TY - GEN
T1 - Ship detection from optical satellite images based on visual search mechanism
AU - Yang, Feng
AU - Xu, Qizhi
AU - Gao, Feng
AU - Hu, Lei
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/11/10
Y1 - 2015/11/10
N2 - Automatic ship detection from high-resolution optical satellite images has attracted great interest in the wide applications of maritime security and traffic control. However, most of the popular methods have much difficulty in extracting targets without false alarms due to the variable appearances of ships and complicated background. In this paper, we propose a ship detection approach based on visual search mechanism to solve this problem. First, salient regions are extracted by a global contrast model fast and easily. Second, geometric properties and neighborhood similarity of targets are used for discriminating the ship candidates with ambiguous appearance effectively. Furthermore, we utilize the SVM algorithm to classify each image as including target(s) or not according to the LBP feature of each ship candidate. Extensive experiments validate our proposed scheme outperforms the state-of-the-art methods in terms of detection time and accuracy.
AB - Automatic ship detection from high-resolution optical satellite images has attracted great interest in the wide applications of maritime security and traffic control. However, most of the popular methods have much difficulty in extracting targets without false alarms due to the variable appearances of ships and complicated background. In this paper, we propose a ship detection approach based on visual search mechanism to solve this problem. First, salient regions are extracted by a global contrast model fast and easily. Second, geometric properties and neighborhood similarity of targets are used for discriminating the ship candidates with ambiguous appearance effectively. Furthermore, we utilize the SVM algorithm to classify each image as including target(s) or not according to the LBP feature of each ship candidate. Extensive experiments validate our proposed scheme outperforms the state-of-the-art methods in terms of detection time and accuracy.
KW - Ship detection
KW - geometric properties
KW - global contrast model
KW - neighborhood similarity
KW - optical satellite image
UR - https://www.scopus.com/pages/publications/84962563086
U2 - 10.1109/IGARSS.2015.7326621
DO - 10.1109/IGARSS.2015.7326621
M3 - Conference contribution
AN - SCOPUS:84962563086
T3 - International Geoscience and Remote Sensing Symposium (IGARSS)
SP - 3679
EP - 3682
BT - 2015 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2015 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2015 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2015
Y2 - 26 July 2015 through 31 July 2015
ER -