Simultaneous Wood Defect and Species Detection with 3D Laser Scanning Scheme
Wood grading and wood price are mainly connected with the wood defect and wood species. In this paper, a wood defect quantitative detection scheme and a wood species qualitative identification scheme are proposed simultaneously based on 3D laser scanning point cloud. First, an Artec 3D scanner is us...
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2016-01-01
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| Series: | International Journal of Optics |
| Online Access: | http://dx.doi.org/10.1155/2016/7049523 |
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| author | Zhao Peng Li Yue Ning Xiao |
| author_facet | Zhao Peng Li Yue Ning Xiao |
| author_sort | Zhao Peng |
| collection | DOAJ |
| description | Wood grading and wood price are mainly connected with the wood defect and wood species. In this paper, a wood defect quantitative detection scheme and a wood species qualitative identification scheme are proposed simultaneously based on 3D laser scanning point cloud. First, an Artec 3D scanner is used to scan the wood surface to get the 3D point cloud. Each 3D point contains its X, Y, and Z coordinate and its RGB color information. After preprocessing, the Z coordinate value of current point is compared with the set threshold to judge whether it is a defect point (i.e., cavity, worm tunnel, and crack). Second, a deep preferred search algorithm is used to segment the retained defect points marked with different colors. The integration algorithm is used to calculate the surface area and volume of every defect. Finally, wood species identification is performed with the wood surface’s color information. The color moments of scanned points are used for classification, but the defect points are not used. Experiments indicate that our scheme can accurately measure the surface areas and volumes of cavity, worm tunnel, and crack on wood surface with measurement error less than 5% and it can also reach a wood species recognition accuracy of 95%. |
| format | Article |
| id | doaj-art-1f3c99dc33a74838a1686f7c080da54d |
| institution | DOAJ |
| issn | 1687-9384 1687-9392 |
| language | English |
| publishDate | 2016-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Optics |
| spelling | doaj-art-1f3c99dc33a74838a1686f7c080da54d2025-08-20T03:17:35ZengWileyInternational Journal of Optics1687-93841687-93922016-01-01201610.1155/2016/70495237049523Simultaneous Wood Defect and Species Detection with 3D Laser Scanning SchemeZhao Peng0Li Yue1Ning Xiao2Information and Computer Engineering College, Northeast Forestry University, Harbin 150040, ChinaInformation and Computer Engineering College, Northeast Forestry University, Harbin 150040, ChinaInformation and Computer Engineering College, Northeast Forestry University, Harbin 150040, ChinaWood grading and wood price are mainly connected with the wood defect and wood species. In this paper, a wood defect quantitative detection scheme and a wood species qualitative identification scheme are proposed simultaneously based on 3D laser scanning point cloud. First, an Artec 3D scanner is used to scan the wood surface to get the 3D point cloud. Each 3D point contains its X, Y, and Z coordinate and its RGB color information. After preprocessing, the Z coordinate value of current point is compared with the set threshold to judge whether it is a defect point (i.e., cavity, worm tunnel, and crack). Second, a deep preferred search algorithm is used to segment the retained defect points marked with different colors. The integration algorithm is used to calculate the surface area and volume of every defect. Finally, wood species identification is performed with the wood surface’s color information. The color moments of scanned points are used for classification, but the defect points are not used. Experiments indicate that our scheme can accurately measure the surface areas and volumes of cavity, worm tunnel, and crack on wood surface with measurement error less than 5% and it can also reach a wood species recognition accuracy of 95%.http://dx.doi.org/10.1155/2016/7049523 |
| spellingShingle | Zhao Peng Li Yue Ning Xiao Simultaneous Wood Defect and Species Detection with 3D Laser Scanning Scheme International Journal of Optics |
| title | Simultaneous Wood Defect and Species Detection with 3D Laser Scanning Scheme |
| title_full | Simultaneous Wood Defect and Species Detection with 3D Laser Scanning Scheme |
| title_fullStr | Simultaneous Wood Defect and Species Detection with 3D Laser Scanning Scheme |
| title_full_unstemmed | Simultaneous Wood Defect and Species Detection with 3D Laser Scanning Scheme |
| title_short | Simultaneous Wood Defect and Species Detection with 3D Laser Scanning Scheme |
| title_sort | simultaneous wood defect and species detection with 3d laser scanning scheme |
| url | http://dx.doi.org/10.1155/2016/7049523 |
| work_keys_str_mv | AT zhaopeng simultaneouswooddefectandspeciesdetectionwith3dlaserscanningscheme AT liyue simultaneouswooddefectandspeciesdetectionwith3dlaserscanningscheme AT ningxiao simultaneouswooddefectandspeciesdetectionwith3dlaserscanningscheme |