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discrete-wavelet-transformation
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Embolic Doppler ultrasound signal detection using discrete wavelet transform
, Article IEEE Transactions on Information Technology in Biomedicine ; Volume 8, Issue 2 , 2004 , Pages 182-190 ; 10897771 (ISSN) ; Marvasti, F ; Markus, H. S ; Sharif University of Technology
2004
Abstract
Asymptomatic circulating emboli can be detected by Doppler ultrasound. Embolic Doppler ultrasound signals are short duration transient like signals. The wavelet transform is an ideal method for analysis and detection of such signals by optimizing time-frequency resolution. We propose a detection system based on the discrete wavelet transform (DWT) and study some parameters, which might be useful for describing embolic signals (ES). We used a fast DWT algorithm based on the Daubechies eighth-order wavelet filters with eight scales. In order to evaluate feasibility of the DWT of ES, two independent data sets, each comprising of short segments containing an ES (N = 100), artifact (N = 100) or...
A sparse representation-based wavelet domain speech steganography method
, Article IEEE/ACM Transactions on Speech and Language Processing ; Volume 23, Issue 1 , 2015 , Pages 80-91 ; 23299290 (ISSN) ; Ghaemmaghami, S ; Wang, Z. J ; Sharif University of Technology
Abstract
In this paper, we present a novel speech steganography method using discrete wavelet transform and sparse decomposition to address the undetectability concern in speech steganography. The proposed speech steganography method exploits the sparse representation to embed secret messages into higher semantic levels of the cover signal, resulting in increased undetectability. The proposed method also yields improvements on both stego signal quality and embedding capacity, which are the two major requirements of a steganography algorithm. Our experimental results illustrate that the stego signals generated by the proposed method are perceptually indistinguishable from the original cover signals,...
Image steganography based on sparse decomposition in wavelet space
, Article Proceedings 2010 IEEE International Conference on Information Theory and Information Security, ICITIS 2010, 17 December 2010 through 19 December 2010, Beijing ; 2010 , Pages 632-637 ; 9781424469406 (ISBN) ; Ghaemmaghami, S ; Sharif University of Technology
Abstract
Sparse decomposition of wavelet coefficients of cover image blocks for data hiding is addressed in this paper. By using the proposed algorithm, the embedded secret message can be reliably extracted without resorting to the original image. We use all four sub-images (LL, LH, HL and HH) of the 2D wavelet transform for data embedding without losing the image imperceptibility. An over-complete dictionary matrix is estimated by using the KSVD dictionary learning algorithm, and then the secret message bits are inserted in the sparse representation of the wavelet coefficients over the estimated dictionary. This is believed to be one of the first approaches to the image data hiding that uses the...
Detection of geochemical anomalies using a fractal-wavelet model in Ipack area, Central Iran
, Article Journal of Geochemical Exploration ; Volume 220 , 2021 ; 03756742 (ISSN) ; Afzal, P ; Yasrebi, A. B ; Gholinejad, M ; Wetherelt, A ; Sharif University of Technology
Elsevier B.V
2021
Abstract
The purpose of this study is to detect geochemical anomalies utilizing a Wavelet-Number (W-N) fractal model based on combination of a two-dimensional Discrete Wavelet Transformation (DWT) signal analysis and a Concentration-Area (C-A) fractal modeling. The DWT was carried by Sym8 as a selected wavelet pattern (by energy matching method) for Zn and Pb based on rock samples collected from the Ipack area, Central Iran. In addition, the DWT was decomposed by continuous wavelet coefficients at five levels and a final image was synthesized. Furthermore, the DWT data were classified using a fractal-wavelet model for delineation of both Zn and Pb anomalies from background levels in this area....
On the reduction of the number of required motions in the dynamic analysis using a refined spectral matching
, Article Earthquake and Structures ; Volume 21, Issue 4 , 2021 , Pages 425-444 ; 20927614 (ISSN) ; Mashayekhi, M ; Mohammadnezhad, H ; Jaberi, H ; Estekanchi, H. E ; Sharif University of Technology
Techno-Press
2021
Abstract
This study aims to show the efficiency of a proposed spectral matching technique for the reduction of required ground motions in the dynamic time history analysis. In this non-stationary spectral matching approach, unconstrained optimization is employed to adjust the signal to match a target spectrum. Adjustment factors of discrete wavelet transform (DWT) coefficients associated with the signals are then considered as decision variables and the Levenberg-Marquardt algorithm is employed to find the optimum values of DWT coefficients. This matching algorithm turns out to be quite effective in the spectral matching objective, where matching at multiple damping ratios can be readily achieved....
