TY - JOUR
T1 - Multiple Auxiliaries Assisted Airborne Power Line Detection
AU - Shan, Haotian
AU - Zhang, Jun
AU - Cao, Xianbin
AU - Li, Xuelong
AU - Wu, Dapeng
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/6
Y1 - 2017/6
N2 - Airborne power line detection is a key technique to ensure low altitude flight safety. Yet, it is a challenging problem due to the extremely small size of power line targets. Recently, auxiliary assisted detection has shown great potential in improving the power line detection performance. However, in existing methods, the auxiliaries and the contexts between the power lines and the auxiliaries are both manually assigned, thus limits its applicability. In this paper, a novel multiple auxiliaries assisted power line detection method is proposed. With an optimization based auxiliaries selection and contexts acquisition scheme, the proposed method cannot only decide which auxiliaries should be selected to assist the detection, but also acquire the context information of each kind of auxiliaries, all in an automatic way. Experimental results show that the proposed method surpasses the state-of-the-art power line detection methods, both in terms of detection accuracy and false alarm probability.
AB - Airborne power line detection is a key technique to ensure low altitude flight safety. Yet, it is a challenging problem due to the extremely small size of power line targets. Recently, auxiliary assisted detection has shown great potential in improving the power line detection performance. However, in existing methods, the auxiliaries and the contexts between the power lines and the auxiliaries are both manually assigned, thus limits its applicability. In this paper, a novel multiple auxiliaries assisted power line detection method is proposed. With an optimization based auxiliaries selection and contexts acquisition scheme, the proposed method cannot only decide which auxiliaries should be selected to assist the detection, but also acquire the context information of each kind of auxiliaries, all in an automatic way. Experimental results show that the proposed method surpasses the state-of-the-art power line detection methods, both in terms of detection accuracy and false alarm probability.
KW - Automatic auxiliaries selection
KW - Bayesian network
KW - context
KW - low altitude flight
KW - power line detection
UR - https://www.scopus.com/pages/publications/85028776035
U2 - 10.1109/TIE.2017.2668994
DO - 10.1109/TIE.2017.2668994
M3 - Article
AN - SCOPUS:85028776035
SN - 0278-0046
VL - 64
SP - 4810
EP - 4819
JO - IEEE Transactions on Industrial Electronics
JF - IEEE Transactions on Industrial Electronics
IS - 6
M1 - 7855717
ER -