• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.6
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• pp.737-742
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• 2003

In this paper, we propose a new wavelet-based fuzzy modeling using a DNA coding method. Generally, it is well known that the DNA coding method is more diverse in the knowledge expression and better in the optimization performance than the genetic algorithm (GA) because it can encode more plentiful genetic information based on the biological DNA. The proposed method makes a fuzzy model by using the wavelet transform, in which coefficients are identified by the DNA coding method. Thus we can effectively get the fuzzy model of nonlinear system by using the advantages of both wavelet transform and DNA coding method. In order to demonstrate the superiority of the proposed method, it is compared with the GA.

• Journal of the Korea institute for structural maintenance and inspection
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• v.12 no.6
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• pp.140-146
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• 2008

The damage evaluation method for framed structures using continuous wavelet transform (CWT) is proposed. CWT is applied to the response acceleration of a structure subjected to earthquake load to decompose the response acceleration corresponding to each scale, then the normalized energy value for each scale is calculated. The difference between the normalized energy curvature (NEC) in each node before and after damage indicates a damaged element, which makes it possible to assess the soundness of structural elements. As damage becomes more severe the difference in normalized energy curvature becomes larger. The NEC calculated from the signal corresponding to high scale in CWT analysis is found to be a good index that shows the location and severity of damage.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.19 no.7
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• pp.726-735
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• 2009

In this paper, we propose an approach to signal model-based fault detection and diagnosis system for induction motors. The current fault detection techniques used in the industry are limit checking techniques, which are simple but cannot predict the types of faults and the initiation of the faults. The system consists of two consecutive processes: fault detection process and fault diagnosis process. In the fault detection process, the system extracts the significant features from sound signals using combination of variance, cross-correlation and wavelet. Consequently, the pattern classification technique is applied to the fault diagnosis process to recognize the system faults based on faulty symptoms. The sounds generated from different kinds of typical motor's faults such as motor unbalance, bearing misalignment and bearing loose are examined. We propose two approaches for fault detection and diagnosis system that are waveletand-variance-based and wavelet-and-crosscorrelation-based approaches. The results of our experiment show more than 95 and 78 percent accuracy for fault classification, respectively.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.10
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• pp.2317-2328
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• 1997

The objective of this paper is to develop an algorithm for a real-time automatic fingerprint recognition system. The algorithm employs the wavelet transform(WT) and the dominat local orientation that derived from the gradient Gaussian(GoG) and coherence in determining the directions of ridges in fingerprint images. By using the WT, the algorithm does not require conventional preprocessing procedures such as smothing, binarization, thining and restoration. For recognition, two fingerprint images are compared in three different ST domains;one that represents the original image compressed to quarter(LL), another that shows vertical directional characteristic(LH), and third as the block that contains horizontal direction(HL) in WT domain. Each block has dominat local orientation that derived from the GoG and coherence. The proposed algorithm is imprlemented on a SunSparc-2 workstation under X-window environment. Our simulation results, in real-time have shown that while the rate of Type II error-Incorrect recognition of two identical fingerprints as the identical fingerprints-is held at 0%, the rate of Type I error-Incorrect recognitionof two identical fingerprints as the different ones-is 2.5%.

• Journal of the Institute of Convergence Signal Processing
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• v.7 no.4
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• pp.169-177
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• 2006

In this paper, we present an efficient image reconstruction method which is suited to remove various noise generated from measurement using X-ray attenuation. To be specific, we present a wavelet method to efficiently remove ring artifacts, which are caused by inevitable mechanical error in X-ray emitters and detectors. and streak artifacts, which are caused by general observation errors and Fourier transform-based reconstruction process. To remove ring artifacts related noise from projections, we suggest to estimate the noise intensity by using the fact that the noise related to ring artifacts has a strong correlation in the angle direction, and remove them by using wavelet shrinkage. We also suggest to use wavelet-vaguelette decomposition for general-purpose noise removal and image reconstruction. Through simulation studies. we show that the proposed method provides a better result in ring artifact removal and image reconstruction over the traditional Fourier transform-based methods.

