Shape recognition systems usually order a fixed number of best matches to each query, but do not address or answer the two following questions: Is a query shape in a given database ? How can we be sure that a match is correct ? This communication deals with these two key points. A database being given, with each shape S and each distance δ, we associate its number of false alarms NFA(S, δ), nam...

In this paper we present a new one-dimensional shape matching technique based on elastic deformation of a model or template. Deformations of the given template are introduced as a way to improve the matching with the image data. A trade-o is made between the amount of deformation and a gure of merit that accounts for the match. This approach yields a new optimization functional so that the opti...

We propose an efficient procedure for calculating partial dense intrinsic correspondence between deformable shapes performed entirely in the spectral domain. Our technique relies on the recently introduced partial functional maps formalism and on the joint approximate diagonalization (JAD) of the Laplace-Beltrami operators previously introduced for matching non-isometric shapes. We show that a ...

The problem of defect detection in 2D and 3D shapes is analyzed. A shape is represented by a set of its contour, or surface, points. Mathematically, the problem is formulated as a speciic matching of two sets of points, a reference one and a measured one. Modiied Hausdorr distance between these two point sets is used to induce the matching. Based on a distance transform, a 2D algorithm is propo...

Acknowledgements First and foremost, I would like to thank my advisors Professor Andrea Massa and Professor Francesco G.B. De Natale who taught me a lot about research and life in general. They were always there to provide everything not only to support my research but also to help me adjust myself in new country as Italy. Without their guidance and support, this thesis would not have been comp...

In order to determine the similarity between two planar shapes, which is an important problem in computer vision and pattern recognition, it is necessary to first match the two shapes as good as possible. As sets of allowed transformation to match shapes we consider translations, rigid motions, and similarities. We present a generic probabilistic algorithm based on random sampling for matching ...

We use segmentations to match images by shape. To address the unreliability of segmentations, we give a closed form approximation to an average over all segmentations. Our technique has many extensions, yielding new algorithms for tracking, object detection, segmentation, and edge-preserving smoothing. For segmentation, instead of a maximum a posteriori approach, we compute the “central” segmen...