• Title/Summary/Keyword: Wavelet energy

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A Study on Efficient Feature-Vector Extraction for Content-Based Image Retrieval System (내용 기반 영상 검색 시스템을 위한 효율적인 특징 벡터 추출에 관한 연구)

  • Yoo Gi-Hyoung;Kwak Hoon-Sung
    • The KIPS Transactions:PartB
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    • v.13B no.3 s.106
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    • pp.309-314
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    • 2006
  • Recently, multimedia DBMS is appeared to be the core technology of the information society to store, manage and retrieve multimedia data efficiently. In this paper, we propose a new method for content based-retrieval system using wavelet transform, energy value to extract automatically feature vector from image data, and suggest an effective retrieval technique through this method. Wavelet transform is widely used in image compression and digital signal analysis, and its coefficient values reflect image feature very well. The correlation in wavelet domain between query image data and the stored data in database is used to calculate similarity. In order to assess the image retrieval performance, a set of hundreds images are run. The method using standard derivation and mean value used for feature vector extraction are compared with that of our method based on energy value. For the simulation results, our energy value method was more effective than the one using standard derivation and mean value.

Adaptive Discrete Wavelet Transform Based on Block Energy for JPEG2000 Still Images (JPEG2000 정지영상을 위한 블록 에너지 기반 적응적 이산 웨이블릿 변환)

  • Kim, Dae-Won
    • Journal of the Institute of Convergence Signal Processing
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    • v.8 no.1
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    • pp.22-31
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    • 2007
  • The proposed algorithm in this paper is based on the wavelet decomposition and the energy computation of composed blocks so the amount of calculation and complexity is minimized by adaptively replacing the DWT coefficients and managing the resources effectively. We are now living in the world of a lot. of multimedia applications for many digital electric appliances and mobile devices. Among so many multimedia applications, the digital image compression is very important technology for digital cameras to store and transmit digital images to other sites and JPEG2000 is one of the cutting edge technology to compress still images efficiently. The digital cm technology is mainly using the digital image compression features so that those images could be efficiently saved locally and transferred to other sites without any losses. JPEG2000 standard is applicable for processing the digital images usefully to keep, send and receive through wired and/or wireless networks. The discrete wavelet transform (DWT) is one of the main differences to the previous digital image compression standard such as JPEG, performing the DWT to the entire image rather than splitting into many blocks. Several digital images m tested with this method and restored to compare to the results of conventional DWT which shows that the proposed algorithm get the better result without any significant degradation in terms of MSE & PSNR and the number of zero coefficients when the energy based adaptive DWT is applied.

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A Parametric Voice Activity Detection Based on the SPD-TE for Nonstationary Noises (비정체성 잡음을 위한 SPD-TE 기반 계수형 음성 활동 탐지)

  • Koo, Boneung
    • The Journal of the Acoustical Society of Korea
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    • v.34 no.4
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    • pp.310-315
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    • 2015
  • A single channel VAD (Voice Activity Detection) algorithm for nonstationary noise environment is proposed in this paper. Threshold values of the feature parameter for VAD decision are updated adaptively based on estimates of means and standard deviations of past non-speech frames. The feature parameter, SPD-TE (Spectral Power Difference-Teager Energy), is obtained by applying the Teager energy to the WPD (Wavelet Packet Decomposition) coefficients. It was reported previously that the SPD-TE is robust to noise as a feature for VAD. Experimental results by using TIMIT speech and NOISEX-92 noise databases show that decision accuracy of the proposed algorithm is comparable to several typical VAD algorithms including standards for SNR values ranging from 10 to -10 dB.

