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International conference on distributed Computing in Sensor Systems (DCOSS)

作者： Saptarshi Hazra Martina Brachmann Thiemo Voigt RISE Research Institutes of Sweden Stockholm Sweden

ISBN: (数字)9781728143514

ISBN: (纸本)9781728198040

The ubiquity of wirelessly connected sensing devices in IoT applications provides the opportunity to enable various types of interaction with our digitally connected environment. Currently, low processing capabilities and high energy costs for communication limit the use of energy-constrained devices for this purpose. In this paper, we address this challenge by exploring the new possibilities highly capable deep neural network classifiers present. To reduce the energy consumption for transferring continuously sampled data, we propose to compress the sensed data and perform classification at the edge. We evaluate several compression methods in the context of a shadow-based hand gesture detection application, where the classification is performed using a convolutional neural network. We show that simple data reduction methods allow us to compress the sensed data into a single IEEE 802.15.4 packet while maintaining a classification accuracy of 93%. We further show the generality of our compression methods in an audio-based interaction scenario.

关键词： image edge detection Cloud computing Machine learning Gesture recognition Microsoft Windows Performance evaluation IEEE 802.15 Standard

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Divisible Load Scheduling of image processing Applications on the Heterogeneous Star Network Using a New Genetic Algorithm 26

Divisible Load Scheduling of Image Processing Applications o...

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26th Euromicro International conference on parallel, distributed, and Network-Based processing (PDP)

作者： Aali, Sahar Nikbakht Shahhosseini, Hadi Shahriar Bagherzadeh, Nader Iran Univ Sci & Technol Tehran Iran Univ Calif Irvine Irvine CA USA

ISBN: (纸本)9781538649756

The divisible load scheduling of image processing applications on the heterogeneous star network is addressed in this paper. In our platform, processors and links have different speeds. Also the computation and communication overheads are considered. A new genetic algorithm for minimizing the processing time of low level image applications using divisible load theory is introduced. A closed form solution for the processing time and the image fractions that should be assigned to each processor are obtained. The optimum number of participating processors and the optimal sequence for load distribution with a new genetic algorithm are derived. The effect of different image and kernel sizes on processing time and speed up are investigated. Finally, to indicate the efficiency of our algorithm, several numerical experiments are presented.

关键词： Divisible load scheduling local operation image fractions load distibution sequence genetic algorithm

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A Fast Method for Large-scale Scene Data Acquisition and 3D Reconstruction 18

A Fast Method for Large-scale Scene Data Acquisition and 3D ...

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International Normal Labour and Birth Research conference

作者： Li, Yao Xie, Yang Wang, Xijing Luo, Xun Qi, Yue State Key Lab Virtual Real Technol & Syst Beijing Peoples R China Tianjin Univ Technol Sch Comp Sci & Engn Tianjin Peoples R China Beihang Univ Shenzhen Qingdao Res Inst Peng Cheng Lab Qingdao Peoples R China

ISBN: (纸本)9781728147659

Large-scale 3D scene has an important application prospect in virtual reality and augmented reality. However, due to the doubling of the amount of data in the 3D reconstruction of large-scale outdoor scene, the index of time becomes a great challenge under the condition of maintaining a certain degree of accuracy. In this paper, we provide a set of methods of aerial photography data acquisition and cluster-based 3D model reconstruction for large-scale scene. Firstly, for the data acquisition end, we adopt two strategies of track pre-planning and feedback-based trajectory planning to meet the requirements of efficient data acquisition. Secondly, we have designed and implemented a distributed 3D reconstruction system to process a large number of aerial photographs, which can quickly and robustly reconstruct large-scale 3D models. Finally, we simulate the crowd behavior based on the PEM model in the reconstructed 3D scene, which has a useful guiding significance for people's daily activities and emergency problems.

关键词： Large-Scale distributed modeling Path planning Crowd simulation I.4.5 [image processing and Computer Vision]: Reconstruction Summation methods I.4.1 [image processing and Computer Vision]: Digitization and image Capture Imaging geometry I.6.4 [Simulation and Modeling]: Model Validation and Analysis

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parallel image encryption with bitplane decomposition and genetic algorithm

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MULTIMEDIA TOOLS AND APPLICATIONS 2018年第19期77卷 25799-25819页

作者： Mozaffari, Saeed Semnan Univ Fac Elect & Comp Engn Semnan Iran

image encryption is an efficient technique to protect image content from unauthorized parties. In this paper a parallel image encryption method based on bitplane decomposition is proposed. The original grayscale image is converted to a set of binary images by local binary pattern (LBP) technique and bitplane decomposition (BPD) methods. Then, permutation and substitution steps are performed by genetic algorithm (GA) using crossover and mutation operations. Finally, these scrambled bitplanes are combined together to obtain encrypted image. Instead of random population selection in GA, a deterministic method with security keys is utilized to improve security level. The proposed encryption method has parallel processing capability for multiple bitplanes encryption. This distributed GA with multiple populations increases encryption speed and makes it suitable for real-time applications. Simulations and security analysis are done to demonstrate efficiency of our algorithm.

