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A River Flood Monitoring Technique based on image Splitting algorithms 10

A River Flood Monitoring Technique based on Image Splitting ...

10th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing systems - Technology and Applications (IDAACS)

作者： Avanzato, Roberta Beritelli, Francesco Cavallaro, Angelo Cuccia, Massimiliano Lombardo, Tiziana Univ Catania Dept Elect Elect & Comp Engn Catania Italy AC2 Srl Adv Consulting Via Cassone 23 I-95019 Zafferana Etnea CT Italy

ISBN: (纸本)9781728140698

The development of innovative solutions to reduce hydrogeological risk is one of the most important research topics of recent years. The paper proposes a technique for river flood detection based on image processing for sub-blocks. The tests carried out with the proposed method have shown that the system is able to estimate the flooding event with good precision and with very short timeframes. The research activity was carried out within the CORA (COntrollo del Rischio Ambientale, Environmental Risk Control) project financed by the Calabria Region (Italy)(1).

关键词： image processing flood monitoring and prevention natural disaster video surveilliance

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The image series forgery detection algorithm based on the camera pattern noise analysis 5

The image series forgery detection algorithm based on the ca...

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5th Information Technology and Nanotechnology 2019: image processing and Earth Remote Sensing, ITNT 2019

作者： Evdokimova, N.I. Myasnikov, v.v. Samara National Research University Moskovskoe Shosse 34 Samara443086 Russia Image Processing Systems Institute of RAS - Branch of the FSRC "Crystallography and Photonics" RAS Molodogvardejskaya street 151 Samara443001 Russia

In the paper, the image series forgery detection algorithm based on the analysis of camera pattern noise is proposed. Distribution characteristics of the camera pattern noise are obtained by extracting the noise component of images from the non-tampered image series. A noise residual of a forgery image is compared with the camera pattern noise. We compare various noise filtering algorithms to choose the one that achieves the best performance of the proposed method. The proposed algorithm is tested both on examples of copy-move forgeries and forgery fragments which were inserted from an image not included in the image series. © 2019 CEUR-WS. All rights reserved.

关键词： Cameras

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A Concept of Smart Medical Autonomous Distributed System for Diagnostics Based on Machine Learning Technology 19th

A Concept of Smart Medical Autonomous Distributed System for...

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19th International Conference on Next Generation Teletraffic and Wired/Wireless Advanced Networks and systems (NEW2AN) / 12th Conference on the Internet of Things and Smart Spaces ruSMART (Are You Smart)

作者： velichko, Elena Nepomnyashchaya, Elina Baranov, Maxim Galeeva, Marina A. Pavlov, vitalii A. Zavjalov, Sergey v. Savchenko, Ekaterina Pervunina, Tatiana M. Govorov, Igor Komlichenko, Eduard Peter Great St Petersburg Polytech Univ St Petersburg Russia Almazov Natl Med Res Ctr St Petersburg Russia

ISBN: (纸本)9783030308599;9783030308582

Telemedicine is a promising direction in the development of medical technologies for the interaction of patients with doctors at a distance. In this paper, we consider the use of telemedicine technologies for the development of smart medical autonomous technology. An example of a smart medical autonomous distributed system for diagnostics is also discussed. To develop this system for medical image analysis we review several processing methods and machine learning algorithms. Some examples of medical system processing results are presented.

关键词： Telemedicine Medical diagnostics image processing

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Improving the stabilization level of ISP system using feedforward compensators 16

Improving the stabilization level of ISP system using feedfo...

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Conference on Electro-Optical and Infrared systems - Technology and Applications XvI

作者： vu, Thuan D. Nguyen, Thang v. Hoang, Chinh D. Nguyen, Ban D. Viettel High Technol Ind Corp Viettel Grp Hoa Lac Hitech Pk Hanoi Vietnam

ISBN: (数字)9781510630222

ISBN: (纸本)9781510630222

The stabilization of the Line of Sight (LOS) of an Electro-Optical System (EOS) locating on a moving platform contributes significantly to the image quality. A portion of perturbation inherited by the base motion can be eliminated by numbers of algorithms with powerful processors boards. However, it is difficult to implement these algorithms in embedded systems because of memory capacity and processing speed limitation. This paper introduces a method for identifying gimbal parameters and feedforward compensators. The key parameters including the friction force, cross-coupling effect and misalignment compensator are investigated using feedforward compensator theory and verified by practical experiments. The effectiveness in the stabilization loop is validated through many scenarios of disturbance. The result shows that the good improvement for the stabilization level of inertial stabilization platform has been achieved, and the reduction of LOS RMS errors is up to 40 per cent.

关键词： Feedforward disturbance stabilization level system identification

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Optimized Implementation of Modified Gram Schmidt Algorithm on vLIW Architecture

Optimized Implementation of Modified Gram Schmidt Algorithm ...

