• Journal of Digital Contents Society
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• v.5 no.4
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• pp.311-315
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• 2004

In this paper, we proposed a robust watermarking algorithm based on fuzzy inference and human visual system. In the first, discrete wavelet transform(DWT) is involved to calculate additive energy strength, then we devised fuzzy inference, which was established by computing contrast and texture degree in gray-level image. Watermark is embeded into the coefficients of 3-level DWT so as to consider a spatial effects. Visual recognizable patterns such as binary image were used as a watermark Consequently, experimental results showed that proposed algorithm is robust in JPEC compression.

• Proceedings of the KIEE Conference
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• 2007.10a
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• pp.365-366
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• 2007

본 워터마크를 삽입 할 수 있는 임베디드 시스템을 구현 하였다. 워터마크 삽입을 위해 DWT와 Data Matrix가 사용되었다. DWT(Discrete Wavelet Transform)는 주파수 공간에서 워터마크를 삽입하기 위해 사용되었고, Data Matrix는 워터마크로 사용되었다. 데이터 매트릭스는 미국의 Data Matrix사가 만든 이차원 바코드로 오류검출 및 복원 알고리즘을 가지고 있어 작은 에러는 복원이 가능하다. 시스템으로는 PDA를 사용하였고, 틀로는 EVC를 사용하였다. 삽입 알고리즘은 다음과 같다. DWT를 한 경우 4개의 서브밴드로 나누어지며, 그 중 cV(horizontal detail)와 cH(vertical detail)를 선택하여 4*4블록 단위로 나눈다. 나누어진 블록과 대응하는 워터마크의 픽셀 값에 의해 계수에 일정 값(가중치)을 더하거나 때주어 워터마크를 삽입한다. 추출 알고리즘은 역으로 이루어진다. 성능평가는 PDA에서 워터마크 삽입 알고리즘을 통하여 워터마크를 삽입, 추출된 영상을 가지고 Matlap을 이용하여 평가하였다.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.13 no.6
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• pp.33-43
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• 2003

In this paper, we proposed a real-time watermarking algorithm to be combined and to work with a DWT(Discrete Wavelet Transform)-based image compressor. To reduce the amount of computation in selecting the watermarking positions, the proposed algorithm uses a pre-established look-up table for critical values, which was established statistically by computing the correlation according to the energy values of the corresponding wavelet coefficients. That is, watermark is embedded into the coefficients whose values are greater than the critical value in the look-up table which is searched on the basis of the energy values of the corresponding level-1 subband coefficients. Therefore, the proposed algorithm can operate in a real-time because the watermarking process operates in parallel with the compression procession without affecting the operation of the image compression. Also it improved the property of losing the watermark and the efficiency of image compression by watermark inserting, which results from the quantization and Huffman-Coding during the image compression. Visual recognizable patterns such as binary image were used as a watermark The experimental results showed that the proposed algorithm satisfied the properties of robustness and imperceptibility that are the major conditions of watermarking.

• Transactions on Control, Automation and Systems Engineering
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• v.3 no.4
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• pp.283-288
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• 2001

In this paper, we proposed a method for extracting facial characteristics of human being in an image. Given a pair of gray level sample images taken with and without human being, the face of human being is segmented from the image. Noise in the input images is removed with the help of Gaussian filters. Edge maps are found of the two input images. The binary edge differential image is obtained from the difference of the two input edge maps. A mask for face detection is made from the process of erosion followed by dilation on the resulting binary edge differential image. This mask is used to extract the human being from the two input image sequences. Features of face are extracted from the segmented image. An effective recognition system using the discrete wave let transform (DWT) is used for recognition. For extracting the facial features, such as eyebrows, eyes, nose and mouth, edge detector is applied on the segmented face image. The area of eye and the center of face are found from horizontal and vertical components of the edge map of the segmented image. other facial features are obtained from edge information of the image. The characteristic vectors are extrated from DWT of the segmented face image. These characteristic vectors are normalized between +1 and -1, and are used as input vectors for the neural network. Simulation results show recognition rate of 100% on the learned system, and about 92% on the test images.

• Journal of Advanced Navigation Technology
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• v.10 no.3
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• pp.219-225
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• 2006

This paper presents a method of object classification based on discrete wavelet transform (DWT) and fuzzy inference(FI). It concentrated not only on the design of fuzzy inference algorithm which is suitable for low speed uninhabited transportation such as, conveyor but also on the minimize the number of fuzzy rule. In the preprocess of feature extracting, feature parameters are extracted by using characteristics of the coefficients matrix of DWT. Such feature parameters as area, perimeter and a/p ratio are used obtained from DWT coefficients blocks. Secondly, fuzzy if - then rules that can be able to adapt the variety of surroundings are developed. In order to verify the performance of proposed scheme, In the middle of fuzzy inference, the Mamdani's and the Larsen 's implication operators are utilized. Experimental results showed that proposed scheme can be applied to the variety of surroundings.

