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mathematics of data/image pattern recognition, compression, and encryption with applications xi

ISBN: (纸本)9780819472953

The proceedings contain 22 papers. The topics discussed include: data compression in emitter location systems via sensor pairing and selection;impact of wavelet types on image data characteristics during compression;optimization of HVS-based objective image quality assessment with eye tracking;lossless compression of images with permutation codes;neural network-based watermark embedding and identification;an image watermark tutorial tool using Matlab;the optimum approximation of an orthogonal expansion having bounded higher order correlations of stochastic coefficients;simultaneous minimization of various worst case measures of error in FIR filter bank;flash hyperspectral imaging of non-stellar astronomical objects;area-based novel approach for fuzzy edge detection using type II fuzzy sets;and compensation method for quantitative observation of multicolor fluorescence with nonlinear mapping.

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mathematics of data/image pattern recognition, compression, and encryption with applications xi: Introduction

Proceedings of SPIE - The International Society for Optical ...

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Proceedings of SPIE - The International Society for Optical Engineering 2008年 7075卷 ix-xi页

作者： Schmalz, Mark S. Ritter, Gerhard X. Barrera, Junior Astola, Jaakko T.

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ISBN: (纸本)9780819472953

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Proceedings of SPIE - mathematics of data/image pattern recognition, compression, and encryption with applications IX

Proceedings of SPIE - Mathematics of Data/Image Pattern Reco...

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mathematics of data/image pattern recognition, compression, and encryption with applications IX

ISBN: (纸本)0819463949

The proceedings contain 23 papers. The topics discussed include: biorthogonal wavelets of maximum coding through pseudoframes for subspaces;a skinning prediction scheme for dynamic 3D mesh compression;multi-modal multi-fractal boundary encoding in object-based image compression;perspectives on data compression methods for network-level management of multi-sensor systems;exploiting data compression methods for network-level management of multi-sensor systems;a model utilizing artificial neural network for perceptual image;use of adaptive models in watermark identification;data payload optimality: a key issue for for video watermarking applications;quantization index modulation-based watermarking using holography;the optimum estimation of statistical signals based on systematic expression of many types of sample arrays in multidimensional space;and segmentation of motion textures using mixed-state Markov random fields.

关键词： pattern recognition

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Proceedings of SPIE - mathematics of data/image pattern recognition, compression, Coding, and encryption X, with applications

Proceedings of SPIE - Mathematics of Data/Image Pattern Reco...

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mathematics of data/image pattern recognition, compression, Coding, and encryption X, with applications

ISBN: (纸本)9780819468482

The proceedings contain 18 papers. The topics discussed include: model based compression of the calibration matrix for hyperspectral imaging systems;optimization of a lossless object-based compression embedded on GAIA a next-generation space telescope;design of multichannel filter banks for subband coding of audio signals using multirate signal processing techniques;the optimum running-type approximation for time-limited worst-case measures of error based on Fredholm integral equation using Pincherle-Goursat kernel;adaptive model and neural network based watermark identification;compressed versus uncompressed domain video watermarking;generation of lattice independent vector sets for pattern recognition applications;and the validity of pyramid k-means clustering.

关键词： pattern recognition

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mathematics of data/ image pattern recognition, compression, Coding, and encryption X, With applications

Mathematics of Data/ Image Pattern Recognition, Compression,...

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2007年

作者： Gerhard X Ritter Mark Steven Schmalz Junior Barrera Jaakko T Astola

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Efficient and Confidentiality-Preserving Bloom Filter-Encoded Video Search

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IEEE Internet of Things Journal 2025年

作者： Yang, Xu Zhao, Hongguang Qi, Saiyu Li, Ke Wang, Qiuhao Qi, Yong Wei, Wei Mumtaz, Shahid School of Computer Science and Technology 710049 China Xi’an University of Technology School of Computer Science and Engineering Xi’an710048 China Shaanxi University of Technology School of Mathematics and Computer Science Hanzhong723000 China Silesian University of Technology Department of Applied Informatics Akademicka 16 Gliwice44-100 Poland Nottingham Trent University Department of Computer Sciences Nottingham United Kingdom

Content based video search services find extensive applications across various domains including video surveillance and object detection. In recent times, researchers have increasingly turned their attention towards enhancing the security of video search over outsourced encrypted videos. Nonetheless, prior researchers often leverage cost-expensive techniques like Homomorphic encryption or Order-preserving encryption to ensure privacy preservation. To reduce the overhead, Bloom Filter (BF)-encoded keyword search is a promising technology for retrieving encrypted videos with image queries. However, it generally suffers from serious data privacy leakage since it will reveal the inclusion relationship between "1" and "0" in the BF. Fortunately, the privacy-preserving bloom filter-based search scheme (PBKS) was recently proposed to achieve secure and effective search while protecting the values in BFs, but it still has two limitations. One is the size of a search token is very large in some cases and the other is the cloud server can infer the true value of each bit in the BF by doing a few operations. In this paper, we propose an efficient and confidentiality-preserving bloom filter-encoded video search (ECVS) scheme for retrieving encrypted videos with image queries. We first design a new CPRF (prefix-constrained pseudorandom function)-based token compression method to reduce the size of the search token and reduce the communication cost largely. Furthermore, we customize a periodic refresh mechanism to conceal the true value of each bit in the BF while avoiding excessive computational pressure on resource-limited users. Security analysis and experiments confirm the security and efficiency of our schemes. © 2014 IEEE.

