• Title/Summary/Keyword: Similarity transform

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Micro-seismic monitoring in mines based on cross wavelet transform

  • Huang, Linqi;Hao, Hong;Li, Xibing;Li, Jun
    • Earthquakes and Structures
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    • v.11 no.6
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    • pp.1143-1164
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    • 2016
  • Time Delay of Arrival (TDOA) estimation methods based on correlation function analysis play an important role in the micro-seismic event monitoring. It makes full use of the similarity in the recorded signals that are from the same source. However, those methods are subjected to the noise effect, particularly when the global similarity of the signals is low. This paper proposes a new approach for micro-seismic monitoring based on cross wavelet transform. The cross wavelet transform is utilized to analyse the measured signals under micro-seismic events, and the cross wavelet power spectrum is used to measure the similarity of two signals in a multi-scale dimension and subsequently identify TDOA. The offset time instant associated with the maximum cross wavelet transform spectrum power is identified as TDOA, and then the location of micro-seismic event can be identified. Individual and statistical identification tests are performed with measurement data from an in-field mine. Experimental studies demonstrate that the proposed approach significantly improves the robustness and accuracy of micro-seismic source locating in mines compared to several existing methods, such as the cross-correlation, multi-correlation, STA/LTA and Kurtosis methods.

Developing a Three-dimensional Spectral Model Using Similarity Transform Technique (유사변환기법을 이용한 3차원 모델의 개발)

  • Kang, Kwan-Soo;So, Jae-Kwi;Jung, Kyung-Tae;Sonu, Jung Ho
    • Journal of Korean Society of Coastal and Ocean Engineers
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    • v.5 no.2
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    • pp.107-120
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    • 1993
  • This paper presents a new modal solution of linear three-dimensional hydrodynamic equations using similarity transform technique. The governing equations are first separated into external and internal mode equations. The solution of the internal mode equation then proceeds as in previous modal models using the Galerkin method but with expansion of arbitrary basis functions. Application of similarity transform to resulting full matrix equations gives rise to a set of uncoupled partial differential equations of which the unknowns are coefficients of mode vector. Using the transform technique a computationally efficient time integration is possible. In present from the model use Chebyshev polynomials for Galerkin solution of internal mode equations. To examine model performance the model is applied to a homogeneous, rectangular basin of constant depth under steady, uniform wind field.

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Iris Recognition Based on a Shift-Invariant Wavelet Transform

  • Cho, Seongwon;Kim, Jaemin
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.4 no.3
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    • pp.322-326
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    • 2004
  • This paper describes a new iris recognition method based on a shift-invariant wavelet sub-images. For the feature representation, we first preprocess an iris image for the compensation of the variation of the iris and for the easy implementation of the wavelet transform. Then, we decompose the preprocessed iris image into multiple subband images using a shift-invariant wavelet transform. For feature representation, we select a set of subband images, which have rich information for the classification of various iris patterns and robust to noises. In order to reduce the size of the feature vector, we quantize. each pixel of subband images using the Lloyd-Max quantization method Each feature element is represented by one of quantization levels, and a set of these feature element is the feature vector. When the quantization is very coarse, the quantized level does not have much information about the image pixel value. Therefore, we define a new similarity measure based on mutual information between two features. With this similarity measure, the size of the feature vector can be reduced without much degradation of performance. Experimentally, we show that the proposed method produced superb performance in iris recognition.

Viewpoint Unconstrained Face Recognition Based on Affine Local Descriptors and Probabilistic Similarity

  • Gao, Yongbin;Lee, Hyo Jong
    • Journal of Information Processing Systems
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    • v.11 no.4
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    • pp.643-654
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    • 2015
  • Face recognition under controlled settings, such as limited viewpoint and illumination change, can achieve good performance nowadays. However, real world application for face recognition is still challenging. In this paper, we propose using the combination of Affine Scale Invariant Feature Transform (SIFT) and Probabilistic Similarity for face recognition under a large viewpoint change. Affine SIFT is an extension of SIFT algorithm to detect affine invariant local descriptors. Affine SIFT generates a series of different viewpoints using affine transformation. In this way, it allows for a viewpoint difference between the gallery face and probe face. However, the human face is not planar as it contains significant 3D depth. Affine SIFT does not work well for significant change in pose. To complement this, we combined it with probabilistic similarity, which gets the log likelihood between the probe and gallery face based on sum of squared difference (SSD) distribution in an offline learning process. Our experiment results show that our framework achieves impressive better recognition accuracy than other algorithms compared on the FERET database.

