• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.2059-2064
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• 2004

Texture analysis is an important role for automatic visual insfection. This paper presents an application of wavelet extension and Gray level co-occurrence matrix (GLCM) for detection of defect encountered in textured images. Texture characteristic in low quality images is not to easy task to perform caused by noise, low frequency and small dimension. In order to solve this problem, we have developed a procedure called wavelet image extension. Wavelet extension procedure is used to determine the frequency bands carrying the most information about the texture by decomposing images into multiple frequency bands and to form an image approximation with higher resolution. Thus, wavelet extension procedure offers the ability to robust feature extraction in images. Then the features are extracted from the co-occurrence matrices computed from the sub-bands which performed by partitioning the texture image into sub-window. In the detection part, Mahalanobis distance classifier is used to decide whether the test image is defective or non defective.

• The Pure and Applied Mathematics
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• v.31 no.2
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• pp.179-187
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• 2024

In image and signal processing, the wavelet transform is frequently employed. However, it has the drawback of having weak directionality, which has limited its use in many applications. A recent addition to the wavelet transform, the curvelet transform attempts to address crossing phenomena that occur along curved edges in 2-D images. As an extension of the wavelet transform, we discuss various curvelet transform features in this paper. There are numerous uses for the curvelet and wavelet transforms in image and signal processing.

• East Asian mathematical journal
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• v.26 no.1
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• pp.105-113
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• 2010

In the spectral analysis, Fourier coeffcients are very important to give informations for the original signal f on a finite domain, because they recover f. Also Fourier analysis has extension to wavelet analysis for the whole space R. Various kinds of reconstruction theorems are main subject to analyze signal function f in the field of wavelet analysis. In this paper, we will present a new reconstruction theorem of functions in $L^1(R)$ using a nonharmonic Fourier series. When we construct this series, we have used dyadic subdivision schemes.

• Kyungpook Mathematical Journal
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• v.61 no.2
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• pp.371-381
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• 2021

In this paper, we attempt to obtain sufficient conditions for the existence of tight wavelet frame sets in locally compact abelian groups. The condition is generated by modulating a collection of characteristic functions that correspond to a generalized shift-invariant system via the Fourier transform. We present two approaches (for stationary and non-stationary wavelets) to construct the scaling function for L²(G) and, using the scaling function, we construct an orthonormal wavelet basis for L²(G). We propose an open problem related to the extension principle for Riesz wavelets in locally compact abelian groups.

• Journal of Biomedical Engineering Research
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• v.25 no.5
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• pp.377-382
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• 2004

In the present study, thirteen healthy volunteers performed lumbar extension exercises at 48$^{\circ}$/s, loaded by 40, 50, 60kg(about 44, 55, 66％ of maximum voluntary contraction). During the whole period of exercises, electromyographic(EMG) signal was measured in the erector spinae muscle in order to determine muscle fatigue. Using the wavelet transform, EMG signal was separated by various frequency ranges in the time-frequency domain, and muscle fatigue was analyzed, comparing with the results based on the median frequency(MDF). MDF shifted toward the lower frequency ranges with the muscle fatigue, showing a single characteristic frequency. On the other hand, wavelet transform of EMG signals resulted in increased power amplitude in lower frequency ranges(0-125Hz), and decreased power amplitude in higher frequency ranges(375-468Hz). This study reveals that the muscle fatigue during dynamic movement is explained better by wavelet analysis.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2003.06a
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• pp.86-89
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• 2003

타일링을 통해 손실 압축된 데이터에 대해 점대칭 확장(point symmetric extension)을 사용하면 경계에서의 인공물(artifact)들을 줄일 수 있다 실제 확장 샘플 없이 경계 필터(boundary filter)를 사용하는 것과 같은 효과를 내는 방법을 리프팅(lifting)을 사용하여 수행할 수 있다. 본 논문에서 사용된 필터는 PR 특성을 준수하고, 경계근처에서 어떠한 후처리 기술이나 이웃하는 타일들로부터의 추가정보 없이 경계 인공물들을 현저히 감소시켰다.

• Proceedings of the KIEE Conference
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• 2005.07a
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• pp.178-180
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• 2005

Recently, electrical demands increase rapidly in metropolitan areas according to the extension of urban areas. Therefore underground transmission lines are getting expanded. This paper presents the rapid and accurate algorithm for fault discrimination and fault location in underground transmission lines. This paper uses fuzzy logic method using voltage and zero sequence for fault discrimination. And this paper uses travelling wave and wavelet transform for fault location. To prove the performance of the algorithm, it test algorithm with signal obtained from ATPDraw simulation.

• Proceedings of the KIEE Conference
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• 2005.11b
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• pp.350-352
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• 2005

Recently, electrical demands increase rapidly in metropolitan areas according to the extension of urban areas. Therefore underground transmission lines are getting expanded. This paper presents the rapid and accurate algorithm for fault discrimination and fault location in underground transmission lines. This paper uses fuzzy logic method using voltage and zero sequence for fault discrimination. And this paper uses travelling wave and wavelet transform for fault location. To prove the performance of the algorithm, it test algorithm with signal obtained from ATPDraw simulation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.7
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• pp.1488-1492
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• 2004

The digital signal has been replaced the analog signal in most of every field of multimedia including still image, animation, and audio due to the enormous extension of computer supply and the fast development of computer network. The consumers of information are able to enjoy the abundance of information because of one of the digital signal traits that very easy to regenerate the original data. Because of the trait, however, it is very hard for the producers of information to keep the copyright with the merit of original copy in quality excellency. In this paper, the watermarking technology which inserts a RGB color watermark in color image using the visual characteristics of wavelet coefficient was proposed. As a result, the PSNR value of image was varied depending on perceptual parameter, but we can obtain 32dB as a whole.

• Journal of Internet Computing and Services
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• v.11 no.2
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• pp.99-107
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• 2010

In this paper a blind watermarking algorithm for digital image is presented. The proposed method operates in wavelet domain. The watermark is decomposed into 2D-IMFs using BEMD which is the 2-dimensional extension of 1 dimensional empirical mode decomposition. The CDMA based on SS technique is applied to watermark embedding and detection process. In the watermark embedding process, each IMF of watermark is embedded into middle frequency subimages in wavelet domain, so subimages just include partial information about embedded watermark. By characteristics of BEMD, when the partial information of watermark is synthesized, the original watermark is reconstructed. The experimental results show that the proposed watermarking algorithm is imperceptible and moreover is robust against JPEG compression, common image processing distortions.