• Journal of the Institute of Convergence Signal Processing
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• v.11 no.4
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• pp.310-319
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• 2010

In this paper, digital watermarking method using wavelet transform and quad-tree algorithm is proposed. The proposed algorithm transforms the input image by DWT(Discrete Wavelet Transform) and AWPT(Adaptive Wavelet Packet Transform), inserts the watermark by quad-tree algorithm and the Cox's algorithm. The simulation for performance analysis of the proposed algorithm is implemented about the effect of embedding watermark in each subband coefficient (HH, LH, HL) of DWT, each DWT level, and each AWPT level. The simulation result by using DWT is compared with that using AWPT in the proposed algorithm. In addition, the effect of embedding watermark in the lowest frequency band (LL) is simulated. As a simulation result using DWT, the watermarking performance of simultaneously embedding in HH, LH, and HL band of DWT(6 level) is better than that of different cases. The result of AWPT(3 level) improves the correlation value compared to that of DWT(3 level). In addition, insertion the watermark to the LL band about 30~60% of all watermarks improves the correlation value while PSNR performance decreases 1~2dB.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.28.5-28
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• 2001

This paper investigates a classification method of the electrocardiogram (ECG) into different disease categories. The features for the classification of the ECG are the coefficients of the discrete wavelet transform (DWT) of ECG signals. The coefficients are calculated with Haar wavelet, and after DWT we can get 64 coefficients. Each coefficient has morphological information and they may be good features when conventional time-domain features are not available. Since all of them are not meaningful, it is needed to reduce the size of meaningful coefficients set. The distributions of each coefficient can be the rules to classify ECG signal. The optimally reduced feature set is obtained by fuzzy c-means algorithm and rough set theory. First, the each coefficient is clustered by fuzzy c-means algorithm and the clustered ...

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.42 no.6
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• pp.83-92
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• 2005

This paper presents a watermarking approach that the 1-level Discrete Wavelet Transform(DWT) coefficients of a $64{\ast}64$ binary logo image as watermarks are inserted in LL band and other specific frequency bands of the host image using Multi-Resolution Analysis(MRA) Wavelet transform for copyright protection of image data. The DWT coefficients of the binary logo image are inserted in blocks of LL band and specific bands of the host image that the 3-level DWT has been performed in the same orientation. We investigate Significant Coefficients(SCs) in each block of the frequency areas in order to prevent the quality deterioration of the host image and the watermark is inserted by SCs. When the host image is distorted by difference of the distortion degree in each frequency, we set the thresholds of SCs on each frequency and completely insert the watermark in each frequency of the host image. In order to be invisibility of the watermark, the Human Visual System(HVS) is applied to the watermark. We prove the proper embedding method by experiment. Thereby, we rapidly detect the watermark using this watermarking method and because the small size watermarks are inserted by HVS and SCs, the results confirm the superiority of the proposed method on invisibility and robustness.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.1
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• pp.171-181
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• 2012

This paper introduces the double-density discrete wavelet transform(DWT) using quincunx sampling, which is a DWT that combines the double-density DWT and quincunx sampling method, each of which has its own characteristics and advantages. The double-density DWT is an improvement upon the critically sampled DWT with important additional properties: Firstly, It employs one scaling function and two distinct wavelets, which are designed to be offset from one another by one half. Secondly, the double-density DWT is overcomplete by a factor of two, and Finally, it is nearly shift-invariant. In two dimensions, this transform outperforms the standard DWT in terms of denoising; however, there is room for improvement because not all of the wavelets are directional. That is, although the double-density DWT utilizes more wavelets, some lack a dominant spatial orientation, which prevents them from being able to isolate those directions. A solution to this problem is a quincunx sampling method. The quincunx lattice is a sampling method in image processing. It treats the different directions more homogeneously than the separable two dimensional schemes. Proposed wavelet transformation can generate sub-images of multiple degrees rotated versions. Therefore, This method services good performance in image processing fields.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.527-528
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• 2006

In this paper, we propose an IP design and implementation of System on a chip(SoC) for Discrete Cosine Transform (DCT) and Discrete Wavelet Transform (DWT) processor using adder-based DA(Adder-based Distributed Arithmetic). To reduced hardware cost and to improve operating speed, the combined DCT/ DWT processor used the bit-serial method and DA module. The transform of coefficient equation result in reduction in hardware cost and has a regularity in implementation. We use Verilog-HDL and Xilinx ISE for simulation and implement FPGA on SoCMaster-3.

