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signal processing in dual domain by adaptive projected subgradient method

Signal processing in dual domain by adaptive projected subgr...

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International conference on Digital signal processing (DSP)

作者： Masahiro Yukawa Konstantinos Slavakis Isao Yamada Amari Research Unit RIKEN Brain Science Institute Japan Department Telecommunications Science and Technology University of Peloponnese Greece Department Communications and Integrated Systems Tokyo Institute of Technology Japan

The goal of this paper is to establish a novel signal processing paradigm that enables us to find a point meeting time-variable specifications in dual domain (e.g., time and frequency domains) simultaneously. For this purpose, we define a new problem which we call adaptive split feasibility problem (ASFP). In the ASFP formulation, we have (i) a priori knowledge based convex constraints in the Euclidean spaces Ropf N and Ropf M and (ii) data-dependent convex sets in Ropf N and Ropf M ; the latter are obtained in a sequential fashion. Roughly speaking, the problem is to find a common point of all the sets defined on Ropf N such that its image under a given linear transformation is a common point of all the sets defined on Ropf M , if such a point exists. We prove that the adaptive projected subgradient method (APSM) deals with the ASFP by employing (i) a projected gradient operator with respect to (w.r.t.) a dasiafixedpsila proximity function reflecting the convex constraints and (ii) a subgradient projection w.r.t. dasiatime-varyingpsila objective functions reflecting the data-dependent sets. The resulting algorithm requires no unwanted operations such as matrix inversion, therefore it is suitable for real-time implementation. A convergence analysis is presented and verified by numerical examples.

关键词： Adaptive signal processing Vectors Frequency domain analysis signal processing algorithms Convergence of numerical methods Algorithm design and analysis Biomedical applications of radiation Neoplasms Lesions Time measurement

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Phasesplit: A Variable Splitting Framework for Phase Retrieval

Phasesplit: A Variable Splitting Framework for Phase Retriev...

引用

IEEE International conference on Acoustics, Speech and signal processing

作者： Subhadip Mukherjee Suprosanna Shit Chandra Sekhar Seelamantula Department of Electrical Engineering Indian Institute of Science Bangalore 560012 India

ISBN: (纸本)9781538646595

We develop two techniques based on alternating minimization and alternating directions method of multipliers for phase retrieval (PR) by employing a variable-splitting approach in a maximum likelihood estimation framework. This leads to an additional equality constraint, which is incorporated in the optimization framework using a quadratic penalty. Both algorithms are iterative, wherein the updates are computed in closed-form. Experimental results show that: (i) the proposed techniques converge faster than the state-of-the-art PR algorithms;(ii) the complexity is comparable to the state of the art;and (iii) the performance does not depend critically on the choice of the penalty parameter. We also show how sparsity can be incorporated within the variable splitting framework and demonstrate concrete applications to image reconstruction in frequency-domain optical-coherence tomography.

关键词： Phase retrieval Sparsity ADMM Alternating Minimization FDOCT maximum likelihood estimation retrieval state of the art penalty Multiplying circuits Public Relations image reconstruction Praseodymium Frameworks

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Artificial intelligence for pattern recognition in automated surface engineering

Artificial intelligence for pattern recognition in automated...

引用

International conference on Systems and Informatics (ICSAI)

作者： E. Sheybani S. Garcia-Otero F. Adnani G. Javidi DSP Laboratory Virginia State University Petersburg VA USA

