• Title/Summary/Keyword: wavelet technique

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Best Use of the Measured Earthquake Data (지진관측자료의 효과적인 활용에 관한 고찰)

  • 연관희;박동희;김성주;최원학;장천중
    • Proceedings of the Earthquake Engineering Society of Korea Conference
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    • 2001.09a
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    • pp.36-43
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    • 2001
  • In Korea, we are absolutely short of earthquake data in good quality from moderate and large earthquakes, which are needed fur the study of strong ground motion characteristics. This means that the best use of the available data is needed far the time being. In this respect, several methods are suggested in this paper, which can be applied in the process of data selection and analysis. First, it is shown that the calibration status of seismic stations can be easily checked by comparing the spectra from accelerometer and velocity sensor both of which are located at the same location. Secondly, it is recommended that S/N ratio in the frequency domain should be checked before discarding the data by only look of the data in time domain. Thirdly, the saturated earthquake data caused by ground motion level exceeding the detection limit of a seismograph are considered to see if such data can be used for spectrum analysis by performing numerical simulation. The result reveals that the saturated data can still be used within the dominant frequency range according to the levels of saturation. Finally, a technique to minimize the window effect that distorts the low frequency spectrum is suggested. This technique involves detrending in displacement domain once the displacement data are obtained by integration of low frequency components of the original data in time domain. Especially, the low frequency component can be separated by using discrete wavelet transform among many alternatives. All of these methods mentioned above may increase the available earthquake data and frequency range.

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Diagnostic System for Crashing and Damping Signals in Engine-Assembly Line (엔진 양산라인의 충격성 불량유형 신호 진단을 위한 진단시스템 개발)

  • Oh, Se-Do;Kim, Young-Jin;Seo, Hae-Yun;Lee, Tae-Hwi;Lee, Jae-Won
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.35 no.8
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    • pp.965-970
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    • 2011
  • We develop a diagnostic system to monitor failures in an engine-assembly line. Existing techniques such as sensory analysis, time domain analysis, frequency analysis, and statistical analysis have limitations in the diagnosis of engine-assembly failure when there are abnormal vibration waveforms (crashing and damping signals) during the assembly. We use a wavelet technique to deal with crashing and damping signals. We also implement a new technique for developing diagnostic rules from sensor data, and we demonstrate its validity.

Design and Implementation of Low-Power DWT Processor for JPEG2000 Compression of Medical Images (의료영상의 JPEG2000 압축을 위한 저전력 DWT 프로세서의 설계 및 구현)

  • Jang Young-Beom;Lee Won-Sang;Yoo Sun-Kook
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.54 no.2
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    • pp.124-130
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    • 2005
  • In this paper, low-power design and implementation techniques for DWT(Discrete Wavelet Transform) of the JPEG2000 compression are proposed. In DWT block of the JPEG2000, linear phase 9 tap and 7 tap filters are used. For low-power implementation of those filters, processor technique for DA(Distributed Arithmetic) filter and minimization technique for number of addition in CSD(Canonic Signed Digit) filter are utilized. Proposed filter structure consists of 3 blocks. In the first CSD coefficient block, every possible 4 bit CSD coefficients are calculated and stored. In second processor block, multiplication is done by MUX and addition processor in terms of the binary values of filter coefficient. Finally, in third block, multiplied values are output and stored in flip-flop train. For comparison of the implementation area and power dissipation, proposed and conventional structures are implemented by using Verilog-HDL coding. In simulation, it is shown that 53.1% of the implementation area can be reduced comparison with those of the conventional structure.

Sound Watermarking Technique based on Blackfin Processor (블랙핀 프로세서 기반의 사운드 워터마킹 기법)

  • Kim, Ye-il;Seo, Jung-hee;Park, Hung-bog
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2015.10a
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    • pp.757-758
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    • 2015
  • The digital watermark is one of important techniques to solve copyright authentication problems of digital media. Researches on the digital watermark are rapidly increasing in various media. The watermark system can resist some attacks such as signal attack, geometric attack and protocol attach. However, so far the robustness of the watermark needs to be improved. This paper suggests a watermarking technique with which a watermark is embedded on a coefficient of wavelet-based frequency band and extracted from it for protection of property rights and authentication of Blackfin processor-based digital sound. By carrying out hardware implementation of the suggested sound watermarking, the commercialization of protection of property rights and robustness of watermarks resulted from development of high-level programs can be confirmed.

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Zero-tree packetization without additional memory using DFS (DFS를 이용한 추가 메모리를 요구하지 않는 제로트리 압축기법)

  • Kim, Chung-Kil;Lee, Joo-Kyong;Chung, Ki-Dong
    • The KIPS Transactions:PartB
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    • v.10B no.5
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    • pp.575-578
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    • 2003
  • SPIHT algorithm is a wavelet based fast and effective technique for image compression. It uses a list structure to store status information which is generated during set-partitioning of zero-tree. Usually, this requires lots of additional memory depending on how high the bit-rate is. Therefore, in this paper, we propose a new technique called MZP-DFS, which needs no additional memory when running SPIHT algorithm. It traverses a spatial-tree according to DFS and eliminates additional memory as it uses test-functions for encoding and LSB bits of coefficients for decoding respectively. This method yields nearly the same performance as SPIHT. This may be desirable in hardware implementation because no additional memory is required. Moreover. it exploits parallelism to process each spatial-tree that it can be applied well in real-time image compression.

