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IEEE International Conference on Signal processing, Communications and Computing (ICSPCC)

作者： Amit M Joshi Anand Darji Vivekanand Mishra Electronics Department SVNIT Surat India

The digital watermarking is a multimedia technology for information hiding which provides the authentication and copyright protection. The digital images are easily exchanged through internet and threaten to some malicious attacks. Wavelet based frequency domain watermarking provides the robustness against different attacks. Bit plane slicing scheme of spatial domain watermarking provides lesser computational complexity suitable for real time implementation. We combine advantages of the both the domains for the proposed algorithm. We have developed algorithm for robust and invisible application where we used non blind detection scheme. This approach is also implemented on FPGA. Several software implementations of the watermarking algorithms are available, but very few attempts have been made for hardware implementations. Software based watermarking schemes are more prone to offline attacks due to the delay between image captured and embedding the watermark. Hardware based watermarking provides real time embedding process where watermark is embedded at the same time when image is captured. This is very much useful in applications like real-time broad casting, video authentication and secure camera system for courtroom evidence. The goal of hardware implementation is to achieve low-power, high-performance, real-time, reliable and secure watermarking systems using FPGA.

关键词： Watermarking Discrete wavelet transforms Hardware Real time systems Field programmable gate arrays

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GPU Implementation of Orthogonal Matching Pursuit for Compressive Sensing

GPU Implementation of Orthogonal Matching Pursuit for Compre...

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International Conference on Parallel and Distributed systems (ICPADS)

作者： Yong Fang Liang Chen Jiaji Wu Bormin Huang College of Information Engineering Northwest A&F University Angling Shaanxi China College of Information Engineering Northwest A&F University Yangling Shaanxi China Key Laboratory Intelligent Perception & Image Understanding of Ministry of Education Xidian University Xi'an Shaanxi China Space Science & Engineering Center University of Wisconsin-Madison Madison USA

Recovery algorithms play a key role in compressive sampling (CS). Currently, a popular recovery algorithm for CS is the orthogonal matching pursuit (OMP), which possesses the merits of low complexity and good recovery quality. Considering that the OMP involves massive matrix/vector operations, it is very suited to being implemented in parallel on graphics processing unit (GPU). In this paper, we first analyze the complexity of each module in the OMP and point out the bottlenecks of the OMP lie in the projection module and the least-squares module. To speedup the projection module, Fujimoto's matrix-vector multiplication algorithm is adopted. To speedup the least-squares module, the matrix-inverse-update algorithm is adopted. Experimental results show that +40x speedup is achieved by our implementation of OMP on GTX480 GPU over on Intel(R) Core(TM) i7 CPU. Since the projection module occupies more than 2/3 of the total run time, we are looking for a faster matrix-vector multiplication algorithm.

关键词： Graphics processing unit Matching pursuit algorithms Complexity theory Instruction sets Vectors Kernel Registers

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Online Kernel SVM for real-time fMRI brain state prediction

Online Kernel SVM for real-time fMRI brain state prediction

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International Conference on Acoustics, Speech, and Signal processing (ICASSP)

作者： Yongxin Taylor xi Hao Xu Ray Lee Peter J. Ramadge Department of Electrical Engineering Princeton University USA Department of Psychology Princeton University USA

The Support Vector Machine (SVM) methodology is an effective, supervised, machine learning method that gives state-of-the-art performance for brain state classification from functional magnetic resonance brain images (fMRI). Due to the poor scalability of SVM (cubic in the number of training points) and the massive size of fMRI images, a SVM analysis is usually performed after data collection. Recent advances in real-time fMRI applications, such as Brain Computer Interfaces, require a fast and reliable classification method running in synchronization with the image collection. We design an online Kernel SVM (OKSVM) algorithm based on the Sequential Minimization Optimization (SMO) method, that is fast (training on each new image within 1 sec), has memory and time cost that scales linearly with the number of points used, and yields comparable prediction performance to an offline SVM. We analyze the method's performance by testing it on real fMRI data sets, and show that OKSVM performs well at greatly reduced computational cost. Our work provides a feasible online Kernel SVM for real-time fMRI experiments, and can be used to guide for the design of similar online classifiers in fMRI cognitive state classification.