关键词： parallel image encryption Bitplain decomposition Local binary pattern Metaheuristic algorithms parallel genetic algorithm GPU programming

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distributed image processing based on the same IP-cores in FPGA-architecture 5

Distributed image processing based on the same IP-cores in F...

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Data Science Session at the 5th International conference on Information Technology and Nanotechnology, DS-ITNT 2019

作者： Zakharov, V.M. Shalagin, S.V. Eminov, B.F. Kazan National Research Technical University named after A.N. Tupolev Karl Marks 10 Kazan420111 Russia

The problem of processing images, i. e., two-dimensional data arrays, was solved through implementing two-dimensional fast Fourier transform (FFT) when using single-type hardware modules – IP-cores in the Virtex-6 FPGA architecture. We have shown the possibility of the parallel implementation of each stage in the two-dimensional FFT, based on four "butterfly"-type transforms (BTr) over four elements of the data array being processed. Estimations were obtained regarding time- and hardware complexity of the IP-core implementing BTrs and used in implementing the one-dimensional FFT. The results obtained can be used in estimating hardware and time consumption when performing a two-dimensional FFT over an array of the pre-defined dimensionality in using existing and forthcoming distributed programmable-architecture systems. © 2019 CEUR Workshop Proceedings.

关键词： Intellectual property core

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Development of an Accelerated Method for Calculating Streaming Video Data Obtained from UAVs

Development of an Accelerated Method for Calculating Streami...

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International conference on Control, Mechatronics and Automation (ICCMA)

作者： V.M Khachumov E. M Portnov P.A Fedorov R.A Kasimov Aung Naing Linn Institute of Systems and Software Engineering and Information Technology National Research University of Electronic Technology Zelenograd Moscow RUSSIA

ISBN: (数字)9781728192109

ISBN: (纸本)9781728192116

The problem of accelerating the processing of video streams captured from the unmanned aerial vehicle (UAV) is solved by the example of detecting smoke and fires (onboard) and finding target objects on panoramic images (on a ground computing platform). Due to the limited computing resources, all processing of video streams should be subdivided into tasks to be solved onboard and ground installations with operator control. It is proposed to use an algorithm for analyzing spectrographic textures based on the Euclidean-Mahalanobis metric. The use of the classifier of spectrographic textures provides finding it difficult to detect objects, which is unattainable for classifiers working with separate image points. It is proposed to use a ground computing facility with a neural network target recognition system with support for pipelining and parallelization. When implementing the processing of flows at ground stations, the advantage should be given to the methods of pipeline-parallel computations using cluster installations, which can be equipped with graphics accelerators; here an essential role is played not only by methods of accelerating computations but also by methods of automating the construction of computational schemes of problems due to a special graphical interface and modular organization of software. An experimental study in terms of speeding up computations in problems of recognizing objects and areas of interest in various computing systems has confirmed the correctness of the proposed approaches. The proposed methods and approaches together provide acceleration of computations by more than 10 times.

关键词： Measurement Streaming media Covariance matrices Acceleration Unmanned aerial vehicles image color analysis Process control

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Challenges of Ship Focusing with Long Coherence processing Interval 39

Challenges of Ship Focusing with Long Coherence Processing I...

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IEEE International Geoscience and Remote Sensing Symposium (IGARSS)

作者： Liu, WenKang Xing, MengDao Sun, Guang-Cai Xidian Univ Xian 710071 Peoples R China

ISBN: (纸本)9781538691540

Ship oscillatory motions with long coherence processing interval (CPI) are complex and hard to accurately estimate. The traditional ship imaging methods usually avoid long-CPI focusing by dealing with a short observation time interval, which may make it hard to obtain a high-resolution and high-SNR image. In this paper, the mechanisms and challenges of long CPI imaging of oscillatory targets are investigated. The properties of wavenumber domain support (WDS) and point spreading function (PSF) of oscillatory targets are analyzed. It's found that the WDS spreads as a three-dimensional (3D) thin and curved sweep surface, with time-variant energy density, non-parallel boundaries and a complex structure. The PSF of an oscillatory target has a 3D resolution, but also multiple side-lobes with high level. We inspect the relationships between the properties of the WDS and the non-ideal PSF. Moreover, it's found that scatters distributed on a 3D oscillatory target cannot be focused uniformly on a predefined imaging plane (IP). The projection relationship of the target focusing positions on the slant-range plane (SRP) and the IP are also derived. The simulation results can well validate the proposed method.

