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Scientific and technical journal established by OSTU. Media registration number: ПИ № ФС77-75780 dated May 23, 2019. ISSN: 2220-4245. Subscription index in the online catalog «Subscription Press» (www.akc.ru): E28002. Subscription to the electronic version is available on the «Rucont» platform.
The journal is included in the Russian Science Citation Index and in the List of Russian Scientific Journals .

Search results

  • V.1(25), 2016
    70-76

    Application algorithms of computer vision for оbject detection on the railway crossing

    Development of innovative methods and hardware gives additional opportunities for the solution of various tasks. For example, innovations allow increasing safety in places of crossing highways and railroads by means of detection methods of objects in the required control zone. The big risk of emergencies in places as a railway crossing is caused by a high speed and the inertial movement of the train. In this connection, there is no possibility of timely braking of the train and prevention of collision with an obstacle. At the present time, the biggest percent of accident rate belongs to uncontrollable railway crossings. On such railway crossings completely are absent the blocking means or the warning technical tools. Controlled railway crossings are equipped with the blocking means for the automobiles. Also, they are equipped with the systems of video supervision. But the current systems of video supervision have no function of informing the driver of the train in an emergency. Therefore, to priorities belongs development of technical requirements for a hardware and software system. The automatic analysis of a dynamic situation in borders of a railway crossing, transfer to the driver of the approaching train of the required information belongs to priorities too. This work describes briefly main algorithms of computer vision which allow distinguishing any object on a railway crossing. The example of algorithmic modeling of detection of contours and allocation of a background on video has been considered in this work. Received results led to the conclusion about a necessary adaptation of modern computer vision algorithms for the solution of a detection problem of various objects with the required accuracy and in various working conditions.
  • V.1(21), 2015
    74-80

    Improvement of methods of «background subtraction» for searching moving objects at railway crossings through computer vision

    This article describes the approaches to extract from the video sequence of areas relating to movable objects, which may cause a dangerous situation at a railway crossing. The proposed approach will improve the quality of the mobile object allocation, which will reduce the time image processing to identify moving objects in order to determine the degree of risk. To assess the quality of algorithms was develop a software product and simulated motion capture.
  • V.3(23), 2015
    85-94

    Application of cluster technology for development of systems of video surveillance and video registration on territorially the distributed objects of railway transport

    Is executed the analysis of the special features of the territorially distributed objects of rail transport for developing the systems of video surveillance and video registration. Is proposed the three-stage design procedure of such systems, at basis of which lies the separation of entire system into the zones of video surveillance, zones of video registration and the information clusters, which ensure the optimization of system on the criterion of minimum expenditures.
  • V.3(27), 2016
    99-110

    Composition of the mathematical methods of programming for the optimization of the systems of video registration in the territorially distributed objects of rail transport

    Is executed the analysis of the special features of the process of the optimization of the complex systems of video surveillance and video registration in the territorially distributed objects of rail transport. Is proposed the procedure of setting optimization problem during the local level for the group of adjacent clusters into supers-clusters and the step-by-step optimization of entire system at the global level. The procedure of two-level optimization and the association of the adjacent information clusters of system into the supers-cluster make it possible to combine the methods of linear and dynamic programming for the optimization of the complex branched systems on the criterion of minimum expenditures.