A Novel Approach to Enhance Dual-Energy X-Ray Images Using Region of Interest and Discrete Wavelet Transform

  • Ullah, Burhan;Khan, Aurangzeb;Fahad, Muhammad;Alam, Mahmood;Noor, Allah;Saleem, Umar;Kamran, Muhammad
    • Journal of Information Processing Systems
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    • v.18 no.3
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    • pp.319-331
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    • 2022
  • The capability to examine an X-ray image is so far a challenging task. In this work, we suggest a practical and novel algorithm based on image fusion to inspect the issues such as background noise, blurriness, or sharpness, which curbs the quality of dual-energy X-ray images. The current technology exercised for the examination of bags and baggage is "X-ray"; however, the results of the incumbent technology used show blurred and low contrast level images. This paper aims to improve the quality of X-ray images for a clearer vision of illegitimate or volatile substances. A dataset of 40 images was taken for the experiment, but for clarity, the results of only 13 images have been shown. The results were evaluated using MSE and PSNR metrics, where the average PSNR value of the proposed system compared to single X-ray images was increased by 19.3%, and the MSE value decreased by 17.3%. The results show that the proposed framework will help discern threats and the entire scanning process.

DWT-Based Parameter and Iteration Algorithm for Preventing Arc False Detection in PV DC Arc Fault Detector (태양광 직렬 아크 검출기의 오검출 방지를 위한 DWT 기반 파라미터 및 반복 알고리즘)

  • Ahn, Jae-Beom;Lee, Jin-Han;Lee, Jin;Ryoo, Hong-Je
    • The Transactions of the Korean Institute of Power Electronics
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    • v.27 no.2
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    • pp.100-105
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    • 2022
  • This paper applies the arc detection algorithm to prevent the false detection in photo voltaic series arc detection circuit, which is required not only to detect the series arc quickly, but also not falsely detect the arc for the non-arc noise. For this purpose, this study proposes a rapid and preventive false detection method of single peak noise and short noise signals. First, to prevent false detection by single peak noise, Discrete wavelet transform (DWT)-based characteristic parameters are applied to determine the shape and the amplitude of the noise. In addition, arc fault detection within a few milliseconds is performed with the DWT iterative algorithm to quickly prevent false detection for short noise signals, considering the continuity of serial arc noise. Thus, the method operates not only to detect series arc, but also to avoid false arc detection for peak and short noises. The proposed algorithm is applied to real-time serial arc detection circuit based on the TMS320F28335 DSP. The serial arc detection and peak noise filtering performances are verified in the built simulated arc test facility. Furthermore, the filtering performance of short noise generated through DC switch operation is confirmed.

ASIC Design of Wavelet Transform Filter for Moving Picture (동영상용 웨이브렛 변환 필터의 ASIC 설계)

  • Kang, Bong-Hoon;Lee, Ho-Joon;Koh, Hyung-Hwa
    • Journal of the Korean Institute of Telematics and Electronics S
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    • v.36S no.12
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    • pp.67-75
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    • 1999
  • In this paper, we present an ASIC(Application Specific Integrated Circuit) design of wavelet transform filter Wavelet transform is used in lots of application fields which include image compression, because it has an excellent energy compaction. The operation characteristic and performance of wavelet transform filter are analyzed by using verilog-HDL(Hardware Description Language). In this paper, the designed wavelet transform filter uses line memory to improve data processing rate. Generally, when it reads and writes data of DRAM by using Fast Page Mode, input and output processing is very fast in horizontal direction but substantially slow in vertical direction. The use of line memory solves this low speed processing problem. As a result, though the size of the chip is getting larger, processing time for an image frame becomes 4.66ms. Generally, since the limit of 1 frame processing time on the data of TV video is 33ms, so it is appropriate for TV video.

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Flaw Detection in Pipe-Welded Zone by Using Wavelet Transform and SH-EMAT (웨이브렛 변환과 SH-EMAT을 이용한 배관 용접부 결함 검출)

  • Lee, Jin-Hyuk;Kim, Dae-Hyun
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.36 no.12
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    • pp.1511-1519
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    • 2012
  • Pipe structures contain many welded zones, and ultrasonic tests are increasingly being performed by using automated testing devices in order to evaluate the weld integrity. An electromagnetic acoustic transducer (EMAT) is a noncontact transducer that can transmit or receive ultrasonic waves without a couplant. Furthermore, it can easily generate specific guided waves such as SH (shear horizontal) or Lamb waves by altering the design of the coil and magnet. Therefore, an EMAT should be useful for application to an automated ultrasonic inspection system. In this study, SH waves generated using an EMAT were applied to inspect the pipe-weld zone. To analyze the specific SH mode (SH0) from the SH wave signals, wavelet transform was applied. It was found that flaws could be detected precisely because the intensity of the $SH_0$ mode-frequency, which is analyzed by using wavelet transform, is proportional to the length of the flaw.

