Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.13091/1214
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Sağlam, Ali | - |
dc.contributor.author | Baykan, Nurdan Akhan | - |
dc.date.accessioned | 2021-12-13T10:38:35Z | - |
dc.date.available | 2021-12-13T10:38:35Z | - |
dc.date.issued | 2021 | - |
dc.identifier.issn | 2548-0960 | - |
dc.identifier.issn | 2548-0960 | - |
dc.identifier.uri | https://doi.org/10.26833/ijeg.709212 | - |
dc.identifier.uri | https://app.trdizin.gov.tr/makale/TkRBNE56TXdNQT09 | - |
dc.identifier.uri | https://hdl.handle.net/20.500.13091/1214 | - |
dc.description.abstract | Two important features of the points in the LiDAR point clouds are the spatial and the color features. The spatial feature is mostly used in the point cloud processing field due to its 3D informative and distinctive characteristic. The local geometric difference derived from the spatial features of the points is usually benefited by graph-based point cloud segmentation methods, because the geometric features of the local point groups are highly distinctive. In this paper, we use both the geometric and color differences of the adjacent local point groups at the impact rates 0.3, 0.5, and 0.7 and cooperate the Euclidean and the vector color differences within several averaging techniques for the color difference. The difference forms have been tested within a graph-based segmentation method on four point cloud segmentation datasets, two indoor and two outdoor, using their spatial and color information. The geometric mean as an averaging techniques increases the segmentation success for the all datasets except one outdoor when the color differences are used in the segmentation at the impact rate 0.3, while the harmonic mean increases the success for the all datasets the successes except the other outdoor at the same impact rate. According to the test results, the cooperating of the Euclidean and vector angular color difference measurements can considerable increase the segmentation success on the point clouds with color information in a high quality. | en_US |
dc.language.iso | en | en_US |
dc.relation.ispartof | International Journal of Engineering and Geosciences | en_US |
dc.rights | info:eu-repo/semantics/openAccess | en_US |
dc.title | A new color distance measure formulated from the cooperation of the Euclidean and the vector angular differences for lidar point cloud segmentation | en_US |
dc.type | Article | en_US |
dc.identifier.doi | 10.26833/ijeg.709212 | - |
dc.identifier.scopus | 2-s2.0-85118971138 | en_US |
dc.department | Fakülteler, Mühendislik ve Doğa Bilimleri Fakültesi, Bilgisayar Mühendisliği Bölümü | en_US |
dc.identifier.volume | 6 | en_US |
dc.identifier.issue | 3 | en_US |
dc.identifier.startpage | 117 | en_US |
dc.identifier.endpage | 124 | en_US |
dc.identifier.wos | WOS:000608477000001 | en_US |
dc.relation.publicationcategory | Makale - Ulusal Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
dc.identifier.trdizinid | 408730 | en_US |
item.openairetype | Article | - |
item.languageiso639-1 | en | - |
item.cerifentitytype | Publications | - |
item.grantfulltext | open | - |
item.fulltext | With Fulltext | - |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
crisitem.author.dept | 02.03. Department of Computer Engineering | - |
Appears in Collections: | Mühendislik ve Doğa Bilimleri Fakültesi Koleksiyonu Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collections TR Dizin İndeksli Yayınlar Koleksiyonu / TR Dizin Indexed Publications Collections WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collections |
Files in This Item:
File | Size | Format | |
---|---|---|---|
856d0eda-99da-4016-86e5-d9668929d2de.pdf | 1.19 MB | Adobe PDF | View/Open |
CORE Recommender
SCOPUSTM
Citations
3
checked on Mar 23, 2024
WEB OF SCIENCETM
Citations
5
checked on Mar 23, 2024
Page view(s)
102
checked on Mar 25, 2024
Download(s)
30
checked on Mar 25, 2024
Google ScholarTM
Check
Altmetric
Items in GCRIS Repository are protected by copyright, with all rights reserved, unless otherwise indicated.