The Segmentation Method of Target Point Cloud for Polarization-Modulated 3D Imaging
To implement target point cloud segmentation for a polarization-modulated 3D imaging system in practical projects, an efficient segmentation concept of multi-dimensional information fusion is designed. As the electron multiplier charge coupled device (EMCCD) camera can only acquire the gray image, b...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2019-12-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/20/1/179 |
| _version_ | 1811280712490287104 |
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| author | Shengjie Wang Bo Liu Zhen Chen Heping Li Shuo Jiang |
| author_facet | Shengjie Wang Bo Liu Zhen Chen Heping Li Shuo Jiang |
| author_sort | Shengjie Wang |
| collection | DOAJ |
| description | To implement target point cloud segmentation for a polarization-modulated 3D imaging system in practical projects, an efficient segmentation concept of multi-dimensional information fusion is designed. As the electron multiplier charge coupled device (EMCCD) camera can only acquire the gray image, but has no ability for time resolution owing to the time integration mechanism, large diameter electro-optic modulators (EOM) are used to provide time resolution for the EMCCD cameras to obtain the polarization-modulated images, from which a 3D image can also be simultaneously reconstructed. According to the characteristics of the EMCCD camera’s plane array imaging, the point-to-point mapping relationship between the gray image pixels and point cloud data coordinates is established. The target’s pixel coordinate position obtained by image segmentation is mapped to 3D point cloud data to get the segmented target point cloud data. On the basis of the specific environment characteristics of the experiment, the maximum entropy test method is applied to the target segmentation of the gray image, and the image morphological erosion algorithm is used to improve the segmentation accuracy. This method solves the problem that conventional point clouds’ segmentation methods cannot effectively segment irregular objects or closely bound objects. Meanwhile, it has strong robustness and stability in the presence of noise, and reduces the computational complexity and data volume. The experimental results show that this method is better for the segmentation of the target in the actual environment, and can avoid the over-segmentation and under-segmentation to some extent. This paper illustrates the potential and feasibility of the segmentation method based on this system in real-time data processing. |
| first_indexed | 2024-04-13T01:19:40Z |
| format | Article |
| id | doaj.art-3048396909444643acec2a374d4674d5 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-13T01:19:40Z |
| publishDate | 2019-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-3048396909444643acec2a374d4674d52022-12-22T03:08:48ZengMDPI AGSensors1424-82202019-12-0120117910.3390/s20010179s20010179The Segmentation Method of Target Point Cloud for Polarization-Modulated 3D ImagingShengjie Wang0Bo Liu1Zhen Chen2Heping Li3Shuo Jiang4Key Laboratory of Space Optoelectronic Precision Measurement Technology, CAS, Chengdu 610209, ChinaKey Laboratory of Space Optoelectronic Precision Measurement Technology, CAS, Chengdu 610209, ChinaKey Laboratory of Space Optoelectronic Precision Measurement Technology, CAS, Chengdu 610209, ChinaUniversity of Electronic Science and Technology of China, Chengdu 611731, ChinaKey Laboratory of Space Optoelectronic Precision Measurement Technology, CAS, Chengdu 610209, ChinaTo implement target point cloud segmentation for a polarization-modulated 3D imaging system in practical projects, an efficient segmentation concept of multi-dimensional information fusion is designed. As the electron multiplier charge coupled device (EMCCD) camera can only acquire the gray image, but has no ability for time resolution owing to the time integration mechanism, large diameter electro-optic modulators (EOM) are used to provide time resolution for the EMCCD cameras to obtain the polarization-modulated images, from which a 3D image can also be simultaneously reconstructed. According to the characteristics of the EMCCD camera’s plane array imaging, the point-to-point mapping relationship between the gray image pixels and point cloud data coordinates is established. The target’s pixel coordinate position obtained by image segmentation is mapped to 3D point cloud data to get the segmented target point cloud data. On the basis of the specific environment characteristics of the experiment, the maximum entropy test method is applied to the target segmentation of the gray image, and the image morphological erosion algorithm is used to improve the segmentation accuracy. This method solves the problem that conventional point clouds’ segmentation methods cannot effectively segment irregular objects or closely bound objects. Meanwhile, it has strong robustness and stability in the presence of noise, and reduces the computational complexity and data volume. The experimental results show that this method is better for the segmentation of the target in the actual environment, and can avoid the over-segmentation and under-segmentation to some extent. This paper illustrates the potential and feasibility of the segmentation method based on this system in real-time data processing.https://www.mdpi.com/1424-8220/20/1/179polarization-modulatedlidardata fusiontarget segmentation |
| spellingShingle | Shengjie Wang Bo Liu Zhen Chen Heping Li Shuo Jiang The Segmentation Method of Target Point Cloud for Polarization-Modulated 3D Imaging Sensors polarization-modulated lidar data fusion target segmentation |
| title | The Segmentation Method of Target Point Cloud for Polarization-Modulated 3D Imaging |
| title_full | The Segmentation Method of Target Point Cloud for Polarization-Modulated 3D Imaging |
| title_fullStr | The Segmentation Method of Target Point Cloud for Polarization-Modulated 3D Imaging |
| title_full_unstemmed | The Segmentation Method of Target Point Cloud for Polarization-Modulated 3D Imaging |
| title_short | The Segmentation Method of Target Point Cloud for Polarization-Modulated 3D Imaging |
| title_sort | segmentation method of target point cloud for polarization modulated 3d imaging |
| topic | polarization-modulated lidar data fusion target segmentation |
| url | https://www.mdpi.com/1424-8220/20/1/179 |
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