The ability to determine the 3D structure of small objects is of value in a variety of applications, including intra-oral or dental imaging. Intra-oral imaging presents a number of challenges for detecting 3-D structure, such as those relating to difficulty in access and positioning, optical characteristics of teeth and other features within the mouth, and the need for precision measurement of irregular surfaces.
One common dental application for which surface imaging would be particularly advantageous relates to obtaining the profile of a tooth surface that has been prepared for the insertion of a dental crown. The typical method for fitting the crown is to take an impression of the prepared tooth and to forward the impression to a laboratory for fabrication. The returned crown then needs to be adjusted to make a proper fit. The process of making the impression is generally an unpleasant operation for the patient and too often yields unsatisfactory results.
An intra-oral surface image can be obtained using a single camera system that projects a light pattern, such as the barcode pattern described in U.S. Pat. No. 7,724,932 entitled “Three-dimensional modeling of the oral cavity” to Ernst et al. With such a system, however, contour over significant portions of the tooth surface can be difficult to image. Moreover, some external means must be provided in order to register reference points on the surface of the tooth with the image from the camera device.
Stereoscopic or stereo imaging has inherent advantages over single-camera imaging for detecting surface contour. A stereo intra-oral system comprises two cameras and a projector. The projector, typically positioned between the two cameras, illuminates the dental surface with a pattern in order to provide feature points as corresponding points for the stereo depth calculation. Enabling stereo imaging requires identifying the position of a point on an object in each image. This is often referred to as the correspondence problem. Solving the correspondence problem can be confounded by a host of reasons, including the lack of distinguishing features. One means of simplifying the problem is to illuminate the scene with structured light, i.e., light with a known pattern. The purpose of the patterned light is to overlay a number of features onto the object at fixed positions, so that these features can be used to register each camera and thus solve the correspondence problem. Various approaches and patterns can be used, such as to illuminate the object with lines of laser light or to illuminate the tooth surface or other area with different spectral content, such as using light patterns having different spectral content. One example of this approach is described in U.S. Pat. No. 6,937,348 entitled “Method and apparatus for generating structural pattern illumination” to Geng.
A correspondence problem that is common to solutions that use a projected light pattern relates to inherent localized dependencies. The region about a specific point of interest on a surface affects how well the corresponding pixel location for that point can be identified. Where the surrounding surface is sharply contoured or irregular, for example, there can be significant distortion that makes it difficult to provide accurate correspondence data.
Solutions using spectral patterning have also proved disappointing. Because of the nature of the tooth surface, for example, not all light wavelengths can be detected with equal accuracy. Thus, the multi-spectral approach described in the Geng '348 patent can be less satisfactory in some cases. Other patterning strategies encounter various problems related to signal detection due to the irregular contour of the tooth surface, the compact area over which imaging devices can be used, patient discomfort, and related factors that constrain the relative space that is available for imaging components, and other factors. Problems such as these continue to make it difficult to achieve the proper correspondence between two cameras as needed for stereo imaging.
Thus, although conventional methods for mapping points on a surface to imaging pixels have provided some measure of success, there is room for improvement. It would be highly advantageous to have a method for providing correspondence that is able to isolate a single pixel from its neighbors and accurately identify the corresponding surface point. There is, then, a need for apparatus and methods for providing improved correspondence mapping for single-camera and stereo imaging in the intra-oral environment and in other applications.