Ability to measure the surface quality in real-time has many applications in manufacturing automation and product optimization, especially in processes in which the surface qualities such as roughness, grain size, thickness of coding, impurities size and distribution, hardness, and other mechanical properties are of importance. Surface analysis in manufacturing environments requires specialized filtering techniques. Due to the immense effect of rough environment and corruptive parameters, it is often impossible to evaluate the quality of a surface that has undergone various grades of processing. The algorithm presented here is capable of performing this comparison analytically and quantitatively at a low computational cost (real-time) and high efficiency. The parameters used for comparison are the degree of blurriness and the amount of various types of noise associated with the surface image. Based on a heuristic analysis of these parameters the algorithm assesses the surface image and quantifies the quality of the image by characterizing important aspects of human visual quality. Extensive effort has been set forth to obtain real-world noise and blur conditions so that the various test cases presented here could justify the validity of this approach well. The tests performed on the database of images produced valid results for the proposed algorithm consistently. This research aims at providing image processing tools for comparison and assessment of a surface processed under different grades of a manufacturing process all the way up to optimal processing. This paper presents the description and validation (along with test results) of the proposed algorithm for surface image quality assessment.

关键词： Surface treatment Noise Algorithm design and analysis Filter banks image quality signal processing algorithms wavelet transforms

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Improving Block Matching and 3 Dimensions (BM3D) Filtering for image Noise Removal Using Discrete wavelet Transformation (DWT)

Improving Block Matching and 3 Dimensions (BM3D) Filtering f...

引用

Sciences and Techniques of Automatic Control and Computer Engineering MI-STA, IEEE International Maghreb Meeting of the conference on

作者： Warda Kshem Asem Khmag Department of Computer Engineering Faculty of Engineering University of Zawia Az zawia Libya

ISBN: (数字)9798350372632

ISBN: (纸本)9798350372649

In the field of image denoising, Block Matching 3 Dimensions technique (BM3D) stated as a powerful technique that works to remove white Gaussian noise (A WGN). Despite BM3D shows its great success in comparison with the best denoising methods, still its visual quality decreases as the noise density escalates in noisy digital images. Therefore, the need to create a powerful image denoising method is necessary to accomplish the processing of image enhancement applications. The proposed method is introduced by. In this study, discrete wavelet transformation is applied on the LL level of the wavelet decomposition due to its ability to keep the smallest change in the original image. Furthermore, the coefficients of LL will be then divided to small blocks that contain contaminated pixels that suffer from additive white Gaussian noise (A WGN). Comparing with conventional block matching 3D (BM3D) that works well only on the similar patches, our proposed method has the ability to work on similar and dissimilar patches in order to find the inter and intra- correlations between dissimilar pixels. The proposed technique is examined on several digital benchmark images with different noise levels in terms of the quantity of the lost in the original and resulted pixels. In this regard, the performance of the tested images is estimated and then compared proposed with several high quality noise removal techniques according to several assessments such as peak signal-to-noise ratio (PSNR), structural similarity index measure (SSIM), and the figure of merits (FOM). The high amount of these factors reflects the success of the proposed technique. Further, it is interesting to observe the improvement in the running time where it was far less than the investigated noise removal algorithms.

关键词： Visualization Correlation PSNR Three-dimensional displays Noise Estimation Discrete wavelet transforms

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Improvement of Edge-Tracking Methods using Genetic Algorithm and Neural Network

Improvement of Edge-Tracking Methods using Genetic Algorithm...

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International conference of signal processing and Intelligent Systems (ICSPIS)

作者： Sajjad Ghazanfari Shabankareh Saeid Ghazanfari Shabankareh Faculty of Electrical Engineering Islamic Azad University Shiraz Iran Faculty of Science and Technology Aix-Marseille University Marseille France

