scholarly journals A Face Image Virtualization Mechanism for Privacy Intrusion Prevention in Healthcare Video Surveillance Systems

Symmetry ◽  
2020 ◽  
Vol 12 (6) ◽  
pp. 891 ◽  
Author(s):  
Jinsu Kim ◽  
Namje Park
Keyword(s):  
Video Surveillance ◽  
Visual Information ◽  
Face Image ◽  
Video Data ◽  
Surveillance Systems ◽  
Image Information ◽  
Video Information ◽  
Face Area ◽  
Blockchain Technology ◽  
Wide Range

Closed-circuit television (CCTV) and video surveillance systems (VSSs) are becoming increasingly more common each year to help prevent incidents/accidents and ensure the security of public places and facilities. The increased presence of VSS is also increasing the number of per capita exposures to CCTV cameras. To help protect the privacy of the exposed objects, attention is being drawn to technologies that utilize intelligent video surveillance systems (IVSSs). IVSSs execute a wide range of surveillance duties—from simple identification of objects in the recorded video data, to understanding and identifying the behavioral patterns of objects and the situations at the incident/accident scenes, as well as the processing of video information to protect the privacy of the recorded objects against leakage. Besides, the recorded privacy information is encrypted and recorded using blockchain technology to prevent forgery of the image. The technology herein proposed (the “proposed mechanism”) is implemented to a VSS, where the mechanism converts the original visual information recorded on a VSS into a similarly constructed image information, so that the original information can be protected against leakage. The face area extracted from the image information is recorded in a separate database, allowing the creation of a restored image that is in perfect symmetry with the original image for images with virtualized face areas. Specifically, the main section of this study proposes an image modification mechanism that inserts a virtual face image that closely matches a predetermined similarity and uses a blockchain as the storage area.

scholarly journals Algorithms for selecting the outlines of objects images in intellectual video surveillance systems

Connectivity ◽  
2020 ◽  
Vol 146 (5) ◽  
Author(s):  
L. P. Kriuchkova ◽  
◽  
V. I. Strelnikov ◽  
M. V. Akulinicheva ◽  
O. S. Bortnyk ◽  
...  
Keyword(s):  
Real Time ◽  
Video Surveillance ◽  
Intelligent Systems ◽  
Surveillance Systems ◽  
Contour Analysis ◽  
Space Length ◽  
Intelligent Video Surveillance ◽  
Video Information ◽  
Wide Range ◽  
Selection Of

Intensive development of means of receiving and transmitting digital images creates the problem of processing huge amounts of video information flows. There is a wide range of tasks in which images are considered as a source of information on the basis of which it is necessary to make a decision. Important tasks to be solved by intelligent video surveillance systems are: identification of objects and determination of their trajectories; measuring the speed of objects; detection of alarming events in the tasks of object-territorial protection in real time. One of the main operations in intelligent video surveillance systems in image processing for further analysis is the selection of contours of images of objects, because the contour contains all the necessary information to recognize objects by their shape. This approach allows you to not consider the internal points of the image and, thus, significantly reduce the amount of information processed. This makes it possible to analyze images in real time. Contour analysis is a set of methods for selecting, describing and processing image contours that allows you to describe, store, compare and search for objects presented in the form of their external contours, as well as effectively solve the main problems of pattern recognition — transfer, rotate and zoom image of the object. In this case, the contour means a space-length gap, difference or abrupt change in brightness values. The purpose of the publication is to consider the algorithms for selecting the contours of images of objects in the problems of detecting alarming events by intelligent video surveillance systems. The problem of selection of contours of images of objects in problems of detection of disturbing events by intelligent systems of video surveillance is considered. In order to improve the basic characteristics of intelligent video surveillance systems, algorithms for contouring images of objects are proposed to ensure the detection of four types of alarming events: the appearance and presence of the object in the surveillance zone, moving the object in the forbidden direction, leaving the object and overturning the object.

