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5th International Conference on Information Technology and Nanotechnology, ITNT 2019

作者： Denisova, A.Y. Egorova, A.A. Sergeyev, v.v. Samara National Research University Moskovskoe Shosse 34A Samara443086 Russia Image Processing Systems Institute of RAS-Branch of the FSRC Crystallography and Photonics RAS Molodogvardejskaya street 151 Samara443001 Russia

Detection of structural changes in images is one of the important tasks of remote sensing (RS) data thematic analysis. The effective way to solve it is applying the Pyt'ev's morphological projector to the pair of images of the same scene acquired on different dates. The main advantage of this method is its invariance to global brightness transformations, which in the case of RS images correspond to different parameters of the atmosphere or the different values of the brightness-contrast ratio of the scene. However, the classical Pyt'ev's morphological projector and its regularized versions do not take into account the spatial connectivity of image samples. As a result, they ignore the textural features of images. In this article, we suggest the algorithm of structural changes detection based on superpixel segmentation and Pyt'ev's morphological projector that takes into account local characteristics of the image pixels. In the experimental research, we analyzed the accuracies of the proposed and classical Pyt'ev's structural change detection methods using simulated and real RS images. The comparison of two algorithms showed that the proposed method is more robust to the additive white Gaussian noise (AWGN) at different values of signal-To-noise (SNR) ratio. Additionally, the experiments with nonlinear brightness distortions (vignetting) of one of the pair of images demonstrated that the proposed method has lower false positive rates than the classical one. © Published under licence by IOP Publishing Ltd.

关键词： Luminance

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Reducing dimension of parametric space based on the approximation of components for interpolation of multidimensional signals 5

Reducing dimension of parametric space based on the approxim...

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5th International Conference on Information Technology and Nanotechnology, ITNT 2019

作者： Gashnikov, M.v. Samara National Research University Moskovskoe Shosse 34A Samara443086 Russia Image Processing Systems Institute of RAS-Branch of the FSRC Crystallography and Photonics RAS Molodogvardejskaya street 151 Samara443001 Russia

In this paper, we address the problem of parametric space dimension reduction in the interpolation of multidimensional signals task. We develop adaptive parameterized interpolation algorithms for multidimensional signals. We perform a dimension reduction of the parameter space to reduce the complexity of optimizing such algorithms. The dependences of the samples inside the signal sections and between the signal sections are taken into account in various ways to reduce the dimension. We consider the dependencies between the signal sections through the approximation algorithm for the sections. We take into account the sample dependencies inside sections due to an adaptive parameterized interpolation algorithm. As a result, we solve the optimization problem of an adaptive interpolator in the parameter space of lower dimension for each signal section separately. To study the effectiveness of adaptive interpolators, we perform computational experiments using real-world multidimensional signals. Experimental results showed that the proposed interpolator improves the efficiency of the compression method up to 10% compared with the prototype algorithm. © Published under licence by IOP Publishing Ltd.

关键词： Interpolation

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Development of a module for identifying a person by photography to improve the quality of the machine-engineering plant in remote mode

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Journal of Physics: Conference Series 2021年第2期1889卷

作者： D A Shabalina S A Yurkov T v Masharova E K Gerasimova S S Pichugin Department of Digital Technologies in Education Vyatka State University Kirov Russia Department of Criminal Law Procedure and National Security of Vyatka State University Kirov Russia Department of Pedagogy Institute of Pedagogy and Psychology of Education FSEI HE Moscow City Pedagogical University Moscow Russia Department of Informatics Institute of Mathematics and Information Technologies (named after Prof. Nikolay Chervyakov) North Caucasus Federal University Stavropol Russia Department of General Education Academy of Public Administration Moscow Russia

A machine vision performs a variety of face verification tasks in different infrastructure environments. A facial recognition system is technically implemented as an image recognition program. It serves to automatically identify a face in an image, and then identify the person by comparing and analyzing the biometric data of the human face. Cameras are able to capture an image at a distance, which is perfect for building monitoring systems and contactless biometrics. Such software systems are particularly important in the context of remote work of employees of industrial enterprises. The purpose of research is to develop and implement a facial recognition web service for the staff department of a machine-engineering enterprise. The web service should work in conjunction with the existing data bank. Tasks of research are: to consider the fundamental algorithms of facial recognition, to formulate the basic requirements for the development and implementation of the corresponding automated web service. The significant result of research is that the developed module uses library of computer vision algorithms, image processing and general-purpose numerical algorithms with open-source code. Identification system was checked by testing on the company's website.

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Explore the possibilities for objective assessment of some beer quality indicators

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IOP Conference Series: Materials Science and Engineering 2021年第1期1031卷

作者： R Gabrova A Danev v Ganchovska H Andreeva University of Food Technologies Technical Faculty Department of Computer systems and technologies Maritza 26 4000 Plovdiv Bulgaria

The aim of this research is to develop an appropriate experimental setting and to explore the possibilities for objective automatic and express assessment of some appearance indicators of beer quality using computer vision techniques. The goal of the research will be achieved by developing a computer vision system, including a hardware module for obtaining primary information and a software module for processing primary information and extracting the desired characteristics through algorithms based on adapted image processing methods.