关键词： Privacy by design

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data compression in emitter location systems via sensor pairing and selection

Data compression in emitter location systems via sensor pair...

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Conference on mathematics of data/image pattern recognition, compression, Coding, and encryption X, with applications xi

作者： Hu, xi Fowler, Mark L. SUNY Binghamton Dept Elect & Comp Engn Binghamton NY 13902 USA

ISBN: (纸本)9780819472953

data compression ideas can be extended to assess the data quality across multiple sensors to manage the network of sensors to optimize the location accuracy subject to communication constraints. From an unconstrained-resources viewpoint it is desirable to use the complete set of deployed sensors;however, that generally results in an excessive data volume. We have previously presented here results on selecting pre-paired sensors. We have now extended Our results to enable optimal joint pairing/selection of sensors. Pairing and selecting sensors to participate in sensing is crucial to satisfying trade-offs between accuracy and time-line requirements. We propose two methods that use Fisher information to determine sensor pairing/selection. The first method optimally determines pairings as well as selections of pairs but with the constraint that no sensors are shared between pairs. The second method allows sensors to be shared between pairs. In the first method, it is simple to evaluate the Fisher information but is challenging to make the optimal selections of sensors. However, the opposite is true in the second method: it is more challenging to evaluate the Fisher information but is simple to make the optimal selections of sensors.

关键词： Sensor Selection Sensor Management data compression Sensor Networks TDOA/FDOA Emitter Location Fisher Information

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Impact of signal model on data compression for TDOA/FDOA emitter location

Impact of signal model on data compression for TDOA/FDOA emi...

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Conference on mathematics of data/image pattern recognition, compression, Coding, and encryption X, with applications xi

作者： Fowler, Mark L. Hu, xi SUNY Binghamton Dept Elect & Comp Engn Binghamton NY 13902 USA

ISBN: (纸本)9780819472953

Early work in source location using time-difference-of-arrival/frequency-difference-of-arrival (TDOA/FDOA) focused on locating acoustic sources while later work focused on locating electromagnetic sources. The key difference is the signal model assumptions: WSS Gaussian process is widely used in the acoustic case but is not appropriate in the electromagnetic case. The Fisher information (FI) is fundamentally different for the two scenarios and leads to different distortion metrics for data compression algorithms that seek to maximize the F1 for a given data rate. We discuss the philosophical impacts of this relevant to the following question: having collected a single of data and wanting to do the best "job" for that data, should it matter if the data is viewed as coming from a WSS random process? This work shows that one must be careful when using a random signal model. If one takes the operational rate-distortion view, the goal of compression is to adapt the algorithm to the specific data observed. This is a modern view that contrasts with classical rate-distortion where the distortion measure includes an averaging over the ensemble. We assert that for the operational rate-distortion approach with FI as distortion measure, one should not use a random signal model.

关键词： data compression Sensor Networks TDOA/FDOA Emitter Location Fisher Information

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Exploiting data compression methods for network-level management of multi-sensor systems

Exploiting data compression methods for network-level manage...

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Conference on mathematics of data/image pattern recognition, compression and encryption with Application IX

作者： Hu, xi Chen, Mo Fowler, Mark L. SUNY Binghamton Dept Elect & Comp Engn Binghamton NY 13902 USA

ISBN: (纸本)0819463949

data compression ideas can be extended to assess the data quality across multiple sensors to manage the network of sensors to optimize the location accuracy subject to communication constraints. From an unconstrained-resources viewpoint it is desirable to use the complete set of deployed sensors;however, that generally results in an excessive data volume. Selecting a subset of sensors to participate in a sensing task is crucial to satisfying trade-offs between accuracy and time-line requirements. For emitter location it is well-known that the geometry between sensors and the target plays a key role in determining the location accuracy. Furthermore, the deployed sensors have different data quality. Given these two factors, it is no trivial matter to select the optimal subset of sensors. We attack this problem through use of a data quality measure based on Fisher Information for set of sensors and optimize it via sensor selection and data compression.

关键词： sensor selection sensor management data compression sensor networks TDOA/FDOA emitter location Fisher information

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image registration error analysis using pattern recognition algorithms

Image registration error analysis using pattern recognition ...

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Conference on mathematics of data/image Coding, compression, and encryption with applications xiI

作者： Duraisamy, Prakash Shen, Yao Yuan, xiaohui Univ N Texas Denton TX 76203 USA

ISBN: (纸本)9780819482952

image segmentation is one of the important applications in computer vision applications. In this paper, we present an image registration method that stiches multiple images into one complete view. Also, we demonstrate how image segmentation is used as an error metric to evaluate image registration. This paper explains about the error analysis using pattern recognition algorithm such as watershed algorithm for calculating the error for image registration applications. In this paper, we compare pixel intensity-based error metric with object-based error metric for evaluating the registration results. We explain in which situation pattern recognition algorithm is superior to other conventional algorithm such as mean square error.

关键词： Homography image Registration Evaluation

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