Global Thresholding for Scene Understanding Towards Autonomous Drone Navigation

被引：0

作者：

Lee, Alvin Wai Chung ^{[1
]}

Yong, Suet-Peng ^{[1
]}

Watada, Junzo ^{[1
]}

机构：

[1] Univ Teknol PETRONAS, Seri Iskandar 32610, Perak Darul Rid, Malaysia

来源：

JOURNAL OF ADVANCED COMPUTATIONAL INTELLIGENCE AND INTELLIGENT INFORMATICS | 2019年 / 23卷 / 05期

关键词：

object detection; thresholding; scene understanding; drone; navigation; IMAGE;

D O I：

10.20965/jaciii.2019.p0909

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Unmanned aerial vehicles, more typically known as drones are flying aircrafts that do not have a pilot onboard. 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.

引用

页码：909 / 919

页数：11

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