title: An enhanced method for registration of dental surfaces partially scanned by a 3D dental laser scanning.
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.
authors.affiliation: Creative Content Research Laboratory, Electronics and Telecommunications Research Institute, 218 Gajeong-Ro, Yuseong-Gu, Daejeon 305-700, South Korea.
authors.forename: Seongjin
authors.initials: S
authors.lastname: Park
authors.affiliation: School of Electrical Engineering and Computer Science, Seoul National University, San 56-1 Shinlim 9-dong, Kwanak-gu, Seoul 151-742, South Korea.
authors.forename: Ho Chul
authors.initials: HC
authors.lastname: Kang
authors.affiliation: School of Computer Science & Engineering, Soongsil University, 369 Sangdo-Ro, Dongjak-Gu, Seoul 156-743, South Korea. Electronic address: leejeongjin@ssu.ac.kr.
authors.forename: Jeongjin
authors.initials: J
authors.lastname: Lee
authors.affiliation: Department of Systems Management Engineering, Sungkyunkwan University, 2066, Seobu-ro, Jangan-gu, Suwon-si, Gyeong gi-do 440-746, South Korea.
authors.forename: Juneseuk
authors.initials: J
authors.lastname: Shin
authors.affiliation: School of Electrical Engineering and Computer Science, Seoul National University, San 56-1 Shinlim 9-dong, Kwanak-gu, Seoul 151-742, South Korea.
authors.forename: Yeong Gil
authors.initials: YG
authors.lastname: Shin
mesh_terms: D000465:Algorithms; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D007834:Lasers; D003765:Models, Dental; D013499:Surface Properties; D014070:Tooth / Q000033:anatomy & histology
keywords: 3D dental laser scanning; Depth map; Depth map-based registration; Iterative closest point; Surface registration