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A Modified Ant Colony Optimisation based Optimal Path Finding on a Thematic Map

A Modified Ant Colony Optimisation based Optimal Path Findin...

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2019 IEEE International Conference on Intelligent Techniques in Control, Optimization and Signal processing, INCOS 2019

作者： Sangeetha, v. Sivagami, R. Krishankumar, R. Ravichandran, K.S. Tyagi, Sanjay K. SASTRA Deemed University School of Computing Thanjavur TamilNadu India Higher College of Technology Department of General Studies Fujairah United Arab Emirates

ISBN: (纸本)9781538695425

Increasing demands for unmanned systems and the availability of high resolution satellite images havebeen promoting researchers to contribute innovations to increase the robustness and efficiency of the optimal path planning. An effectively classified satellite image and a robust path planning strategy are highly desirable in finding an optimal path. in this paper, satellite images from ISPRS are classified to identify the traversable areas using a Deep Convolutional Encoder-Decoder architecture-Seg Net and cost map is generated. Using the cost map, Modified Gain based Ant Colony optimization(MGACO) is introduced to find an energy efficient path. The path is finally smoothened using Bezier Spline approximation. MGACO has been compared with up-to-date algorithms and results outperform existing methods in terms of run time and length of the path. © 2019 IEEE.

关键词： Ant colony optimization

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A system for image acquisition and processing operating in the visible and the IR bands 2019

A system for image acquisition and processing operating in t...

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Proceedings of the 13th International Conference on Distributed Smart Cameras

作者： J. A. Leñero-Bardallo J. Bernabéu-Wittel J. Ceballos-Cáceres Á. Rodríguez-vázquez Inst. Microelectrónica de Sevilla (IMSE-CNM) CSIC-Univ. Sevilla (Spain) Hospital Virgen de Rocío Sevilla (Spain)

ISBN: (纸本)9781450371896

This demo displays an autonomous image acquisition and processing system that operates simultaneously with two image sensors either in the visible and the Long Wave Infrared Band (LWIR), inside the Infrared (IR) band. The entire system is controlled a Raspberry Pi board that allows to easily program image processing algorithms to process the images acquired with each sensor. It is a competitive alternative to conventional commercial closed systems with infrared cameras. The proposed imaging system can be easily adapted to different operation scenarios by adding new peripherals, sensors and full custom image processing algorithms.

关键词： image processing IR camera Raspberry Pi Camera interface Multi-spectral imaging

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image steganography using uncorrelated color space and its application for security of visual contents in online social networks

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FUTURE GENERATION COMPUTER systems-THE INTERNATIONAL JOURNAL OF ESCIENCE 2018年 86卷 951-960页

作者： Muhammad, Khan Sajjad, Muhammad Mehmood, Irfan Rho, Seungmin Baika, Sung Wook Sejong Univ Intelligent Media Lab Digital Contents Res Inst Coll Elect & Informat Engn Seoul South Korea Islamia Coll Peshawar Dept Comp Sci Digital Image Proc Lab Peshawar Pakistan Sejong Univ Dept Comp Sci & Engn Seoul South Korea Sungkyul Univ Dept Media Software Anyang South Korea

image steganography is a growing research field, where sensitive contents are embedded in images, keeping their visual quality intact. Researchers have used correlated color space such as RGB, where modification to one channel affects the overall quality of stego-images, hence decreasing its suitability for steganographic algorithms. Therefore, in this paper, we propose an adaptive LSB substitution method using uncorrelated color space, increasing the property of imperceptibility while minimizing the chances of detection by the human vision system. In the proposed scheme, the input image is passed through an image scrambler, resulting in an encrypted image, preserving the privacy of image contents, and then converted to HSv color space for further processing. The secret contents are encrypted using an iterative magic matrix encryption algorithm (IMMEA) for better security, producing the cipher contents. An adaptive LSB substitution method is then used to embed the encrypted data inside the v-plane of HSv color model based on secret key-directed block magic LSB mechanism. The idea of utilizing HSv color space for data hiding is inspired from its properties including de-correlation, cost-effectiveness in processing, better stego image quality, and suitability for steganography as verified by our experiments, compared to other color spaces such as RGB, YCbCr, HSI, and Lab. The quantitative and qualitative experimental results of the proposed framework and its application for addressing the security and privacy of visual contents in online social networks (OSNs), confirm its effectiveness in contrast to state-of-the-art methods. (C) 2016 Elsevier B.v. All rights reserved.

关键词： Information security Online social networks image steganography Security in social networking image and video processing Uncorrelated color space

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Dynamic Approach for Lane Detection using Google Street view and CNN

Dynamic Approach for Lane Detection using Google Street View...

