TY - GEN
T1 - Damaged Airport Runway Extraction Based on Line and Corner Constraints
AU - Zhao, Yalun
AU - Cong, Yanchao
AU - Wang, Zepeng
AU - Gong, Jiulu
AU - Chen, Derong
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - The incompleteness of damaged airport runway areas is a significant challenge to the existing airport runway extraction methods. In this paper, we propose a damaged airport runway extraction method that combines line with corner constraints. In the proposed method, we first extract lines and corners from the continuous edges of the region of interest. Then, based on line and corner constraints, we identify the rough location of each runway by calculating its central axis parameters and generate candidate runway areas by calculating and connecting the runway vertex coordinates. Further, the candidate runway areas are selected as final results that satisfy the runway length constraint. In 6 typical airport satellite images and 3 post-damage images, the average integrity of runway extraction is more than 95%, and the average quality of runway extraction is nearly 93%. The experimental results show that the proposed method performs well both on damaged and undamaged airport runway areas. Compared with the state-of-the-art method, the proposed method is more effective and efficient.
AB - The incompleteness of damaged airport runway areas is a significant challenge to the existing airport runway extraction methods. In this paper, we propose a damaged airport runway extraction method that combines line with corner constraints. In the proposed method, we first extract lines and corners from the continuous edges of the region of interest. Then, based on line and corner constraints, we identify the rough location of each runway by calculating its central axis parameters and generate candidate runway areas by calculating and connecting the runway vertex coordinates. Further, the candidate runway areas are selected as final results that satisfy the runway length constraint. In 6 typical airport satellite images and 3 post-damage images, the average integrity of runway extraction is more than 95%, and the average quality of runway extraction is nearly 93%. The experimental results show that the proposed method performs well both on damaged and undamaged airport runway areas. Compared with the state-of-the-art method, the proposed method is more effective and efficient.
KW - airport runway extraction
KW - corner constraint
KW - google earth image
KW - line constraint
KW - post-damage image
UR - http://www.scopus.com/inward/record.url?scp=85146491998&partnerID=8YFLogxK
U2 - 10.1109/ICUS55513.2022.9986783
DO - 10.1109/ICUS55513.2022.9986783
M3 - Conference contribution
AN - SCOPUS:85146491998
T3 - Proceedings of 2022 IEEE International Conference on Unmanned Systems, ICUS 2022
SP - 1282
EP - 1287
BT - Proceedings of 2022 IEEE International Conference on Unmanned Systems, ICUS 2022
A2 - Song, Rong
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2022 IEEE International Conference on Unmanned Systems, ICUS 2022
Y2 - 28 October 2022 through 30 October 2022
ER -