Some Enhancement of Aerial and Terrestrial Photo for 3D Modeling of Texture-Less Object Surface
Today, the combination of Aerial and Terrestrial photos has been more implemented for 3D modelling purposes. This 3D modelling technique getting popular because it is supporting with photogrammetry structure from motion algorithm (SFM). The SFM algorithm makes automation in the processing step. One...
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| Format: | Conference or Workshop Item |
| Language: | English |
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2022
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| Online Access: | https://repository.ugm.ac.id/282143/1/Rokhmana%20et%20al%20-%202022%20-%20Some%20Enhancement%20of%20Aerial.pdf |
| _version_ | 1797037542498893824 |
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| author | Rokhmana, Catur Aries Fauzi, Hanif Muhammad |
| author_facet | Rokhmana, Catur Aries Fauzi, Hanif Muhammad |
| author_sort | Rokhmana, Catur Aries |
| collection | UGM |
| description | Today, the combination of Aerial and Terrestrial photos has been more implemented for 3D modelling purposes. This 3D modelling technique getting popular because it is supporting with photogrammetry structure from motion algorithm (SFM). The SFM algorithm makes automation in the processing step. One of the main problems that will occur in the automation of 3D modelling objects with the SFM algorithm is whether objects have texture-less surfaces. The purpose of this research is to evaluate some enhancement processes that were applied before running the SFM algorithm for 3D modelling. Some pre-processing enhancements are a combination Contrast-Limited Adaptive Histogram Equalization (CLAHE) from Fiji-ImageJ and JPEG to RAW Ai artefact algorithm from Topaz Labs. Two sample objects are tested which are a heritage object that has a texture-less wall surface object and a paddy field that has a similar object pattern. Some aerial and terrestrial photos have been enhanced before processing in 3D modelling. The result shows that applying preprocessing enhancement can improve the completeness of the object, especially in texture-less wall surface area. Pre-processing enhancement improves the geometric accuracy and number of vertex and surfaces also. In the future, the combination of the Jpeg to Raw Ai and the CLAHE enhancement should be explored for the best 3D model solution. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG. |
| first_indexed | 2024-03-14T00:04:53Z |
| format | Conference or Workshop Item |
| id | oai:generic.eprints.org:282143 |
| institution | Universiti Gadjah Mada |
| language | English |
| last_indexed | 2024-03-14T00:04:53Z |
| publishDate | 2022 |
| record_format | dspace |
| spelling | oai:generic.eprints.org:2821432023-11-29T07:20:13Z https://repository.ugm.ac.id/282143/ Some Enhancement of Aerial and Terrestrial Photo for 3D Modeling of Texture-Less Object Surface Rokhmana, Catur Aries Fauzi, Hanif Muhammad Geodesy Today, the combination of Aerial and Terrestrial photos has been more implemented for 3D modelling purposes. This 3D modelling technique getting popular because it is supporting with photogrammetry structure from motion algorithm (SFM). The SFM algorithm makes automation in the processing step. One of the main problems that will occur in the automation of 3D modelling objects with the SFM algorithm is whether objects have texture-less surfaces. The purpose of this research is to evaluate some enhancement processes that were applied before running the SFM algorithm for 3D modelling. Some pre-processing enhancements are a combination Contrast-Limited Adaptive Histogram Equalization (CLAHE) from Fiji-ImageJ and JPEG to RAW Ai artefact algorithm from Topaz Labs. Two sample objects are tested which are a heritage object that has a texture-less wall surface object and a paddy field that has a similar object pattern. Some aerial and terrestrial photos have been enhanced before processing in 3D modelling. The result shows that applying preprocessing enhancement can improve the completeness of the object, especially in texture-less wall surface area. Pre-processing enhancement improves the geometric accuracy and number of vertex and surfaces also. In the future, the combination of the Jpeg to Raw Ai and the CLAHE enhancement should be explored for the best 3D model solution. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG. 2022 Conference or Workshop Item PeerReviewed application/pdf en https://repository.ugm.ac.id/282143/1/Rokhmana%20et%20al%20-%202022%20-%20Some%20Enhancement%20of%20Aerial.pdf Rokhmana, Catur Aries and Fauzi, Hanif Muhammad (2022) Some Enhancement of Aerial and Terrestrial Photo for 3D Modeling of Texture-Less Object Surface. In: UASG 2021: Unmanned Aerial System in Geomatics. https://link.springer.com/book/10.1007/978-3-031-19309-5 |
| spellingShingle | Geodesy Rokhmana, Catur Aries Fauzi, Hanif Muhammad Some Enhancement of Aerial and Terrestrial Photo for 3D Modeling of Texture-Less Object Surface |
| title | Some Enhancement of Aerial and Terrestrial Photo for 3D Modeling of Texture-Less Object Surface |
| title_full | Some Enhancement of Aerial and Terrestrial Photo for 3D Modeling of Texture-Less Object Surface |
| title_fullStr | Some Enhancement of Aerial and Terrestrial Photo for 3D Modeling of Texture-Less Object Surface |
| title_full_unstemmed | Some Enhancement of Aerial and Terrestrial Photo for 3D Modeling of Texture-Less Object Surface |
| title_short | Some Enhancement of Aerial and Terrestrial Photo for 3D Modeling of Texture-Less Object Surface |
| title_sort | some enhancement of aerial and terrestrial photo for 3d modeling of texture less object surface |
| topic | Geodesy |
| url | https://repository.ugm.ac.id/282143/1/Rokhmana%20et%20al%20-%202022%20-%20Some%20Enhancement%20of%20Aerial.pdf |
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