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Automatic Detection of Defects in Tire Radiographic images

IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING 2017年第3期14卷 1378-1386页

作者： Zhang, Yan Lefebvre, Dimitri Li, Qingling Qingdao Univ Sci & Technol Coll Electromech Engn Qingdao 266061 Peoples R China Normandie Univ F-76600 Le Havre France

This paper is about the detection of tire defects in multi-textural radiographic images. We consider the tire defects characterization problem in ways of local regularity analysis and scale characteristic. Optimal scale and threshold parameters are selected using a defect edge measurement model to frame defect edge detection. This framework distinguishes the defects from the background textures. Finally, a novel method for detection of tire defects is proposed based on wavelet multiscale analysis. We provide examples with a consistent dataset of 400 images selected over 3700 industrial images in order to illustrate and validate the obtained results which demonstrate substantial improvement over the state of the art. Note to Practitioners-Defects detection is a major challenge in numerous industrial applications. This contribution is of particular interest for tire manufacturers for which pneumatic tire defect detection mainly rely on human vision. Using computer-based technologies and signal processing methods based on wavelet transform, this paper proposes an efficient approach to implement the detection operations in a systematic way. Moreover, the proposed method is also extendable to other defect detection problems with image processing.

关键词： Defect detection pneumatic tire radiographic image wavelet multiscale analysis

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GPU-based anisotropic diffusion algorithm for video image denoising

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MICROPROCESSORS AND MICROSYSTEMS 2017年 53卷 190-201页

作者： Fredj, Amira Hadj Malek, Jihene Monastir Univ Elect & Microelect Lab Fac Sci Monastir Tunisia

image filtering is the process of removing noise which perturbs image analysis methods. In some applications like segmentation, denoising is intended to smooth homogeneous areas while preserving the contours. Real-time denoising is required in a lot of applications like image-guided surgical interventions, video analysis and visual serving. This paper presents an anisotropic diffusion method named the Oriented Speckle Reducing Anisotropic Diffusion (OSRAD) filter. The OSRAD works very well for denoising images with speckle noise. However, this filter has a powerful computational complexity and is not suitable for real time implementation. The purpose of this study is to decrease the processing time implementation of the OSRAD filter using a parallel processor through the optimization of the graphics processor unit. The results show that the suggested method is very effective for real-time video processing. This implementation yields a denoising video rate of 25 frames per second for 128 x 128 pixels. The proposed model magnifies the acceleration of the image filtering to 30 x compared to the standard implementation of central processing units (CPU). A quantitative comparison measure is given by parameters like the mean structural similarity index, the peak signal-to-noise ratio and the figure of merit. The modified filter is faster than the conventional OSRAD and keeps a high image quality compared to the bilateral filter and the wavelet transformation. (C) 2017 Elsevier B.V. All rights reserved.

关键词： OSRAD filter Graphic processor unit (GPU) CUDA Ultasound image Real time implementation

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A Review on Recent Improved image Fusion Techniques 2

A Review on Recent Improved Image Fusion Techniques

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2nd IEEE International Conference on Wireless Communications, signal processing and Networking (WiSPNET)

作者： Rajini, K. C. Roopa, S. Siddaganga Inst Technol Dept Elect & Commun Tumakuru 572103 Karnataka India

ISBN: (纸本)9781509044429

An image fusion is a process used to increase the visual interpretation of images in various applications. It integrates the necessary features of two or more images into a single image without introducing artifacts. The traditional image fusion methods are generally successful at inserting spatial detail into the multispectral imagery despite the color information in the mechanism is distorted. The significant amount of research has been conducted over the past decade related to the application of wavelet transforms in image fusion. wavelets have gained a lot of importance due to its energy compaction and multiresolution properties. This paper presents the overview of image fusion technique and the results from a number of wavelet-based image fusion schemes are compared.

关键词： image fusion multispectral multiresolution wavelet transform

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A P300 potential evaluation wavelet method comparing individuals with high and low risk for alcoholism

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NEURAL COMPUTING & applications 2017年第12期28卷 3737-3748页

作者： Lopes, Carla Diniz Becker, Tiago Kozakevicius, Alice de Jesus Rasia-Filho, Alberto A. Macq, Benoit Susin, Altamiro Amadeu Univ Fed Pelotas Engn Ctr CENg Pelotas Brazil Univ Fed Rio Grande do Sul Mech Engn Dept Porto Alegre RS Brazil Univ Fed Santa Maria Math Dept Santa Maria RS Brazil Univ Fed Rio Grande do Sul Elect Engn Dept Porto Alegre RS Brazil Univ Fed Ciencias Saude Porto Alegre Basic Sci Dept Porto Alegre RS Brazil Univ Catholic Louvain Lab Telecomun & Teledict Louvain La Neuve Belgium

