• Journal of Korea Multimedia Society
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• v.22 no.11
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• pp.1233-1241
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• 2019

The goal of the sound-based mechanical fault diagnosis technique is to automatically find abnormal signals in the machine using acoustic emission. Conventional methods of using mathematical models have been found to be inaccurate due to the complexity of industrial mechanical systems and the existence of nonlinear factors such as noise. Therefore, any fault diagnosis issue can be treated as a pattern recognition problem. We propose an automatic fault diagnosis method using discrete wavelet transform and power spectrum density using multi pattern recognition. First, we perform DWT-based filtering analysis for noise cancelling and effective feature extraction. Next, the power spectral density(PSD) is performed on each subband of the DWT in order to effectively extract feature vectors of sound. Finally, each PSD data is extracted with the features of the classifier using multi pattern recognition. The results show that the proposed method can not only be used effectively to detect faults as well as apply to various automatic diagnosis system based on sound.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.4
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• pp.341-348
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• 2013

A location estimation algorithm based on the sea-surface beacon is proposed in this paper. The beacon is utilized to provide ultrasonic signals to the underwater vehicles around the beacon to estimate precise position of underwater vehicles (ROV, AUV, Diver robot), which is named as USBL (Ultra Short Baseline) system. It utilizes GPS and INS data for estimating its position and adopts DWT (Discrete Wavelet Transform) de-noising filter and UKF (Unscented KALMAN Filter) elaborating the position estimation. The beacon system aims at estimating the precise position of underwater vehicle by using USBL to receive the tracking signals. The most important one for the precise position estimation of underwater vehicle is estimating the position of the beacon system precisely. Since the beacon is on the sea-waves, the received GPS signals are noisy and unstable most of times. Therefore, the INS data (gyroscope sensor, accelerometer, magnetic compass) are obtained at the beacon on the sea-surface to compensate for the inaccuracy of the GPS data. The noises in the acceleration data from INS data are reduced by using DWT de-noising filter in this research. Finally the UKF localization system is proposed in this paper and the system performance is verified by real experiments.

• Journal of Multimedia Information System
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• v.3 no.2
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• pp.35-42
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• 2016

Electrocardiogram (ECG) signal gives a clear indication whether the heart is at a healthy status or not as the early notification of a cardiac problem in the heart could save the patient's life. Several methods were launched to clarify how to diagnose the abnormality over the ECG signal waves. However, some of them face the problem of lack of accuracy at diagnosis phase of their work. In this research, we present an accurate and successive method for the diagnosis of abnormality through Discrete Wavelet Transform (DWT), QRS complex detection and Support Vector Machines (SVM) classification with overall accuracy rate 95.26%. DWT Refers to sampling any kind of discrete wavelet transform, while SVM is known as a model with related learning algorithm, which is based on supervised learning that perform regression analysis and classification over the data sample. We have tested the ECG signals for 10 patients from different file formats collected from PhysioNet database to observe accuracy level for each patient who needs ECG data to be processed. The results will be presented, in terms of accuracy that ranged from 92.1% to 97.6% and diagnosis status that is classified as either normal or abnormal factors.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.8B
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• pp.1119-1128
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• 2001

본 논문에서는 이차원(2-D) 이산 웨이블릿 면환(Discrete Wavelet Transform, DWT)을 이용한 연상압축기를 FPGA 칩에서 실시간으로 동작 가능하도록 하는 효율적인 메모리 스케줄링 방법(E$^2$M$^2$)을 제안하였다. S/W적으로 위의 메모리 사상 방법을 검증한 후, 실제로 상용화된 SFRAM을 선정하여 메모리 제어기를 구현하였다. 본 논문에서는 Mallet-tree를 이용한 2-D DWT 영상압축 칩을 구현할 경우를 가정하였다. 이 알고리즘은 연산 과정에서 많은 데이터를 정장하여야 하는데, FPGA는 많은 데이터를 저장할 수 있는 메모리가 내장되어 있지 않으므로 외부 메모리를 사용하여야 한다. 외부메모리는 열(row)에 대해서만 연속(burst) 읽기, 쓰기 동작이 가능하기 때문에 Mallet-tree 알고리즘의 데이터 입출력을 그대로 적용할 경우 실시간 동작을 수행하는 DWT 압축 칩을 구현할 수 없다. 본 논문에서는 데이터 쓰기를 수행할 경우에는 메모리 셀(cell)의 수직 방향을 저장시키고 읽기를 수행할 때는 수평으로 데이터의 연속 읽기를 수행함으로써 필터가 항상 수평 방향에 위치하게 하는 방법을 제안하였다. 입방법을 C-언어로 DWT 커넬(Kernel)과 메모리의 에뮬레이터(emulator)를 구현하여 실험한 결과, Mallat-tree 이론을 그대로 적용시켰을 때와 동일한 필터링을 수행할 수 있음을 검증하였다. 또한, 상용화된 SDRAM의 메모리 제어기를 H/W로 구현하여 시뮬레이션 함으로써 본 논문에서 제안한 방법이 실제적인 하드웨어로 실시간 동작을 할 수 있음을 보였다.

