• Korean Journal of Cognitive Science
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• v.20 no.2
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• pp.155-181
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• 2009

Psychophysiologists are often interested in the EEG signals that accompany certain psychological events. When one is interested in a time series of event-related changes in EEG, one focuses on examining how the waveforms recorded at individual electrode sites vary over time across one or more experimental conditions. This is an analysis of event-related potentials (ERPs). In addition to such a classical EEG analysis in the time domain, the EEG measures can be investigated in the frequency domain. Moreover, it has been demonstrated that spectral analyses can often yield significant insight into the functional cognitive correlations of the signals. Therefore, this review paper tries to summarize essential concepts (e.g. phase-locking) and conventional methods (e.g. wavelet transformation) for understanding spectral analyses of brain oscillatory activity. Phase-coherence is also introduced in relation to functional connectivity of the brain.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.5
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• pp.183-193
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• 2019

This study developed a shockwave detection and prediction of their extinction point method based on continuous wavelet transform using trajectory data from probe vehicles equipped with automotive sensors.. To analyze the effectiveness of the proposed method, this paper proposed two measures which are a distance error between the extinction points of the predictor and an time-location error of the extinction points. The proposed concept was proved using the micro simulation based experiment with three exogenous variables of traffic volume, lane-close duration, market penetration of probe vehicles. The analysis results show that the proposed method is capable of detecting the traffic shockwaves as well as predicting their extinction point, and also that the accuracy of the proposed method is highly dependent on the rate of the probe vehicles.

• Journal of the Korea Society for Simulation
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• v.19 no.2
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• pp.127-135
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• 2010

The validation of a simulation model is a key to demonstrate that the simulation model is reliable. However, among various validation methods have been introduced, it is very poor to research the specific techniques for the time series data. Therefore, this paper suggests the methodology to verify the simulation using the time series data by Wavelet Transform, Power Spectrum and Coherence. This method performs 2 steps as followed. Firstly, we get spectrum using the Wavelet transform available for non-periodic signal separation. Secondly, we compare 2 patterns of output data from simulation model and actual system by Coherence Analysis. As a result of comparing it with other validation techniques, the suggested way can judge simulation model accuracy more clearly. By this way, we can make it possible to perform the simulation validation test under various situations using detailed sectional validation method, which has been impossible using a single statistics for the whole model.

• Journal of KIISE:Software and Applications
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• v.30 no.7_8
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• pp.687-695
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• 2003

In this paper, we present a document image compression system based on segmentation, Quincunx downsampling, (5/3) wavelet lifting and subband-oriented SPIHT coding. We reduced the coding time by the adaptation of subband-oriented SPIHT coding and Quincunx downsampling. And to increase compression rate further, we applied arithmetic coding to the bitstream of SPIHT coding output. Finally, we present the reconstructed images for visual comparison and also present the compression rates and PSNR values under various scalar quantization methods.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2011.11a
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• pp.69-70
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• 2011

최근 해저지진의 활동에 따른 극한 쯔나미 파랑이 해안도시와 항만에 어마어마한 손상을 가져오고 있다. 전세계에 걸쳐 특정해역에서는 강한 정진형태의 부진동과 처오름이 관측되고 있다. 한반도에서는 그렇게 빈번한 발생을 나타내고 있지는 않으나, 과거기록을 보면 동해에서 몇 개의 중요한 발생사례도 존재한다. 본 연구에서는 특히 만이나 내수해역에서 최근 해저지진의 발생 추이를 분석하고 이에 따른 쯔나미 발생 메카니즘을 해석하여 새롭게 내수역에서의 수치모델에의 적용을 통해 공진을 통한 쯔나미 파랑의 변환을 다루어 통항선박에 대한 안정성 확보에 기초자료를 제공하고자 하였다. 내수역에서의 쯔나미 파랑에 대한 반응을 정합성 및 웨이블릿 해석으로 탁월 주기와 지속시간에 대한 분석으로 파악하였으며, 쯔나미파의 입사와 독립적인 공진모드의 도출은 쯔나미 재해의 경감을 위한 시설물 및 재난지역을 식별하는데 도움을 주고, 나아가서는 장래 재난에 대한 적절한 대비에 기여할 수 있을 것으로 본다.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2000.12a
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• pp.157-160
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• 2000

