• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.4
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• pp.76-84
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• 1998

The requirements of the accuracy, the high speed and the stability are very important factors in the defect-detection sytem for the texture. In this paper, we describe a novel scheme of the defect detection using a statistical behavior of defect patterns. Some prior knowledge as to the characteristics of flaws is that the defects are consistently distributed in the space and the noise are randomly generated. An empirical knowledge is adapted for the binarization and the determination process of defects in textured image. Since the process of the determination exclude the segmentations or delineation steps, we are able to meet the speed requirements. We show the validity of the scheme through the simulation of textured images.

• Journal of Power Electronics
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• v.2 no.1
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• pp.1-10
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• 2002

An advanced active power filter for the compensation of instantaneous harmonic current components in nonlinear current load is presented in this paper. A novel signal processing technique using an adaptive neural network algorithm is applied for the detection of harmonic components generated by three-phase nonlinear current loads and this method can efficiently determine the instantaneous harmonic components in real time. The control strategy of the switching signals to compensate current harmonics of the three-phase inverter is also discussed and its switching signals are generated with the space voltage vector modulation scheme. The validity of this active filtering processing system to compensate current harmonics is substantiated on the basis of simulation results.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.7
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• pp.1803-1813
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• 1996

This paper describes an automatic threshold decision using a maximum mismatched correlation value in the direct sequence spread spectrum (DS-SS) system. For received PN codes with different single-to-noise ratio (SNR), this scheme is able to detect a desired threshold value in the search mode, i.e. a maximum mismstched correlation value, so that value is utilized as a threshold for the verification mode. Performance of the proposed scheme in both the additive white gaussian noise (AWGN) and frequency-selective Rayleigh fading channels is analyzed through the Monte Carlo simulation. And hardware implementation of this scheme using a DSP processor is demonstrated. The proposed acquisition shceme is compared to the conventional constant threshold (CT) scheme, and significant improvement of performance is shown. Analysis of system performance in the verification mode is presented, and key quantities such as the false alarm probability and the detection probability are derived in a AWGN channel.

• KIEE International Transaction on Systems and Control
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• v.2D no.2
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• pp.115-119
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• 2002

In this paper we present a generalized directional morphological filtering algorithm for the removal of impulse noise, which is based on a combination of impulse noise detection and a weighted rank-order morphological filtering technique. For salt (or pepper) noise suppression, the generalized directional opening (or closing) filtering of the input signal is selectively used. The detection of impulse noise can be done by the geometrical difference of opening and closing filtering. Simulations show that this new filter has better detail feature preservation with effective noise reduction compared to other nonlinear filtering techniques.

• Proceedings of the KIEE Conference
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• 1998.07c
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• pp.1046-1049
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• 1998

This paper deals with the new fault detection technique for transmission line using Neuro-fuzzy Scheme. Neuro-fuzzy Scheme is ANFIS(Adaptive-network Fuzzy Inference System) based on fusion of fuzzy logic and neural networks. The proposed scheme has five layers. Each layer is the component of fuzzy Inference system and performs different action. Using learning method of neural network, fuzzy premise and consequent parameters is tuned properly.

• Journal of the Korea Society of Computer and Information
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• v.23 no.4
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• pp.33-39
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• 2018

In this paper, we propose a describes how to detect a false iris image by inserting watermark into a iris image. The existing method, which inserts the watermark into the entire iris image to detect a fake iris, has a problem that can evade it by segmenting iris region of an iris image. The purpose of overcoming the problem, this paper proposes a new fake iris detection technique based on digital watermark. It first searches a central point of an iris image, divide the image into blocks with respect to the point. executes Discrete Cosine Transform, inserts watermark into the blocks, and then verifies an iris image using NC(Normalized Correlation). In the experiments, we confirm the robustness for attacks - crop and JPEG.

• Proceedings of the IEEK Conference
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• 2000.07b
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• pp.889-893
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• 2000

In this paper, a method to detect lanes and obstacles from the images captured by a CCD camera fitted in an automobile is proposed, and a new terminology “Moving Window” is defined. Processing the input dynamic images in real time can cause quite a few constraints in terms of hardware. In order to overcome these problems and detect lanes and obstacles in real time using the images, the optimal size of “Moving Window” is determined, based upon road conditions and automobile states. The real time detection is made possible through the technique. For each image frame, the moving window is moved in a predicted direction, the accuracy of which is improved by the Kalman filter estimation. The feasibility of the proposed algorithm is demonstrated through the simulated experiments of freeway driving.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.13 no.1
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• pp.74-84
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• 1988

This paper presents feature extraction technique for linear image using edge detection algorithms. The process of edge finding consists of determining edge magnitud and direction by convolution of an image with a number of edge masks, of thinning and ghresholding these edge magnitudes, of linking the edge elemtnts based on proximity ans orientation, and finally, of approximating the linked elements by piede-wise linear segmentss. These techniques are intened to be general and opplications to terminal detection and road recognition tasks are described. The presentation will be helpful to other researchers attempting to implement similar algorithms.

• Journal of Power Electronics
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• v.16 no.1
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• pp.48-56
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• 2016

This paper proposes a method for detecting irreversible demagnetization using the harmonic analysis of back electromotive force (BEMF) in interior permanent magnet-type brushless DC motors. First, demagnetization patterns, such as equality, inequality, and weighted demagnetizations, are defined and classified by considering the possibility of demagnetization resulting from motor operating characteristics. Second, an available diagnostic model for the harmonic analysis of BEMFs is defined according to pole-slot coefficients because the characteristics of BEMFs under demagnetization conditions are affected by the combination of poles and slots. Third, BEMFs and their harmonic components under normal and demagnetization conditions are analyzed through simulation and experiment to verify the proposed demagnetization detection technique.

• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2289-2291
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• 2003

NLPCA(Nonlinear Principal Component Analysis is a novel technique for multivariate data analysis, similar to the well-known method of principal component analysis. NLPCA can be implemented by a feedforward neural network called AANN (AutoAssociative Neural Network) which performs the identity mapping. In this work, a sensor fault detection system based on NLPCA and Maximum Likelihood Estimation scheme is presented. To verify its applicability, simulation study on the data supplied from Saemangeum measurement stations is executed.