A RECOGNITION METHOD FOR AIRPLANE TARGETS USING 3D POINT CLOUD DATA
LiDAR is capable of obtaining three dimension coordinates of the terrain and targets directly and is widely applied in digital city, emergent disaster mitigation and environment monitoring. Especially because of its ability of penetrating the low density vegetation and canopy, LiDAR technique has...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2012-07-01
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| Series: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| Online Access: | https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XXXIX-B3/199/2012/isprsarchives-XXXIX-B3-199-2012.pdf |
| _version_ | 1818083847473987584 |
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| author | M. Zhou L.-L. Tang C.-R. Li Z. Peng J.-M. Li |
| author_facet | M. Zhou L.-L. Tang C.-R. Li Z. Peng J.-M. Li |
| author_sort | M. Zhou |
| collection | DOAJ |
| description | LiDAR is capable of obtaining three dimension coordinates of the terrain and targets directly and is widely applied in digital city,
emergent disaster mitigation and environment monitoring. Especially because of its ability of penetrating the low density vegetation
and canopy, LiDAR technique has superior advantages in hidden and camouflaged targets detection and recognition. Based on the
multi-echo data of LiDAR, and combining the invariant moment theory, this paper presents a recognition method for classic
airplanes (even hidden targets mainly under the cover of canopy) using KD-Tree segmented point cloud data. The proposed
algorithm firstly uses KD-tree to organize and manage point cloud data, and makes use of the clustering method to segment objects,
and then the prior knowledge and invariant recognition moment are utilized to recognise airplanes. The outcomes of this test verified
the practicality and feasibility of the method derived in this paper. And these could be applied in target measuring and modelling of
subsequent data processing. |
| first_indexed | 2024-12-10T19:44:30Z |
| format | Article |
| id | doaj.art-869c95991abf459592614af5f7f43d05 |
| institution | Directory Open Access Journal |
| issn | 1682-1750 2194-9034 |
| language | English |
| last_indexed | 2024-12-10T19:44:30Z |
| publishDate | 2012-07-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| spelling | doaj.art-869c95991abf459592614af5f7f43d052022-12-22T01:35:55ZengCopernicus PublicationsThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences1682-17502194-90342012-07-01XXXIX-B319920310.5194/isprsarchives-XXXIX-B3-199-2012A RECOGNITION METHOD FOR AIRPLANE TARGETS USING 3D POINT CLOUD DATAM. Zhou0L.-L. Tang1C.-R. Li2Z. Peng3J.-M. Li4Academy of Opto-Electronics, Chinese Academy of Sciences, No.9, Dengzhuang Nanlu, Beijing, ChinaAcademy of Opto-Electronics, Chinese Academy of Sciences, No.9, Dengzhuang Nanlu, Beijing, ChinaAcademy of Opto-Electronics, Chinese Academy of Sciences, No.9, Dengzhuang Nanlu, Beijing, ChinaAcademy of Opto-Electronics, Chinese Academy of Sciences, No.9, Dengzhuang Nanlu, Beijing, ChinaAcademy of Opto-Electronics, Chinese Academy of Sciences, No.9, Dengzhuang Nanlu, Beijing, ChinaLiDAR is capable of obtaining three dimension coordinates of the terrain and targets directly and is widely applied in digital city, emergent disaster mitigation and environment monitoring. Especially because of its ability of penetrating the low density vegetation and canopy, LiDAR technique has superior advantages in hidden and camouflaged targets detection and recognition. Based on the multi-echo data of LiDAR, and combining the invariant moment theory, this paper presents a recognition method for classic airplanes (even hidden targets mainly under the cover of canopy) using KD-Tree segmented point cloud data. The proposed algorithm firstly uses KD-tree to organize and manage point cloud data, and makes use of the clustering method to segment objects, and then the prior knowledge and invariant recognition moment are utilized to recognise airplanes. The outcomes of this test verified the practicality and feasibility of the method derived in this paper. And these could be applied in target measuring and modelling of subsequent data processing.https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XXXIX-B3/199/2012/isprsarchives-XXXIX-B3-199-2012.pdf |
| spellingShingle | M. Zhou L.-L. Tang C.-R. Li Z. Peng J.-M. Li A RECOGNITION METHOD FOR AIRPLANE TARGETS USING 3D POINT CLOUD DATA The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| title | A RECOGNITION METHOD FOR AIRPLANE TARGETS USING 3D POINT CLOUD DATA |
| title_full | A RECOGNITION METHOD FOR AIRPLANE TARGETS USING 3D POINT CLOUD DATA |
| title_fullStr | A RECOGNITION METHOD FOR AIRPLANE TARGETS USING 3D POINT CLOUD DATA |
| title_full_unstemmed | A RECOGNITION METHOD FOR AIRPLANE TARGETS USING 3D POINT CLOUD DATA |
| title_short | A RECOGNITION METHOD FOR AIRPLANE TARGETS USING 3D POINT CLOUD DATA |
| title_sort | recognition method for airplane targets using 3d point cloud data |
| url | https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XXXIX-B3/199/2012/isprsarchives-XXXIX-B3-199-2012.pdf |
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