• Proceedings of the Acoustical Society of Korea Conference
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• autumn
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• pp.201-204
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• 2000

음성신호에 섞인 잡음을 처리하기 위해서 단 일 마이크로폰을 이용한 방법이 많이 연구되고 있는데, 그 중에서 Kalman 필터를 이용한 방법은 먼저 음성신호의 모델을 검출하고 잡음이 섞인 신호에서 표준 Kalman 필터를 이용해서 음성신호 성분만을 검출하게 된다. 본 논문에서는 음성신호에 섞인 유색잡음을 백색화하는 방법을 적용하여 Kalman 필터의 잡음제거 성능을 향상시키는 방법을 제안하였다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.4
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• pp.817-822
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• 2011

This paper first proposes the speech recognition algorithm by detection of the speech and noise sections at each frame using a neural network training by back-propagation algorithm, then proposes the spectral subtraction method which removes the noises at each frame according to detection of the speech and noise sections. In this experiment, the performance of the proposed recognition system was evaluated based on the recognition rate using various speeches that are degraded by white noise and car noise. Moreover, experimental results of the noise reduction by the spectral subtraction method demonstrate using the speech and noise sections detecting by the speech recognition algorithm at each frame. Based on measuring signal-to-noise ratio, experiments confirm that the proposed algorithm is effective for the speech by corrupted the noise using signal-to-noise ratio.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.3
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• pp.598-604
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• 2012

Image signal is corrupted by various noises in image processing, many studies are being accomplished to restore those images. In this paper, we proposed a cascade filter algorithm for removing random valued impulse noise. The algorithm consists two steps that noise detection and noise elimination. Variance of filtering mask and center pixel variance are calculated for noise detection, and the noise pixel is replaced by estimated value which first apply switching self adaptive weighted median filter and finally processed by modified weight filter. Considering the proposed algorithm only remove noise and preserve the uncorrupted information that the algorithm can not only remove noise well but also preserve edge.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.6A
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• pp.562-567
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• 2002

Noise predictive maximum likelihood(NPML) detector embeds noise predictions/ whitening process in branch metric calculation of Viterbi detector and improves the reliability of branch metric computation. Therefore, PRML detector with a noise predictor achieves some performance improvement and has an advantage of low complexity. This paper shows that NP(1221)ML system through noise predictive PR-equalized signal has less complexity and better performance than high order PR(12321)ML system in high density perpendicular magnetic recording. The simulation results are evaluated using (1) random sequence and (2) run length limited (1,7) sequence, and they are applied to linear channel and nonlinear channel with normalized linear density $1.0{\leq}K_p{\leq}3.0$.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.3C
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• pp.336-342
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• 2003

Noise predictive maximum likelihood(NPML) detector embeds noise prediction/whitening process in branch metric calculation of Viterbi detector and improves the reliability of branch metric computation. Therefore, PRML detector with a noise predictor achieves some performance improvement and has an advantage of low complexity. This thesis random sequences are applied to linear channel. In perpendicular magnetic recording density KP=2.5, NP(121)ML and NP(1221)ML detection system which is based on a noise predictive PR-equalized signal are evaluated by the Performance through a computing simulation. Therefore, NPML systems are implemented and are verified by VHDL.

• Journal of Korea Multimedia Society
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• v.17 no.3
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• pp.312-323
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• 2014

Voice activity detection is very important process that find voice activity from noisy speech signal for noise cancelling and speech enhancement. Over the past few years, many studies have been made on voice activity detection, it has poor performance for speech signal of sentence form in a low SNR environment. In this paper, it proposed new voice activity detection algorithm that has beginning VAD process using entropy and main VAD process using fuzzy membership shifted c-means clustering. We conduct an experiment in various SNR environment of white noise to evaluate performance of the proposed algorithm and confirmed good performance of the proposed algorithm.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.1
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• pp.97-103
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• 2012