An Intelligent Traffic Engineering Method over Software Defined Networks for Video Surveillance Systems Based on Artificial Bee Colony

2016 ◽  
Vol 12 (4) ◽  
pp. 45-62 ◽  
Author(s):  
Reza Mohammadi ◽  
Reza Javidan
Keyword(s):  
Video Surveillance ◽  
Traffic Engineering ◽  
Surveillance System ◽  
Artificial Bee Colony ◽  
Heuristic Algorithms ◽  
Optimal Solution ◽  
Video Data ◽  
Surveillance Systems ◽  
Bee Colony

In applications such as video surveillance systems, cameras transmit video data streams through network in which quality of received video should be assured. Traditional IP based networks cannot guarantee the required Quality of Service (QoS) for such applications. Nowadays, Software Defined Network (SDN) is a popular technology, which assists network management using computer programs. In this paper, a new SDN-based video surveillance system infrastructure is proposed to apply desire traffic engineering for practical video surveillance applications. To keep the quality of received videos adaptively, usually Constraint Shortest Path (CSP) problem is used which is a NP-complete problem. Hence, heuristic algorithms are suitable candidate for solving such problem. This paper models streaming video data on a surveillance system as a CSP problem, and proposes an artificial bee colony (ABC) algorithm to find optimal solution to manage the network adaptively and guarantee the required QoS. The simulation results show the effectiveness of the proposed method in terms of QoS metrics.

scholarly journals A novel performance evaluation paradigm for automated video surveillance systems

2011 ◽  
Vol 1 (4) ◽  
Author(s):  
Chung-Hao Chen ◽  
Yi Yao ◽  
Andreas Koschan ◽  
Mongi Abidi
Keyword(s):  
Performance Evaluation ◽  
Video Surveillance ◽  
Tracking System ◽  
Failure Process ◽  
Algorithm Design ◽  
Video Tracking ◽  
Surveillance Systems ◽  
System Failures ◽  
Wide Range ◽  
Automated Video Surveillance

AbstractMost existing performance evaluation methods concentrate on defining various metrics over a wide range of conditions and generating standard benchmarking video sequences to examine the effectiveness of a video tracking system. It is a common practice to incorporate a robustness margin or factor into the system/algorithm design. However, these methods, deterministic approaches, often lead to overdesign, thus increasing costs, or underdesign, causing frequent system failures. In order to overcome the aforementioned limitations, we propose an alternative framework to analyze the physics of the failure process via the concept of reliability. In comparison with existing approaches where system performance is evaluated based on a given benchmarking sequence, the advantage of our proposed framework lies in that a unified and statistical index is used to evaluate the performance of an automated video surveillance system independent of input sequences. Meanwhile, based on our proposed framework, the uncertainty problem of a failure process caused by the system’s complexity, imprecise measurements of the relevant physical constants and variables, and the indeterminate nature of future events can be addressed accordingly.

Design and Implementation of a Prototype Cloud Video Surveillance System

2014 ◽  
Vol 18 (1) ◽  
pp. 40-47 ◽  
Author(s):  
Yong-Hua Xiong ◽  
◽  
Shao-Yun Wan ◽  
Yong He ◽  
Dan Su
Keyword(s):  
Cloud Computing ◽  
Video Surveillance ◽  
Surveillance System ◽  
Distributed Storage ◽  
Video Data ◽  
Video Surveillance System ◽  
Surveillance Systems ◽  
Campus Network ◽  
Design And Implementation ◽  
Cloud Computing Service

Cloud-based video surveillance systems, as a new cloud computing service model, are an emerging research topic, both at home and abroad. Current research is mainly focused on exploring applications of the system. This paper proposes a design and implementation method for cloud-based video surveillance systems using the characteristics of cloud computing, such as parallel computing, large storage space, and easy expandability. The system architecture and function modules are built, and a prototype cloud-based video surveillance system is established in a campus network using key technologies, including virtual machine task access control, video-data distributed storage, and database-active communicationmethods. Using the system, the user is able to place a webcam in a location that requires monitoring so that video surveillance can be achieved, and video data can be viewed through a browser. The system has the following advantages: low investment and maintenance cost, high portability, easily extendable, superior data security, and excellent sharing. As a private cloud server in the campus network, the system is able to not only provide convenient video surveillance services, but it can also be an excellent practical experimental platform for cloud computing-related research, which carries outstanding application value.