An Improved Motion Compensated Temporal Filtering for Efficient Scalable Video Coding (효율적인 스케일러블 비디오 부호화를 위한 향상된 움직임 보상 시간적 필터링 방법)

  • Jeon, Ki-Cheol;Kim, Jong-Ho;Jeong, Je-Chang
    • 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.

Texture segmentation using Neural Networks and multi-scale Bayesian image segmentation technique (신경회로망과 다중스케일 Bayesian 영상 분할 기법을 이용한 결 분할)

  • Kim Tae-Hyung;Eom Il-Kyu;Kim Yoo-Shin
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.42 no.4 s.304
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    • pp.39-48
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    • 2005
  • This paper proposes novel texture segmentation method using Bayesian estimation method and neural networks. We use multi-scale wavelet coefficients and the context information of neighboring wavelets coefficients as the input of networks. The output of neural networks is modeled as a posterior probability. The context information is obtained by HMT(Hidden Markov Tree) model. This proposed segmentation method shows better performance than ML(Maximum Likelihood) segmentation using HMT model. And post-processed texture segmentation results as using multi-scale Bayesian image segmentation technique called HMTseg in each segmentation by HMT and the proposed method also show that the proposed method is superior to the method using HMT.

Texture Segmentation Using Statistical Characteristics of SOM and Multiscale Bayesian Image Segmentation Technique (SOM의 통계적 특성과 다중 스케일 Bayesian 영상 분할 기법을 이용한 텍스쳐 분할)

  • Kim Tae-Hyung;Eom Il-Kyu;Kim Yoo-Shin
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.42 no.6
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    • pp.43-54
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    • 2005
  • This paper proposes a novel texture segmentation method using Bayesian image segmentation method and SOM(Self Organization feature Map). Multi-scale wavelet coefficients are used as the input of SOM, and likelihood and a posterior probability for observations are obtained from trained SOMs. Texture segmentation is performed by a posterior probability from trained SOMs and MAP(Maximum A Posterior) classification. And the result of texture segmentation is improved by context information. This proposed segmentation method shows better performance than segmentation method by HMT(Hidden Markov Tree) model. The texture segmentation results by SOM and multi-sclae Bayesian image segmentation technique called HMTseg also show better performance than by HMT and HMTseg.

Zero-tree Packetization without Additional Memory using BFS (BFS를 이용한 추가 메모리를 요구하지 않는 제로트리 압축기법)

  • 김충길;정기동
    • Journal of KIISE:Computer Systems and Theory
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    • v.31 no.5_6
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    • pp.321-327
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    • 2004
  • SPIHT algorithm is a wavelet based fast and effective technique for image compression. It uses a list structure to store status information which is generated during set-partitioning of toro-tree. Usually, this requires lots of additional memory depending on how high the bit-rate is. Therefore, in this paper, we propose a new technique called MZC-BFS, which needs no additional memory when running SPIHT algorithm. It explicitly performs a breadth first search of the spatial-tree using peano-code and eliminates additional memory as it uses pre-status significant test for encoding and LSB bits of some coefficients for decoding respectively. This method yields nearly the same performance as SPIHT. This may be desirable in fast and simple hardware implementation and reduces the cost of production because no lists and additional memory are required.

Encryption-based Image Steganography Technique for Secure Medical Image Transmission During the COVID-19 Pandemic

  • Alkhliwi, Sultan
    • International Journal of Computer Science & Network Security
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    • v.21 no.3
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    • pp.83-93
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    • 2021
  • COVID-19 poses a major risk to global health, highlighting the importance of faster and proper diagnosis. To handle the rise in the number of patients and eliminate redundant tests, healthcare information exchange and medical data are transmitted between healthcare centres. Medical data sharing helps speed up patient treatment; consequently, exchanging healthcare data is the requirement of the present era. Since healthcare professionals share data through the internet, security remains a critical challenge, which needs to be addressed. During the COVID-19 pandemic, computed tomography (CT) and X-ray images play a vital part in the diagnosis process, constituting information that needs to be shared among hospitals. Encryption and image steganography techniques can be employed to achieve secure data transmission of COVID-19 images. This study presents a new encryption with the image steganography model for secure data transmission (EIS-SDT) for COVID-19 diagnosis. The EIS-SDT model uses a multilevel discrete wavelet transform for image decomposition and Manta Ray Foraging Optimization algorithm for optimal pixel selection. The EIS-SDT method uses a double logistic chaotic map (DLCM) is employed for secret image encryption. The application of the DLCM-based encryption procedure provides an additional level of security to the image steganography technique. An extensive simulation results analysis ensures the effective performance of the EIS-SDT model and the results are investigated under several evaluation parameters. The outcome indicates that the EIS-SDT model has outperformed the existing methods considerably.