关键词： ship image 3D oscillatory motion long coherence processing interval (long-CPI) imaging

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Generalizing Spectral Difference Method for Multispectral image Demosaicking and Analyzing the Role of MSFA Patterns

Generalizing Spectral Difference Method for Multispectral Im...

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International conference on System Modeling & Advancement in Research Trends (SMART)

作者： Medha Gupta Graphic Era University Dehradun India

ISBN: (数字)9781728189086

ISBN: (纸本)9781728189093

Multispectral images contain more content and details in comparison to color images and are observed to be beneficial for several applications. However, large size and cost restricts the wider usage and adoption of the multi-sensors multispectral imaging systems. Multispectral image demosaicking methods can help develop single-sensor equivalent systems at low cost. In this work, we present an efficient generic method for multispectral image demosaicking by extending the spectral difference method and we also present the analysis of multispectral filter array (MSFA) patterns on the performance, evaluated using two different metrics and by considering two different benchmark multispectral images datasets. Experimental results demonstrate the efficacy of the proposed method, except in cases when non compact MSFA patterns are used.

关键词： Measurement Multispectral imaging Color Systems modeling parallel processing Benchmark testing Market research

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Optimizing Performance of Aggregate Query processing with Histogram Data Structure 8th

Optimizing Performance of Aggregate Query Processing with Hi...

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8th Computer Science On-Line conference (CSOC)

作者： Liang Yong Mu Zhaonan Guizhou Univ Commerce Network & Informat Ctr Guiyang 550014 Guizhou Peoples R China

ISBN: (纸本)9783030198077;9783030198060

In today's big data era, the capability of analyze massive data efficient and return the results within an short time limit is critical to decision making, thus many big data system proposed and various distributed and parallel processing techniques are heavily investigated. Among previous research, most of them are working on precise query processing, while approximate query processing (AQP) techniques which make interactive data exploration more efficiently and allows users to tradeoff between query accuracy and response time have not been investigate comprehensively. In this paper, we study the characteristics of aggregate query, a typical type of analytical query, and proposed an approximate query processing approach to optimize the execution of massive data based aggregate query with a histogram data structure. We implemented this approach into big data system Hive and compare it with Hive and AQP-enabled big data system BlinkDB, the experimental results verified that our approach is significantly fast than these existing systems in most scenarios.

关键词： Massive data Approximate query processing Histogram Aggregate query Performance optimization

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Phase-only optical image encryption and hiding based on normalization and orthogonalization phase-shifting algorithm 11

Phase-only optical image encryption and hiding based on norm...

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11th International conference on Information Optics and Photonics (CIOP)

作者： Li, Jiaosheng Lu, Xiaoxu Zhang, Qinnan Tian, Jindong Zhong, Liyun South China Normal Univ Guangdong Prov Key Lab Nanophoton Funct Mat & Dev Guangzhou 510006 Peoples R China Shenzhen Univ Shenzhen Key Lab Micronano Measuring & Imaging Bi Coll Phys & Optoelect Engn Shenzhen 518060 Peoples R China

ISBN: (数字)9781510631748

ISBN: (纸本)9781510631748

Optical encryption technology using phase-shifting interferometry (PSI) is widely used in many security fields, showing the advantages of parallel processing and the high security due to the information can be encrypted in multiple dimensions. The traditional PSI- based encryption methods are realized by the traditional multi-step phase-shifting algorithms (PSAs), although they are fast and accurate, the phase shifts deviation (PSD) caused by phase shifter detuning often affect the performance of the above methods. In order to solve this problem, a phase-only encryption method combining a normalization and orthogonalization phase-shifting algorithm (NOPSA) is proposed to eliminate the influence of PSD on the effective on decryption. First, the original image is phase encoded and encrypted by a phase key loaded on a liquid crystal spatial light modulator (SLM). Subsequently, the modulated reference light will be overlapped with the object wave to form interference pattern. Finally, the encrypted image hiding can be implemented based on NOPSA. Compared with the current PSI- based encryption methods, its obvious advantage is that when the phase shifts are not accurate or unknown, the proposed method can still achieve high quality encryption and hiding, which broadens the working conditions of PSI- based encryption methods.

关键词： Phase-shifting interferometry (PSI) optical image encryption and hiding phase shifts deviation (PSD) normalization and orthogonalization

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