• International Journal of Control, Automation, and Systems
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• v.3 no.1
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• pp.43-55
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• 2005

In this paper, a predictive control method using self-recurrent wavelet neural network (SRWNN) is proposed for chaotic systems. Since the SRWNN has a self-recurrent mother wavelet layer, it can well attract the complex nonlinear system though the SRWNN has less mother wavelet nodes than the wavelet neural network (WNN). Thus, the SRWNN is used as a model predictor for predicting the dynamic property of chaotic systems. The gradient descent method with the adaptive learning rates is applied to train the parameters of the SRWNN based predictor and controller. The adaptive learning rates are derived from the discrete Lyapunov stability theorem, which are used to guarantee the convergence of the predictive controller. Finally, the chaotic systems are provided to demonstrate the effectiveness of the proposed control strategy.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.7
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• pp.487-494
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• 2013

Medical image watermarking has received extensive attention as wide security services in the healthcare information system. This paper proposes a blind medical image watermarking approach on the segmented gray-matter (GM) images by utilizing discrete wavelet transform (DWT) and discrete cosine transform (DCT) along with enhanced suppressed fuzzy C-means (EnSFCM) for the optimal selection of sub-blocks position to insert a watermark. Experimental results show that the proposed approach outperforms other methods in terms of peak signal to noise ratio (PSNR) and M-SVD. In addition, the proposed approach shows better robustness than other methods in normalized correlation (NC) values against several attacks, such as noise addition, filtering, JPEG compression, blurring, histogram equalization, and cropping.

• Journal of the Institute of Convergence Signal Processing
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• v.15 no.1
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• pp.1-8
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• 2014

Digital watermarking techniques are attracting attention as a proper solution to protect copyright for multimedia data. This paper proposes a new audio watermarking method based on Discrete Cosine Transformation (DCT) and Discrete Wavelet Transformation (DWT) for copyright protection. In our proposed watermarking method, the original audio is transformed into DCT domain and divided into two parts. Synchronization code is applied on the signal in first part and 2 levels DWT domain is applied on the signal in second part. The absolute value of DWT coefficient is divided into arbitrary number of segments and calculates the energy of each segment and middle peak. Watermarks are then embedded into each middle peak. Watermarks are extracted by performing the inverse operation of watermark embedding process. Experimental results show that the hidden watermark data is robust to re-sampling, low-pass filtering, re-quantization, MP3 compression, cropping, echo addition, delay, and pitch shifting, amplitude change. Performance analysis of the proposed scheme shows low error probability rates.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.3
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• pp.603-611
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• 2013

In this paper, we propose a new method which estimates and encrypts significant component of digital image such as digital cinema using discrete wavelet packet transform (DWPT). After analyzing the characteristics of images in spatial and frequency domain, the required information for ciphering an image was extracted. Based on this information an ciphering method was proposed with wavelet transform and packetization of subbands. The proposed algorithm can encrypt images in various robust from selecting transform-level and energy threshold. From analyzing the encryption effect numerically and visually, the optimized parameter for encryption is presented. Without additional analyzing process, one can encrypt efficiently digital image using the proposed parameter. Although only 0.18% among total data is encrypted, the reconstructed image dose not identified. The paketization information of subbands and the cipher key can be used for the entire secret key.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.3
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• pp.240-248
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• 2013

In this paper, we propose a super-resolution algorithm using an adaptive weighted interpolation(AWI) and discrete wavelet transform(DWT). In general, super-resolution algorithms for single-image, probability based operations have been used for searching high-frequency components. Consequently, the complexity of the algorithm is increased and it causes the increase of processing time. In the proposed algorithm, we first find high-frequency sub-bands by using DWT. Then we apply an AWI to the obtained high-frequency sub-bands to make them have the same size as the input image. Now, the interpolated high-frequency sub-bands and input image are properly combined and perform the inverse DWT. For the experiments, we use the down-sampled version of the original image($512{\times}512$) as a test image($256{\times}256$). Through experiment, we confirm the improved efficiency of the proposed algorithm comparing with interpolation algorithms and also save the processing time comparing with the probability based algorithms even with the similar performance.

