Autofocus Vision System Enhancement for UAVs via Autoencoder Generative Algorithm
Received: 25 July 2024 | Revised: 5 September 2024 | Accepted: 8 September 2024 | Online: 18 November 2024
Corresponding author: Anwer Ahmed
Abstract
The Autofocus (AF) technology has become well-known over the past four decades. When attached to a camera, it eliminates the need to manually focus by giving the viewer a perfectly focused image in a matter of seconds. Modern AF systems are needed to achieve high-resolution images with optimal focus, and AF has become very important for many fields, possessing advantages such as high efficiency and autonomously interacting with Fenvironmental conditions. The proposed AF vision system for Unmanned Aerial Vehicle (UAV) navigation uses an autoencoder technique to extract important features from images. The system's function is to monitor and control the focus of a camera mounted to a drone. On an AF dataset, the proposed autoencoder model exhibited an amazing 95% F-measure and 90% accuracy, so it can be considered a robust option for achieving precision and clarity in varying conditions since it can effectively identify features.
Keywords:
Unmanned Aerial Vehicle (UAV) navigation, autofocus, feature extraction, autoencoderDownloads
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