Year: 2024
Type: article
Abstract: In the world, the integration of controlled weapons into combat vehicles has been done for a long time and many weapon manufacturers have utilized image processing software to enhance the combat effectiveness of weapon systems, resulting in positive outcomes. Fire control systems, especially fire control systems on vehicles, require requirements for processing speed, durability as well as flexibility, which are essential when fighting the enemy. Kernelized Correlation Filters image processing algorithms and Temple Matching algorithms have promoted the advantages of image processing with vehicle fire control system in the weapons field. In this article, from the analysis of the Kernelized Correlation Filters image processing algorithm and the Temple Matching algorithm on hardware platforms suitable for vehicle fire control systems, the authors built a software program based on taking advantage of the powerful parallel computing capabilities of GPUs applied to 12.7 mm gun fire control systems installed on vehicles. The experiments demonstrated the results of handling targets in the field after completely installing all components of the weapon complex on the vehicle
DOI: 10.47869/tcsj.75.7.5
Author: Vu Xuan Tung
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4402809997