Electrophysiological recordings of event-related potential P300 reveal transient information contained in electroencephalogram, helping to diagnose individuals that are predisposed to alcoholism. Generally, this component has an amplitude significantly smaller in patients at high risk of developing the disease than in low risk ones, being a major endophenotype of the disease. In this work, we propose an alternative system to automatically classify P300 signals of individuals with high risk and low risk, composed by two modules: a discrete wavelet transform that extracts features and an artificial neural network module which identifies the patterns. After training, 97.36 % of correct classification was obtained in the database from Collaborative Study on the Genetics of Alcoholism.

关键词： Electroencephalogram Visual event-related potential Alcoholism Discrete wavelet transform Artificial neural networks

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SPARSE BASED image COMPRESSION IN wavelet DOMAIN

SPARSE BASED IMAGE COMPRESSION IN WAVELET DOMAIN

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IEEE International Conference on signal processing and Communication (ICSPC)

作者： Ashwini, K. Amutha, R. Harini, K. SSN Coll Engn Dept ECE Chennai Tamil Nadu India

ISBN: (纸本)9781509067305

Sparse representation techniques have been found to provide improved results in many signaling and imaging applications. Especially in the field of image compression, this technique is able to compress the images with higher compression ratio and is also able to retrieve back the compressed image with good quality and resolution. In this paper, wavelet and Sparse based image compression technique is presented. Using Discrete wavelet Transform (DWT), the image to be compressed is initially decomposed into approximation and detail coefficients. The approximation coefficients are encoded directly with lossless encoding technique. In the case of detailed coefficients, their sparse representations are obtained using learned dictionary and these sparse vectors are quantized and encoded. Inverse discrete wavelet transform (IDWT) is applied with the estimated detail and approximation coefficients at the decompression stage, to retrieve back the decompressed image. They key issue of learning appropriate dictionaries for obtaining the sparse vectors is addressed in this paper. The proposed algorithm is tested on several standard test images and has been validated with popular metrics namely Peak signal to noise ratio (PSNR), Structural similarity index (SSIM) and Correlation coefficient.

关键词： Sparse representation DWT IDWT Dictionary

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An image Watermarking Algorithm Based on Energy Scheme in the wavelet Transform Domain

An Image Watermarking Algorithm Based on Energy Scheme in th...

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International Conference on image, Vision and Computing (ICIVC)

作者： Jinhua Liu School of Mathematics and Computer Science Shangrao Normal University Shangrao China

ISBN: (纸本)9781538649923

With the increasing demands of copyright protection, digital watermarking has been paid more and more attention. In the design of a watermarking method, the modeling of signal by a general parametric family of statistical distributions plays an important role in many image watermarking applications. In this paper, the probability density function of wavelet coefficients is modeled by the generalized Gaussian distribution (GGD), and the decision threshold is obtained by the Neyman-Pearson (NP) criterion. In the procedure of watermark embedding, the energy of image block is considered in the watermark embedding. Only those blocks whose energy exceeds a predetermined threshold are used to embed the watermark data. Its improved robustness is due to embedding in the significant wavelet coefficients based on the energy scheme and control of its strength factor from the variance of coefficient. Experimental results demonstrate that the effectiveness of the presented watermarking and its robustness against common image processing and some kinds of geometric attacks.

关键词： Watermarking Robustness wavelet coefficients Discrete wavelet transforms Gaussian distribution

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Hybrid Technique for Robust image Watermarking Using Discrete Time Fourier Transform 25

Hybrid Technique for Robust Image Watermarking Using Discret...

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25th signal processing and Communications applications Conference (SIU)

作者： Abodena, Omar Agoyi, Mary Celebi, Erbug Cyprus Int Univ Inst Grad Studies & Res Dept Management Informat Syst Via Mersin 10 Lefkosa Kktc Turkey Cyprus Int Univ Fac Engn Dept Comp Engn Via Mersin 10 Lefkosa Kktc Turkey

ISBN: (纸本)9781509064946

The current paper proposes a novel scheme for nonblind watermarking of images, making use of discrete wavelet transform (DWT), discrete time Fourier transform (DTFT), as well as singular value decomposition, or SVD. During the process of embedding, 1-level DWT is used to decompose the host image into its various frequency sub-bands. After this, the high-frequency sub band receives an application of DTFT. This is followed then by SVD, after which the watermark becomes embedded into the nowtransformed host image's singular matrix. Then, the inverses of 1-level DWT, DTFT and SVD are applied in order to obtain a watermarked final image. This paper evaluates the performance of the proposed method of watermarking against a number of attacks, including sharpening, salt and pepper noise, AWGN, gamma correction, histogram equalisation, flipping and cropping. Results obtained during experiments have found that the scheme as proposed does provide high levels of robustness and imperceptibility against various signal processing attacks.