• Journal of the Institute of Convergence Signal Processing
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• v.11 no.1
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• pp.1-8
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• 2010

Noise removal methods for noisy images have been studied a lot in the domain of spatial and transform filtering. Low pass filtering was initially applied in the spatial domain. Recently, discrete wavelet transform has widely used for image denoising as well as image compression due to an excellent energy compaction and a property of multiresolution. In this paper, Gabor cosine and sine transform which is considered as human visual filter is applied to image denoising areas using soft thresholding technique. GCST is compared with excellent wavelet transform which uses existing soft thresholding methods from PSNR point of view. Resultant images removed noises are also visually compared. Experimental results with adding four different standard deviation levels of Gaussian distributed noises to real images show that the proposed transform has better PSNR performance of a maximum of 1.18 dB and visible perception than wavelet transform.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.1
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• pp.65-74
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• 2012

In this paper, we explore the application of 2-D dual-tree discrete wavelet transform (DDWT), which is a directional and redundant transform, for image coding. DDWT introduces limited redundancy and allows the transform to provide approximate shift invariance and directionally selective filters while preserving the usual properties of perfect reconstruction and computational efficiency with good well-balanced frequency responses. Also, quincunx lattice yields a non separable 2D-wavelet transform, which is also symmetric in both horizontal and vertical direction. And non-separable wavelet transformation can generate sub-images of multiple degrees rotated versions. The proposed 2-D non-separable DDWT can provide efficient approximation for directional features of images schemes, such as edges and contours in images that are not aligned with the horizontal or vertical direction. Finally, non-separable image processing using DDWT services good performance.

• Proceedings of the KIEE Conference
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• 2007.04c
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• pp.46-48
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• 2007

This paper presents research about improvement of fault detection algorithm in FRTU on the feeder of distribution system. FRTU(Feeder Remote Terminal Unit) is applied to fault detection schemes for phase fault, ground fault, and cold load pickup and Inrush restraint functions distinguish the fault current and the normal load current. FRTU is occurred FI(Fault Indicator) when current is over pick-up value also inrush current is occurred FRTU indicate FI. Discrete wavelet transform(DWT) analysis gives the frequency and time-scale information. The neural network system as a fault detector was trained to discriminate inrush current from the fault status by a gradient descent method. In this paper, fault detection is improved using voltage monitoring system with DWT and neural network. These data were measured in actual 22.9kV distribution system.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.1
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• pp.1017-1021
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• 2005

현대에 있어서 영상정보는 아주 큰 비중을 차지하고 있다. 따라서 이러한 영상정보를 얼마나 빨리 그리고 많이 압축 시킬 수 있는가가 핵심적인 관건이다. 본 논문에서는 공간적 압축 방식의 핵심인 DCT와 비교하여 블록킹 효과(Blocking Effect)과 없고, 우수한 압축 성능을 갖는 DWT(Discrete Wavelet Transform)알고리즘을 적용한 2차원 이산 웨이브렛 변환 필터를 설계하였다. 본 논문에서 구현한 DWT 필터는 FIR필터 방법으로 설계하였으며, Daubenchies-4 Tap을 이용하였고, 파이프라인 연산으로 승산기, 가산기를 병렬로 처리하여 고속연산을 수행하였다. 뿐만 아니라 메모리 맵핑 과정과 메모리 컨트롤 어드레스 발생기를 사용하여 메모리와 연산량을 최소화 하여 칩사이즈를 줄여 설계하였다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.5C
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• pp.654-654
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• 2004

본 논문에서는 이산웨이블렛 변환을 이용한 영상 압축 프로세서를 하드웨어로 구현하였다. 웨이블렛 변환을 위하여 필터뱅크 및 피라미드 알고리즘을 이용하였고 각 필터들은 FIR 필터로 구현하였다. 병렬구조로 이루어져 동일 클럭 싸이클에서 하이패스와 로패스를 동시에 수행함으로써 속도를 향상시킬 뿐 아니라 QMF 특성을 이용하여 DWT 연산에 필요한 승산기의 수를 절반으로 줄임으로써 하드웨어 크기를 줄이고 이용효율 또한 높일 수 있다. 다중 해상도 분해 시 필요한 메모리 컨트롤러를 하드웨어로 구현하여 DWT 계산이 수행되므로 이 융자는 단순한 파라메터 입력만으로 효과적인 압축율을 얻을 수 있도록 구조적으로 설계하였다. 실시간 영상압축 프로세서의 성능 예측을 위하여 MATLAB을 통하여 시뮬레이션 하였고, VHDL을 이용하여 각 모듈들을 설계하였다. 설계한 영상압축기는 Leonaro-Spectrum에서 합성하였고, ALTERA FLEX10KE(EPF10K100 EFC256) FPGA에 이식하여 하드웨어적으로 동작을 검증하였다. 설계된 부호화기는 512×512 Woman 영상에 대하여 33㏈의 PSNR값을 갖는다. 그리고 설계된 프로세서를 FPGA 구현 시 35㎒에서 정상적으로 동작한다.