• Journal of Information Processing Systems
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• v.16 no.3
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• pp.557-571
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• 2020

The existing methods for detection of fire smoke in a video easily lead to misjudgment of cloud, fog and moving distractors, such as a moving person, a moving vehicle and other non-smoke moving objects. Therefore, an algorithm for detection of fire smoke in a video based on wavelet energy slope fitting is proposed in this paper. The change in wavelet energy of the moving target foreground is used as the basis, and a time window of 40 continuous frames is set to fit the wavelet energy slope of the suspected area in every 20 frames, thus establishing a wavelet-energy-based smoke judgment criterion. The experimental data show that the algorithm described in this paper not only can detect smoke more quickly and more accurately, but also can effectively avoid the distraction of cloud, fog and moving object and prevent false alarm.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.25 no.5
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• pp.73-78
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• 2011

We developed a noise reduction algorithm for the measurement accuracy improvement of a fiber-optic distributed temperaure sensor system. The denoising technique is based on the wavelet transform. The proposed algorithm was applied to a FBG sensor output with the Gaussian line-fitting algorithm to minimize the output noise which originated from the intensity noise of the laser light source and the instability of signal porcessing. We confirmed the feasibility of the denoising algorithm by comparing the measurement results with those obtained with the Gaussian line-fitting algorithm only.

• Proceedings of the Acoustical Society of Korea Conference
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• autumn
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• pp.85-88
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• 1999

Adapted Local Trigonometric Transforms은 매우 높은 energy compaction을 가지므로 음성 및 영상신호에 이용하려는 시도가 이루어지고 있다. [1] 그러나 이 경우 복원 된 신호에는 시간 영역에서 불연속점이 발생하여 일종의 tick noise가 발생한다. 또한 phase성분을 잃게 되어 금속성 잡음도 추가하여 나타난다. 본 논문에서는 이러한 문제점을 해결하기 위한 Polynomial fitting 방식과 Wavelet Packet Transforms 방식을 제안한다. Polynomial fitting 방식으로는 시간축상에서 발생하는 문제를 해결하고 Wavelet Packet Transforms으로 Phase 문제를 해결한다. [2,3] 실험결과, 압축이전의 신호와 비교할 때 SNR에 있어서 개선을 보이며 tick noise와 금속성 잡음이 제거된 개선된 신호음을 확인 할 수 있었다.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.294-294
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• 2000

In this paper, we would like to discuss the signal processing and the algorithm for ECG analysis. The ECG gives us information about the condition of the heart muscle, because myocardial abnormality or infarction is inscribed on the ECG during myocardial depolarization and repolarization. Analyzing the ECG signal, we can find heart disease, for example, arrhythmia and myocardial infarction, etc. Particularly, detecting arrhythmia is more important, because serious arrhythmia can take away the life from patients within ten minutes. The wavelet transform decomposes the ECG signal into high and low frequency component using wavelet function. Recomposing high frequency bands including QRS complex, we can detect QRS complex and eliminate the noise from the original ECG signal. To recognize the ECG signal pattern, we adopted the curve-fitting partially and statistical method. The ECG signal is divided into small parts based on QRS complex, and then, each part is approximated to the polynomials. Comparing the approximated ECG pattern with some kinds of heart disease ECG pattern, we can detect and classify the kind of heart disease.

• Proceedings of the KIEE Conference
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• 2003.11a
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• pp.88-90
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• 2003

In this paper, an algorithm to compensate the distorted signals due to CT(Current Transformer) saturation is suggested. Firstly, WT(Wavelet Transform) is used to detect a start point and an end point of saturation. Filter banks which can be easily realized in real-time applications are employed in detecting CT saturation. Secondly, least-square curve fitting method is used to restore the distorted section of the secondary current. Fault simulations are performed on a power system model using EMTP(Electromagnetic Transient Program). A series of test results indicate that WT has superior detection accuracy and the proposed algorithm which shows very stable features under various levels of remanent flux is also satisfactory.

