Global thresholding for scene understanding towards autonomous drone navigation

Lee, A.W.C. and Yong, S.-P. and Watada, J. (2019) Global thresholding for scene understanding towards autonomous drone navigation. Journal of Advanced Computational Intelligence and Intelligent Informatics, 23 (5). pp. 909-919. ISSN 13430130

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Abstract

Unmanned aerial vehicles, more typically known as drones are flying aircrafts that do not have a pilot on-board. For drones to fly through an area without GPS signals, developing scene understanding algorithms to assist in autonomous navigation will be useful. In this paper, various thresholding algorithms are evaluated to enhance scene understanding in addition to object detection. Based on the results obtained, Gaussian filter global thresholding can segment regions of interest in the scene effectively and provide the least cost of processing time. © 2019 Fuji Technology Press. All rights reserved.

Item Type: Article
Additional Information: cited By 1
Uncontrolled Keywords: Aircraft detection; Antennas; Navigation; Object detection; Object recognition, Autonomous navigation; Gaussian filters; Global thresholding; Processing time; Regions of interest; Scene understanding; Thresholding; Thresholding algorithms, Drones
Depositing User: Mr Ahmad Suhairi UTP
Date Deposited: 10 Nov 2023 03:26
Last Modified: 10 Nov 2023 03:26
URI: https://khub.utp.edu.my/scholars/id/eprint/12064

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