• Journal of the Korean Society for Precision Engineering
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• v.16 no.10
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• pp.194-202
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• 1999

A method for pattern recognition based on wavelet transform is proposed in this paper. The boundary of the object to be recognized includes shape information for object of machine parts. The contour is first represented using a one-dimensional signal and normalized about translation, rotation and scale, then is used to build the wavelet transform representation of the object. Wavelets allow us to decompose a function into multi-resolution hierarchy of localized frequency bands. The recognition of 2-dimensional object based on the wavelet is described to analyze the shape of analysis technique; the discrete wavelet transform(DWT). The feature vectors obtained using wavelet analysis is classified using a multi-layer neural network. The results show that, compared with the use of fourier descriptors, recognition using wavelet is more stable and efficient representation. And particularly the performance for objects corrupted with noise is better than that of other method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.3
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• pp.600-607
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• 2007

In the next generation mobile multimedia communications, the broad band shot-burst transmissions are used to reduce end-to-end transmission delay, and to limit the time variation of wireless channels over a burst. However, training overhead is very significant for such short burst formats. So, the availability of the short training sequence and the fast converging adaptive algorithm is essential in the system adopting the symbol-by-symbol adaptive equalizer. In this paper, we propose an adaptive equalizer using the DWMT (discrete multi-wavelet transform) and LMS (least mean square) adaptation. The proposed equalizer has a faster convergence rate than that of the existing transform-domain equalizers, while the increase of computational complexity is very small.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.40 no.1
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• pp.45-51
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• 2003

JPEG200, a new international standard for still image compression based on wavelet and bit-plane coding techniques, is developed. In this paper, we design the DWT(Discrete Wavelet Transform) and quantizer for JPEG2000 CODEC. DWT handles both lossy and lossless compression using the same transform-based framework: The Daubechies 9/7 and 5/3 transforms, and quantizer is implemented as SQ(Scalar Quantization). The architecture of the proposed DWT and SQ are synthesized and verified using Xilinx FPGA technology. It operates up to 30MHz, and executes algorithms of wavelet transform and quantization for VGA 10 frame per second.

• Journal of the Korean Data and Information Science Society
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• v.15 no.3
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• pp.575-584
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• 2004

We propose a Bayesian model-based approach using a mixture of Dirichlet processes model with discrete wavelet transform, for curve clustering in the microarray data with time-course gene expressions.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.6 no.8
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• pp.1139-1145
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• 2002

Wavelet transformed data can filter signal with each frequency band, because it includes detail information about original signal. Therefore, in this paper, important two noises were removed by wavelet. About AWGN environment UDWT(undecimated discrete wavelet transform), applying hard-threshold, was used and about impulse noise environment, it can be possible to recognize edge of original signal as well as superior denoising effect by using two methods, denoising by threshold and slope of signal by wavelet. SNR was used as a judgemental criterion of a denoising effect and Blocks and DTMF(dual tone multi frequency) were used as a test signal.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.5
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• pp.1095-1100
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• 2003

The wavelet transform pair used simultaneously when two wavelets are designed to form an approximate Hilbert transform pair provide excellent property than present DWT(discrete wavelet transform), especially in field that detect wide-band signals like pulse and increase the bit rate at the same bandwidth. In this paper, the two dyadic wavelet bases which form an approximate Hilbert transform pair were designed, and flat delay filter which has the truncated coefficient vector is used in order that the two filters can form Hilbert transform relation in the process of design.

• KIEE International Transactions on Power Engineering
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• v.3A no.3
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• pp.130-138
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• 2003

This paper presents a discrete wavelet transform approach for determining the beginning and end times of voltage sags. Firstly, investigations in the use of some typical mother wavelets, namely Daubechies, Symlets, Coiflets and Biorthogonal are carried out and the most appropriate mother wavelet is selected. The proposed technique is based on utilizing the maximum value of Dl (at scale 1) coefficients in multiresolution analysis (MRA) based on the discrete wavelet transform. The results are compared with other methods for determining voltage sag duration, such as the Root Mean Square (RMS) voltage and Short Time Fourier Transform (STFT) methods. It is shown that the voltage sag detection technique based on the wavelet transform is a satisfactory and reliable method for detecting voltage sags in power quality disturbance analysis.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.505-508
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• 2005

Wavelet scheme can be applied to the various remote sensing problems: conventional multi-resolution image analysis, compression of large image sets, fusion of heterogeneous sensor image and segmentation of features. In this study, we attempted wavelet-based filtering and its analysis. Traditionally, statistical methods and adaptive filter are used to manipulate noises in the image processing procedure. While we tried to filter random noise from optical image and radar image using Discrete Wavelet Transform (DW1) and Stationary Wavelet Transform (SW1) and compared with existing methods such as median filter and adaptive filter. In result, SWT preserved boundaries and reduced noises most effectively. If appropriate thresholds are used, wavelet filtering will be applied to detect road boundaries, buildings, cars and other complex features from high-resolution imagery in an urban environment as well as noise filtering

• Journal of Navigation and Port Research
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• v.32 no.10
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• pp.777-783
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• 2008

Nowadays wavelet transforms are widely used for the analyses of PIV velocity vector fields. This is bemuse the wavelet provides not only spatial information of the velocity vectors but also of time and frequency domains. In this study, a discrete wavelet trC1f1$form has been applied to real PIV images of bubbly flows. The vector fields obtained by a self-made cross-correlation PIV algorithm were used for the discrete wavelet transform The performances of the discrete wavelet transform is investigated by changing the level of power of discretization. The decomposed images by the wavelet multiresolution showed conspicuous characteristics of the bubbly flows according to the level changes. The high spatial bubble concentrated area could be evaluated by the constructed discrete wavelet transform algorithm, at which high leveled wavelets could play a dominant roles to reveal the flow characteristics.

• Proceedings of the IEEK Conference
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• 2000.09a
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• pp.605-608
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• 2000

This paper introduces a new structure for the undecimated discrete wavelet transform (UDWT). This structure combines the stationary wavelet transform with a lifting scheme and its design is based on a polyphase structure .where the downsampling and split stage are removed. The suggested structure inherits the simplicity of the lifting scheme, such that the inverse transform is easily implemented. The performanace of the proposed undecimated lifting is verified on a signal denoising application.