关键词： Support vector machines Kernel Training Accuracy Real time systems Prediction algorithms Algorithm design and analysis

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RSA-based digital image encryption algorithm in wireless sensor networks

RSA-based digital image encryption algorithm in wireless sen...

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2010 2nd International Conference on Signal processing systems, ICSPS 2010

作者： Zhao, Gaochang Yang, xiaolin Zhou, Bin Wei, Wei Xi'an University of Science and Technology Xi'an 710054 China Chengdu University of Technology Chengdu 610059 China Xi'an Jiaotong University Xi'an 710049 China

ISBN: (纸本)9781424468911

Digital image Encryption is the image processing in the field of a new branch. This paper discusses the modern cryptography, and RSA algorithms. Root According to the data features of digital image itself, designed and implemented digital image based on RSA encryption algorithm, and made further studies of the head. The wireless sensor networks, which self-organized, are data-centered. The current urgent problem with which the wireless faced is how to protect the security of the sensor data effectively. To deal with the weakness of limitation in sensor node resources and the security threats, a novel secure transmission strategy based on information hiding for sensor data security is proposed. In ordering to protect the security of the data, we obtain the sensitive information safely to make use of the advantage of information hiding technique without encryption to safeguard the data security. The simulation experiments illustrate that it is workable to utilize the existing WSN to transmit the sensitive information covertly with the characteristics of lower energy costs and invisibility, and it is suitable for stream data in sensor nodes. © 2010 IEEE.

关键词： Sensor nodes

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A novel fast motion estimation algorithm for video coding

A novel fast motion estimation algorithm for video coding

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2010 3rd International Congress on image and Signal processing, CISP 2010

作者： Liu, Long Song, Qijun Wang, Zhanhui Hong, Song School of Xi'an University of Technology Xi'an China China Electronic Systems Engineering Corporation Beijing China School of Naval University of Engineering Wuhan China School of Xi'an Shiyou University Xi'an China

ISBN: (纸本)9781424465149

This paper presents an efficient search algorithm utilizes the relationship between local motion similarity and the variation degree of motion vector. The main feature of proposed algorithm are: the motion vectors are classified as the unchanged, the slightly changed and the greatly changed motion vector according to corresponding local motion similarity;then different search schemes are adopted for different kind motion vectors. The experimental results show the proposed algorithm has a significant computational speedup compared with other popular fast algorithms, but offers a similar, even better performance. ©2010 IEEE.

关键词： Motion estimation

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A fruit size detecting and grading system based on image processing

A fruit size detecting and grading system based on image pro...

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International Conference on Intelligent Human-Machine systems and Cybernetics

作者： Dang, Hongshe Song, Jinguo Guo, Qin School of Electric and Information Engineering Shaanxi University of Science and Technology Xi'an City Shaanxi 710021 China

ISBN: (纸本)9780769541518

This paper presents a fruit size detecting and grading system based on image processing. After capturing the fruit side view image, some fruit characters is extracted by using detecting algorithms. According to these characters, grading is realized. Experiments show that this embedded grading system has the advantage of high accuracy of grading, high speed and low cost. It will have a good prospect of application in fruit quality detecting and grading areas. © 2010 IEEE.

