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检索条件"主题词=compression algorithms"

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Author Identification Using compression Models

Author Identification Using Compression Models

引用

International Conference on Document Analysis and Recognition

作者： D. Pavelec L.S. Oliveira E. Justino F.D. Nobre Neto L.V. Batista Pontifícia Universidade Católica do Paraná Curitiba Brazil Universidade Federal do Paraná Curitiba Brazil Universidade Federal da Paraíba Joao Pessoa Brazil

ISBN: (纸本)9781424445004

In this paper we discuss the use of compression algorithms for author identification. We present the basic background about compression algorithms and introduce the prediction by partial matching algorithm, which has been used in our experiments. To better compare the results produced by the PPM algorithm, we present some experiments using stylometric features used very often by forensic examiners. In this case the authors are modeled using support vector machines. Comprehensive experiments performed on a database composed of 20 different authors show that the PPM algorithm is an interesting alternative for author identification, since all the process of feature definition, extraction, and selection can be avoided.

关键词： compression algorithms Forensics Feature extraction Frequency Text analysis Algorithm design and analysis Support vector machines Spatial databases History Pediatrics

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Improved lossless compression of color palette images by re-indexing with particle swarm optimization

Improved lossless compression of color palette images by re-...

引用

International Conference on Soft Computing, Computing with Words and Perceptions in System Analysis, Decision and Control, ICSCCW

作者： Joshua Van Hook Ferat Sahin Ziya Arnavut Electrical Engineering Rochester Institute of Technology Rochester NY USA Computer Science SUNY Fredonia Fredonia NY USA

This work builds on previous work in the area of one dimensional lossless color compression. The previous work applied a cross entropy (CE) solution to traveling salesman problem (TSP) for color re-indexing with a Burrows-Wheeler transformation and inversion ranks. The proposed technique replaces the cross entropy based TSP algorithm with a particle swarm optimization (PSO) for the task of color re-indexing. The proposed method yields improvement over the previous work regardless of the number of colors in the image.

关键词： Image coding Color Particle swarm optimization Equations Entropy compression algorithms Traveling salesman problems Genetic algorithms Computer science Optimization methods

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Color compression in video registration and security systems

Color compression in video registration and security systems

引用

Central and Eastern European Software Engineering Conference in Russia (CEE-SECR)

作者： Nikolai S. Kazantsev Vladimir M. Degtyrev Higher School of Economics Russia

This research work refers to solution of the practical security, anti-terrorist fighting problems, providing effective tools against different non-authorized penetrations. From the informatics and the software points of view these problems are linked to the image processing and creating of the compression algorithms applicable for the video array frames obtained by standard registration systems. compression solutions become crucially important when the temporal evolution of the video stream exceeds the traffic capacity of the communication network. All algorithms and methods known and exploited nowadays are unable to meet the reliable security requirements. The MPEG and the MPEG4 compression codes distort the initial image. Fragmentation or splitting the video stream into separate frames with the subsequent application of the ordinary DCT or DWT procedures provides better compression rate, but the quality of the image still remains rather poor with no chance for creating a justified and documented personal identification protocol. The main research objective of this paper is providing significant reduction of the information traffic within a standard security registration system (a network of about 10 cameras and microphones relayed to an operating server) possibly maintaining the highest quality of records in the server. The basic image processing approach we exploited is to maintain of the highest resolution degree for the main part of the object we survey (for example man's face or figure) whilst minimizing the information traffic from the image background by its artificial substitution with a homogeneous color filling. This method allowed obtaining significant compression rate already (up to 7000) and presently we are carrying on even more promising studies on this subject.

关键词： Video compression Security Image coding Image processing Streaming media Telecommunication traffic Network servers Informatics compression algorithms Software standards

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A novel scheme for the compression and classification of hyperspectral images

A novel scheme for the compression and classification of hyp...