ISBN: (数字)9781728153506

ISBN: (纸本)9781728153513

One of the most basic and important operations in the field of image processing is image extraction and detection. Edge recognition is very important for image clarity and image segmentation. The importance of edge detection is that the human eye can recognizes the existence of different objects by observing the edges. So it makes sense to do edge detection before interpreting images in automated systems. Edges are points in the image where the two pixels are two different values, or two values very large in numerical value. It can be said that one of the goals of edge reduction in data size in images is to preserve the original structure and shape of the images. Editing has various applications, including object recognition, segmentation and image coding, in a variety of medical images. One of the problems we encounter when editing images has noises. In this paper, a combination of several standard edge- matching algorithms, neural network and multi-objective genetic algorithm NonDominated Sorting Genetic Algorithm (NSGA-ii) is used to edge detection. In the proposed method, we give the standard multiedge finder to a forward propagating (FP) neural network as input. A multi-objective genetic algorithm with Non- Dominated Sorting Genetic Algorithm (NSGA-ii was used to select the number of edge detectors to access the neural network and to select the most accurate ones. The genetic algorithm selects the least accurate number of edge detectors to enter the neural network. To evaluate the proposed method, TP, TN, FP, FN criteria were used to compare with other methods. Finally, by comparing the results obtained on different images using existing methods and the proposed method it is observed that the proposed method has better accuracy in detecting the edge of noise images.

关键词： image edge detection Detectors signal processing algorithms Genetic algorithms Biological neural networks Sociology

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Efficient parking lot management system for parking attendants based on real-time impulsive sound detection and voice command recognition

Efficient parking lot management system for parking attendan...

引用

International conference on image and signal processing and their applications (ISPA)

作者： Faycal Ykhlef Ouahiba Cherir Amal Mekdour Djamel Bouchaffra Ratiba Boutaleb Wahiba Benzaba Division Architecture des Systèmes et Multimédia Centre de Développement des Technologies Avancées Algiers Algeria Département d’Electronique Université Blida 1 Blida Algeria

ISBN: (数字)9798350309249

ISBN: (纸本)9798350309256

The mission of parking attendants includes several tasks. One can mention, the supervision of automobile access, the management of parking facility, and the promotion of parking areas safety. Therefore, an intelligent system which allows carrying out some tasks only by speaking will definitely help attendants to complete their mission properly. The solution we propose activates the main computer to listen and promptly recognizes commands spoken in Arabic by the parking attendant in real-time. It seamlessly performs various tasks, including (i) opening and closing the main barrier, (ii) controlling the lights in the parking area automatically, and (iii) triggering and stopping theft alarms. The solution is based on two main phases: (i) querying the computer in real time through an impulsive waveform such as hands clapping, (ii) and recognizing voice commands. The first phase is accomplished using impulsive sound identification technique based on normalized version of power sequences. However, the second phase uses Google's application programming interface. The software was designed using Python language. We controlled external hardware such as parking barrier, light bulb, and alarm device using Arduino board. The execution time of the proposed software is nearly real-time and ranges from 5 to 6 seconds. The average subjective evaluation score conducted by 6 users is 4/5.

关键词： image recognition Speech recognition signal processing Turning Real-time systems Software Internet

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FPGA based real-time image segmentation for medical systems and data processing

FPGA based real-time image segmentation for medical systems ...

引用

IEEE NPSS conference on Real Time

作者： P. Dillinger J.F. Vogelbruch J. Leinen S. Suslov R. Patzak H. Winkler K. Schwan Research Center Jülich Central Institute for Electronics Julich Germany Array Electronics GmbH Egmating Germany

3D image segmentation is one of the most demanding tasks in image processing. The applications comprise industrial and scientific tasks. Due to the high data volume advanced algorithms cannot be processed on standard hardware in real time. We propose the perfectly parallelizable 3D grey-value structure code (3D-GSC) for image segmentation on a new FPGA custom machine. This 128-bit FPGA co-processing board features an up-to-date Virtex-ii Pro architecture, two large independent DDR-SDRAM channels, two fast independent ZBT-SRAM channels, and PCI-X bus and CameraLink interfaces. The hardware speeds up the segmentation algorithm and allows processing of a 512 3 image (16 bpv) in about 2 sec

关键词： Field programmable gate arrays Real time systems image segmentation Biomedical imaging Data processing Hardware image processing image edge detection Digital signal processing Medical services

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Optical disc detection in retinal images

Optical disc detection in retinal images

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International conference on Optimization of Electrical and Electronic Equipment, OPTIM

