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Selection of Security Elliptic Curve Based on Evolution Algorithm

Selection of Security Elliptic Curve Based on Evolution Algo...

引用

international conference on Computational Intelligence and Natural computing, CINC

作者： Maocai Wang Guangming Dai Hanping Hu Lei Pen Institute of Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan China School of Computer China University of Geoscience Wuhan China

Applying evolution algorithm to selection of security elliptic curve (EC) is first researched in the paper. In order to ensure the security of elliptic curve cryptosystem (ECC), it is necessary that the elliptic curves are safe against all kinds of attack algorithms about the elliptic curve discrete logarithm problem (ECDLP). Therefore, selection of secure elliptic curves is a mathematics difficult problem. In this paper, selection principles of secure EC are firstly analyzed. Then, based on the selection principle, a selection algorithm of security EC based on evolution algorithm is put forward. The thoughts of encoding, crossover and mutation of evolution algorithm for selection of EC are discussed in detail. The implementation result shows the availability and efficiency of the algorithm.

关键词： Security Elliptic curves Elliptic curve cryptography Public key cryptography Galois fields Equations Mathematics Public key Computational intelligence pattern recognition

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Local Trinary patterns for human action recognition

Local Trinary Patterns for human action recognition

引用

international conference on Computer Vision (ICCV)

作者： Lahav Yeffet Lior Wolf Blavatnik School of Computer Science Tel-Aviv University Israel

We present a novel action recognition method which is based on combining the effective description properties of Local Binary patterns with the appearance invariance and adaptability of patch matching based methods. The resulting method is extremely efficient, and thus is suitable for real-time uses of simultaneous recovery of human action of several lengths and starting points. Tested on all publicity available datasets in the literature known to us, our system repeatedly achieves state of the art performance. Lastly, we present a new benchmark that focuses on uncut motion recognition in broadcast sports video.

关键词： Humans pattern recognition Histograms Optical computing Atom optics Concatenated codes Computer science pattern matching System testing Benchmark testing

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An Implementation of Viterbi Algorithm on GPU

An Implementation of Viterbi Algorithm on GPU

引用

international conference on Information Science and Engineering (ICISE)

作者： Dan Zhang Rongcai Zhao Lin Han Tao Wang Jin Qu Technology Research Center China National Digital Switching System Engineering and Technological Research Center Zhengzhou China

ISBN: (纸本)9781424449095

General purpose computation based on GPU is a hot topic for research in recent years. The paper presents the parallel implementation of Viterbi algorithm on GPU based on features of GPU and characteristics of Viterbi algorithm in keyword spotting system. The results of examination by using NVIDIA 9600 GT GPU show that the GPU, in comparison to traditional processing platform, could enhance the processing performance if the recognition accuracy of keyword spotting system is ensured.

关键词： Viterbi algorithm Speech recognition Hidden Markov models Concurrent computing Speech processing Data flow computing Decoding pattern recognition Signal processing algorithms Parallel processing

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Block based curvelet feature extraction for face recognition

Block based curvelet feature extraction for face recognition

引用

IEEE international conference on Multimedia computing and Systems (ICMCS)

作者： Mohamed El Aroussi Mohammed El Hassouni Sanaa Ghouzali Mohammed Rziza Driss Aboutajdine GSCM-LRIT Faculty of Sciences Mohammed V University Rabat Morocco

In this paper, an efficient local appearance feature extraction method based the multi-resolution Curvelet transform is proposed for face recognition. Each face is described by a subset of band filtered images containing block-based Curvelet coefficients. These coefficients characterize the face texture and a set of simple statistical measures allows us to form compact and meaningful feature vectors. The proposed method is compared with some related feature extraction methods such as Principal component analysis (PCA), as well as Linear Discriminant Analysis LDA and Boosted LDA (BLDA). Two different muti-resolution transforms, Wavelet (DWT) and Contourlet, were also compared against the Block Based Curvelet algorithm. Experimental results on ORL, Yale and FERET face databases convince us that the proposed method provides a better representation of the class information and obtains much higher recognition accuracies.

关键词： Feature extraction Face recognition Spatial databases Image databases Principal component analysis Linear discriminant analysis Multiresolution analysis Discrete wavelet transforms pattern recognition Character recognition

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An Application of a Parallel Algorithm on a Image recognition

An Application of a Parallel Algorithm on a Image Recognitio...

引用

international conference on New Trends in Information and Service Science, NISS

作者： Ran Baik Department of Computer Engineering Honam University Gwangju South Korea

This paper is to introduce an application of face recognition algorithm in parallel. We have experiments of 25 images with different motions and simulated the image recognitions; grouping of the image vectors, image normalization, calculating average image vectors, etc. We also discuss an analysis of the related eigen image vectors and a parallel algorithm.

关键词： Parallel algorithms Image recognition pattern recognition Principal component analysis Application software Algorithm design and analysis Character recognition Eigenvalues and eigenfunctions Radio access networks Concurrent computing

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An Algorithm for Fingerprint Identification Based on Wavelet Transform and Gabor Feature

An Algorithm for Fingerprint Identification Based on Wavelet...