scholarly journals Development of a Method of Terahertz Intelligent Video Surveillance Based on the Semantic Fusion of Terahertz and 3D Video Images

2019 ◽  
pp. 134-143 ◽  
Author(s):  
A A Morozov ◽  
O S Sushkova ◽  
I A Kershner ◽  
A F Polupanov
Keyword(s):  
Video Surveillance ◽  
First Generation ◽  
Semantic Content ◽  
3D Video ◽  
Video Data ◽  
The Body ◽  
Video Image ◽  
Surveillance Systems ◽  
Public Places ◽  
Video Images

The terahertz video surveillance opens up new unique opportunities in the field of security in public places, as it allows to detect and thus to prevent usage of hidden weapons and other dangerous items. Although the first generation of terahertz video surveillance systems has already been created and is available on the security systems market, it has not yet found wide application. The main reason for this is in that the existing methods for analyzing terahertz images are not capable of providing hidden and fully-automatic recognition of weapons and other dangerous objects and can only be used under the control of a specially trained operator. As a result, the terahertz video surveillance appears to be more expensive and less efficient in comparison with the standard approach based on the organizing security perimeters and manual inspection of the visitors. In the paper, the problem of the development of a method of automatic analysis of the terahertz video images is considered. As a basis for this method, it is proposed to use the semantic fusion of video images obtained using different physical principles, the idea of which is in that the semantic content of one video image is used to control the processing and analysis of another video image. For example, the information about 3D coordinates of the body, arms, and legs of a person can be used for analysis and proper interpretation of color areas observed on a terahertz video image. Special means of the object-oriented logic programming are developed for the implementation of the semantic fusion of the video data, including special built-in classes of the Actor Prolog logic language for acquisition, processing, and analysis of video data in the visible, infrared, and terahertz ranges as well as 3D video data.

Special Issue on Visual Inspection

1993 ◽  
Vol 5 (2) ◽  
pp. 87-87
Author(s):  
Masanori Idesawa ◽  
Keyword(s):  
Visual Function ◽  
Information Acquisition ◽  
Visual Information ◽  
Visual Inspection ◽  
Image Sensor ◽  
Human Vision ◽  
Sensor Technology ◽  
Special Issue ◽  
Image Information ◽  
Wide Range

We acquire more than 60 percent of information from our activity environment through our visual sense. The visual sense allows us to collect information about an object from a position away from it without exerting any effects it such as constraining its motion. Visual information acquisition plays a very important role in the industrial field including visual appearance inspection and various other monitoring. A field called machine vision or computer vision has been formed, it is related to the artificial realization and application of the visual function and is now under aggressive study. Inspection using the visual sense, so-called visual inspection, is extremely important; and its automation has been studied for a long time. However, many problems remain to be solved; and in many cases, this operation must rely on human vision. In order to realize the visual function from an engineering point of view, there are many demands for the development of an image sensor that acquires visual information as image information, a method that processes and recognizes image information, and a method that integrates the observation control system allowing processed image information to be systematically organized and the operation to be checked. In consideration of long-term vision as stated above, this special issue provides a description of sensor technology for image information acquisition in the visual inspection process as well as the neural network processing method which is expected as a flexible method for image processing and recognition. For robot sensors, an active method is used to simplify the recognition process, which projects a special light on an object for measurement. This issue includes the topics covering the development of sensors, aiming at their downsizing and high performance. The human visual sense may function by two operating modes: the monitoring mode that senses an unusual situation appearing in the view field and the attention mode that provides detailed analysis of the situation in this area. The former is permitted to have a low detecting, accuracy, but it requires a wide detectable range. The latter is permitted to have a narrow sensing range, but it requires a high sensing accuracy. In other words, multi-resolution sensing operations are performed in the human visual sense. It is desirable for robot sensors to perform the multi-resolution operations that enable coarse sensing to be realized in a wide range and high-accuracy sensing in the attentive area. This issue also includes the development of these sensors. The appearance inspection of welded boats and the recognition of vehicle numbers have been put to practical use, and these topics are also described in this issue. In some cases, techniques visual information processing can make visible to us those that can not be seen by our visual system. This can be thought as an extension of the visual function and the level of sight is very interesting.

