• The Transactions of the Korea Information Processing Society
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• v.7 no.7
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• pp.2238-2245
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• 2000

In this papr, eatue parameters, extracted using Wavelet transform for Korean isolated worked speech, are sued for speech detection and recognition feature. As a result of the speech detection, it is shown that it produces more exact detection result than eh method of using energy and zero-crossing rate on speech boundary. Also, as a result of the method with which the feature parameter of MFCC, which is applied to he recognition, it is shown that the result is equal to the result of the feature parameter of MFCC using FFT in speech recognition. So, it has been verified the usefulness of feature parameters using Wavelet transform for speech analysis and recognition.

• The Journal of the Acoustical Society of Korea
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• v.18 no.6
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• pp.57-64
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• 1999

In this paper, we investigated the robust endpoint detection algorithm in noisy environment. A new feature parameter based on a discrete wavelet transform is proposed for word boundary detection of isolated utterances. The sum of standard deviation of wavelet coefficients in the third coarse and weighted first detailed scale is defined as a new feature parameter for endpoint detection. We then developed a new and robust endpoint detection algorithm using the feature found in the wavelet domain. For the performance evaluation, we evaluated the detection accuracy and the average recognition error rate due to endpoint detection in an HMM-based recognition system across several signal-to-noise ratios and noise conditions.

• Journal of the Semiconductor & Display Technology
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• v.17 no.2
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• pp.26-31
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• 2018

In this paper, surface defects and typical illumination mechanisms for steel plates are analyzed, and then optimum illumination mechanism is selected using discrete wavelet transform (DWT) synthetic images and discriminant measure (DM). The DWT synthetic images are generated using component images decomposed by Haar wavelet transform filter. The best synthetic image according to surface defects is determined using signal to noise ratio (SNR). The optimum illumination mechanism is selected by applying discriminant measure (DM) to the best synthetic images. The DM is applied using the tenengrad-euclidian function. The DM is evaluated as the degree of contrast using the defect boundary information. The performance of the optimum illumination mechanism is verified by quantitative data and intuitive image looks.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.3
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• pp.357-362
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• 2005

Iris recognition system is the one of the most reliable biometries recognition system. An algorithm is proposed to determine the localized iris from the iris image received from iris input camera in client. For the first step, the algorithm determines the center of pupil. For the second step, the algorithm determines the outer boundary of the iris and the pupillary boundary. The localized iris area is transformed into polar coordinates. After performing three times Wavelet transformation, normalization was done using a sigmoid function. The converting binary process performs normalized value of pixel from 0 to 255 to be binary value, and then the converting binary process is compared pairs of two adjacent pixels. The binary code of the iris is transmitted to the server by the network. In the server, the comparing process compares the binary value of presented iris to the reference value in the database. The process of recognition or rejection is dependent on the value of Hamming Distance. After matching the binary value of presented iris with the database stored in the server, the result is transmitted to the client.

• Proceedings of the Korea Technical Association of the Pulp and Paper Industry Conference
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• 2005.11a
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• pp.45-53
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• 2005

A novel method for evaluating the anisotropy of the deterministic features in a stochastic 2D data is introduced. The ability of the wavelet transform for the identification of the abrupt discontinuities could be used to characterize the boundary of the deterministic area in a 2D stochastic data, such as flocs in paper structure. The one-dimensional wavelet transform with a small-scale range in MD and CD could quantify the amount of the edge in both directions, depending on the intensity of each floc. The flocs that are aligned in the MD direction result in a higher value of local wavelet energy in the CD direction. Therefore, the ratio of the total wavelet energy in CD and MD directions can be used as a new anisotropy index. This index is a measure of the floc-orientation and can provide an excellent tool to obtain the orientation distribution and the major oriented angle of flocs. Various simulated images and real stochastic data such as local gloss variation of printed image and formation image, have been tested and the results show this analysis method is very reliable to measure the anisotropy of the deterministic features.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2003.04a
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• pp.277-281
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• 2003

We fused RADARSAT image and SPOT panchromatic image by wavelet transform in order to improve the accuracy of classification on the water area. Fused image in water not only maintained the characteristic of SAR image (low pixel value)but also had boundary information improved. This leads to accurate method to classify water areas.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.12B
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• pp.2369-2381
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• 1999

In this paper, we propose an iterative algorithm for reducing the blocking artifact in block transform-coded images by using a wavelet transform. In the proposed method, an image is considered as a set of one-dimensional horizontal and vertical signals and one-dimensional wavelet transform is utilized in which the mother wavelet is the first order derivative of a Gaussian like function. The blocking artifact is reduced by removing the blocking component, that causes the variance at the block boundary position in the first scale wavelet domain to be abnormally higher than those at the other positions, using a minimum mean square error (MMSE) filter in the wavelet domain. This filter minimizes the MSE between the ideal blocking component-free signal and the restored signal in the neighborhood of block boundaries in the wavelet domain. It also uses local variance in the wavelet domain for pixel adaptive processing. The filtering and the projection onto a convex set of quantization constraint are iteratively performed in alternating fashion. Experimental results show that the proposed method yields not only a PSNR improvement of about 0.56-1.07 dB, but also subjective quality nearly free of the blocking artifact and edge blur.

• Journal of Power Electronics
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• v.9 no.3
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• pp.377-385
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• 2009

In this paper, a diagnosis method for switch open-circuit faults in three-phase PWM inverters is proposed, which employs support vector machine (SVM) as classifying method. At first, a discrete wavelet transform (DWT) is used to detect a discontinuity of currents due to the fault, and then the features for fault diagnosis are extracted. Next, these features are employed as inputs for the SVM training. After training, the SVM produces an optimized boundary which is used identifying the fault. Finally, the fault classification is performed online with instantaneous features. The experimental results have verified the validity of the proposed estimation algorithm.

• ETRI Journal
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• v.23 no.2
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• pp.85-95
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• 2001

The surface modeling capability of CAD systems is widely used to design products bounded by free form surfaces and curves. However, the surfaces or curves generated by popular data fitting methods usually have shape imperfections such as wiggles. Thus, fairing operations are required to remove the wiggles, which makes the surfaces or curves smooth. This paper proposes a new method based on the wavelet transform for fairing the surfaces or curves while preserving the continuity with adjacent surfaces or curves. The wavelet transform gives a hierarchical perspective of the surfaces and the curves, which can be decomposed into the overall sweep and details, i.e., local deviations from sweep like the wiggles. The proposed fairing method provides a similar effect on the mathematical surface as that of the grinding operation using sandpaper on the physical surface.

• The Journal of the Acoustical Society of Korea
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• v.22 no.2
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• pp.153-161
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• 2003

In this paper, we propose a wavelet-based detection method to identify efficiently the time-delay or multipath channel of ocean acoustic signals due to complex ocean medium and boundary layers. Our proposed method employs wavelet packet transform to analyze the received broadband acoustic signals and applies the matched filter to determine the time region of interest. Also, we present numerical testing that results on both the simulated and real data revealed the efficiency of this method in time-delay estimation and moreover its capability in estimating the time-delay of individual path in multipath channel, in which the arrival patterns are too close to be separated by the matched filter method.