引用

international conference on Genetic and Evolutionary computing (WGEC)

作者： Cheng Xu Xin-Ming Cheng Dept. of Inf. & Command Autom. AFRA Wuhan China

This paper presents an algorithm for fingerprint identification based on wavelet transform and Gabor features. Firstly, a center point area of the fingerprint is detected, then the image in this area is decomposed into different sub-images using wavelet transform, finally we extract Gabor features from these sub-images to generate feature vectors for matching. The experiment conducted over the four FVC2004 databases shows that the proposed approach can capture much texture information at different scales and orientations, achieve high recognition rates.

关键词： Fingerprint recognition Wavelet transforms Image matching Feature extraction Data mining Image processing pattern matching Genetics conference management Image databases

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Application of Wavelet Packet in Defect recognition of Optical Fiber Fusion Based on ISO14000

Application of Wavelet Packet in Defect Recognition of Optic...

引用

international conference on Networks Security, Wireless Communications and Trusted computing, NSWCTC

作者： Zhen Zhang Jun-jie Xi Zhengzhou Inst. of Aeronaut. Ind. Manage. Zhengzhou

The important meaning of the optical fiber fusion defect recognition was introduced based on ISO14000. Detecting the optical fiber fusion point by using the UltraPAC system, aiming at the defect feature, the method of analyzing and extracting the defect eigenvalue by using wavelet packet analysis and pattern recognition by making use of the wavelet neural network is discussed. This method can realize to extract the interrelated information which can reflect defect feature from the ultrasonic information being detected and analysis it by the information. Constructing the network model for realizing the qualitative recognition of defects. The results of experiment show that the wavelet packet analysis adequately make use of the information in time-domain and in frequency-domain of the defected echo signal, multi-level partition the frequency bands and analyze the high-frequency part further which donpsilat been subdivided by multi-resolution analysis, and choose the interrelated frequency bands to make it suited with signal spectrum. Thus, the time-frequency resolution is risen, the good local amplificatory property of the wavelet neural network and the study characteristic of multi-resolution analysis can achieve the higher accuracy rate of the qualitative classification of fusion defects.

关键词： Wavelet packets Optical fibers Wavelet analysis Information analysis Signal analysis pattern analysis Data mining Neural networks Frequency Optical detectors

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Shift Invariant Iris Feature Extraction Using Rotated Complex Wavelet and Complex Wavelet for Iris recognition System

Shift Invariant Iris Feature Extraction Using Rotated Comple...

引用

international conference on Advances in pattern recognition (ICAPR)

作者： Rajesh M. Bodade Sanjay N. Talbar Mil. Coll. of Telecommun. Eng. Indore S.G.G.S. Institute of Engineering and Technology Nanded India

In this paper, authors have proposed a novel approach of feature extraction of iris images using combination of 2D Dual Tree Rotated Complex Wavelet Transform (RCWT) and 2D Dual Trace Complex Wavelet Transform(CWT). This method provides features in 12 directions against 3 and 6 directions in DWT and CWT respectively. Iris features are obtained by computing energies and standard deviation of detailed coefficients in 12 directions per stage, at 3 levels of decomposition. Canberra distance is used for matching. The results are obtained using DWT, CWT combination of CWT and RCWT on UBIRIS database of 2400 images. The performance measure, ZeroFAR, is reduced from 6.3 using DWT to 2.7 using proposed method. The method is also computationally efficient as compared to Gabor Filters.

关键词： Feature extraction Iris recognition Continuous wavelet transforms Gabor filters Discrete wavelet transforms Image databases Spatial databases Wavelet transforms pattern recognition Military communication

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Benchmarking validity procedures for unsupervised fuzzy pattern classification

Benchmarking validity procedures for unsupervised fuzzy patt...

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IEEE international conference on Multimedia computing and Systems (ICMCS)

作者： Abdellah Lachhab Abdelaziz Bouroumi Ben M'sik Faculty of Science Hassan II Mohamedia University UH2M Casablanca Morocco

In this paper, we present some numerical results of an experimental study of the problem of automatic determination of the number of clusters in unsupervised fuzzy clustering. The study was conducted using the well-known fuzzy c-means algorithm and four associated validity criteria that we applied to illustrative examples of artificial and real data sets. We will mainly focus on the risk of validating bad solutions or rejecting good ones. This risk is inherent to traditional validity procedures, which generally make use of a single criterion, and a multi-criteria procedure is proposed in order to avoid it in real-world applications.

关键词： pattern classification Clustering algorithms Fuzzy sets Unsupervised learning pattern recognition Laboratories Guidelines Testing Signal processing Image processing

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An Approach of Passive Vehicle Type recognition by Acoustic Signal Based on SVM

An Approach of Passive Vehicle Type Recognition by Acoustic ...

引用

international conference on Genetic and Evolutionary computing (WGEC)

作者： Xiao-xuan Qi Jian-wei Ji Xiao-wei Han Zhong-hu Yuan Coll. of Inf. & Electr. Eng. Shenyang Agric. Univ. Shenyang China Coll. of Inf. Eng. Shenyang Univ. Shenyang China

An approach of power spectrum estimation is utilized to extract the feature vectors from acoustic signal radiated from different types of moving vehicles. A method of feature selection based on principal component analysis (PCA) is proposed to reconstruct effective feature vectors via dimension reduction. The classification of three typical targets is achieved by supported vector machine (SVM). Experiment results show that the approach presented in the paper for automatic recognition of vehicle type is effective.

关键词： Vehicles Support vector machines Feature extraction Spectral analysis pattern recognition Principal component analysis Signal analysis Support vector machine classification Acoustic noise Cepstral analysis

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