作者： M. Ivanovici V. Scurtu Computers and Electronics Department Faculty of Electrical Engineering and Science IEEE Signal Processing and Communications Societies Computer Transilvania University of Brasov Brasov Romania Computers and Electronics Department Faculty of Electrical Engineering and Computer Science Transilvania Transilvania University of Brasov Brasov Romania

Lasers are currently used for a wide spectrum of medical applications, including the treatment of eye disorders. When combined with digital image processing techniques, the issue of retinal image segmentation becomes of high importance. In this paper, our purpose is twofold: i) to identify and briefly present the existing approaches for the retinal image segmentation and ii) to test our hypothesis that the Viola-Jones algorithm-initially designed for face detection-can be suited as well for optical disc detection.

关键词： Optical imaging Biomedical optical imaging Adaptive optics Training Histograms Optical saturation Optical filters

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NON-LOCAL GRAPH-BASED PREDICTION FOR REVERSIBLE DATA HIDING IN imageS

NON-LOCAL GRAPH-BASED PREDICTION FOR REVERSIBLE DATA HIDING ...

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IEEE International conference on image processing

作者： Qi Chang Gene Cheung Yao Zhao Xiaolong Li Rongrong Ni Institute of Information Science Beijing Jiaotong University National Institute of Informatics

Reversible data hiding (RDH) is desirable in applications where both the hidden message and the cover image need to be recovered without loss. Among many RDH approaches is prediction-error expansion (PEE), containing two steps: i) prediction of a target pixel value, and ii) embedding according to the value of the prediction error. In general, higher prediction performance leads to larger embedding capacity and/or lower signal distortion. Leveraging on recent advances in graph signal processing (GSP), we pose pixel prediction as a graph-signal restoration problem, and design non-local graph-based prediction schemes where the appropriate edge weights of the underlying graph are computed using a similar patch searched in a semi-local neighborhood. Specifically, for each candidate patch, we first examine eigenvalues of its structure tensor to estimate its local smoothness. If sufficiently smooth, we pose a maximum a posteriori (MAP) problem using either a quadratic Laplacian regularizer or a graph total variation (GTV) term as signal prior. While the MAP problem using the first prior has a closed-form solution, we design an efficient algorithm for the second prior using alternating direction method of multipliers (ADMM) with nested proximal gradient descent. Finally, hidden message will be embedded into the image according to the resulting prediction errors. Experimental results show that with better quality GSP-based prediction, at low capacity the visual quality of the embedded image exceeds state-of-the-art methods noticeably.

关键词： Histograms Tensile stress image restoration Eigenvalues and eigenfunctions Laplace equations Distortion image coding

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Real-time estimation of point-of-interest in video surveillance based on visual fixation

Real-time estimation of point-of-interest in video surveilla...

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International Symposium on signal processing and Its applications (ISSPA)

作者： Lim Mei Kuan Tang Sze Ling Zulaikha Kadim Ahmed A. Al-Obaidi Norshuhada Samudin Liang Kim Meng Mimos Berhad Kuala Lumpur Malaysia

Analyzing and interpreting the behavior of humans in a sequence of images from a video stream is an active and growing topic in computer vision and its applications. This paper focuses on real-time visual fixation analysis in which the study of human's gaze allows investigation and reasoning of a point-of-interest (POI) in the scene. The system's architecture comprises of 3 major components; (i) head detection, (ii) head direction detection and (iii) POI analysis. We employ the 3D color space (RGB) model as proposed in the installation of “15 Seconds of Fame” to detect skin color pixels for head detection. The head direction specified is based on estimating the orientation in tilt angle and pan angle using neural network. Finally, the POI is determined via the correlation between multiple head directions. Experimental results are given to demonstrate the reliability of our system in estimating POI in a sequence of low-resolution images.

关键词： Iris recognition Real time systems image color analysis Analytical models Fitting Approximation methods Robots

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