• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.12
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• pp.27-33
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• 1999

A wavelet based multiresolution watermarking method using the human visual system (HVS) is proposed, in which a different number of watermarks, in proportion to the energy contained in each band, are embedded into each band. Experiments with various test images show that the proposed three-level wavelet based method is robust to various attacks such as joint photographic experts group (JPEG) compression, smoothing, cropping, collusion, multiple watermarking, and so on.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2303-2306
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• 2003

The Wavelet Transform providing both of the frequency and time information of an image is proved to be very much effective for the compression of images, and recently lot of studies on coding algorithms for images decomposed by the wavelet transform together with the multiresolution theory are going on. This paper proposes a Quadtree decompositon method of image compression applied to the images decomposed by wavelet transform by using the correlations between pixels .Since the coefficients obtained by the wavelet transform have high correlations between scales, the Quadtree method can reduce the data quantity effectively The experimental image with 256${\times}$256 size was used to compare the Performances of the existing and the proposed compression methods.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.28 no.12
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• pp.1608-1615
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• 2004

CFD data compression methods based on Full-3D and Quasi-1D supercompact multiwavelets are presented. Supercompact wavelets method provide advantageous benefit that it allows higher order accurate representation with compact support. Therefore it avoids unnecessary interaction with remotely located data across singularities such as shock. Full-3D wavelets entails appropriate cross-derivative scaling function & wavelets, hence it can allow highly accurate multi-spatial data representation. Quasi-1D method adopt 1D multiresolution by alternating the directions rather than solving huge transformation matrix in Full-3D method. Hence efficient and relatively handy data processing can be conducted. Several numerical tests show swift data processing as well as high data compression ratio for CFD simulation data.

• Proceedings of the KSME Conference
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• 2003.11a
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• pp.1310-1315
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• 2003

In many practical engineering design problems, there are some design and manufacturing considerations that are difficult or infeasible to express in terms of an objective function or a constraint. In this situation, a set of optimal candidate designs having different topological complexities, not just a single optimal design, is preferred. To generate systematically such design candidates, we propose a hierarchical multiscale design resolution control scheme. In order to adjust its topological complexity by choosing a different starting resolution level in the hierarchical design space, we propose to employ a general M-band wavelet transform in transforming the original design space into the multiscale design space.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.3 no.2
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• pp.178-186
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• 2003

Recently, many researchers have been interested in biometric systems such as fingerprint, handwriting, key-stroke patterns and human iris. From the viewpoint of reliability and robustness, iris recognition is the most attractive biometric system. Moreover, the iris recognition system is a comfortable biometric system, since the video image of an eye can be taken at a distance. In this paper, we discuss human iris recognition, which is based on accurate iris localization, robust feature extraction, and Neural Network classification. The iris region is accurately localized in the eye image using a multiresolution active snake model. For the feature representation, the localized iris image is decomposed using wavelet transform based on dyadic Haar wavelet. Experimental results show the usefulness of wavelet transform in comparison to conventional Gabor transform. In addition, we present a new method for setting initial weight vectors in competitive learning. The proposed initialization method yields better accuracy than the conventional method.

• Journal of Welding and Joining
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• v.17 no.6
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• pp.100-107
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• 1999

In this paper, we deal with the speckle noise reduction and parameter estimation of ultrasonic NDT(non-destructive test) signals obtained during weld inspection of piping. The overall approach consists of three major steps, namely, speckle noise analysis, proposition of wavelet domain AR(autoregressive) model and flaw detection by proposed model parameter. The data are first processed whereby signals obtained using vertical and angle beam transducer. Correlation properties of speckle noise are then analyzed using multiresolution analysis in wavelet domain. The parameter estimation curve obtained using the proposed model is classified a flaw in weld region where is contaminated by severe speckle noise and also clear flaw signal is obtained through CA-CFAR threshold estimator that is a nonlinear post-processing method for removing the noise from reconstructed ultrasonic signal.

• Journal of the Semiconductor & Display Technology
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• v.6 no.3
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• pp.55-59
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• 2007

Wavelet Transform is amenable to efficient algorithms. So wavelet transform was adopted many signal processing and communication applications. For example, the wavelet transform was adopted as the transform for JPEG2000. However, Wavelet has weakness about smoothness along the contours and limited directional information. Hence, recently, some new transforms have been introduced to take advantage of this property. So we use to other transform, called contourlet transform in compression. In this paper, we propose a new method for image compression based on the contourlet transform, which has been recently introduced. Contourlet transform has a good result about images with smooth contours. Moreover, Contourlet is feasible multiresolution and multidirection expansion using non-separable filter bank. This treatise shows a good image representation after compressing using contourlet transform.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1997.10a
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• pp.16-23
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• 1997

The Reproducing Kernel Particle Method (RKPM), one of the popular meshless methods, is developed and applied to stress concentration problems. Since the meshless methods require only a set of particles (or nodes) and the description of boundaries in their formulation, the adaptivity can be implemented with much more ease than finite element method. In addition, due to its intrinsic property of multiresolution, the shape function of RKPM provides us a new criterion for adaptivity. Recently, this multiple scale Reproducing Kernel Particle Method and its adaptive procedure have been formulated for large deformation problems by the authors. They are also under development for damage materials and localization problems. In this paper the multiple scale RKPM for linear elasticity is presented and the adaptive procedure is applied to stress concentration problems. Therefore, this work may be regarded as the edition of linear elasticity in the complete framework of multiple scale RKPM and the associated adaptivity.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.12
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• pp.81-90
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• 1994

This paper proposes a motphological fast reconstructive filter (FRF) using up/down sampling techniques for reconstructive opening and closing, and a parallel structure for fast multiresolution decomposition. Compuer simulation shows that, compared with the conventional RF, the proposed FRF can reduce the processing time up to 8 times while it maintains a similar performance in reconstructed shapes. Further reduction in the decomposition time achieved by the paralellized algorithm combined with the FRF, which can be applied in areas such as defect detection, image segmentation, pattern recognition, etc.

• Proceedings of the IEEK Conference
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• 2000.07a
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• pp.66-69
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• 2000

In this paper, we propose a progressive transmission of a video using a 2$\times$2$\times$2 DCT First of all, the video data is transformed into multiresolution represented video data using a 2$\times$2$\times$2 DCT. Then. it is represented by a 3-D EZT(Embedded Zero Tree) coding fur the progressive transmission with a bit-rate scalability. The proposed progressive transmission algorithm needs much less computations and buffer memories than the higher-order convolution based wavelet filter. Also, since the 2$\times$2$\times$2 DCT requires independent local computations, parallel processing can be applied.