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IEEE 4th World Conference on Complex systems (WCCS)

作者： Najoui, Mohamed Hatim, Anas Belkouch, Said Chabini, Noureddine Mohamed V Univ ENSET Rabat E2SN Lab Rabat Morocco Ibn Zohr Univ ENSA Agadir LGEMS Lab Agadir Morocco Cadi Ayyad Univ ENSA Marrakech LGECOS Lab Marrakech Morocco Royal Mil Coll Canada Dept Elect & Comp Engn Kingston ON Canada

ISBN: (纸本)9781728112329

Modified Gram Schmidt (MGS) is one of the well-known forms of QR decomposition (QRD) algorithms. It has been used in many signal and image processing applications to solve least square problem, linear equations or to invert matrices. Nevertheless, QRD is considered a computationally expensive operation, and its sequential implementation doesn't meet the requirements of many real time applications. In this paper, we propose an optimized MGS algorithm version based on software pipelining and loop unrolling techniques. The suggested MGS version is parallel and well suited for vLIW architectures. The implementation is done under TI C6678 vLIW DSP and the obtained results show great improvements against the standard MGS and the optimized vendor QRD implementations.

关键词： Signal and image processing MGS vLIW Software Pipelining DSP

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Enhanced sparse representation classifier for text classification

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EXPERT systems WITH APPLICATIONS 2019年第0期129卷 260-272页

作者： Unnikrishnan, P. Govindan, v. K. Kumar, S. D. Madhu Natl Inst Technol Calicut Dept Comp Sci & Engn Kozhikode India

Classification of text based on its substance is an essential part of analysis to organize enormously large text data and to mine the salient information contained in it. It is gaining greater attention with the surge in the volume of on-line data available. Classical algorithms like k-NN (k-nearest neighbor), SvM (Support vector Machine) and their variations have been observed to yield only reasonable results in addressing the problem, leaving enough room for further improvement. A class of algorithms commonly referred to as Sparse Methods has been emerged recently from compressive sensing and found numerous effective applications in many areas of data analysis and image processing. Sparse Methods as a tool for text analysis is an alley that is largely unexplored rigorously. This paper presents exploration of sparse representation-based methods for text classification. Based on the success of sparse representation based methods in different areas of data analysis, we intuitively hypothesized that it should work well on text classification problems as well. This paper empirically reinforces the hypothesis by testing the method on Reuters and WebKB data sets. The empirical results on Reuters and WebKB benchmark data show that it can outperform classical classification algorithms like SvM and k-NN. It has been observed that obtaining the basis of representation and sparse codes are computationally costly operations affecting the performance of the system. We also propose a class-wise dictionary refinement algorithm and dynamic dictionary selection algorithm to make sparse coding faster. The addition of dictionary refinement to the classification system not only reduces the time taken for sparse coding but also gives improved classification accuracy. The outcomes of the study are empirical verification of sparse representation classifier as a text classification tool and a computationally efficient solution for the bottleneck operation of sparse coding. (C) 2019 Elsevi

关键词： Text classification Sparse representation Orthogonal matching pursuit Dictionary

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Simultaneous localisation and mobilisation using image processing

Simultaneous localisation and mobilisation using image proce...

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2019 International Conference on Intelligent Computing and Control systems, ICCS 2019

作者： Sakila, Ms Sahaya v. Narayanan, Abishek Selva, Adithya Sai Khanna, Sabbarish S. Chennai India SRM Institute of Science and Technology Dept. of Computer Science and Engineering Chennai India

ISBN: (纸本)9781538681138

SLAM(Simultaneous Localisation And Mobilisation) is a problem in robotics that revolves around the idea of a robot which can map a location by moving around in a sequential manner. Robot has to move and as well as recognize the path its traversing through by stitching the images into a map. Most models that have been created till now only focuses on small scale indoor applications and do not have a scope for real time usage outside an experimental area. Our project focuses on a large scale approach on the problem that deals with ambiguity of real life scenarios and also additional features like pinpointing its location. Neural networks is used for image processing and mapping and various robotics algorithms are used for the mobilisation of the robot. © 2019 IEEE.

关键词： Mapping

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Hardware Implementation of Floating Point Matrix Inversion Modules on FPGAs

Hardware Implementation of Floating Point Matrix Inversion M...

