• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.10B
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• pp.1382-1389
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• 2001

움직임 보상-이산 코사인 변환 (motion compensation-discrete cosine transform : MC-DCT) 기반의 동영상 부호화 기법이 부호화 효율성 및 구현의 단순성으로 인해 널리 사용되고 있으나, 에러 환경에서 구조적으로 취약한 면이 있다. 본 논문에서는 다중 메모리 움직임 보상 예측 (long-term memory motion compensated prediction : LTMP) 기반의 다중 레프런스 프레임을 사용하여 에러에 강인한 동영상 부호화 기법을 제안한다. 또한 제안하는 알고리듬에 기반한 에러 은닉 기법 (error concealment : EC)을 구현한다. 즉, R-D (rate-distortion) 최적화에 프레임간 움직임 벡터 (temporal motion vectors)의 확산 인자를 추가하여 에러에 대한 강인성 및 에러 은닉 기법의 효율성을 증가시켰다. 또한, 제안하는 알고리듬은 시간축상의 에러 전파를 피드백 정보 (negative acknowledgement : NAK)를 사용하여 억제한다. 즉, NAK는 채널 에러에 의해 손실된 영역과 에러가 전파된 영역을 추정하여 움직임 보상 영역에서 제외되도록 하는데 이용된다. 따라서, 제안하는 알고리듬은 PSNR 측면에서 FIU (forced intra update)에 근사하는 성능을 보이나, FIU와는 달리 비트율의 증가를 피할 수 있어 제한된 대역폭의 네트웍을 효율적으로 사용할 수 있다. 컴퓨터 모의 실험을 통해 제안하는 알고리듬이 기존의 H.263 및 LTMP 기반의 부호기에 비해 에러 환경에서 주관적 및 객관적 화질 측면에서 성능이 우수함을 보인다.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.9
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• pp.111-118
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• 2014

This paper presents an efficient Markov feature extraction method for detecting splicing forged images. The Markov states used in our method are composed of the difference between DCT coefficients in the adjacent blocks. Various first-order Markov state transition probabilities are extracted as features for splicing detection. In addition, we propose a feature reduction algorithm by analysing the distribution of the Markov probability. After training the extracted feature vectors using the SVM classifier, we determine whether the presence of the image splicing forgery. Experimental results verify that the proposed method shows good detection performance with a smaller number of features compared to existing methods.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.3
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• pp.467-472
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• 2005

ECG signals are recorded for diagnostic purposes in many clinical situations. Also, In order to permit good clinical interpretation, data is needed at high resolutions and sampling rates. Therefore In this paper, we designed to compression structure using multiple wavelet basis function(SWBF) and compared to single wavelet basis function(SWBF) and discrete cosine transform(DCT). For experience objectivity, Simulation was performed using the arrhythmia data with sampling frequency 360Hz, resolution lIbit at MIT-BIH database. An estimate of performance estimate evaluate the reconstruction error. Consequently compression structure using MWBF has high performance result.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.7A
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• pp.1050-1056
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• 2000

In this paper, We Propose the automobile license plate extraction method using Discrete Cosin Transform and Correlation fem automobile image obtained through digital camera. The automobile license plate is consisted of the character and rectangle background of it. We extracted the automobile edge image by the DCT processing of automobile image and Obtained the automobile license plate from the automobile edge image by Correlation processing. We separated characters from automobile license plate using the projection histogram. Compare to the previous methods, we obtained the good result from extracting the automobile license plate at night, very strong light and bad weather.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.9B
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• pp.1570-1578
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• 2000

A quadrature pair of filter banks that are composed of a pair of cosine and sine modulated filter banks is applied to MC-CDMA data transmultiplexing in the view point of mitigating inter-channel interferences. Exploiting superior capabilities of wavelet properties in composing the filter banks the proposed scheme is capable of compromising inter-channel interference problems better than the conventional DFT-based MC-CDMA due to superior subchannelization effects. To verify the behavior of our proposed MC-CDMA system based on the quadrature filter banks the reverse-link bit error rates with respect to signal-to-noise ratio under Rayleigth fading and additive white Gaussian noise channel environments are computed. The results show an improved system performance over the conventional MC-CDMA in the view point of minimizing interference effects.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.10a
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• pp.907-910
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• 2019