본 논문에서는 교통 감시 시스템의 필수 단계중에 하나인 실시간 자동차 검출 방법을 제안한다. 제안한 방법은 후보 영역 추출 단계와 자동차 인식 단계로 이루어진다. 첫 번째 단계에서는 연속된 두 프레임간의 차영상 분석 방법을 기반으로 하여 움직임이 있는 후보 영역을 추출한다. 두 번째 단계에서는 추출된 후보 영역에 자동차가 포함되어 있는지를 판별하기 위해 웨이블릿 변환 계수들을 입력으로 하는 신경망을 사용한다. 일반 도로에서 획득한 230대의 자동차가 포함된 동영상을 실험한 결과, 자동차 검출율은 97.8%, 프레임당 처리 시간은 0.12ms이다. 본 논문에서 제안한 실시간 자동차 검출 방법은 교통 감시 시스템에 유용하게 적용될 수 있다.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.6
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• pp.57-65
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• 2010

In this paper, we present a universal steganalysis scheme. The proposed method extract features of two types. First feature set is extracted from histogram characteristic of the wavelet subbands. Second feature set is determined by statistical moments of wavelet characteristic functions. 3-level wavelet decomposition is performed for stego image and cover image using the Haar wavelet basis. We extract one features from 9 high frequency subbands of 12 subbands. The number of second features is 39. We use total 48 features for steganalysis. Multi layer perceptron(MLP) is applied as classifier to distinguish between cover images and stego images. To evaluate the proposed steganalysis method, we use the CorelDraw image database. We test the performance of our proposed steganalysis method over LSB method, spread spectrum data hiding method, blind spread spectrum data hiding method and F5 data hiding method. The proposed method outperforms the previous methods in sensitivity, specificity, error rate and area under ROC curve, etc.

• Journal of the Korea society of information convergence
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• v.6 no.2
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• pp.45-49
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• 2013

Electrocardiogram(ECG) signal noise as well as conducting other bio-signal measurement were generated. It was intened to enhance the accuracy of cadiac disease diagnosis with removing signal white-noise. Sampling signal was made with generating white-noise. The noise were removed using wavelet transforms and thresholding. Removed noise were compared numerical using SNR(signal to noise ratio). The results compared SNR showed that SURE method was 5.931, 4.9301 in 3, 5dB noise, uninversal was 3.6590, 1.9698 in 7, 9dB noise. De-noising by Thresholding removed noise effectively. ECG signal is expected to improve the accuracy of cadiac desease dianosis.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2002.10a
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• pp.219-223
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• 2002

Many data fusion techniques have been widely studied, but some methods were hard to apply due to complicated theoretical backgrounds and complexed steps. In this study, we tried to compare the wavelet transform, which has been accepted as the best method in terms of spectral distortion, and other three handy methods, which are available in most commercial software. Four clipped test areas were selected for different spectral information. There is, however, no huge improvement in clipped images except water areas. Overall the wavelet transform are superior in most areas, but the multiplicative method relatively gives good correlation.

• The KIPS Transactions:PartB
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• v.17B no.3
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• pp.197-206
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• 2010

High-quality and low-price digital printing devices are nowadays abused to print or forge official documents and bills. Identifying color laser printers will be a step for media forensics. This paper presents a new method to identify color laser printers with printed color images. Since different printer companies use different manufactural systems, printed documents from different printers have little difference in visual. Analyzing this artifact, we can identify the color laser printers. First, high-frequency components of images are extracted from original images with discrete wavelet transform. After calculating the gray-level co-occurrence matrix of the components, we extract some statistical features. Then, these features are applied to train and classify the support vector machine for identifying the color laser printer. In the experiment, total 2,597 images of 7 printers (HP, Canon, Xerox DCC400, Xerox DCC450, Xerox DCC5560, Xerox DCC6540, Konica), are tested to classify the color laser printer. The results prove that the presented identification method performs well with 96.9% accuracy.