关键词： Grading

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Memetic computation based on regulation between neural and immune systems: the framework and a case study

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Science China(Information Sciences) 2010年第8期53卷 1519-1527页

作者： GONG MaoGuo , JIAO LiCheng, LIU Fang & YANG Jie Key Lab of Intelligent Perception and image Understanding of Ministry of Education of China, Institute of Intelligent Information processing, xidian University, xi’an 710071, China 1. Key Lab of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi’an 710071 China

Lamarckian learning has been introduced into evolutionary computation to enhance the ability of local search. The relevant research topic, memetic computation, has received significant amount of interest. In this study, a novel memetic computational framework is proposed by simulating the integrated regulation between neural and immune systems. The Lamarckian learning strategy of simulating the unidirectional regulation of neural system on immune system is designed. Consequently, an immune memetic algorithm based on the Lamarckian learning is proposed for numerical optimization. The proposed algorithm combines the advantages of immune algorithms and mathematical programming, and performs well in both global and local search. The simulation results based on ten low-dimensional and ten high-dimensional benchmark problems show that the immune memetic algorithm outperforms the basic genetic algorithm-based memetic algorithm in solving most of the test problems.

关键词： memetic computation artificial immune system Lamarckian learning genetic algorithm numerical optimization

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Dynamic modeling of electrical characteristics of solid oxide fuel cells using fractional derivatives

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INTERNATIONAL JOURNAL OF HYDROGEN ENERGY 2010年第4期35卷 1749-1758页

作者： Cao, Hongliang Deng, Zhonghua Li, xi Yang, Jie Qin, Yi Huazhong Univ Sci & Technol Dept Control Sci & Engn Key Lab Educ Minist Image Proc & Intelligent Control Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Sch Mat Sci & Engn State Key Lab Mat Proc & Die & Mould Technol Wuhan 430074 Peoples R China China Univ Geosci Sch Mech & Elect Informat Wuhan 430074 Peoples R China

An efficient controller is greatly important for the quick load-following response of solid oxide fuel cell (SOFC) power systems, which is vital for the fuel utilization and the life of the stack. To design such a controller, an accurate dynamic model of SOFC electrical characteristics is critical. Here an integer order dynamic model is established by a transient equivalent circuit, and then a fractional order dynamic model is done in the perspective of the fractional derivatives theory. The parameters of the dynamic models then are optimized via genetic algorithms according to electrochemical impedance spectroscopy (EIS) experimental data. Finally, the dynamic response experiments from the models are studied. The results show that the fractional order dynamic model has higher accuracy for representing the dynamics of the SOFC electrical characteristics, which lays a solid foundation for the controller based on the accurate model. (c) 2009 Professor T. Nejat Veziroglu. Published by Elsevier Ltd. All rights reserved.

关键词： Solid oxide fuel cell Transient equivalent circuit Electrochemical impedance spectroscopy Integer order dynamic model Fractional order dynamic model

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RSA-based digital image encryption algorithm in wireless sensor networks

RSA-based digital image encryption algorithm in wireless sen...

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International Conference on Signal processing systems, ICSPS

作者： Gaochang Zhao xiaolin Yang Bin Zhou Wei Wei Xi'an University of Science and Technology Xi'an China Chengdu University of Technology Chengdu China Xi'an Jiaotong University Xi'an China

关键词： Encryption Signal processing algorithms Wireless sensor networks Algorithm design and analysis Digital images

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A novel fast motion estimation algorithm for video coding

A novel fast motion estimation algorithm for video coding

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Congress on image and Signal processing, CISP

作者： Long Liu Zhanhui Wang Qijun Song Song Hong Xi''an University of Technology Xi'an China China Electronic Systems Engineering Corporation Beijing China Naval University of Engineering Wuhan China Xi''an Shiyou University Xi'an China

This paper presents an efficient search algorithm utilizes the relationship between local motion similarity and the variation degree of motion vector. The main feature of proposed algorithm are: the motion vectors are classified as the unchanged, the slightly changed and the greatly changed motion vector according to corresponding local motion similarity; then different search schemes are adopted for different kind motion vectors. The experimental results show the proposed algorithm has a significant computational speedup compared with other popular fast algorithms, but offers a similar, even better performance.

关键词： Classification algorithms Support vector machine classification Signal processing algorithms Motion estimation Algorithm design and analysis Least squares approximation Diamond-like carbon

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