• Journal of Magnetics
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• v.9 no.3
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• pp.69-74
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• 2004

A method of processing signals of unaligned geomagnetic sensors placed on the seabed is presented. The offset drifts of the fluxgate sensors are processed by polynomial fitting and the orientations of the sensor axes are found by minimizing the noise power using wavelet analysis. The noise power was reduced by 9.1 dB by processing the components of magnetic field separately using subtraction filter, polynomial fitting and wavelet analysis.

• The Journal of the Acoustical Society of Korea
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• v.25 no.4E
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• pp.154-158
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• 2006

In this paper, we suggest a noise estimation method for speech enhancement in nonstationary noisy environments. The proposed method consists of the following two main processes. First, in order to receive fewer affect of variable signals, a best fitting regression line is used, which is obtained by applying a least squares method to coefficient magnitudes in a node with a uniform wavelet packet transform. Next, in order to update the noise estimation efficiently, a differential forgetting factor and a correlation coefficient per subband are used, where subband is employed for applying the weighted value according to the change of signals. In particular, this method has the ability to update the noise estimation by using the estimated noise at the previous frame only, without utilizing the statistical information of long past frames and explicit nonspeech frames by voice activity detector. In objective assessments, it was observed that the performance of the proposed method was better than that of the compared (minima controlled recursive averaging, weighted average) methods. Furthermore, the method showed a reliable result even at low SNR.

• Analytical Science and Technology
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• v.27 no.1
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• pp.41-59
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• 2014

The aims of this work were the identification and the classification of fresh lubricants and used engine oils of vehicles for the application in forensic science field-80 kinds of fresh lubricants were purchased and 86 kinds of used engine oils were sampled from 24 kinds of diesel and gasoline vehicles with different driving conditions. The sample of lubricants and used engine oils were analyzed by GC/MS. The Bayesian model technique was developed for classification or identification. Both the wavelet fitting and the principal component analysis (PCA) techniques as a data dimension reduction were applied. In fresh lubricants classification, the rates of matching by Bayesian model technique with wavelet fitting and PCA were 97.5% and 96.7%, respectively. The Bayesian model technique with wavelet fitting was better to classify lubricants than it with PCA based on dimension reduction. And we selected the Bayesian model technique with wavelet fitting for classification of lubricants. The other experiment was the analysis of used engine oils which were collected from vehicles with the several mileage up to 5,000 km after replacing engine oil. The eighty six kinds of used engine oil sample with the mileage were collected. In vehicle classification (total 24 classes), the rate of matching by Bayesian model with wavelet fitting was 86.4%. However, in the vehicle's fuel type classification (whether it is gasoline vehicle or diesel vehicle, only total 2 classes), the rate of matching was 99.6%. In the used engine oil brands classification (total 6 classes), the rate of matching was 97.3%.

• Journal of Urban Science
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• v.6 no.2
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• pp.49-57
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• 2017

A new Fiber Bragg Grating (FBG) wavelength demodulation scheme is studied in the paper, which consists of an improved de-noising method and Gaussian fitting peak searching algorithm. The improved translational invariant wavelet without threshold adjust factor is proposed to get a better de-noising performance for FBG sensor signal and overcome the drawbacks of soft or hard threshold wavelets. In order to get a high wavelength demodulation precision of FBG sensor signal, this de-noising method is designed to combine with Gaussian fitting peak searching algorithm. The simulation results show that the wavelength maximum measurement error is lower than 1pm, and can get a much higher accuracy.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.7
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• pp.1469-1474
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• 2004

A wavelet-based image watermarking scheme is proposed, based on the insertion of pseudo-random codes in the frequency domain. The original image is required for the watermark detection. The 'strength' of the signature to be embedded depends on the image to be marked, thus fitting signal capacity. The experimental results prove that the method is more tamper resistant and less perceptible for any type of images than other well-known private methods in the frequency domains.