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IEEE Region 10 Conference on Technology, Knowledge, and Society (TENCON)

作者： Mamidala, Rama Sai Uthkota, Uday Shankar, Mahamkali Bhavani Antony, A. Joseph Narasimhadhan, A. v. Natl Inst Technol Mangalore India Dublin City Univ Insight Ctr Data Analyt Dublin Ireland

ISBN: (纸本)9781728118956

Lane detection algorithms have been the key enablers for a fully-assistive and autonomous navigation systems. In this paper, a novel and pragmatic approach for lane detection is proposed using a convolutional neural network (CNN) model based on SegNet encoder-decoder architecture. The encoder block renders low-resolution feature maps of the input and the decoder block provides pixel-wise classification from the feature maps. The proposed model has been trained over 2000 image data-set and tested against their corresponding ground truth provided in the data-set for evaluation. To enable real-time navigation, we extend our model's predictions interfacing it with the existing Google APIs evaluating the metrics of the model tuning the hyper-parameters. The novelty of this approach lies in the integration of existing segnet architecture with google APIs. This interface makes it handy for assistive robotic systems. The observed results show that the proposed method is robust under challenging occlusion conditions due to pre-processing involved and gives superior performance when compared to the existing methods.

关键词： Lane detection Autonomous navigation Convolutional neural network SegNet architecture Pixel-wise classification Semantic-segmentation Google API's Real-time navigation

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Real Time image processing on FPGAs: A THESIS SUBMITTED TO THE UNIvERSITY OF LIvERPOOL FOR THE DEGREE OF DOCTOR OF PHILOSOPHY IN THE FACULTY OF SCIENCE AND ENGINEERING

Real Time Image Processing on FPGAs: A THESIS SUBMITTED TO T...

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作者： Shaonan Zhang University of Liverpool

学位级别：博士

In recent years, due to improvements in semiconductor technology, FPGA devices and embedded systems have both been gaining popularity in numerous areas, from vehicle-mounted systems to the latest iPhones. Recently, as Intel (Altera) and Xilinx both released their new generations of ARM A9 processor integrated FPGAs, they have become very popular platforms which combine the hardware features of an FPGA and an embedded systems software's flexibility. This makes it suitable platforms to apply complex algorithms for real time processing of video images. Feature tracking is a popular topic in image processing and usually includes one or more pre-processing methods such as corner detection, colour segmentation, etc. that could be undertaken on the FPGA with little latency. After the pre-processing, complex post-processing algorithms running on the ARM processors, that use the results from the pre-processing, can be implemented in the embedded systems. The research described in this thesis investigated the use of low cost FPGASoC devices for real time image processing by developing a real-time image processing system with several methods for implementing the pre-processing algorithms within the FPGA. The thesis also provides the details of an embedded Linux based FPGASoC design and introduces the OpenCv library and demonstrates the use of OpenCv co-processing with the FPGA. The tested system used a low cost FPGASoC board, the DE1-SOC, which is manufactured by Terasic Inc. As a platform which contains a Cyclone v FPGA designed by Intel with a dual-core ARM A9 processor, the application developed is based on a customized OpenCv programme running on the ARM processors and concurrently receives the pre-processing result processed by the FPGA. With the FPGA acceleration, the developed system outperforms a software-only system by reducing the total processing time by 48.2%, 49.5% and 56.1% at resolutions of 640x480, 800x600 and 1024x768 separately. This reduction in processing t

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Exploring DNS, HTTP, and ICMP Response Time Computations on Brain Signal/image Databases using a Packet Sniffer Tool

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IEEE ACCESS 2018年 6卷 59672-59678页

作者： Elamaran, v Arunkumar, N. Babu, G. venkat Balaji, v. S. Gomez, Jorge Figueroa, Cristhian Ramirez-Gonzalez, Gustavo SASTRA Deemed Univ Sch EEE Thanjavur 61341 India Univ Cordoba Syst Dept Cordoba 14071 Colombia Univ Cauca Telemat Dept Popayan 190001 Colombia

Neurological signal processing is of significance not only the physiologist doing research and the clinician investigating patients but also to the biomedical engineer who is needed to collect, process, and interpret the physiological signals by prototyping systems and algorithms for their manipulations. While it is a fact that there does hold immense stuff (material) on the subject of digital neurological signal processing, however, it is dispersed in various scientific, technological, and physiological journals, databases also in various international conference proceedings. Consequently, it is a quite hard, more time-consuming, and often tiresome job, especially to the stranger to the domain Hence, this study concentrates on how much time would require to access the databases belong to the brain signal/image collections, neurological signals, etc. The sixteen US-based Servers, ten UK-based Servers, and the five Servers from other countries are included in this study. Mainly, the domain name system, hyper text transfer protocol, and the Internet control message protocol query/response times are analyzed using a popular packet sniffer called Wireshark.

关键词： Brain signal/image DNS HTTP ICMP packet sniffer Wireshark

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