In this paper, we propose a novel voice activity detection (VAD) algorithm to effectively distinguish speech from nonspeech in various noisy environments. Global speech absence probability (GSAP) derived from likelihood ratio (LR) based on the statistical model is widely used as the feature parameter for VAD. However, the feature parameter based on conventional GSAP is not sufficient to distinguish speech from noise at low SNRs (signal-to-noise ratios). The presented VAD algorithm utilizes GSAP based on Teager energy (TE) as the feature parameter to provide the improved performance of decision for speech segments in noisy environment. Performances of the proposed VAD algorithm are evaluated by objective test under various environments and better results compared with the conventional methods are obtained.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2016.06a
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• pp.361-363
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• 2016

현재 차량 내 운전자에게 편의성과 안전성을 제공하는 시스템이 활발히 개발 중이고 향후 ADAS(Advanced Driver Assistance System)와 스마트 자동차에서 영상 정보를 이용한 물체 추적과 분석은 매우 중요한 부분을 차지하고 있다. 영상에서 얻을 수 있는 정보 중 현재 도로의 이정표 정보는 중요한 분석 정보로 사용된다. 하지만 국내 도로표지판 검출 연구의 경우 유럽과 북미와 비교하여 연구 개발이 활발히 진행되고 있지 않다. 국내의 경우 도로 이정표에서 영문자뿐만 아니라 한글 문자 정보까지 포함하고 있어 검출이 쉽지 않다. 또한 비교적 밝고 잡음이 적은 검출하기 좋은 환경에서는 검출이 잘 되지만 명암이 뚜렷하지 않고 잡음이 많은 환경에서는 도로 이정표 문자 검출이 어렵다. 이에 본 논문에서는 CLAHE(Contrast-Limited Adaptive Histogram Equalization) 방법을 적용하여 영상이 어둡고 잡음이 많은 환경에서 국내 도로 이정표의 문자 정보를 얻는다. 실험 결과, 기존 방법에 비해 문자 영역 검출 성능이 향상되었다.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.4
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• pp.9-15
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• 2009

This paper proposes a cancellation algorithm of impulse noise using a rank-order method. The proposed method is a fast and simple algorithm that is composed of two parts. The first part involves noise detection using a fuzzy technique, where an image is divided into RGB color channels. Then every pixel in each color channel is investigated and assigned a probability indicating its chances of being a noise pixel. At this time, the rank order method using a noise-detection mask is utilized for accurate noise detection. Thereafter, the second part involves noise-cancellation, where each noise-pixel value in an image is replaced in proportion to its fuzzy probability. Through the experiments, both the conventional and proposed methods were simulated and compared. As a result, it is shown that proposed method is able to detect noisy pixels more accurately, and produce resulting images with high PSNR values.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2012.11a
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• pp.246-248
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• 2012

심전도는 측정 기기에서 발생하는 전기적 잡음이나 근육에서 발생하는 근전도에 의한 잡음, 전극을 부착한 사람의 움직임에 의한 동잡음 등에 민감한 특성을 보인다. 또한 심장의 이상으로 인하여 왜곡이 심하게 발생하므로 심전도에서 의미 있는 구간을 검출하기 위해서는 이들을 보완하는 알고리즘이 필수적이라 할 수 있다. 논문에서는 심전도 분석의 보조를 위하여 입력된 심전도가 가지는 잡음과 왜곡을 제거하고 구간의 위치를 출력하는 시스템을 제안한다. 이를 위해 관련 알고리즘 중, 가장 널리 알려진 'Pan & tompkins algorithm'을 시스템에 이식하였고 알고리즘의 각 단계를 알아보기 쉽게 출력하는 인터페이스를 구성하였다. 시스템의 기능을 확인하기 위해 MIT/BIH 데이터베이스를 이용하였으며, 잡음과 왜곡이 심하여 육안으로 구간을 확인하기 힘든 심전도에서도 높은 구간검출 정확도를 확인할 수 있었다.