Method for motion detecting in the frame and large-sized object identification

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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.

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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

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Supplementary files

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2. Fig. 1. Installation diagram of a complex of two optical measuring devices on a pier

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3. Fig. 2. Large-tonnage sea vessels at various distances from the berth

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4. Fig. 3. Visualization of the brightness of image pixels normalized in the range [0;1]; X, Y – longitudinal and vertical coordinates of pixels

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5. Fig. 4. Visualization in different projections of the brightness of image pixels after applying a rectangular low-pass filter; X, Y – longitudinal and vertical coordinates of pixels

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6. Fig. 5. Visualization in different projections of the brightness of image pixels after applying the threshold transformation; X, Y are the longitudinal and vertical coordinates of the pixels

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7. Fig. 6. Visualization of the difference between two adjacent frames; X, Y – longitudinal and vertical coordinates of pixels

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8. Fig. 7. Visualization of the difference between adjacent frames using the example of ships of different sizes, with different speeds of movement and at different distances from the berth

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9. Fig. 8. Visualization of contour analysis

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10. Fig. 9. Scheme of the algorithm for determining movement in the frame and identifying a large area object. LPF – low-pass filter

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11. Fig. 10. Examples of moving image areas (left) and moving areas potentially belonging to the vessel and its deck structures (right)

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