-799
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• 2006

The aim of this paper is to design an adaptive speed control system of a marine diesel engine by fusion of hard computing based proportional integral derivative (PID) control and soft computing based fuzzy control methods. The model of a marine diesel engine is considered as a typical non oscillatory second order system. When its model and the actual marine diesel engine ate not matched, it is hard to control the speed of the marine diesel engine. Therefore, this paper proposes two methods in order to obtain the speed control characteristics of a marine diesel engine. One is an efficient method to determine the PID control parameters of the nominal model of a marine diesel engine. Second is a reference adaptive speed control method that uses a fuzzy controller and derivative operator for tracking the nominal model of the marine diesel engine. It was found that the proposed PID parameters adjustment method is better than the Ziegler & Nichols' method, and that a model reference adaptive control is superior to using only PID controller. The improved control method proposed here, could be applied to other systems when a model of a system does not match the actual system.

• Journal of the Korean Institute of Telematics and Electronics
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• v.25 no.5
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• pp.482-489
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• 1988

In this paper, we proposed a generalized model reference adaptive control theory which can be applied to single-input single-output discrete system by using V.M.Popov's hyperstability theory. As the result of theoretical analysis, it is proved that the discrete adaptive control scheme proposed by Narendra is a special case of the adaptive control schemes proposed in this paper. Also we suggest a variety of parameter adaptiations methods of controller through hyperstability theory.