A two dimensional wavelet packet approach for ECG compression
, Article 6th International Symposium on Signal Processing and Its Applications, ISSPA 2001, Kuala Lumpur, 13 August 2001 through 16 August 2001 ; Volume 1 , 2001 , Pages 226-229 ; 0780367030 (ISBN); 9780780367036 (ISBN) ; Nayebi, K ; Sharif University of Technology
IEEE Computer Society
2001
Abstract
An improved compression algorithm for ECG signals is presented using temporal alignment of beats and 2-D wavelet packet transform (WPT). This 2-D transform based approach utilizes the fact that the electrocardiogram (ECG) signals generally show two types of correlation, namely correlation between subsequent samples within each ECG cycle (intrabeat) and correlation between subsequent cycles (interbeat). One simple compression algorithm in the 2-D WPT domain, which is applied to some records in the MIT-BIH arrhythmia database shows lower percent root mean square difference (PRD) than 1-D wavelet based compression methods for the same compression ratio (CR). © 2001 IEEE
Robust algorithm for brain magnetic resonance image (MRI) classification based on GARCH variances series
, Article Biomedical Signal Processing and Control ; Volume 8, Issue 6 , 2013 , Pages 909-919 ; 17468094 (ISSN) ; Shayesteh, M. G ; Zali Vargahan, B ; Sharif University of Technology
2013
Abstract
In this paper, a robust algorithm for disease type determination in brain magnetic resonance image (MRI) is presented. The proposed method classifies MRI into normal or one of the seven different diseases. At first two-level two-dimensional discrete wavelet transform (2D DWT) of input image is calculated. Our analysis show that the wavelet coefficients of detail sub-bands can be modeled by generalized autoregressive conditional heteroscedasticity (GARCH) statistical model. The parameters of GARCH model are considered as the primary feature vector. After feature vector normalization, principal component analysis (PCA) and linear discriminant analysis (LDA) are used to extract the proper...
A novel motion detection method using 3d discrete wavelet transform
, Article IEEE Transactions on Circuits and Systems for Video Technology ; Volume 29, Issue 12 , 2019 , Pages 3487-3500 ; 10518215 (ISSN) ; Manzuri Shalmani, M. T ; Lin, J ; Staring, M ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2019
Abstract
The problem of motion detection has received considerable attention due to the explosive growth of its applications in video analysis and surveillance systems. While the previous approaches can produce good results, the accurate detection of motion remains a challenging task due to the difficulties raised by illumination variations, occlusion, camouflage, sudden motions appearing in burst, dynamic texture, and environmental changes such as weather conditions, sunlight changes during a day, and so on. In this paper, a novel per-pixel motion descriptor is proposed for motion detection in video sequences which outperforms the current methods in the literature particularly in severe scenarios....
Improving the Robustness of Image Watermarking for Publicly Copyright-Proving
, M.Sc. Thesis Sharif University of Technology ; Jamzad, Mansour (Supervisor)
Abstract
The advent of Internet and advancement of computer technologies have enabled convenient and fast exchange of multimedia so the illegal reproduction and modification of digital media has become increasingly serious. Hence, how to protect the intellectual property rights of digital multimedia is an imperative issue. Digital watermarking is one of the solutions to prevent unauthorized use of images. Traditional digital watermarking techniques embed a watermark such as logo, trademark, or copyright information into a host image so that it is not perceptible. These techniques, depending on the amount of embedded data, will distort the content of host image which results in quality degradation of...
Watermarking of a Fingerprint Image
, M.Sc. Thesis Sharif University of Technology ; Fatemizadeh, Emadeddin (Supervisor)
Abstract
Extracting the minutia of a fingerprint image and then hiding this information in the original image in order to increase the security has been explained and implemented in this thesis. One of the methods which can embed the predetermined digital data in the image is digital watermarking. In this thesis, the host image is a fingerprint image whose minutia has been embedded in that image. Embedding can be done in two spatial and frequency domains. In this thesis, embedding is implemented by combining two domains. Embedding in the frequency domain is applied to transforming coefficients directly from the image then by spatial method the information is embedded. Actually combining DWT and LSB...
