• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.57-60
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• 2003

We have proposed the adaptive noise reduction algorithm using the MDFT. The algorithm proposed use the linear prediction coefficients of the AR method based on Sign algorithm that is the modified LMS instead of the least mean square(LMS). The signals with a random noise tracking performance are examined through computer simulations and confirmed that the high speed adaptive noise reduction processing system is realized with rapid convergence.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2014.06a
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• pp.179-180
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• 2014

The main goal of this paper is to present an adaptive filter system using NLMS(Normalized Least mean square) adaptive algorithm for noise cancellation. The proposed algorithm has less computational complexity and better convergence property than the former algorithms like spectral subtraction algorithm, etc. We use TIMIT criterion voice and Noisex-92 for the experiment. The experimental result shows the feasibility of our algorithm for filtering noise from voice effectively.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.46 no.11
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• pp.32-39
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• 2009

In this thesis, design effective elimination interference algorithm of ICS repeat system for repeater that improve frequency efficiency. Gennerally, LMS Algorithm apply to ICS repeat system. Error convergence speed and accuracy of LMS Algorithm are influenced by reference signal. For improve LMS Algorithm, suggest Adaptive searching channel estimate algorithm. For using channel characteristic, adaptive searching channel estimate algorithm make reference signal similar interference signal by convolution operation and complement LMS algorithm demerit. For make channel similar pratical channel, apply Jake's Rayleigh multi-path model. LMS algorithm and suggested adaptive searching channel estimate algorithm that have 16 taps apply to ICS repeat system under Rayleigh multi-path channel, so simulate with MATLAB. According to simulate, ICS repeat system with LMS algorithm show -40 dB mean square error convergent after 110 datas iteration and ICS repeat system with adaptive searching channel estimate algorithm show -80 dB mean square en-or convergent after 120 datas iteration. Analyze simulation result, suggested adaptive searching channel estimate algorithm show 40 dB accuracy than LMS algorithm.

• The Journal of Information Systems
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• v.14 no.3
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• pp.117-122
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• 2005

This paper presents a method for detecting scene changes in video sequences, in which the $chi^{2}$-test is modified by imposing weights according to NTSC standard. To automatically determine threshold values for scene change detection, the proposed method utilizes the frame differences that are obtained by the weighted $chi^{2}$-test. In the first step, the mean and the standard deviation of the difference values are calculated, and then, we subtract the mean difference value from each difference value. In the next step, the same process is performed on the remained difference values, mean-subtracted frame differences, until the stopping criterion is satisfied. Finally, the threshold value for scene change detection is determined by the proposed automatic threshold estimation algorithm. The proposed method is tested on various video sources and, in the experimental results, it is shown that the proposed method is reliably estimates the thresholds and detects scene changes.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.10a
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• pp.649-650
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• 2010

This paper construct the sensibility database by extracting sensibility of 28 colors based on 12 color wheel. And, after the large color values are grouped by clustering of input image using k-mean algorithm, sensibility was extracted by matching with color and database. Also, we see the color sensible psychology of child using color distribution of children in painting.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.11
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• pp.2733-2737
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• 2014

Motion detection according to the movement and the change area detection method according to the background difference and the motion history image for use in a motion estimation technique using a real-time image, the motion detection method according to the optical flow, the back-projection of the histogram of the object to track for motion tracking At the heart of MeanShift center point of the object and the object to track, while used, the size, and the like due to the motion tracking algorithm CamShift, Kalman filter to track with direction. In this paper, we implemented the motion detection algorithm based on color and shape information of the object and verify.

• The Journal of the Acoustical Society of Korea
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• v.15 no.3E
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• pp.66-73
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• 1996

In this paper, we propose the filtered-x least mean fourth (LMF) algorithm where the error raised to the power of four is minimized and analyze its convergence behavior for a multiple sinusoidal acoustic noise and Gaussian measurement noise. Application of the filtered-x LMF adaptive filter to active noise control(ANC) requires estimating of the transfer characteristic of the acoustic path between the output and error signal of the adaptive controller. The results of the convergence analysis of the filtered-x LMF algorithm indicates that the effects of the parameter estimation inaccuracy on the convergence behavior of the algorithm are characterized by two distinct components : Phase estimation error and estimated gain. In particular, the convergence is shown to be strongly affected by the accuracy of the phase response estimate. Also, we newly show that convergence behavior can differ depending on the relative sizes of the Gaussian measurement noise and convergence constant.

• Proceedings of the Korean Information Science Society Conference
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• 2006.06b
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• pp.388-390
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• 2006

This paper presents an object tracking with radical change of color. Conventional Mean Shift do not provide appropriate result when major color distribution disappear. Our tracking approach is based on Mean Shift as basic tracking method. However we propose tracking algorithm that shows good results for an object of radical variation. The key idea is iterative update previous color information of an object that shows different color by using EM algorithm. As experiment results, we show that our proposed algorithm is an effective approach in tracking for a real object include an object having radical change of color.

• Proceedings of the Acoustical Society of Korea Conference
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• 1985.10a
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• pp.87-94
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• 1985

In this paper, enhancement of speech corrupted by additive white or colored noise is stuided. The nuconstrained frequency-domain block least-mean-square (UFBLMS) adaptation algorithm and its frequency-weighted version are newly applied to speech enhancement. For enhancement of speech degraded by white noise, the performance of the UFBLMS algorithm is superior to the spectral subtraction method or Wiener filtering technique by more than 3 dB in segmented frequency-weighted signal-to-noise ratio(FWSNERSEG) when SNR of speech is in the range of 0 to 10 dB. As for enhancement of noisy speech corrupted by colored noise, the UFBLMS algorithm is superior to that of the spectral subtraction method by about 3 to 5 dB in FWSNRSEG. Also, it yields better performance by about 2 dB in FWSNR and FWSNRSEG than that of time-domain least-mean-square (TLMS) adaptive prediction filter(APF). In view of the computational complexity and performance improvement in speech quality and intelligibility, the frequency-weighted UFBLMS algorithm appears to yield the best performance among various algorithms in enhancing noisy speech corrupted by white or colored noise.

• The Journal of the Acoustical Society of Korea
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• v.17 no.3E
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• pp.43-46
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• 1998

Many of the active noise control system utilize a form of the least mean square(LMS) algorithm. This paper discusses the dependence of the convergence rate on the acoustic error path in the popular algorithm which is conventional "filtered-x LMS" and introduces new algorithm "constrained filtered-x LMS". The proposed method increase the convergence region regardless of the time-delay in the acoustic error path. In the algorithms, coefficients of the controller are adapted using the residuals of constrained structure which are defined in such a way that the control process become stationary. Advantages of constrained filtered-x LMS algorithm is illustrated by convergence analysis in the mean sense.