scholarly journals VIDEO SURVEILLANCE SYSTEMS FOR RAILWAY TRANSPORT

2020 ◽  
Vol 17 (5) ◽  
pp. 298-314
Author(s):  
M. R. Ivashevsky
Keyword(s):  
Video Surveillance ◽  
Traffic Safety ◽  
Data Transmission ◽  
Surveillance Systems ◽  
Video Signals ◽  
Video Information ◽  
Advantages And Disadvantages ◽  
Intelligent Video Surveillance System ◽  
Train Driver ◽  
Data Transmission System

The article is devoted to analysis of ways to increase train traffic safety. One of ways to reduce accident rate on railways is timely detection of dangerous objects and notification of all traffic participants, primarily, the driver. Such a notification can be performed with the help of intelligent video surveillance system (IVS). The objective of the article is to study the possibility of using IVS to increase train traffic safety. Method (way to achieve the objective) consists of several stages: development of criteria of compliance of functional possibilities of IVS with tasks to increase train traffic safety, assessment, and calculation of permissible values of fitting criteria. The work suggests a scheme of organization of IVS based on fiber-optic data transmission system (FOTS) and data transmission network, highlights advantages and disadvantages of IVS, formulates requirements for IVS. Advantage of video surveillance is availability of video information about an object to a train driver, which allows to timely prevent an accident. Disadvantage of IVS is high probability of false detection, which can lead to false triggering of a system. To reduce the number of false triggering there are two ways: improvement of algorithms of video analytics in recognition device (RD) and increase of quality of video signals at the input of RD. The work is devoted to reduction of probability of false triggering due to improvement of communication quality. It is noted that an efficient method is the use of a new element base of electronics based on nanostructured materials. These materials allow to improve optoelectronic characteristics of main elements of IVS which are photosensors and photoreceivers.

scholarly journals Real-time marine vessel surveillance video system

2021 ◽  
pp. 98-105
Author(s):  
Ш.С. Фахми ◽  
С.А. Селиверстов ◽  
Е.В. Костикова ◽  
Р.Р. Муксимова ◽  
В.О. Титов
Keyword(s):  
Video Surveillance ◽  
Video Processing ◽  
Image Sensor ◽  
Surveillance Systems ◽  
Processing Unit ◽  
Desktop Computer ◽  
Smart Cameras ◽  
Video Information ◽  
Observation Systems ◽  
High Level

Анализируется процесс развития систем наблюдения. Раскрываются особенности технологических изменений систем наблюдения 1-го, 2-го и 3-го поколений. Декларируется, что современные полупроводниковые технологии позволяют перейти к более развитым системам видеонаблюдения 3-го поколения, где преобразование и обработка видеоинформации выполняются непосредственно в видеодатчиках на этапе формирования кадров. Умные камеры расширяют функциональность видеосенсора 3-го поколения, обеспечивая бортовую высокоуровневую обработку видео. Рассмотрены эволюция систем наблюдения и архитектура обработки видеоинформации с использованием интеллектуальных видеокамер с высоким динамическим диапазоном. Представлена графическая интерпретация, иллюстрирующая процесс эволюции систем видеонаблюдения от 1-го к 3-му поколению. Проанализированы функции современных систем видеонаблюдения и переход от высокоуровневой обработки видео из систем общего назначения во встраиваемые системы. Рассмотрен состав видеосистемы наблюдения с использованием интеллектуальной видеокамеры, включающий видеодатчик, блок обработки и блок управления связи. Описаны условия в которых морские системы видеонаблюдения используются. Приведены результаты экспериментальных исследований и выполнены оценки производительности. Показаны достигнутые результаты производительности для различных реализаций алгоритма обнаружения морских судов и необходимое время выполнения при обработке одного изображения с полным разрешением на стандартном настольном компьютере Pentium 4 с частотой 2,4 ГГц. с использованием реконфигурируемой системой на кристалле. The process of development of observation systems is analyzed. The features of technological changes in observation systems of the 1st, 2nd and 3rd generations are revealed. It is declared that modern semiconductor technologies make it possible to move to more advanced third-generation video surveillance systems, where the conversion and processing of video information is performed directly in video sensors at the stage of framing. Smart cameras extend the functionality of the 3rd generation image sensor to provide on-board high-level video processing. The evolution of surveillance systems and architecture of video information processing using smart cameras with a high dynamic range are considered. A graphical interpretation is presented that illustrates the evolution of video surveillance systems from the 1st to the 3rd generation. The functions of modern video surveillance systems and the transition from high-level video processing from general-purpose systems to embedded systems are analyzed. The composition of a video surveillance system using an intelligent camera is considered, including a video sensor, a processing unit and a communication control unit. The conditions in which marine video surveillance systems are used are described. The results of experimental studies are presented and performance estimates are performed. Shown are the achieved performance results for various implementations of the ship detection algorithm and the required execution time when processing one full resolution image on a standard Pentium 4 desktop computer running at 2.4 GHz. using a reconfigurable system on a chip.

