Email this article 
Method for motion detecting in the frame and large-sized object identification
- Authors: Lopatina V.V.1
-
Affiliations:
- Federal Research Center “Computer Science and Control,” Russian Academy of Sciences
- Issue: No 4 (2024)
- Pages: 139-147
- Section: ARTIFICIAL INTELLIGENCE
- URL: https://kazanmedjournal.ru/0002-3388/article/view/676403
- DOI: https://doi.org/10.31857/S0002338824040097
- EDN: https://elibrary.ru/UDYVBJ
- ID: 676403
Cite item
Open Access
Access granted
Abstract
A method for motion detecting in a frame and large-sized object identification is described in the article. The use-case of the method is illustrated by the example from the maritime transport industry. The example shows the solution of the task of monitoring the position of an autonomous marine large-tonnage ship relative to the berth when performing loading and unloading operations and mooring operations. The paper incudes description of the structure of a measuring complex which includes optical meters. An operating principle of the complex is based on the method of motion detecting in a frame and large-sized object identification. A diagram of the algorithm for motion detecting in the frame and large-sized object identification is presented in the paper. The performance of the software implementation of the algorithm for motion detecting in the frame and large-sized object identification has been assessed in the article.
Full Text
About the authors
V. V. Lopatina
Federal Research Center “Computer Science and Control,” Russian Academy of Sciences
Author for correspondence.
Email: int00h@mail.ru
Russian Federation, Moscow
References
- Poujouly S., Journet B. A Twofold Modulation Frequency Laser Range Finder // J. Optics A: Pure and Applied Optics. 2002. № 4. P. 356–363.
- Zheng X.Y., Zhao C., Zhang H.Y., Zheng Z., Yang H.Z. Coherent Dual-frequency Lidar System Design for Distance and Speed Measurements // Intern. Conf. on Optical Instruments and Technology: Advanced Laser Technology and Applications. International Society for Optics and Photonics. Beijing, China, 2018. V. 10619.
- Jia F.X., Yu J.Y., Ding Z.L., Yuan F. Research on Real-time Laser Range Finding System // Applied Mechanics and Materials. 2013. V. 347.
- Beraldin J.A., Steenaart W. Overflow Analysis of a Fixed-Point Implementation of the Goertzel Algorithm // IEEE Transactions on Circuits and Systems. 1989. V. 36. № 2. P. 322–324.
- Finlayson D.M., Sinclair B. Advances in Lasers and Applications // Boca Raton, Florida, USA. CRC Press, 1998. P. 346.
- Lopatina V.V. Method of Fragment Based Tracking of Displacement of a Large Areal Object in Images // J. Phys.: Conf. Ser. 2021. V. 2061. P. 012113. https://doi.org/10.1088/1742-6596/2061/1/012113.
- Suzuki S., Keiichi A. Topological Structural Analysis of Digitized Binary Images by Border Following // Comput. Vis. Graph. Image Process. 1985. V. 30. P. 32–46.
- OpenCV 4.7.0. Open Source Computer Vision Library, 2022.
- ГОСТ Р 8.1030-2024.
- Lucas B.D., Kanade T. An Iterative Image Registration Technique with an Application to Stereo Vision // Intern. Joint Conf. on Artificial Intelligence. Vancouver, B.C., Canada, 1981.
- Farnebäck G. Two-Frame Motion Estimation Based on Polynomial Expansion // Image Analysis (SCIA). Lecture Notes in Computer Science, Eds J. Bigun, T. Gustavsson. Berlin, Heidelberg: Springer, 2003. V. 2749.
- Jain A., Murty M., Flynn P. Data Clustering: A Review // ACM Computing Surveys. 1999. V. 31. P. 264–323.
- Otsu N. A Threshold Selection Method from Gray-level Histograms // IEEE Trans. Sys., Man., Cyber. J. 1979. V. 9. P. 62–66.
- Гонсалес Р., Вудс Р. Цифровая обработка изображений. Изд. 3-е, исправ. и доп. М.: Техносфера, 2019. 1104 с. ISBN 978-5-94836-331-8.
Supplementary files
