Automatic extraction method of damage point of laser weapon

Jiaowei Shi; Shiyan Sun; Jun Xie; Lin Li

doi:10.1117/12.2635396

6 May 2022 Automatic extraction method of damage point of laser weapon

Jiaowei Shi, Shiyan Sun, Jun Xie, Lin Li

Proceedings Volume 12256, International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2022); 122560U (2022) https://doi.org/10.1117/12.2635396
Event: 2022 International Conference on Electronic Information Engineering, Big Data and Computer Technology, 2022, Sanya, China

Abstract

In the face of increasingly severe air target threats, laser weapons have the advantages of fast attack speed, flexible steering, precision strikes and immunity from electromagnetic interference. They are new concept weapons that are developed by the navies of various countries. At present, laser weapons strike targets, relying on manual point selection to directional strike damage points, which takes a long time, and it is easy to miss the time of damage. In order to solve the timeconsuming problem of manual point selection, this paper proposes an automatic extraction method for damage points of laser weapons. This method divides the missile target by K_means color clustering, and then fits the center line of the missile according to the pixel position index of the missile target area, combined with the least square method, and finally extracts the damage point according to the proportion of each part in the missile. This method can accurately provide damage points in real time and improve the combat effectiveness of laser weapons

Citation Download Citation

Jiaowei Shi, Shiyan Sun, Jun Xie, and Lin Li "Automatic extraction method of damage point of laser weapon", Proc. SPIE 12256, International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2022), 122560U (6 May 2022); https://doi.org/10.1117/12.2635396

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KEYWORDS

Missiles

Image segmentation

Weapons

Detection and tracking algorithms

Image processing algorithms and systems

RGB color model

Edge detection

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