A novel line segment detection algorithm based on graph search

2018 ◽  
Author(s):  
Hong-dan Zhao ◽  
Guo-ying Liu ◽  
Xu Song
Keyword(s):  
Line Segment ◽  
Detection Algorithm ◽  
Graph Search ◽  
Line Segment Detection

scholarly journals Line Segment Detection Algorithm Using Improved PPHT

2016 ◽  
Vol 20 (1) ◽  
pp. 82-88
Author(s):  
Chanho Lee ◽  
Ji-hyun Moon ◽  
Duy Phuong Nguyen
Keyword(s):  
Line Segment ◽  
Detection Algorithm ◽  
Line Segment Detection

scholarly journals A Robust Method for Detecting Wind-Fallen Stems from Aerial RGB Images Using a Line Segment Detection Algorithm

Forests ◽  
2022 ◽  
Vol 13 (1) ◽  
pp. 90
Author(s):  
Tim Ritter ◽  
Christoph Gollob ◽  
Ralf Kraßnitzer ◽  
Karl Stampfer ◽  
Arne Nothdurft
Keyword(s):  
Line Segment ◽  
Bark Beetles ◽  
Management Practice ◽  
Detection Algorithm ◽  
Storm Events ◽  
Line Segment Detection ◽  
Frequency Position ◽  
Efficient Planning ◽  
Rgb Images ◽  
Salvage Harvesting

Increased frequencies and windspeeds of storms may cause disproportionately high increases in windthrow damage. Storm-felled trees provide a surplus of breeding material for bark beetles, often resulting in calamities in the subsequent years. Thus, the timely removal of fallen trees is regarded as a good management practice that requires strategic planning of salvage harvesting. Precise information on the number of stems and their location and orientation are needed for the efficient planning of strip roads and/or cable yarding lines. An accurate assessment of these data using conventional field-based methods is very difficult and time-consuming; remote sensing techniques may be a cost-efficient alternative. In this research, a methodology for the automatic detection of fallen stems from aerial RGB images is presented. The presented methodology was based on a line segment detection algorithm and proved to be robust regarding image quality. It was shown that the method can detect frequency, position, spatial distribution and orientation of fallen stems with high accuracy, while stem lengths were systematically underestimated. The methodology can be used for the optimized planning of salvage harvesting in the future and may thus help to reduce consequential bark beetle calamities after storm events.

UND: Unite-and-Divide Method in Fourier and Radon Domains for Line Segment Detection

2013 ◽  
Vol 22 (6) ◽  
pp. 2501-2506 ◽  
Author(s):  
Daming Shi ◽  
Junbin Gao ◽  
Payam S. Rahmdel ◽  
Michael Antolovich ◽  
Tony Clark
Keyword(s):  
Line Segment ◽  
Line Segment Detection

Step-by-step pipeline processing approach for line segment detection

2017 ◽  
Vol 11 (6) ◽  
pp. 416-424 ◽  
Author(s):  
Chunyan Shao ◽  
Qinghai Ding ◽  
Haibo Luo ◽  
Zheng Chang ◽  
Chi Zhang ◽  
...  
Keyword(s):  
Line Segment ◽  
Processing Approach ◽  
Line Segment Detection ◽  
Pipeline Processing
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