引用

Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, WHISPERS

作者： Bei Xie Tamal Bose Erzsebet Merenyi Wireless Virginia Tech Bradley Department of Electrical and Computer Engineering Virginia Polytechnic Institute and State University Blacksburg VA USA Electrical and Computer Engineering Rice University Houston TX USA

Since hyperspectral images are very large, it is desirable to compress them before transmission. After receiving the compressed image, decompression is applied before performing image classification and other operations. In this paper, a new processing scheme is proposed, where image transform and quantization are applied for image compression at the transmitter and classification is performed directly on the compressed data at the receiver. The advantage of this scheme is that fewer computations are needed. Computer simulations are performed on hyperspectral imagery.

关键词： Image coding Hyperspectral imaging Hyperspectral sensors Image classification Discrete cosine transforms Pulse modulation Discrete transforms compression algorithms Artificial neural networks Quantization

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Hyperspectral Image compression Based on Wavelets and Uniform Directional Filter Banks

Hyperspectral Image Compression Based on Wavelets and Unifor...

引用

Computer Science and Information Engineering, CSIE, WRI World Congress on FLAGGED

作者： Dong Song Lihua Hu Yan Feng Northwestern Polytechnical University Xi'an China

A multiscale geometric analysis method based on wavelet and uniform directional filter banks (WUDFB) is structured in order to overcome the insufficiencies of contourlet transform and wavelet-based contourlet transform which are used in compression. A novel WUDFB-based compression algorithm of hyperspectral imagery is proposed, in which intra-band WUDFB and inter-band prediction are used to remove the spatial and spectral redundancy respectively, and no-list set partitioned embedded block coder makes output embedded stream. The experimental results by using 64 band hyperspectral data show that the algorithm achieves higher peak signal-to-noise ratio at high compression ratio and preserves more detail information of original images than the algorithm based on wavelet transform.

关键词： Hyperspectral imaging Image coding Filter bank Wavelet transforms Hyperspectral sensors Computed tomography Remote sensing Wavelet analysis Image analysis compression algorithms

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Progressive Geometry-Driven compression for Triangle Mesh Based on Binary Tree

Progressive Geometry-Driven Compression for Triangle Mesh Ba...

引用

International Conference on Visualisation, VIS

作者： Liu Hongnian Liu Bo Zhang Hongbin College of Computer Science Beijing University of Technology Beijing China

Efficient algorithms for compressing three-dimensional (3D) triangle meshes have been widely developed in recent years, but most of them are designed to deal with manifold meshes. A progressive geometry-driven 3D triangle meshes algorithm is proposed in this work which can be easily extended to non-manifold mesh compression and polygon mesh compression. Different from connectivity-driven algorithms; our method starts with the geometry; it encodes the geometry data into a symbol sequence consisting of only three kinds of symbols. Edge collapse and vertex unification operator are used to encode the connectivity, and the symbol sequences can be further encoded by arithmetic coding.

关键词： Binary trees Geometry Topology compression algorithms Decoding Mesh generation Visualization Educational institutions Algorithm design and analysis Arithmetic

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A lossless data compression method for an application in high energy physics

A lossless data compression method for an application in hig...

引用

Ph.D. Research in Microelectronics and Electronics (PRIME)

作者： Christian Patauner Wolfgang Pribyl Alessandro Marchioro Department: PH Group: ESE CERN-European Organization for Nuclear Research Geneve Switzerland Institute of Electronics Graz University of Technology Graz Austria

This paper presents a data compression algorithm to be used for data coming from the digitization of signals from particle physics detectors. Modern detectors in high energy physics experiments produce a huge amount of information. Therefore, efficient data reduction methods right at the front end are required to reduce the amount of data to be transmitted and stored. The data compression algorithm proposed in this paper is based on a combination of vector quantization and Huffman coding and is a lossless compression method. This compression algorithm is designed to be implemented in a new front end ASIC for amplification and digitization of signals in TPC detectors. The performance of the described compression method is presented by using a set of measured data from the ALICE TPC recording cosmic rays at CERN. The compression method is compared with the simpler arithmetic coding and Huffman coding. The obtained results show that a compression factor of 2 can be obtained on relevant data. The compression method results in a reduction better than what predicted by the simple entropy of the used data set. An implementation proposal is given and the required memory requirements for an ASIC are estimated.

