Metrological validation for 3D modeling of dental plaster casts.

The contribution of this paper is twofold: (1) it presents an automatic 3D modeling technique and (2) it advances a procedure for its metrological evaluation in the context of a medical application, the 3D modeling of dental plaster casts. The motivation for this work is the creation of a "virtual gypsotheque" where cumbersome dental plaster casts can be replaced by numerical 3D models, thereby alleviating storage and access problems and allowing dentists and orthodontists the use of novel and unprecedented software tools for their medical evaluations. Modeling free-form surfaces of anatomical interest is an intriguing mixture of open issues concerning 3D modeling, geometrical metrology, and medicine. Of general interest is both the fact that a widespread use of 3D modeling in non-engineering applications requires automatic procedures of the kind presented in this work and the adopted validation paradigm for free-form surfaces, rather useful for practical purposes. In this latter respect, the metrological analysis we advance is the first seminal attempt in the field of 3D modeling and can be readily extended to contexts other than the medical one discussed in this paper.

Estimation of two-dimensional affine transformations through polar curve matching and its application to image mosaicking and remote-sensing data registration.

This paper presents a new and effective method for estimating two-dimensional affine transformations and its application to image registration. The method is based on matching polar curves obtained from the radial projections of the image energies, defined as the squared magnitudes of their Fourier transforms. Such matching is formulated as a simple minimization problem whose optimal solution is found with the Levenberg-Marquardt algorithm. The analysis of affine transformations in the frequency domain exploits the well-known property whereby the translational displacement in this domain can be factored out and separately estimated through phase correlation after the four remaining degrees of freedom of the affine warping have been determined. Another important contribution of this paper, emphasized through one example of image mosaicking and one example of remote sensing image registration, consists in showing that affine motion can be accurately estimated by applying our algorithm to the shapes of macrofeatures extracted from the images to register. The excellent performance of the algorithm is also shown through a synthetic example of motion estimation and its comparison with another standard registration technique.

A new class of chromatic filters for color image processing. Theory and applications.

This paper advances a new framework for chromatic filtering of color images. The chromatic content of a color image is encoded in the CIE u'v' chromaticity coordinates whereas the achromatic content is encoded as CIE Y tristimulus value. Within the u'v' chromaticity diagram, colors are added according to the well-known center of gravity law of additive color mixtures, which is generalized here into a nonlinear filtering scheme for processing the two chromatic signals u' and v'. The achromatic channel Y can be processed with traditional filtering schemes, either linear or nonlinear, depending on the specific task at hand. The most interesting characteristics of the new filtering scheme are: 1) the elimination of color smearing effects along edges between bright and dark areas; 2) the possibility of processing chromatic components in a noniterative fashion through linear convolution operations; and 3) the consequent amenability to computationally efficient implementations with fast Fourier transform. The paper includes several examples with both synthetic and real images where the performance of the new filtering method is compared with that of other color image processing algorithms.