Оброблення зображення у безпілотних пристроях

Abstract

This work focuses on studying modern image processing methods used in unmanned systems. The paper looks at how computer vision technologies function in unmanned aerial vehicles and other autonomous platforms. It specifically examines algorithms for object detection, image segmentation, and real-time tracking of moving objects. The paper also considers how machine learning and deep neural networks can improve the accuracy and reliability of visual data analysis. It describes the stages of processing visual information in onboard systems, including preprocessing, feature extraction, and classification. The discussion includes the benefits of combining traditional digital image processing techniques with modern artificial intelligence methods. This approach helps improve the autonomy and navigation skills of unmanned devices. The results show how important image processing technologies are for boosting the efficiency and functionality of modern unmanned systems