Pattern Recognition Letters ( IF 3.255 ) Pub Date : 2020-07-21 , DOI: 10.1016/j.patrec.2020.07.026 Wenting Cui; Shaoyi Du; Teng Wan; Runzhao Yao; Yuying Liu; Mengqi Han; Qingnan Mou; Yu-cheng Guo; Nanning Zheng
In orthodontics, a patient is collected a lot of 3D oral cavity data, including oral cavity gypsum and scan data sets. To accurately measure the patient's tooth movement, this paper proposes a robust and precise isotropic scaling registration algorithm using bi-directional distance and correntropy. Firstly, because the oral cavity gypsum data sets have a lot of gypsum tumors and bubbles, which can cause the accuracy of registration results to decrease. Then, we introduce the correntropy into the traditional scaling registration model. Secondly, since unconstrained scaling registration is an ill-posed problem, bi-directional distance is used to enhance the robustness. In this way, a registration model using bi-directional distance and correntropy is established. In order to solve this problem, this paper proposes a new registration algorithm with iterative closest point. Moreover, the convergence of the algorithm is proved theoretically. Finally, the proposed algorithm is tested on the orthodontic database, and our experimental results demonstrate that our algorithm performs robust and high accuracy.