TY - GEN
T1 - Recognition of windmills in remote sensing image by SVM and morphological attribute filters
AU - Li, Hongbo
AU - Zhao, Jian
AU - Zhang, Yun
AU - Zhang, Yunling
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/10/31
Y1 - 2018/10/31
N2 - Windmills have the characteristics of small area and small quantity in remote sensing images, so the traditional methods of object classification and recognition are not suitable for the recognition of windmills. In this paper, we analyzed the spectral information and shape characteristics of windmill, and proposed a technique of recognition windmills in remote sensing images based on SVM (support vector machines) and morphological attribute filters. The main idea of technique can be parted into two steps: the remote sensing image are divided into windmill and windmill-like areas, using morphological attribute filters to filter out the windmill-like areas. In addition, we have recognized the distributed windmills group in the images of four regions, and verify the accuracy of the recognition technique.
AB - Windmills have the characteristics of small area and small quantity in remote sensing images, so the traditional methods of object classification and recognition are not suitable for the recognition of windmills. In this paper, we analyzed the spectral information and shape characteristics of windmill, and proposed a technique of recognition windmills in remote sensing images based on SVM (support vector machines) and morphological attribute filters. The main idea of technique can be parted into two steps: the remote sensing image are divided into windmill and windmill-like areas, using morphological attribute filters to filter out the windmill-like areas. In addition, we have recognized the distributed windmills group in the images of four regions, and verify the accuracy of the recognition technique.
KW - Morphological attribute filters
KW - Support vector machines
KW - Target recognition
KW - Windmills
UR - https://www.scopus.com/pages/publications/85064152747
U2 - 10.1109/IGARSS.2018.8519274
DO - 10.1109/IGARSS.2018.8519274
M3 - 会议稿件
AN - SCOPUS:85064152747
T3 - International Geoscience and Remote Sensing Symposium (IGARSS)
SP - 6923
EP - 6926
BT - 2018 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 38th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018
Y2 - 22 July 2018 through 27 July 2018
ER -