• Journal of Internet Computing and Services
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• v.9 no.1
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• pp.129-135
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• 2008

This paper presents a methodology to forecast KOSPI index by extracting fuzzy rules based on the neural network with weighted fuzzy membership functions (NEWFM) and the minimized number of input features using the distributed non-overlap area measurement method. NEWFM classifies upward and downward cases of KOSPI using the recent 32 days of CPPn,m (Current Price Position of day n for n-1 to n-m days) of KOSPI. The five most important input features among CPPn,m and 38 wavelet transformed coefficients produced by the recent 32 days of CPPn,m are selected by the non-overlap area distribution measurement method. For the data sets, from 1991 to 1998, the proposed method shows that the average of forecast rate is 67.62%.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.8C
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• pp.811-820
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• 2003

In this paper, multi-watermarking algorithm is proposed to satisfy two purpose of ownership protection and tamper proofing simultaneously. At first, for robust watermarking, the location of the embedding wavelet coefficient is selected by using existing QSWT algorithm. And then, we propose the method inserting discrete cosine transformed watermark. The watermarked image is watermarked again for the tamper proofing. The tamper proofing algorithm is also proposed. According to the experimental results, the proposed multi-watermarking algorithm is robust to the attack, such as blurring, sharpening, JPEG compression. And also, the tampered area are detected in blocks, making it simple to judge which pixels are changed.

• Transactions of Materials Processing
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• v.12 no.4
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• pp.277-283
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• 2003

In a closed-die forging process, blocker has been used to fill and distribute metal well in finisher die. Generally, the blocker shape was determined by an expert with many experiences. However, the manual blocker design process takes much time and efforts, so various automatic methods for the blocker design process have been suggested for the last three decades. The method with filtering in FFT (Fast Fourier Transform) for the blocker design provides general solution than other methods. But. due to the properties of FFT in time-frequency domain, this method has some drawbacks such as long calculation time, difficulty of local control and additional boundary process after filtering. In this study. DWT (Discrete Wavelet Transform), which is more flexible and is more wildly used than FFT, is applied to the blocker design. The method with filtering in DWT is very proper to design blocker in both 2-D and 3-D shapes. To verify the efficiency of this method, blockers of some models are designed and the results show that blocker design with DWT is effective for the blocker designs.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.5C
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• pp.520-529
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• 2007

In this paper, we study the characteristics of parameters which are related to performance of MCTF which is a key technique for wavelet-based scalable video coding, and propose an improved MCTF method. The proposed MCTF method adopts the motion estimation of which motion vector field is distributed more uniformly using variable block sizes. By using the proposed method, the decomposition performance of temporal filter is improved, and the energy in high-frequency frames is reduced. It can help the entropy coder to generate lower bitrate. From simulation results, we verify the decomposed energy on high-frequency frame using the proposed method is reduced by 25.86% at the most in terms of variance of the high-frequency frame.

• IEMEK Journal of Embedded Systems and Applications
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• v.3 no.1
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• pp.8-18
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• 2008

In this paper, we propose an efficient algorithm using wavelet transform for still image database retrieval. Especially, it uses only the lowest frequency sub-band in multi-level wavelet transform so that a retrieval system uses a smaller quantity of memory and takes a faster processing time. We extract different textured features, statistical information such as mean, variance and histogram, from low frequency sub-band. Then we measure the distances between the query image and the images in a database in terms of these features. To obtain good retrieval performance, we use the first feature (mean and variance of wavelet coefficients) to filter out most of the unlikely images. The rest of the images are considered to be candidate images. Then we apply the second feature (histogram of wavelet coefficient) to rank all the candidate images. To evaluate the algorithm, we create various distorted image databases using MIT VisTex texture images and PICS natural images. Through simulations, we demonstrate that our method can achieve performance satisfactorily in terms of the retrieval accuracy as well as the both memory requirement and computational complexity. Therefore it is expected to provide good retrieval solution for JPEG-2000 using wavelet transform.

• Journal of KIISE:Information Networking
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• v.30 no.1
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• pp.30-37
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• 2003

In this paper, a discrete wavelet transform (DWT)-based watermarking system is proposed. The main feature of proposed system is that the embedding system uses adaptive thresholds to control the trade-off between the qualify of the watermarked image and the capacity of the watermark, and the trade-off between the quality and robustness of the watermarked image. Also, the extracting system rebuilds threshold according to various attacks and decides a watermark bit from the least distorted coefficient after measuring the distortion of coefficient. Finally, a new measure to detect the uniqueness of watermark is proposed. The experimental result shows that the proposed watermarking system is robust against conventional signal processing and intentional attacks.

• Journal of the Korea Institute of Military Science and Technology
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• v.13 no.5
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• pp.894-902
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• 2010

This paper presents a vision-based robust off-road terrain classification method against environmental variation. As a supervised classification algorithm, we applied a neural network classifier using wavelet features extracted from wavelet transform of an image. In order to get over an effect of overall image feature variation, we adopted environment sensors and gathered the training parameters database according to environmental conditions. The robust terrain classification algorithm against environmental variation was implemented by choosing an optimal parameter using environmental information. The proposed algorithm was embedded on a processor board under the VxWorks real-time operating system. The processor board is containing four 1GHz 7448 PowerPC CPUs. In order to implement an optimal software architecture on which a distributed parallel processing is possible, we measured and analyzed the data delivery time between the CPUs. And the performance of the present algorithm was verified, comparing classification results using the real off-road images acquired under various environmental conditions in conformity with applied classifiers and features. Experiments show the robustness of the classification results on any environmental condition.

• Journal of Internet Computing and Services
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• v.4 no.4
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• pp.27-34
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• 2003

Digital image manipulation software is now readily available on personal computers. It is therefore very simple to tamper with any image and make it available to others. Therefore. copyright protection of digital contents and insurance of digital image integrity become major issues. In this paper, we propose a hybrid watermarking method to identify locations of tampered region as well as copyright. Our proposed algorithms embed the PN-sequence into low frequency sub-band of the wavelet transform domain and it doesn't need the original image in extraction procedure. The experimental results show good robustness against any signal processing with tamper detection on still image.

• Journal of IKEEE
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• v.22 no.4
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• pp.1175-1179
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• 2018

In this paper, we propose recurrent CNN(Convolutional Neural Networks) for detecting seizures among patients using EEG signals. In the proposed method, data were mapped by image to preserve the spectral characteristics of the EEG signal and the position of the electrode. After the spectral preprocessing, we input it into CNN and extracted the spatial and temporal features without wavelet transform. Results from the Children's Hospital of Boston Massachusetts Institute of Technology (CHB-MIT) dataset showed a sensitivity of 90% and a false positive rate (FPR) of 0.85 per hour.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.561-563
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• 2019

This paper proposes a watermarking method for copyright protection of images used in VR. The Embedding method is that finds the point through the SIFT feature points, inserts the watermark by using DWT and QIM on the surrounding area. The objective image to extract the embedded watermark is the projected image and its method finds the SIFT feature points and extracts watermark data from its surrounding areas after correction by using inverse process of matching and projection in the VR image production process. By comparing the NCC and BER between the extracted watermark and the inserted watermark, the watermark is determined by accumulating the watermark having a threshold value or more. This is confirmed by comparing with a conventional method.