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International Conference on Microelectronics, ICM

作者： S Chetan J Manikandan v Lekshmi S Sudhakar PES University Bangalore Karnataka ISRO UR Rao Satellite Center (URSC) Bangalore Karnataka

ISBN: (数字)9781728196640

ISBN: (纸本)9781728196657

Matrices are employed for diversified applications such as image processing, control systems, video processing, radar signal processing, compressive sensing and many more. Finding inverse of a floating point large scale matrix is considered to be computationally intensive and their hardware implementation is still a research topic. FPGA implementation of four different floating-point matrix inversion algorithms using a novel combination of high level language programming and model based design is proposed in this paper. The proposed designs can compute inverse of a floating point matrix up to a matrix size of 25×25 and can be easily scaled to large size matrices. The performance evaluation of proposed matrix inversion modules are carried out by their hardware implementation on a Zynq 7000 FPGA based ZED board and the results are reported.

关键词： Computational modeling Signal processing algorithms Programming Hardware Resource management High level languages Field programmable gate arrays

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A secure medical image encryption technique based on DNA cryptography with elliptic curves

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Scientific reports 2025年第1期15卷 20003页

作者： v N Senthil Kumaran T Manikandan Rajesh Kumar Dhanaraj Taher Al-Shehari Nasser A Alsadhan Shitharth Selvarajan Department of Electronics and Communication Engineering SRM Institute of Science and Technology Tiruchirappalli Campus Tiruchirappalli India. Department of Computer Science and Business Systems Rajalakshmi Engineering College Thandalam India. Symbiosis Institute of Computer Studies and Research (SICSR) Symbiosis International (Deemed University) Pune India. Computer Skills Department of Self-Development Skill Common First Year Deanship King Saud University 11362 Riyadh Saudi Arabia. Computer Science Department College of Computer and Information Sciences King Saud University 12372 Riyadh Saudi Arabia. Department of Computer Science Kebri Dehar University 250 Kebri Dehar Ethiopia. ShitharthS@kdu.edu.et. Department of Computer Science and Engineering Chennai Institute of Technology Chennai India. ShitharthS@kdu.edu.et. Centre for Research Impact & Outcome Chitkara University Institute of Engineering and Technology Chitkara University Rajpura Punjab 140401 India. ShitharthS@kdu.edu.et. School of Built Environment Engineering and Computing Leeds Beckett University LS6 3HF Leeds UK. ShitharthS@kdu.edu.et.

Health services and telemedicine have proven to be an important area for information protection in research, especially with medical services and smart health care applications. In these systems, medical imaging protection are important not only for clinical diagnosis, but also to protect the very sensitive and confidential patient data. With progress in imaging technologies and biomedical processing algorithms, the amount of image data increases rapidly. However, securing this information while transferring through insecure channel is still a constant challenge. Existing encryption techniques often face limitations such as high computational complexity, insufficient security against advanced cryptographic attacks, poor reversal and pixel correlation. To overcome these challenges, the proposed approach provides an innovative hybrid encryption technique that integrates DNA cryptography with Elliptical Curve Cryptography (ECC). The DNA-based coding shows high randomness and equality while the ECC provides strong security and confidentiality. The DNA encoding and secure key generation are employed in the proposed technique to obtain the encrypted medical image. The combination of these techniques addresses the main boundaries of existing disadvantage by increasing both security and calculation efficiency, making it well suited for real time medical applications. The experimental analysis was carried out with various parameters like histogram analysis, correlation coefficient, Chi square, MSE, PSNR, entropy etc. The result analysis states that the proposed methodology outperforms the state-of-the-art existing methods with enhanced performance such as entropy of 7.9981, Correlation coefficient of 0.0019 and PSNR of 53.97. Also, the proposed methodology is tested for runtime analysis, memory analysis and security analysis.

关键词： Applied AI Biomedical image encryption DNA encoding Elliptic curve cryptography Secure key generation Security

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Rolling element bearing fault diagnosis using convolutional neural network and vibration image

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COGNITIvE systems RESEARCH 2019年 53卷 42-50页

作者： Hoang, Duy-Tang Kang, Hee-Jun Univ Ulsan Grad Sch Elect Engn Ulsan South Korea Univ Ulsan Sch Elect Engn Ulsan South Korea

Detecting in prior bearing faults is an essential task of machine health monitoring because bearings are the vital components of rotary machines. The performance of traditional intelligent fault diagnosis methods depend on feature extraction of fault signals, which requires signal processing techniques, expert knowledge, and human labor. Recently, deep learning algorithms have been applied widely in machine health monitoring. With the capacity of automatically learning complex features of input data, deep learning architectures have great potential to overcome drawbacks of traditional intelligent fault diagnosis. This paper proposes a method for diagnosing bearing faults based on a deep structure of convolutional neural network. Using vibration signals directly as input data, the proposed method is an automatic fault diagnosis system which does not require any feature extraction techniques and achieves very high accuracy and robustness under noisy environments. (C) 2018 Elsevier B.v. All rights reserved.

关键词： Bearing fault diagnosis Convolutional neural network Deep learning Machine learning

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