• Journal of the Korea Computer Industry Society
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• v.4 no.4
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• pp.589-598
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• 2003

In the conventional fractal image compression in the DWT(discrete wavelet transform), the domain and range blocks were classified as B${\times}$B block size first before all domain block for each range block was searched. The conventional method has a disadvantages that the encoding time takes too long, since the domain block for entire image was searched. As an enhancement to such inefficiencies and image quality, this paper proposes wavelet-based fractal image compression with multiscale factors. Thus, this proposed method uses multiscale factor along each level and band to enhance an overall image quality. In encoding process of this method, the range blocks are not searched for all the domain blocks; however, using the self affine system the range blocks are selected from the blocks in the upper level. The image qualify of the conventional method is 32.30[dB], and the proposed method is 35.97[dB]. The image quality is increased by 3.67[dB].

• Earthquakes and Structures
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• v.9 no.6
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• pp.1221-1232
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• 2015

In recent decades, wavelet transforms as a strong signal processing tool have attracted attention of researchers for damage identification. Apart from the wide application of wavelet transforms for damage identification, influence of higher order modes on the quality of damage detection has been a challenging matter for researchers. In this study, influence of higher order modes and different mass configurations on the quality of damage detection through Discrete Wavelet Transform (DWT) was studied. Nine different damage scenarios were imposed to four cantilever structures having different mass configurations. The first four mode shapes of the cantilever structures were measured experimentally and analyzed by DWT. A damage index was defined in order to study the influence of higher order modes. Results of this study showed that change in the mass configuration had a great impact on the quality of damage detection even when the changes altered natural frequencies slightly. It was observed that for successful damage detection all available mode shapes should be taken into account and measured mode shapes had no significant priority for damage detection over each other.

• Journal of Korea Multimedia Society
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• v.20 no.8
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• pp.1299-1311
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• 2017

Sounds based machine fault diagnosis recovers all the studies that aim to detect automatically faults or damages on machines using the sounds emitted by these machines. Conventional methods that use mathematical models have been found inaccurate because of the complexity of the industry machinery systems and the obvious existence of nonlinear factors such as noises. Therefore, any fault diagnosis issue can be treated as a pattern recognition problem. We present here an automatic fault diagnosis system of hand drills using discrete wavelet transform (DWT) and pattern recognition techniques such as principal component analysis (PCA) and artificial neural networks (ANN). The diagnosis system consists of three steps. Because of the presence of many noisy patterns in our signals, we first conduct a filtering analysis based on DWT. Second, the wavelet coefficients of the filtered signals are extracted as our features for the pattern recognition part. Third, PCA is performed over the wavelet coefficients in order to reduce the dimensionality of the feature vectors. Finally, the very first principal components are used as the inputs of an ANN based classifier to detect the wear on the drills. The results show that the proposed DWT-PCA-ANN method can be used for the sounds based automated diagnosis system.

• Journal of Korea Multimedia Society
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• v.11 no.4
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• pp.443-453
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• 2008

In this paper, the 1-level DWT(Discrete Wavelet Transform) coefficients of a binary logo image are used as the watermark. The watermark should be inserted in the same band which is equivalent to the host image when the watermark is inserted in the wavelet domain. This is the image fusion of the proposed watermarking method. The watermark is inserted in relatively significant coefficients after the insertion area is defined. The more significant coefficients have the important information because they are identified as the edge and major surface in images. The significant coefficients are defined when their absolute value exceeds the threshold. The standard deviation is used as the weight value of watermark insertion in order to strengthen the weight of the watermark insertion according to the value of the coefficients. The proposed watermarking method is an adaptive scheme, and the proposed two detection algorithms can be adaptively used when the watermarked image is distorted by cropping, filtering, or compression.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.9
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• pp.1731-1733
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• 2015

Since electroencephalogram(EEG) has non-linear and non-stationary properties, it is effective to analyze the characteristic of EEG with time-frequency method rather than spectrum method. In this letter, we propose the modified drowsiness detection system using discrete wavelet transform combined with errors-in-variables and multilayer perceptron methods. For the comparison of the proposed scheme with the previous one, the state 'others' is added to the previous states of drivers: 'alertness,' 'transition,' and 'drowsiness.' From the computer simulation using machine learning, we confirm that the proposed scheme outperforms the previous one for some conditions.