GS4-1 Study on Detection of Nests on Pylon from Overhead View Based on Halcon

Title:	GS4-1 Study on Detection of Nests on Pylon from Overhead View Based on Halcon
Publication:	ICAROB2018
Volume:	23
Pages:	105-108
ISSN:	2188-7829
DOI:	10.5954/ICAROB.2018.GS4-1
Author(s):	Jiwu Wang, Haibao Luo, Pengfei Yu
Publication Date:	February 2, 2018
Keywords:	XLD contour, pylon, nest detection, fusion of texture and gray-scale features
Abstract:	Aiming at the disadvantages of low accuracy and efficiency of the existing methods of nest detection, this paper proposes an effective method based on Halcon, which could detect the nest in the images from unmanned aerial vehicles(UAVs). This method eliminates most of the background interference by Extracting XLD contour algorithm to identify the pylon area in the image. Within this area, the fusion of texture and gray-scale features of nest are employed to realize the detection. An experiment result is presented to validate that this method can actually realize the precise detection of nests on pylon with images shoot by the UAVs.
PDF File:	https://alife-robotics.co.jp/members2018/icarob/data/html/data/GS_pdf/GS4/GS4-1.pdf
Copyright:	© The authors. This article is distributed under the terms of the Creative Commons Attribution License 4.0, which permits non-commercial use, distribution and reproduction in any medium, provided the original work is properly cited. See for details: https://creativecommons.org/licenses/by-nc/4.0/