关键词： Data compression Detectors Huffman coding Application specific integrated circuits Vector quantization compression algorithms Signal design Algorithm design and analysis Signal detection Cosmic rays

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GQComp: A Query-Supported compression Technique for GML

GQComp: A Query-Supported Compression Technique for GML

引用

International Conference on Computer and Information Technology (CIT)

作者： Qiang Dai Shuliang Zhang Zhihui Wang Department of Geographic Science Nanjing Normal University Nanjing China

GML documents are extremely verbose since containing large amounts of description information of structure. While some compressors are available to address this problem, no one is designed to support direct querying of the compressed documents so far. In this paper, we propose a new query-supported GML compression tool, called GQComp, based on traditional GML compressors and query-supported XML compressors. GQComp not only achieves high compression ratio as the existing GML compression algorithms, but also implements the attribute query, spatial query and mutual query of the compressed files, through the combination of feature structure tree and spatial index. The experiments indicate that GQComp obtains reasonably good results both at compression ratio and query efficiency.

关键词： Compressors compression algorithms XML Spatial indexes Geometry Information technology Geography Markup languages Data communication Roads

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Efficient random codebooks and databases for lossy compression in near-linear time

Efficient random codebooks and databases for lossy compressi...

引用

IEEE (first ITW conference of the year) Information Theory Workshop (ITW)

作者： Ioannis Kontoyiannis Christos Gioran Department of Informatics Athens University of Economics and Business Athens Greece

We examine the compression-complexity trade-off of lossy compression algorithms that are based on a random code-book or a random database. Motivated, in part, by some recent results of Gupta-Verdu-Weissman (GVW) and their underlying connections with the pattern-matching scheme of Kontoyiannis' lossy Lempel-Ziv algorithm, we introduce a non-universal version of the lossy Lempel-Ziv method (termed LLZ), we prove its optimality for memoryless sources, and we compare its performance to that of the GVW divide-and-conquer approach. Experimental results indicate that the GVW approach often yields better compression than LLZ, but at the price of much higher memory requirements. To combine the advantages of both, we introduce a hybrid algorithm (HYB) that utilizes both the divide-and-conquer idea of GVW and the single-database structure of LLZ. We show that HYB shares with GVW the exact same rate-distortion performance and implementation complexity, while, like LLZ, requiring much less memory, typically by at least one or two orders of magnitude. Experimental results are also presented, illustrating the performance of all three methods on data generated by simple discrete memoryless sources. In particular, the HYB scheme is shown to outperform existing schemes for the compression of some simple discrete sources with respect to the Hamming distortion criterion.

关键词： Databases compression algorithms Data compression Rate-distortion Transform coding Convergence Informatics Performance loss Information theory Arithmetic

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Stream-oriented Lossless Packet compression in Wireless Sensor Networks

Stream-oriented Lossless Packet Compression in Wireless Sens...

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IEEE Communications Society Conference on Sensor and Ad Hoc Communications and Networks (SECON)

作者： Andreas Reinhardt Matthias Hollick Ralf Steinmetz Multimedia Communications Laboratory Technische Universität Darmstadt Darmstadt Germany

In wireless sensor networks, the energy consumption of participating nodes has crucial impact on the resulting network lifetime. Data compression is a viable approach towards preserving energy by reducing packet sizes and thus minimizing the activity periods of the radio transceiver. In this paper, we propose a compression framework utilizing a stream-oriented compression scheme for sensor networks. It is specifically tailored to the capabilities of employed nodes and network traffic characteristics, which we determine in a characterization of WSN traffic patterns. To mitigate the inapplicability of traditional compression approaches, we present the squeeze KOM compression layer. By shifting data compression into a dedicated layer, only minor modifications to applications are required, while efficient data transfer between nodes is provided. As a proof-of-concept, we implement a stream-based compression algorithm on sensor nodes and perform an experimental analysis to determine the potential gains under realistic traffic conditions. Results indicate that our presented lossless stream-oriented payload compression leads to considerable savings.

关键词： Wireless sensor networks Data compression Telecommunication traffic Energy consumption Radio transceivers Sensor phenomena and characterization compression algorithms Performance analysis Algorithm design and analysis Performance gain

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