• Proceedings of the KIPE Conference
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• 2012.07a
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• pp.105-106
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• 2012

In this paper, discrete wavelet transform using a PV system covers how the detection of a islanding. Connection point occur exclusively in Grid when the grid voltage and current operation of the wavelet coefficients by changing features will determine if islanding operation. The proposed method has simple computation and fast decision time has the advantage. DSP-based controller through the experiment proved the validity of the proposed method.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.9 no.3
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• pp.178-184
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• 2009

An efficient fault diagnosis system is needed for industry because it can optimize the resources management and improve the performance of the system. In this study, a fault diagnostic system is proposed for rotating machine using wavelet packet transform (WPT) and elman neural network (ENN) techniques. In most fault diagnosis for mechanical systems, WPT is a well-known signal processing technique for fault detection and identification. In previous work, WPT can improve the continuous wavelet transform (CWT) used over a longer computing time and huge operand. It can also solve the frequency-band disagreement by discrete wavelet transform (DWT) only breaking up the approximation version. In the experimental work, the extracted features from the WPT are used as inputs in an Elman neural network. The results show that the scheme can reliably diagnose four different conditions and can be considered as an improvement of previous works in this field.

• Proceedings of the IEEK Conference
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• 2002.07b
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• pp.864-867
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• 2002

Introduction of digital communication network such as Integrated Services Digital Networks(ISDN) and digital storage media have rapidly developed. Due to a large amount of image data, compression is the key techniques in still image and video using digital signal processing for transmitting and storing. Digital image compression provides solutions for various image applications that represent digital image requiring a large amount of data. in this paper, the proposed DWT(Discrete Wavelet Transform) filter bank is consisted of simple architecture, but it is efficiently designed that a user obtains a wanted compression rate as only input parameter. If it is implemented by FPGA chip, the designed encoder operates in 12MHz.

• Proceedings of the CALSEC Conference
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• 2004.02a
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• pp.223-226
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• 2004

Several studies have shown that the trust is a significant barrier for realizing the potential of e-commerce. Trust is not only a short-term issue but also the most significant long-term barrier for realizing the potentials of e-commerce. Because digital contents which have been used in e-commerce are easy to be duplicated, the enforcement of digital copyright protection is an important issue. Watermarking is a technique for labeling digital pictures by hiding secret information in the image. In this paper, a discrete wavelet transform(DWT) based technique for embedding digital watermark into image is proposed. The performance of the proposed watermarking is robust to a variety of signal distortions, such as JPEG and image processing operations.

• Proceedings of the KIPE Conference
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• 2013.07a
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• pp.449-450
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• 2013

본 논문에서는 이산 웨이블릿 변환(DWT;discrete wavelet transform)을 이용한 에너지 저장시스템(ESS;energy storage system)의 고장 검출 방법을 제안한다. ESS에 순간적인 고장 발생시 전압의 급격한 변화가 발생할 수 있으며 이는 다해상도 분석(MRA;multi-resolution analysis)을 이용한 시간-주파수 분석을 통해 분해된 저주파 전압 성분(approximation;$A_n$)과 고주파 전압 성분(detail;$D_n$)중 현저한 성분의 변화가 관찰되는 고주파 전압 성분을 선택한다. 이를 검증하기 위하여 모든 고주파 전압 성분의 절대값을 적용한 뒤 최대값 정보를 추출한다. 이 때, 추출된 각 성분의 최대값과 최대값의 평균을 비교하되 여러 사전실험을 통해 정해진 특정 임계값 대비 큰 값을 나타낼 때 고장이 발생하였음을 판단한다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.6A
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• pp.464-472
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• 2012

In this paper, we propose a new super-resolution algorithm that uses successive frames by applying the block matching motion estimation algorithm. Usually, single frame super-resolution algorithms are based on probability or discrete wavelet transform (DWT) approach to extract high-frequency components of the input image, but only limited information is available for these algorithms. To solve this problem, various multiple-frame based super-resolution algorithms are proposed. The accuracy of registration between frames is a very important factor for the good performance of an algorithm. We therefore propose an algorithm using 6-Tap FIR filter to increase the accuracy of the image registration with sub-pixel unit. Proposed algorithm shows better performance than other conventional interpolation based algorithms such as nearest neighborhood, bi-linear and bi-cubic methods and results in about the same image quality as DWT based super-resolution algorithm.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.319-324
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• 2005

An integrated approach for prostate cancer detection using proteomic data is presented. Due to the high-dimensional feature of proteomic data, the discrete wavelet transform (DWT) is used in the first-stage for data reduction as well as noise removal. After the process of DWT, the dimensionality is reduced from 43,556 to 1,599. Thus, each sample of proteomic data can be represented by 1599 wavelet coefficients. In the second stage, a voting method is used to select a common set of wavelet coefficients for all samples together. This produces a 987-dimension subspace of wavelet coefficients. In the third stage, the Autoassociator algorithm reduces the dimensionality from 987 to 400. Finally, the artificial neural network (ANN) is applied on the 400-dimension space for prostate cancer detection. The integrated approach is examined on 9 categories of 2-class experiments, and also 3- and 4-class experiments. All of the experiments were run 10 times of ten-fold cross-validation (i. e. 10 partitions with 100 runs). For 9 categories of 2-class experiments, the average testing accuracies are between 81% and 96%, and the average testing accuracies of 3- and 4-way classifications are 85% and 84%, respectively. The integrated approach achieves exciting results for the early detection and diagnosis of prostate cancer.

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.37 no.2
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• pp.25-32
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• 2000

Digital watermarking has been recently proposed as the means of intellectual property right protection of multimedia data. We present a novel watermarking scheme to hide a copyright information in a digital image. The method Is based on the 2D DWT(Discrete Wavelet Transform) and image statistics. Gaussian and Laplacian noises as the watermarks are added to the large wavelet coefficients at the high and middle frequency bands in the wavelet domain. Experimental results show that the proposed Laplacian watermark is stronger to several common image distortions, such as noises, JPEG coding as different qualities, Gaussian blurring, and edge enhancement.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.1C
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• pp.124-130
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• 2008

We present in this paper a method of digital watermarking for video data based on the discrete wavelet transform. In the proposed method, a watermark signal is inserted into the decompressed bitstream while detection is performed using the uncompressed video. This method allows detection if video has been manipulated or its format changed. We embed the watermark in the lowest frequency components of each frame in the un-coded video by using wavelet transform. The watermark can be extracted directly from the decoded video without access to the original video. Experimental results show that the proposed method gives the watermarked video of better quality and is robust against MPEG coding, down sampling and re-encoding to other type of video format such as MPEG4, H.264

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.7 no.2
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• pp.143-147
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• 2007

This paper proposes a new watermarking scheme in which a logo watermark is embedded into the discrete wavelet transform (DWT) domain of the original image using exact radial basis function neural networks (RBF). RBF will learn the characteristics of the image, and then watermark is embedded and extracted by the trained RBF. A watermark is added to the coefficients at the low frequency band of the DWT of an image and a watermark is embedded into the DWT domain using the trained RBF. The trained RBF also used in watermark extracting process. Experimental results show that the proposed method has good imperceptibility and high robustness to common image processing attacks.