A new algorithm for detecting and separating marine objects from the background in surveillance systems

被引:2
|
作者
Fahmi, Shakeeb S. [1 ,2 ]
Korolev, Oleg A. [1 ]
Borodina, Olga, V [1 ]
机构
[1] Russian Acad Sci, Solomenko Inst Transport Problems, St Petersburg, Russia
[2] St Petersburg Electrotech Univ LETI, St Petersburg, Russia
来源
关键词
image analysis; artificial vision systems; silhouette; sea transport object; polygonal-recursive method; image pyramid;
D O I
10.37220/MIT.2022.57.3.033
中图分类号
U6 [水路运输]; P75 [海洋工程];
学科分类号
0814 ; 081505 ; 0824 ; 082401 ;
摘要
The main problems in the construction of artificial vision systems in the field of maritime transport are the development and implementation of effective algorithms for the semantic analysis of events unfolding at the scene of events, which allow taking into account the influence of external and internal factors in the process of recognizing the silhouette of an object of study. In this case, the external factors include external illumination, the movement of a marine object, its various external features and properties, and the internal factors include the speed of image signal processing and the computational complexity of the observation system. The main task in the field of detection and recognition of images of marine objects is to identify and separate the object of interest from the background in images under conditions of noise and interference. The paper proposes a new method for detecting and separating objects of maritime transport from the background based on a structured representation of the image pyramid obtained as a result of polygonal-recursive partitioning into polygons of various shapes and sizes. The article presents the results of modeling the proposed method, tested using various video streams, and the estimation of the speed of detection of objects of maritime transport with its help, as well as the results of its work in comparison with already known approaches.
引用
收藏
页码:256 / 264
页数:9
相关论文
共 50 条
  • [21] Two-threshold algorithm for detecting point objects from stereo images
    Kirichuk V.S.
    Shakenov A.K.
    Optoelectronics, Instrumentation and Data Processing, 2014, 50 (06) : 577 - 581
  • [22] Detecting moving objects from dynamic background combining subspace learning with mixed norm approach
    Lu, Yuqiu
    Liu, Jingjing
    Liu, Wang
    Ma, Shiwei
    Xiu, Xianchao
    Liu, Wanquan
    Chen, Hui
    MULTIMEDIA TOOLS AND APPLICATIONS, 2020, 79 (25-26) : 18747 - 18766
  • [23] Detecting moving objects from dynamic background combining subspace learning with mixed norm approach
    Yuqiu Lu
    Jingjing Liu
    Wang Liu
    Shiwei Ma
    Xianchao Xiu
    Wanquan Liu
    Hui Chen
    Multimedia Tools and Applications, 2020, 79 : 18747 - 18766
  • [24] New algorithm of detecting optical surface imperfection based on background correction and image segmentation
    Zhang B.
    Ni K.
    Wang L.
    Liu S.
    Wu L.
    Liu, Shijie (shijieliu@siom.ac.cn), 1600, Chinese Optical Society (36):
  • [25] Detecting Abnormal Activities from Multi-Sensor Surveillance Systems
    Maatta, Marko
    Keranen, Janne
    Raty, Tomi
    Nieminen, Mikko
    2012 INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION AND INFORMATION SCIENCES (ICCAIS), 2012, : 30 - 35
  • [26] Cognitive transport video systems: a new approach in segmentation of marine objects images
    Shatalova, Natalia, V
    Fahmi, Shakeeb S.
    Kostikova, Elena, V
    Borodina, Olga, V
    MARINE INTELLECTUAL TECHNOLOGIES, 2022, (04): : 208 - 214
  • [27] A novel approach of combining temporal segmentation results to the region binding process for separating moving objects from still background
    Liu, TM
    Qi, FH
    Zhan, YQ
    VISUAL COMMUNICATIONS AND IMAGE PROCESSING 2000, PTS 1-3, 2000, 4067 : 1066 - 1073
  • [28] Observation-Prejudged Algorithm of Space-Based Observation Systems-of-Systems for Moving Marine Objects
    Lun W.
    Li Q.
    Zhu Z.
    Xiao G.
    Zhang C.
    Tianjin Daxue Xuebao (Ziran Kexue yu Gongcheng Jishu Ban)/Journal of Tianjin University Science and Technology, 2021, 54 (10): : 1086 - 1093
  • [29] Detecting moving objects from a video taken by a moving camera using sequential inference of background images
    Setyawan, F. X. Arinto
    Tan, Joo Kooi
    Kim, Hyoungseop
    Ishikawa, Seiji
    ARTIFICIAL LIFE AND ROBOTICS, 2014, 19 (03) : 291 - 298
  • [30] A new small device made of glass for separating microplastics from marine and freshwater sediments
    Nakajima, Ryota
    Tsuchiya, Masashi
    Lindsay, Dhugal J.
    Kitahashi, Tomo
    Fujikura, Katsunori
    Fukushima, Tomohiko
    PEERJ, 2019, 7