• Korean Journal of Remote Sensing
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• v.21 no.3
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• pp.243-252
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• 2005

Wavelet transform and its inverse processing provide the effective framework for data fusion. The purpose of this study is to investigate applicability of wavelet transform using texture images for the urban remote sensing application. We tried several experiments regarding image fusion by wavelet transform and texture imaging using high resolution images such as IKONOS and KOMPSAT EOC. As for texture images, we used homogeneity and ASM (Angular Second Moment) images according that these two types of texture images reveal detailed information of complex features of urban environment well. To find out the useful combination scheme for further applications, we performed DWT(Discrete Wavelet Transform) and IDWT(Inverse Discrete Wavelet Transform) using texture images and original images, with adding edge information on the fused images to display texture-wavelet information within edge boundaries. The edge images were obtained by the LoG (Laplacian of Gaussian) processing of original image. As the qualitative result by the visual interpretation of these experiments, the resultant image by each fusion scheme will be utilized to extract unique details of surface characterization on urban features around edge boundaries.

• The KIPS Transactions:PartB
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• v.9B no.3
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• pp.351-358
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• 2002

Video compression based on DCT (Discrete Cosine Transform) has weakpoints of blocking artifacts and pixel loss when the resolution is changed. DWT (Discrete Wavelet Transform) based method can overcome such problems. In SAMCoW (Scalable Adaptive Motion Compensation Wavelet), one of wavelet based video coding algorithm, both intra frames and motion compensated error frames are encoded using EZW(Embedded Zerotree Wavelet) algorithm. However the property of wavelets transform coefficients of motion compensated error frames are different from that of still images. Signal energy is not highly concentrated in the lower bands which is true for most still image cases. Signal energy is rather evenly distributed over all frequency bands. This paper suggests a new video coding algorithm utilizing these properties. Spatial band coding which is known to be very effective for encoding images with relative1y high frequency components and not utilizing the interband coefficients correlation is applied instead of EZW to encode both intra and inter frames. In spatial band coding, the position and value of significant wavelet coefficients in each band are progressively transmitted. Unlike EZW, inter band coefficients correlations are not utilized in spatial band coding. It has been shown that spatial band coding gives better performance than EZW when applied to wavelet based video compression.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.7
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• pp.1437-1446
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• 2012

In this paper we propose a new stereo matching algorithm which is suitable for application to obtain depth information with high-speed in stereoscopic camera environment. For satisfying these condition we propose a new adaptive stereo matching technique using frequency information in discrete wavelet (DWT) domain and variable matching window. The size of the matching window is selected by analysis of the local property of the image in spatial domain and the feature and scaling factor of the matching window is selected by the frequency property in the frequency domain. For using frequency information we use local DWT and global DWT. We identified that the proposed technique has better peak noise to signal ratio (PSNR) than the fixed matching techniques with similar complexity.

• Journal of Advanced Navigation Technology
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• v.20 no.3
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• pp.196-202
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• 2016

In this paper, a stationary wavelet transform method is proposed for improving the altitude control performance of quadrotor UAV using an ultrasonic rangefinder. A ground tests are conducted using an ultrasonic rangefinder that is much used for vertical takeoff and landing. An ultrasonic rangefinder suffers from signal's spike due to specular reflectance and acoustic noise. The occurred spikes in short time span need to be analyzed at both sides time and frequency domain. It was known that stationary wavelet transform is the transferring solution to the problem occurred by down sampling from DWT also more efficient to remove noise than DWT. The analyzed spikes of the ultrasonic rangefinder using a stationary wavelet transform and experimental results show that it can effectively remove the spikes of the ultrasonic rangefinder.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.7
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• pp.1575-1581
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• 2003

As a society has progressed rapidly toward a highly advanced digital information age, a multimedia communication service for acquisition, transmission and storage of image data as well as voice has being commercialized externally and internally. However, in the process of digitalization or transmission of data, noise is generated by several causes, and researches for eliminating those noises have been continued until now. There were the existing FFT(fast fourier transform) and STFT(short time fourier transform) for removing noise but it's impossible to know information about time and time-frequency localization capabilities has conflictive relationship. Therefore, for overcoming these limits, wavelet transform which is presented as a new technique of signal processing field is being applied in many fields recently. Because it has time-frequency localization capabilities it's Possible for multiresolution analysis as well as easy to analyze various signal. And when two wavelet base were designed to form Hilbert transform pair, wavelet pair provide superior performance than the existing DWT(discrete wavelet transform) in data characteristic detection. Therefore in this parer, we removed impulse noise by using adaptive-length median filter and two dyadic wavelet base which is designed by truncated coefficient vector.

• Proceedings of the IEEK Conference
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• 2002.07a
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• pp.353-356
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• 2002

In this paper, we design an efficient, scalable one-dimensional discrete wavelet transform (1DDWT) filter using data reorder unit (DRU). At each level, the required hardware is optimized by sharing multipliers and adders because the input rate is reduced by a factor of two at each level due to decimation. The proposed architecture shows 100% hardware utilization by balancing hardware with input rate. Furthermore, sharing the coefficients of the highpass and the lowpass filters using the mirror filter property reduces the number of multipliers and adders by half. We designed a scalable DRU that efficiently reorders and feeds inputs to highpass and lowpass filters. The proposed DRU-based architecture is so regular and scalable that it can be easily extended to an arbitrary 1D DWT structure with M taps and J levels. Compared to other architectures, the proposed DWT filter shows efficiency in performance with relatively less hardware.