In orthodontics, the diagnosis and the planning of a treatment rest on the knowledge of the dental architecture of the patient using, among others, a dental cast in plaster. Today, dedicated software allow to manipulate digital models of the dental arches obtained after digitalization of the casts. To observe the contact of teeth, it is necessary to register both arches scanned separately. This stage is at present manual and the object of this thesis research is to propose a robust chain processing allowing an automatic registration of both arches guided by several photos of the patient mouth. The proposed approach consists in defining three types of singular points and in setting up strong methods of automatic detection at the same time on the 3D models and the color images leaning on the curvature and the texture. Once put in correspondence, these 2D / 3D equivalent points allow to estimate the projection matrices then the rigid transformation (6ddl) to position at best the mandible in relation to the maxillary by minimizing the reprojection errors in several views. To free itself from the noise of detection, the 2D and/or 3D positions of the singular points are improved during the optimization process. Numerous tests on virtual and real data validate the proposed approach. The final occlusion obtained on the real data by automatic registration is close to the reference of the expert. These are encouraging results to supply an automatic alternative to be integrated into a help tool for the diagnosis.
