• Information and Communications Magazine
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• v.31 no.2
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• pp.21-28
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• 2014

본고에서 디지털 홀로그래피를 위한 SLM중 대표적인 몇 가지 기술에 대한 동향을 살펴보았다. 먼저 SLM픽셀 피치에 따른 홀로그램 영상의 특성에 대해 논의하고, 픽셀화된 SLM으로써 현재 상용화 되고 있는 DMD SLM 과 LCoS SLM의 특성에 대해 살펴 보았다. 픽셀화 되지 않은 SLM 인 음향 광학 변조기와 OASLM 에 대해서도 살펴 보았다. 양질의 디지털 홀로그래피를 구현하기 위하여 궁극적으로 필요한 픽셀 피치 1 ${\mu}m$ 이하 SLM 의 개발 현황과 복소 변조 SLM 에 대해서도 알아보았다.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.1
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• pp.92-97
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• 2005

This paper discusses an intelligent digital redesign technique for designing a fuzzy pulse-width-modulated (PWM) control. First when we are given a well-designed fuzzy analog control, the equivalent digital control is intelligently redesigned. Using the similar technique we intelligently redesign the fuzzy PWM control from the intelligently redesigned fuzzy digital control. A stabilizability of the intelligently redesigned PWM control is rigorously analyzed.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.10 no.1
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• pp.17-30
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• 1985

The error rate performances of digital modulation systems in fluenced by impulsive noise have been investigated and discussed in the enviroment of electromagnetic interference(EMI). Using the derived equations for the probabilities of error of L-level ASK, M-ary PSK, MSK, QAM, and APK signals, the error rate performance of each system has been evaluated and compared each other. The results show that, in the case of gaussian noise enviornment, PSK system is superior to the other systems and the digital amplitude modulation systems are inferior on the contrary. In the environment of impulsive noise, the MSK at low interfere level shows the best error rate performance but in the high level interferer environment, the PSK shows the best error rate performance. Also it is known that the digital amplitude modulation systems are scarcely influenced by the variation of interfere level.

• Journal of the Korea Society of Computer and Information
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• v.26 no.12
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• pp.111-121
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• 2021

As the main carrier of information, digital image is becoming more and more important. However, with the popularity of image acquisition equipment and the rapid development of image editing software, in recent years, digital image counterfeiting incidents have emerged one after another, which not only reduces the credibility of images, but also brings great negative impacts to society and individuals. Image copy-paste tampering is one of the most common types of image tampering, which is easy to operate and effective, and is often used to change the semantic information of digital images. In this paper, a method to protect the authenticity and integrity of image content by studying the tamper detection method of image copy and paste was proposed. In view of the excellent learning and analysis ability of deep learning, two tamper detection methods based on deep learning were proposed, which use the traces left by image processing operations to distinguish the tampered area from the original area in the image. A series of experimental results verified the rationality of the theoretical basis, the accuracy of tampering detection, location and classification.

• Journal of Korea Multimedia Society
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• v.13 no.3
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• pp.457-466
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• 2010

In this paper, we propose a new method for detecting digital forgery that identify interpolated region between digital composited images. For detecting the interpolation factor and the tampered regions, we perform two algorithms: The first algorithm is to estimate the interpolation factors using the differential equation for forgery image along the horizontal, vertical, and diagonal directions, respectively; The second algorithm is to scan the interpolation factors along each direction for detection areas as the mask of the optical window size($64{\times}64$) in order to find out the forgery region. A detection map of the forgery is classified with the magnitude of estimated interpolation factors into colors. This detection map can be used to find out interpolated regions from the tampered image. Experimental results demonstrate the proposed algorithms are proven on several examples. We also show the proposed approach is to accurately detect interpolated regions from digital composite images.

• Journal of Broadcast Engineering
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• v.19 no.6
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• pp.967-970
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• 2014

An efficient peak detection algorithm in magnitude spectrum is proposed to distinguish the M-frequency shift keying(FSK) signals from other digitally modulated signal. In addition, recognition of the modulation order estimation of FSK signals is also studied based on the fact that the magnitude spectrum of FSK signals reveals the number of peaks equal to the modulation order. When no a priori information about the signals, we utilize the histogram of the magnitude spectrum to determine the threshold which is important factor in peak detection algorithm. The simulation results show high probability of classification under 500 symbols and signal-to-noise ratio(SNR) higher than 4dB.

• Journal of Digital Contents Society
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• v.15 no.4
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• pp.547-558
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• 2014

Recently, in the course of business processes a variety of abuse cases of fax documents is common in general corporate, government, and financial institutions. To solve this problem, it is necessary for a technique to prevent falsification of fax documents. In this paper, we propose a new fax sender verification technique based on pattern analysis to prevent falsification of fax documents only using the received fax document. In the proposed technique, the fax sender is verified by analyzing the communication signal patterns between the fax sender and receiver and image pattern in the received fax document. In this paper, we conduct the experiments that apply our technique to real-world fax systems, and then tamper-proof effects were confirmed from the experimental results.

• Journal of the Institute of Convergence Signal Processing
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• v.9 no.2
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• pp.98-103
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• 2008

There are the frequency shift keying(FSK), phase shift keying(PSK) and amplitude shift keying(ASK) in the conventional digital communications method. In this paper, We proposed a new robust wavelet shift keying system using scaling and wavelet function in the digital communication. Wavelet Transform consist of a low frequency and high frequency coefficient. When the input signal is one, if it finds the impulse response, the signal is separated from the scaling and wavelet function. The binary data is encoded by modulator which assigned the scaling function to 1(one), and wavelet to zero(0). It was demonstrated by experiment that the proposed algorithm can be a robust noise.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.14 no.3
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• pp.263-279
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• 1989

In part-1 of this paper, the error rate equations of digitally modulated signals transmitted though the Gaussian/Impulsive noise channel have been derived. Using the derived equations for the error probabilities of ASK, QAM, CPSK, DPSK, FSK and MSK signals, the error rate performances of digital modulation systems have been evaluated and represented in the figures as the functions of carrier-to-noise power ratio(CNR), impulsive index, and the ration of Gaussian noise power component to impulsive noise power component. The results are shown in graphs to known how much impulsive noise effects on digital signals than Gaussian noise.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.10
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• pp.2409-2416
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• 2014

In this paper, an automatic recognition algorithm for linearly modulated signals like PSK, QAM under noncoherent asynchronous condition is proposed. Frequency, phase, and amplitude characteristics of digitally modulated signals are changed periodically. By using this characteristics, cyclic moments and higher order cumulants based features are utilized for the modulation recognition. Hierarchial decision tree method is used for high speed signal processing and totally 4 feature extraction parameters are used for modulation recognition. In the condition where the symbol number is 4,096, the recognition accuracy of the proposed algorithm is more than 95% at SNR 15dB. Also the proposed algorithm is effective to classify the signal which has carrier frequency and phase offset.