• The Korean Journal of Applied Statistics
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• v.24 no.2
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• pp.359-371
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• 2011

Edge detection in images is an important step in image segmentation and object recognition as preprocessing for image processing. This paper presents a new edge detection using local histogram analysis based on wavelet transform. In this work, the wavelet transform uses three components (horizontal, vertical and diagonal) to find the magnitude of the gradient vector, instead of the conventional approach in which tw components are used. We compare the magnitude of the gradient vector with the threshold that is obtained from a local histogram analysis to conclude that an edge is present or not. Some experimental results for our edge detector with a Sobel, Canny, Scale Multiplication, and Mallat edge detectors on sample images are given and the performances of these edge detectors are compared in terms of quantitative and qualitative measures. Our detector performs better than the other wavelet-based detectors such as Scale Multiplication and Mallat detectors. Our edge detector also preserves a good performance even if the Sobel and Canny detector are sharply low when the images are highly corrupted.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.11a
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• pp.295-298
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• 2009

웨이블렛 변환(Wavelet Transform)은 영상압축에 효율적인 방법으로 알려져 있으며 lifting scheme을 이용해서 쉽게 구현이 가능하다. 가장 널리 쓰이는 방법으로는 Daubechies 5/3 필터가 있고, 이를 바탕으로 하여 영상의 기하학적인 특성을 이용한 적응적 예측 방법이 많이 소개되었다. 본 논문에서는 적응적 예측을 위해 템플릿 매칭을 적용한 새로운 알고리즘을 제안하였다.

• The Journal of the Korea institute of electronic communication sciences
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• v.5 no.3
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• pp.309-314
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• 2010

In this paper, an intelligent security camera over internet is proposed. Among ISC methods, watersheds based methods produce a good performance in segmentation accuracy. But traditional watershed transform has been suffered from over-segmentation due to small local minima included in gradient image that is input to the watershed transform. And a zone face candidates of detection using skin-color model. last step, face to check at face of candidate location using SVM method. It is extract of wavelet transform coefficient to the zone face candidated. Therefore, it is likely that it is applicable to read world problem, such as object tracking, surveillance, and human computer interface application etc.

• The Journal of the Acoustical Society of Korea
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• v.22 no.8
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• pp.717-726
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• 2003

This paper presents the methods that design the Wavelet-based pitch detector for 2,4 kbps Harmonic-CELP Coder, and that achieve the effective waveform interpolation by decision window shape of the transition region, Waveform interpolation coder operates by encoding one pitch-period-sized segment, a prototype segment, of speech for each frame, generate the smooth waveform interpolation between the prototype segments for voiced frame, But, harmonic synthesis of the prototype waveforms between previous frame and current frame occur not only waveform errors but also discontinuity at frame boundary on that case of pitch halving or doubling, In addtion, in transition region since waveform interpolation coder synthesizes the excitation waveform by using overlap-add with triangularity window, therefore, Harmonic-CELP fail to model the instantaneous increasing speech and synthesis waveform linearly increases, First of all, in order to detect the precise pitch period, we use the hybrid 1st pitch detector, and increse the precision by using 2nd ACF-pitch detector, Next, in order to modify excitation window, we detect the onset, offset of frame by GCI, As the result, pitch doubling is removed and pitch error rate is decreased 5.4% in comparison with ACF, and is decreased 2,66% in comparison with wavelet detector, MOS test improve 0.13 at transition region.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.37 no.1
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• pp.49-58
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• 2000

This paper presents a new color Image coding method which estimates color component Images from luminance image using spectral correlation m wavelet transformed domain More specifically, the wavelet transform is performed to the luminance image(Y), and then, for an efficient quad-tree division to encompass the varying block size, a cost function IS defined using high frequency coefficients generated by wavelet decomposition Next, a scale factor and an offset factor for each the block to minimize the estimation error between luminance image(Y) and R, B Images, are iteratively calculated With respect to the varying block size With associated cost function.