• Journal of the Korea Society of Computer and Information
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• v.11 no.2 s.40
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• pp.53-63
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• 2006

A discrete wavelet transform(DWT)-based image watermarking algorithm is proposed in this paper, the proposed method decompose the original image into four subsampled images. Subsampled images are transformed by 2 level DWT, respectively. The proposed method embeds the watermark into one of the subsampled DWT images using edge table that represents dege characteristics of the original image. Without an original image, a watermark is extracted through comparison one subsampled DWT image inserted the watermark with the rest of the submapled DWT images. many exiting methodes do not adequately estimate edge regions where intensities are changed abruptly. The proposed method address with an edge table. Also, even if the watermark is embedded into a low frequency area, our method preserves the image quality. The vality of the proposed method is demonstrated through the PSNR test and subjective image quality that human eyes feel.

• Journal of Wetlands Research
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• v.21 no.4
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• pp.365-373
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• 2019

In this study, we investigated the effect of wave height in coastal areas using discrete wavelet transform in Taehwa river basin in Ulsan. Through the decomposition result of tide data using daubechies level 7 wavelet and Curve Fitting Function, we confirmed that detail components of d₃ and d₄ were semidiurnal and diurnal components and approximation component(a₆) was the long period of lunar fortnight constituent. The decomposed tide data in six level was divided into tide component with periodicity and wave component with non-periodicity using autocorrelation function and fourier transform. Finally, we confirmed that the tide component is consisted 66% and wave component is consisted 34%. So, we quantitatively assessed the effect of wave on coastal areas. The result could be used for coastal flood risk management considering the effect of wave.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.6
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• pp.1343-1352
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• 2018

This paper is designed for hardware to be applied to JPEG2000 standard in the fields of digital photography, remote sensing, aerial remote telemetry, medical imaging, high resolution, and high compression telemetry applications. The software implementation of the JPEG2000 standard for image compression has disadvantages that the processing speed is very slow compared to the conventional JPEG, also the degradation occurs when the DWT level of the JPEG2000 standard is improved. In order to solve this problem, we designed and applied JPEG2000 compression/decompressor. In this paper, the hardware of the JPEG 2000 compression/storage device shows optimal compression speed, faster processing speed, and the image quality for still images by changing the optimal DWT level.

• Journal of the Korean Society for Nondestructive Testing
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• v.21 no.1
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• pp.54-61
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• 2001

A software package to classify acoustic emission (AE) signals using the wavelet transform and the neural network was developed Both of the continuous and the discrete wavelet transforms are considered, and the error back-propagation neural network is adopted as m artificial neural network algorithm. The signals acquired during the 3-point bending test of specimens which have artificial defects on weld zone are used for the classification of the defects. Features are extracted from the time-frequency plane which is the result of the wavelet transform of signals, and the neural network classifier is tamed using the extracted features to classify the signals. It has been shown that the developed software package is useful to classify AE signals. The difference between the classification results by the continuous and the discrete wavelet transforms is also discussed.

• Journal of Advanced Navigation Technology
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• v.17 no.6
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• pp.726-735
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• 2013

This paper proposed face recognition methods about performance improvement of the face recognition using the properties of wavelet transform. Using discrete wavelet transform is Daubechies D4 filter that is similar to mother wavelet transform. For discrete wavelet transform method, In this case, by using LL subband only we can reduce processing time and amount of memory in recognition processing. To improve recognition ratio without further loss of 2 dimensional data changing, We applies 2D LDA. We perform SVM training algorithm to the feature vector obtained by 2D LDA. Experiment is performed using ORL database set and Yale database set by Matlab program. Test result shows that proposed method is superior to existence methods in recognition rate and performance time.