关键词： singular value decomposition discrete wavelet transform discrete time Fourier transform

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An Efficient SPIHT Algorithm and System Architecture for image Compression 25

An Efficient SPIHT Algorithm and System Architecture for Ima...

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25th signal processing and Communications applications Conference (SIU)

作者： Cekli, Serap Akman, Ali Maltepe Univ Bilgisayar Muhendisligi Istanbul Turkey

ISBN: (纸本)9781509064946

In this study, an efficient modified SPIHT algorithm and related architecture design is proposed for image compression. The proposed architecture is designed as a three stage pipeline structure. Different sized images are compressed using the designed architecture for different bpp values. The computed PSNR values of the compressed images using the proposed algorithm and also the original algorithm is compared in order to test the performance of the proposed algorithm and architecture.

关键词： wavelet transform image compression SPIHT coding algorithm embedded coding pipeline

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Optimal duration-bandwidth localized antisymmetric biorthogonal wavelet filters

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signal processing 2017年 134卷 87-99页

作者： Sharma, Manish Dhere, Abhinav Pachori, Ram Bilas Gadre, Vikram M. Indian Inst Technol Dept Elect Engn Bombay Maharashtra India Indian Inst Technol Discipline Elect Engn Indore Madhya Pradesh India Acropolis Inst Technol & Res Dept Elect & Commun Engn Indore India

We present a design of a new class of compactly supported antisymmetric biorthogonal wavelet filter banks which have the analysis as well as the synthesis filters of even-length. Here, the analysis and the synthesis filters are designed to have minimum joint duration-bandwidth localization (JDBL). The design of filters has been formulated as a direct time-domain linearly constrained eigenvalue problem that does not involve any parametrization and iterations. The optimal analysis and synthesis filters have been obtained as the eigenvectors of the positive definite matrices. The closed form analytic expression for the objective function has been presented. The perfect reconstruction and regularity conditions have been incorporated in the design by employing time-domain matrix characterization. The method can control duration and bandwidth localizations of the analysis and synthesis filters, independently. A few design examples have been presented and compared with previous works. The performance of the optimal filter banks designed by employing the proposed method has been evaluated in image coding and signal denoising applications.

关键词： Biorthogonal filter banks Antisymmetric wavelets Duration-bandwidth localization image coding

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EVALUATION OF signal processing TECHNIQUES IN DISCRIMINATING ECG signalS OF MEN AND WOMEN DURING REST CONDITION AND EMOTIONAL STATES

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BIOMEDICAL ENGINEERING-applications BASIS COMMUNICATIONS 2018年第4期30卷

作者： Goshvarpour, Ateke Goshvarpour, Atefeh Abbasi, Ataollah Sahand Univ Technol Fac Elect Engn Dept Biomed Engn Tabriz Iran

Great range of electrocardiogram (ECG) signal processing methods can be found in the literature. In addition, the importance of gender differences in physiological activities was also identified in various conditions. This article aims to provide a comprehensive evaluation of linear and nonlinear ECG parameters to indicate suitable signal processing approaches which can show significant differences between men and women. These differences were investigated in two conditions: (i) during rest condition, and (ii) during the affective image inducements. A wide range of parameters from time-, frequency-, wavelet-, and nonlinear-techniques were examined. Applying the Wilcoxon rank sum test, significant differences between two genders were inspected. The analysis was performed on 47 college students at rest condition and while subjects watching four types of affective pictures, including sadness, happiness, fear, and peacefulness. The impact of these emotions on the results was also investigated. The results indicated that 72.95% and 72.61% of all features were significantly different between male and female in rest condition and affective inducements, respectively. In addition, the highest percentage of the significant difference between ECG parameters of men and women was achieved using nonlinear characteristics. Considering all features together, the highest significant difference between two genders was achieved for negative emotions, including sadness and fear. In conclusion, the results of this study emphasized the importance of gender role in cardiac responses during rest condition and different emotional states. Since these gender differences are well manifested by nonlinear signal processing techniques, dynamical gender-specific ECG system may improve the automatic emotion recognition accuracies.

关键词： Electrocardiogram Emotion Linear indices Nonlinear features signal processing wavelet analysis

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