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Journal Article An Enhanced Method for Registration of Dental Surfaces Partially Scanned by a 3D Dental Laser Scanning
Cited 18 time in scopus Share share facebook twitter linkedin kakaostory
Authors
Seongjin Park, Ho Chul Kang, Jeongjin Lee, Juneseuk Shin, Yeong Gil Shin
Issue Date
2015-01
Citation
Computer Methods and Programs in Biomedicine, v.118, no.1, pp.11-22
ISSN
0169-2607
Publisher
Elsevier
Language
English
Type
Journal Article
DOI
https://dx.doi.org/10.1016/j.cmpb.2014.09.007
Abstract
In this paper, we propose the fast and accurate registration method of partially scanned dental surfaces in a 3D dental laser scanning. To overcome the multiple point correspondence problems of conventional surface registration methods, we propose the novel depth map-based registration method to register 3D surface models. First, we convert a partially scanned 3D dental surface into a 2D image by generating the 2D depth map image of the surface model by applying a 3D rigid transformation into this model. Then, the image-based registration method using 2D depth map images accurately estimates the initial transformation between two consequently acquired surface models. To further increase the computational efficiency, we decompose the 3D rigid transformation into out-of-plane (i.e. x-, y-rotation, and z-translation) and in-plane (i.e. x-, y-translation, and z-rotation) transformations. For the in-plane transformation, we accelerate the transformation process by transforming the 2D depth map image instead of transforming the 3D surface model. For the more accurate registration of 3D surface models, we enhance iterative closest point (ICP) method for the subsequent fine registration. Our initial depth map-based registration well aligns each surface model. Therefore, our subsequent ICP method can accurately register two surface models since it is highly probable that the closest point pairs are the exact corresponding point pairs. The experimental results demonstrated that our method accurately registered partially scanned dental surfaces. Regarding the computational performance, our method delivered about 1.5 times faster registration than the conventional method. Our method can be successfully applied to the accurate reconstruction of 3D dental objects for orthodontic and prosthodontic treatment.
KSP Keywords
2D image, 3D surface model, Accurate registration, Computational Efficiency, Conventional methods, Depth Map, Fast and accurate, Fine registration, Image-based, In-plane, Laser Scanning