• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.257-260
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• 1993

A new method of spindle waveform detection is presented for the automated analysis of sleep EEG. The method is based on the combined application of signal conditioning in the time-domain and local spectrum analyzing in the frequency-domain. The overall detection system is implemented and, tested in real-time with a total of 24 hour data obtained from four subjects. The result shows an average agreement of 86.7% with the visually inspected result.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.1127-1130
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• 1999

In this paper, using one method of Additive Synthesis, Analysis-by-synthesis/Overlap-Add (ABS/OLA) method, analysis and synthesis of musical tones is processed. But peak detection of frequency domain is processed by proposed method considering the view of acoustics. It is that that harmonics frequency is times of main frequency. Using this fact, peak detection of frequency domain is useful for detection of tonal component identified musical note. It is possible to realize high-quality lour bit rate audio.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.7
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• pp.1618-1631
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• 1994

In this paper, in-process chatter detection methodology which utilizes nondimensional characteristic variables is introduced. To obtain nondimensional chatter detection indexes which are constant regardless of the cutting conditions during machining with the same tool and workpiece material, both the cutting forces and accelerations are measured and processed in time and frequency domain. The indexes are calculated from the present and past value of the acceleration and cutting force signals in time and frequency domain. The chatter is identified when these chatter detection indexes are bigger than the threshold which is decided by preliminary experiments. The experiment shows that these indexes works very well in-process chatter detection.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.14 no.10
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• pp.1079-1088
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• 2003

In this paper, we propose a high-resolution time-frequency domain reflectometry technique as a methodology of detection and estimation of faults on a wire. This method adopts the time-frequency cross correlation characteristics of the observed signal in both time and frequency domains simultaneously. The accuracy of the proposed method is verified with experiments using a RG type coaxial cable and comparing it with traditional time domain as well as frequency domain reflectometry methods. It is clearly shown here that the proposed algorithm produces excellent results compared to the conventional methods for single as well as multiple fault cables.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.6
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• pp.620-627
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• 2016

This paper proposes an advanced detection technique for cable fault by eliminating the sign of reference signal in STDR(sequence time-domain reflectometry) and SSTDR(spread-spectrum time-domain reflectometry). The proposed fault-detection technique can eliminate the reference signal more effectively than the conventional one since the sign detector can approximately recover the distorted reference signal by cable and connector, and consequently, can detect the reflected signal by fault more effectively than the conventional one. Especially, it is shown that the error rate of proposed technique can be significantly lower than the conventional one in the case of far fault simulation.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.21 no.6
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• pp.635-641
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• 2010

Time-varying channel characteristics in OFDM systems over doubly selective channels cause inter-carrier interferences(ICI) in the frequency domain. Time domain windowing gives rise to restriction on the bandwidth of the frequency domain channel matrix and makes it possible to approximate the OFDM system as a simplified linear input-output model. When successive interference cancellation based on linear MMSE estimation is employed for channel equalization in OFDM systems, symbol detection ordering produces considerable effects on overall system performances. In this paper, we show the reduction of the residual ICI by time domain windowing and the resultant performance improvements, and investigate the effects of SINR- and CSEP-based symbol detection ordering on the performance of successive interference cancellation.

• Proceedings of the IEEK Conference
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• 2003.07d
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• pp.1527-1530
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• 2003

Video is an important and challenge media and requires sophisticated indexing schemes for efficient retrieval from visual databases. Scene change detection is the first step for automatic indexing of video data. Recently, several scene change detection algorithms in the pixel and compressed domains have been reported in the literature. However, using pixel methods are computationally complex and are not very robust in detecting scene change detection. In this paper, we propose robust abrupt scene change detection using macroblock type and DC coefficient. Experimental results show that the proposed algorithm is robust for detection of most abrupt scene changes in the compressed domain.

• Journal of Korea Multimedia Society
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• v.8 no.6
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• pp.783-789
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• 2005

This paper is proposed a watermarking technique for copyright protection of multimedia contents. We proposed adaptive watermark detection algorithm using stochastic perceptual model and statistical decision method in DMWT(discrete multi wavelet transform) domain. The stochastic perceptual model calculates NVF(noise visibility function) based on statistical characteristic in the DMWT. Watermark detection algorithm used the likelihood ratio depend on Bayes' decision theory by reliable detection measure and Neyman-Pearson criterion. To reduce visual artifact of image, in this paper, adaptively decide the embedding number of watermark based on DMWT, and then the watermark embedding strength differently at edge and texture region and flat region embedded when watermark embedding minimize distortion of image. In experiment results, the proposed statistical decision method based on multiwavelet domain could decide watermark detection.

• The Transactions of the Korea Information Processing Society
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• v.6 no.6
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• pp.1703-1712
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• 1999

In the paper, we propose efficient article and scene change detection algorithms to make the index of sports news compressed in MPEG-2 domain. In the proposed algorithm, the information in MPEG-2 compressed domain is directly used without decoding to save the computation time. The scene change detection algorithm is constructed in an hierarchical method so that the time for detection can be greatly reduced. Also, the algorithm can provide the robust detection against abrupt illuminance change because the luminance and chrominance components are simultaneously considered. Also, the scene change caused by special effect such as dissolve and wipe can be detected in the compressed domain. In the article detection, the algorithm is constructed for robust detection of the anchor frame using the concept of CCV(Color Coherent Vector).

• The Journal of the Korea Contents Association
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• v.10 no.1
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• pp.19-26
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• 2010

This paper proposes a classifier based on rectangular feature to detect face in real time. The goal is to realize a strong detection algorithm which satisfies both efficiency in calculation and detection performance. The proposed algorithm consists of the following three stages: Feature creation, classifier study and real time facial domain detection. Feature creation organizes a feature set with the proposed five rectangular features and calculates the feature values efficiently by using SAT (Summed-Area Tables). Classifier learning creates classifiers hierarchically by using the AdaBoost algorithm. In addition, it gets excellent detection performance by applying important face patterns repeatedly at the next level. Real time facial domain detection finds facial domains rapidly and efficiently through the classifier based on the rectangular feature that was created. Also, the recognition rate was improved by using the domain which detected a face domain as the input image and by using PCA and KNN algorithms and a Class to Class rather than the existing Point to Point technique.