scholarly journals DEVELOPMENT OF AN ADVANCED METHOD OF VIDEO INFORMATION RESOURCE COMPRESSION IN NAVIGATION AND TRAFFIC CONTROL SYSTEMS

2020 ◽  
Vol 5 ◽  
pp. 31-42
Author(s):  
Serhii Yevseiev ◽  
Ahmed Abdalla ◽  
Serhii Osiievskyi ◽  
Volodymyr Larin ◽  
Mykhailo Lytvynenko
Keyword(s):  
Video Compression ◽  
Communication Systems ◽  
Information Technologies ◽  
Video Data ◽  
Information Resource ◽  
Specific Information ◽  
Surveillance Systems ◽  
Information Compression ◽  
Video Information ◽  
Onboard Equipment

The Earth's aerospace monitoring (ASM) systems use state-of-the-art integrated information technologies that include radio-based detection and surveillance systems using telecommunications. One of the main tasks of ASM systems is to increase the efficiency of decision-making necessary for the timely prevention, detection, localization and elimination of crisis situations and their probable consequences. Modern conditions impose stricter requirements for efficiency, reliability and quality of the provided video data. To ensure compliance with the requirements, it is necessary to provide the appropriate capabilities of the onboard equipment. On the basis of the existing information and communication systems it is necessary to carry out: continuous or periodic assessment of a condition of objects of supervision and control; continuous (operational) collection, reception, transmission, processing, analysis and display of information resources. It is proposed to use UAVs (unmanned aerial vehicles) as a means to perform ASM tasks. The time of organizing communication sessions and delivery of information should vary from a few seconds to 2.5 hours. Untimely processing and delivery of a specific information resource in the management process leads to its obsolescence or loss of relevance, which contributes to erroneous decisions. One way to reduce time is to encode the data. To do this, it is proposed to use video compression algorithms. However, based on the analysis of the possibility of modern methods of video information compression, taking into account the specifics of the onboard equipment of the UAV, the coding problem is not completely solved. The research results show the expediency of using an improved method of video information compression to reduce the computing resources of the software and hardware complex of the onboard UAV equipment and to ensure the requirements for efficiency and reliability of data in modern threats to ASM systems as a whole.

scholarly journals Artificial Intelligence and Deep Learning for Weapon Identification in Security Systems

2021 ◽  
Vol 2089 (1) ◽  
pp. 012079
Author(s):  
Makkena Brahmaiah ◽  
Srinivasa Rao Madala ◽  
Ch Mastan Chowdary
Keyword(s):  
Artificial Intelligence ◽  
Computer Vision ◽  
Deep Learning ◽  
Video Surveillance ◽  
Real World ◽  
Crime Rates ◽  
Surveillance Systems ◽  
Security Systems ◽  
Trade Off ◽  
Wide Range

Abstract As crime rates rise at large events and possibly lonely places, security is always a top concern in every field. A wide range of issues may be solved with the use of computer vision, including anomalous detection and monitoring. Intelligence monitoring is becoming more dependent on video surveillance systems that can recognise and analyse scene and anomaly occurrences. Using SSD and Faster RCNN techniques, this paper provides automated gun (or weapon) identification. Use of two different kinds of datasets is included in the proposed approach. As opposed to the first dataset, the second one comprises pictures that have been manually tagged. However, the trade-off between speed and precision in real-world situations determines whether or not each method will be useful.

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