ECG based human identification using wavelet distance measurement
, Article Proceedings - 2011 4th International Conference on Biomedical Engineering and Informatics, BMEI 2011, 15 October 2011 through 17 October 2011 ; Volume 2 , October , 2011 , Pages 717-720 ; 9781424493524 (ISBN) ; Shamsollahi, M. B ; Sharif University of Technology
2011
Abstract
In this Paper a new approach is proposed for electrocardiogram (ECG) based human identification using wavelet distance measurement. The main advantage of this method is that it guarantees high accuracy even in abnormal cases. Furthermore, it possesses low sensitivity to noise. The algorithm was applied on 11 normal subjects and 10 abnormal subjects of MIT-BIH Database using single lead data, and a 100% human identification rate was on both normal and abnormal subjects. Adding artificial white noise to signals shows that the method is nearly accurate in SNR level above 5dB in normal subjects and 20dB in abnormal subjects
Speckle noise reduction of ultrasound images using M-band wavelet transform and wiener filter in a homomorphic framework
, Article 1st International Conference on BioMedical Engineering and Informatics, BMEI 2008, Sanya, Hainan, 27 May 2008 through 30 May 2008 ; Volume 2 , 2008 , Pages 510-515 ; 9780769531182 (ISBN) ; Shamsollahi, M. B ; Sharif University of Technology
2008
Abstract
In this paper we make use of M-band discrete wavelet transform (MDWT) and Wiener filter for speckle noise suppression of ultrasound images. Assuming multiplicative model for speckle noise, by applying logarithmic transform to noisy observation we convert multiplicative noise to additive one. Then, speckle noise can be reduced by taking the M-band wavelet transform of log-transformed observation and employing an adaptive thresholding technique. In order to improve the performance of this denosing approach, we propose a preprocessing stage which exploits Wiener filtering. Through this stage logtransformed observation is separated into two images and then each of these two images is denoised...
Wavelet based speech enhancement using a new thresholding algorithm
, Article 2004 International Symposium on Intelligent Multimedia, Video and Speech Processing, ISIMP 2004, Hong Kong, China, 20 October 2004 through 22 October 2004 ; 2004 , Pages 238-241 ; 0780386884 (ISBN) ; Manzuri, M. T ; Dianat, R ; Sharif University of Technology
2004
Abstract
The Wavelet based speech enhancement is considered. In this method, the noisy signal transfers to wavelet domain. Then with applying a thresholding algorithm, the wavelet coefficients will be improved. At last using the inverse wavelet transform the enhanced signal will be obtained. In this paper, we have presented a new method for thresholding algorithm. We compared our algorithm with some of the most popular methods by several experimental tests. Both subjective and objective tests show better performance and achievements
A new wavelet domain block matching algorithm for real-time object tracking
, Article Proceedings: 2003 International Conference on Image Processing, ICIP-2003, Barcelona, 14 September 2003 through 17 September 2003 ; Volume 3 , 2003 , Pages 961-964 ; Rabiee, H. R ; Behazin, F ; Khansari, M ; Sharif University of Technology
2003
Abstract
This paper describes a new real-time algorithm for tracking user-selected objects in a sequence of images based on a new block matching algorithm in wavelet domain. In our algorithm, the amplitude of coefficients in the best basis tree expansion of un-decimated wavelet packet transform is; used as the feature vectors (FVs). Real-time object tracking have been achieved using a new search technique for finding the best match among FVs of the reference block and FVs of the search area in the wavelet domain. Our experimental results show that the algorithm is robust to various object deformations and noisy video sequences
Discrete wavelet transform-neural network crack-like damage identification of welds on chassis cross members
, Article Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering ; Volume 226, Issue 9 , 2012 , Pages 1202-1210 ; 09544070 (ISSN) ; Sharifi K, A ; Azadi, S ; Kazemi, R ; Sharif University of Technology
Abstract
This paper incorporates a discrete wavelet transform and a radial basis function neural network to implement a vibration-based crack-like damage identification approach to the simulated welds of chassis cross members. After finite element method modelling of a vehicle, eight acceleration sensors are placed on the chassis, and their responses are measured to the upward displacement on the excitation of two tyres while the other two tyres are fixed. Then, a discrete wavelet transform with a Daubechies 3 mother wavelet is applied to the responses of the sensors. All detail coefficients and approximation coefficients of the nine levels of the discrete wavelet transform are introduced into the...