본 연구에서는 X-ray 영상에서 비산란 그리드 장치의 영향으로 인한 아티팩트를 제거하기 위하여 이산코사인변환(DCT: discrete cosine transform) 기반의 주파수 분석 기법과 딥러닝 네트워크의 학습 기법을 상호 보완적으로 결합하는 방법론을 제안한다. 피사체의 특성에 따라 다양하게 나타나는 그리드 라인의 억제 기능을 학습하기 위하여 서로 다른 특성을 반영하는 3 종류의 학습데이터를 생성한다. 학습에 사용되는 그리드 라인 영상의 타겟 데이터를 산출하기 위하여 DCT 기반의 밴드스톱 필터링 기법을 사용하였으며 학습데이터의 양적인 부족을 해결하기 위하여 패치 기반의 학습 방법을 적용하였다. 제안된 방법에 대해 기존의 방법과 비교하여 피사체 경계선 영역에서 발생하는 성능저하 현상, 분할의 가장자리에서 발생하는 블로킹 현상, 배경 영상에서의 성능저하 현상 등을 상대적으로 개선할 수 있음을 실험적으로 평가하였다.

• Journal of Korea Society of Industrial Information Systems
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• v.15 no.3
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• pp.51-57
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• 2010

Steganography techniques can be used to hide data within digital images with little or no visible change in the perceived appearance of the image. I propose a steganalysis to detecting hidden message in sequential steganography. This paper presents adjusted technique for detecting abrupt jumps in the statistics of the stego signal during steganalysis. The repeated statistical test based on CUSUM-SPRT runs constantly until it reaches decision. In this paper, I deal with a new and improved statistic $g_t$ by computing $S^{t^*}_j$.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.6 no.2
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• pp.95-106
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• 2007

This paper proposes an effective tempo feature extraction method for music information retrieval. The tempo information is modeled by the narrow-band temporal modulation components, which are decomposed into a modulation spectrum via joint frequency analysis. In implementation, the tempo feature is directly extracted from the modified discrete cosine transform coefficients, which is the output of partial MP3(MPEG 1 Layer 3) decoder. Then, different features are extracted from the amplitudes of modulation spectrum and applied to different music information retrieval tasks. The logarithmic scale modulation frequency coefficients are employed in automatic music emotion classification and music genre classification. The classification precision in both systems is improved significantly. The bit vectors derived from adaptive modulation spectrum is used in audio fingerprinting task That is proved to be able to achieve high robustness in this application. The experimental results in these tasks validate the effectiveness of the proposed tempo feature.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.12
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• pp.2641-2646
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• 2011

In this paper, we studied that the EZW algorithm based in HWT was proposed effective compression technique of wavelet transformed image. The proposed Haar-EZW algorithm is that image was coding by zerotree coding technique using self-similarity of HWT coefficients. If the HWT coefficient is larger than the threshold, that is coding to POS. If the HWT coefficient is smaller than the threshold, that is coding to NEG. If the HWT coefficient is larger than the root of zerotree, that is coding to ZTR. If the HWT coefficient is smaller then the threshold, and if that is not the root of zerotree, that is coding to IZ. This process is repeated until all the HWT coefficients have been encoded completely. This paper is compared Haar-EZW algorithm with Daubechies and Antonini. As the results of compare, it is shown that the PSNR of the Haar-EZW algorithm is better than Daubechies's and Antonini's.

• Journal of KIISE:Software and Applications
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• v.33 no.11
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• pp.936-941
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• 2006

To apply object recognition techniques to real environment, illumination compensation method should be developed. As effective illumination compensation model, we focused our attention on Retinex model and illumination-Reflectance model, implemented them, and experimented on their performance. We implemented Retinex model with Single Scale Retinex, Multi-Scale Retinex, and Retinex Neural Network and Multi-Scale Retinex Neural Network, neural network model of Retinex model. Also, we implemented illumination-Reflectance model with reflectance image calculation by calculating an illumination image by low frequency filtering in frequency domain of Discrete Cosine Transform and Wavelet Transform, and Gaussian blurring. We compare their illumination compensation performance to facial images under nine illumination directions. We also compare their performance after post processing using Principal Component Analysis(PCA). As a result, illumination Reflectance model showed better performance and their overall performance was improved when illumination compensated images were post processed by PCA.