A novel method to aging state recognition of viscoelastic sandwich structures

  • Qu, Jinxiu;Zhang, Zhousuo;Luo, Xue;Li, Bing;Wen, Jinpeng
    • Steel and Composite Structures
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    • v.21 no.6
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    • pp.1183-1210
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    • 2016
  • Viscoelastic sandwich structures (VSSs) are widely used in mechanical equipment, but in the service process, they always suffer from aging which affect the whole performance of equipment. Therefore, aging state recognition of VSSs is significant to monitor structural state and ensure the reliability of equipment. However, non-stationary vibration response signals and weak state change characteristics make this task challenging. This paper proposes a novel method for this task based on adaptive second generation wavelet packet transform (ASGWPT) and multiwavelet support vector machine (MWSVM). For obtaining sensitive feature parameters to different structural aging states, the ASGWPT, its wavelet function can adaptively match the frequency spectrum characteristics of inspected vibration response signal, is developed to process the vibration response signals for energy feature extraction. With the aim to improve the classification performance of SVM, based on the kernel method of SVM and multiwavelet theory, multiwavelet kernel functions are constructed, and then MWSVM is developed to classify the different aging states. In order to demonstrate the effectiveness of the proposed method, different aging states of a VSS are created through the hot oxygen accelerated aging of viscoelastic material. The application results show that the proposed method can accurately and automatically recognize the different structural aging states and act as a promising approach to aging state recognition of VSSs. Furthermore, the capability of ASGWPT in processing the vibration response signals for feature extraction is validated by the comparisons with conventional second generation wavelet packet transform, and the performance of MWSVM in classifying the structural aging states is validated by the comparisons with traditional wavelet support vector machine.

Enhancing seismic reflection signal (탄성파 반사 신호 향상)

  • Hien, D.H.;Jang, Seong-Hyung;Kim, Young-Wan;Suh, Sang-Yong
    • 한국신재생에너지학회:학술대회논문집
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    • 2008.05a
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    • pp.606-609
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    • 2008
  • Deconvolution is one of the most used techniques for processing seismic reflection data. It is applied to improve temporal resolution by wavelet shaping and removal of short period reverberations. Several deconvolution algorithms such as predicted, spike, minimum entropy deconvolution and so on has been proposed to obtain such above purposes. Among of them, $\iota_1$ norm proposed by Taylor et al., (1979) and used to compared to minimum entropy deconvolution by Sacchi et al., (1994) has given some advantages on time computing and high efficiency. Theoritically, the deconvolution can be considered as inversion technique to invert the single seismic trace to the reflectivity, but it has not been successfully adopted due to noisy signals of the real data set and unknown source wavelet. After stacking, the seismic traces are moved to zero offset, thus each seismic traces now can be a single trace that is created by convolving the seismic source wavelet and reflectivity. In this paper, the fundamental of $\iota_1$ norm deconvolution method will be introduced. The method will be tested by synthetic data and applied to improve the stacked section of gas hydrate.

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A Study on Classification and Localization of Structural Damage through Wavelet Analysis

  • Koh, Bong-Hwan;Jung, Uk
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2007.11a
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    • pp.754-759
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    • 2007
  • This study exploits the data discriminating capability of silhouette statistics, which combines wavelet-based vertical energy threshold technique for the purpose of extracting damage-sensitive features and clustering signals of the same class. This threshold technique allows to first obtain a suitable subset of the extracted or modified features of our data, i.e., good predictor sets should contain features that are strongly correlated to the characteristics of the data without considering the classification method used, although each of these features should be as uncorrelated with each other as possible. The silhouette statistics have been used to assess the quality of clustering by measuring how well an object is assigned to its corresponding cluster. We use this concept for the discriminant power function used in this paper. The simulation results of damage detection in a truss structure show that the approach proposed in this study can be successfully applied for locating both open- and breathing-type damage even in the presence of a considerable amount of process and measurement noise.

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