Support vector data description for spoken digit recognition
, Article BIOSIGNALS 2012 - Proceedings of the International Conference on Bio-Inspired Systems and Signal Processing ; 2012 , Pages 32-37 ; 9789898425898 (ISBN) ; Ghasemi, A ; Tavanaei, M ; Sameti, H ; Manzuri, M. T ; Inst. Syst. Technol. Inf., Control Commun. (INSTICC) ; Sharif University of Technology
2012
Abstract
A classifier based on Support Vector Data Description (SVDD) is proposed for spoken digit recognition. We use the Mel Frequency Discrete Wavelet Coefficients (MFDWC) and the Mel Frequency cepstral Coefficients (MFCC) as the feature vectors. The proposed classifier is compared to the HMM and results are promising and we show the HMM and SVDD classifiers have equal accuracy rates. The performance of the proposed features and SVDD classifier with several kernel functions are evaluated and compared in clean and noisy speech. Because of multi resolution and localization of the Wavelet Transform (WT) and using SVDD, experiments on the spoken digit recognition systems based on MFDWC features and...
Adaptive watermarking scheme based on ICA and RDWT
, Article IET Seminar Digest, 3 December 2009 through 3 December 2009 ; Volume 2009, Issue 2 , 2009 ; 9781849192071 (ISBN) ; Dadgostar, M ; Rezai Rad, G ; Fatemizadeh, E ; Sharif University of Technology
Abstract
This paper proposes a new approach to watermarking multimedia products based on the combination of redundant discrete wavelet transform and independent component analysis. The original image is decomposed by RDWT, and watermark is embedded in to LL sub-band frequency according mixing model of the ICA, after that for enhancing the robustness of the watermark, the perceptual model is applied via stochastic approach for watermark adapting. This is based on computation of a noise visibility function (NVF) which has local image properties so the strength of watermarking is controllable. Principal component analysis (PCA) whitening process and FastICA techniques are introduced to ensure a blind...
Robust multiplicative patchwork method for audio watermarking
, Article DSP 2009:16th International Conference on Digital Signal Processing, Santorini, 5 July 2009 through 7 July 2009 ; 2009 ; 9781424432981 (ISBN) ; Akhaee, M. A ; Ahadi, M ; Amindavar, H. R ; Sharif University of Technology
2009
Abstract
A Multiplicative Patchwork Method (MPM) for audio watermarking is proposed in this paper. In order to embed watermark data within the host signal, two subsets of the host signal features are selected using two secret keys. Then, watermark data is inserted simply by multiplying one subset and leaving the other one unchanged. In order to have an error free detection in attack-free case, embedding is performed in the selected frames of the host signal which satisfies a certain condition. This method is implemented in the wavelet domain and approximation coefficients are used for data embedding. Furthermore, the inaudibility of watermark insertion is controlled using iterative approach aided by...
Robust multiplicative patchwork method for audio watermarking
, Article IEEE Transactions on Audio, Speech and Language Processing ; Volume 17, Issue 6 , 2009 , Pages 1133-1141 ; 15587916 (ISSN) ; Akhaee, M. A ; Ahadi, M ; Amindavar, H ; Sharif University of Technology
2009
Abstract
This paper presents a Multiplicative Patchwork Method (MPM) for audio watermarking. The watermark signal is embedded by selecting two subsets of the host signal features and modifying one subset multiplicatively regarding the watermark data, whereas another subset is left unchanged. The method is implemented in wavelet domain and approximation coefficients are used to embed data. In order to have an error-free detection, the watermark data is inserted only in the frames where the ratio of the energy of subsets is between two predefined values. Also in order to control the inaudibility of watermark insertion, we use an iterative algorithm to reach a desired quality for the watermarked audio...
An evolutionary optimization-based approach for simulation of endurance time load functions
, Article Engineering Optimization ; Volume 51, Issue 12 , 2019 , Pages 2069-2088 ; 0305215X (ISSN) ; Esmail pour Estekanchi, H ; Vafai, H ; Ahmadi, G ; Sharif University of Technology
Taylor and Francis Ltd
2019
Abstract
A novel optimization method based on Imperialist Competitive Algorithm (ICA) for simulating endurance time (ET) excitations was proposed. The ET excitations are monotonically intensifying acceleration time histories that are used as dynamic loading. Simulation of ET excitations by using evolutionary algorithms has been challenging due to the presence of a large number of decision variables that are highly correlated due to the dynamic nature of the problem. Optimal parameter values of the ICA algorithm for simulating ETEFs were evaluated and were used to simulate ET excitations. In order to increase the capability of the ICA and provide further search in the optimization space, this...