Pupil Detection using PCA and Hough Transform

  • Jang, Kyung-Shik
    • Journal of the Korea Society of Computer and Information
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    • v.22 no.2
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    • pp.21-27
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    • 2017
  • In this paper, we propose a pupil detection method using PCA(principal component analysis) and Hough transform. To reduce error to detect eyebrows as pupil, eyebrows are detected using projection function in eye region and eye region is set to not include the eyebrows. In the eye region, pupil candidates are detected using rank order filter. False candidates are removed by using symmetry. The pupil candidates are grouped into pairs based on geometric constraints. A similarity measure is obtained for two eye of each pair using PCA and hough transform, we select a pair with the smallest similarity measure as final two pupils. The experiments have been performed for 1000 images of the BioID face database. The results show that it achieves the higher detection rate than existing method.

A Three-Dimensional Galerkin-FEM Model Using Similarity Transform Technique (유사변환기법을 이용한 Galerkin-FEM모델)

  • 강관수;소재귀;정경태
    • Journal of Korean Society of Coastal and Ocean Engineers
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    • v.6 no.2
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    • pp.174-185
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    • 1994
  • This paper presents a modal solution of linear three-dimensional hydrodynamic equations using similarity transform technique. The solution over the vertical space domain is obtained using the Galerkin method with linear shape funtions (Galerkin-FEM model). Application of similarity transform to resulting tri-diagonal matrix equations gives rise 掠 a set of uncoupled partial differential equations of which the unknowns are coefficients of mode shape vectors. The proposed method.

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A Comparison of Similarity in Wavelet for Robust Digital Watermarking (강인한 디지털 워터마킹을 위한 웨이브릿에서의 유사도 비교)

  • 송상주;박두순
    • Journal of the Korea Computer Industry Society
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    • v.2 no.8
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    • pp.1123-1132
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    • 2001
  • We show that image make converts of multiplex resolution using wavelet transform algorithm. To evaluate the robustness, we have measured comparison of similarity using various sequences which is inserted important coefficient of middle frequency band. The wavelet transform is advantage that it has a special quality of frequency domain and a special quality of spatial domain. As result of experiments, it is to certify that The chaos sequence similarity is higher than other sequence. So the chaos sequence will be used for watermark sequence.

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Vegetation Classification from Time Series NOAA/AVHRR Data

  • Yasuoka, Yoshifumi;Nakagawa, Ai;Kokubu, Keiko;Pahari, Krishna;Sugita, Mikio;Tamura, Masayuki
    • Proceedings of the KSRS Conference
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    • 1999.11a
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    • pp.429-432
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    • 1999
  • Vegetation cover classification is examined based on a time series NOAA/AVHRR data. Time series data analysis methods including Fourier transform, Auto-Regressive (AR) model and temporal signature similarity matching are developed to extract phenological features of vegetation from a time series NDVI data from NOAA/AVHRR and to classify vegetation types. In the Fourier transform method, typical three spectral components expressing the phenological features of vegetation are selected for classification, and also in the AR model method AR coefficients are selected. In the temporal signature similarity matching method a new index evaluating the similarity of temporal pattern of the NDVI is introduced for classification.

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An Efficient Design Method of RF Filters via Optimized Rational-Function Fitting, without Coupling-Coefficient Similarity Transformation (무 결합계수-회전변환의, 최적화된 유리함수 Fitting에 의한 효율적인 RF대역 여파기 설계기법)

  • Ju Jeong-Ho;Kang Sung-Tek;Kim Hyeong-Seok
    • 한국정보통신설비학회:학술대회논문집
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    • 2006.08a
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    • pp.202-204
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    • 2006
  • A new method is presented to design RF filters without the Similarity Transform of their coupling coefficient matrix as circuit parameters which is very tedious due to pivoting and deciding rotation angles needed during the iterations. The transfer function of a filter is directly used for the design and its desired form is derived by the optimized rational-function fitting technique. A 3rd order Coaxial Lowpass filter and an 8th order dual-mode elliptic integral function response filter are taken as an example to validate the proposed method.

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Comparison of Similarity to Digital Watermarking using Various Sequences (디지털 워터마킹을 위한 각종 시퀀스의 유사도 비교)

  • 송상주;박두순;김선형
    • Journal of the Korea Society of Computer and Information
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    • v.6 no.4
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    • pp.21-29
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    • 2001
  • We show that image make converts of multiplex resolution using wavelet transform algorithm. To evaluate the robustness. we have measured comparison or similarity using various sequences which is inserted important coefficient of middle frequency band. The wavelet transform is advantage that it has a special quality of frequency domain and a special quality of spatial domain. Watermark is used pseudo random number, gaussian sequence, chaos sequence and sobel sequence. As result of experiments, it is to certify that The chaos sequence similarity is higher than other sequence. So the chaos sequence will be used for watermark sequence.

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