In this paper, we present an efficient algorithm for computing the Euclidean skeleton of an object directly from a point cloud representation on an underlying grid. The key point of this algorithm is to identify those grid points that are (approximately) on the skeleton using the closest point information of a grid point and its neighbors. The three main ingredients of the algorithm are: (1) co...

The traditional closest point criterion has been widely used for 3D free form shape matching, object recognition, internet search, computer graphics and medical imaging. However, the rationale of this criterion has not yet been well understood and exploited. In this paper, we apply vector operations and the triangle inequality to carefully analyse this criterion and reveal that this criterion c...

The problem of finding a center string that is ‘close’ to every given string arises and has many applications in computational molecular biology and coding theory. This problem has two versions: the Closest String problem and the Closest Substring problem. Assume that we are given a set of strings S = {s1, s2, . . . , sn} of strings, say, each of length m. The Closest String problem [1, 2, 4, 5...

In this semitutorial paper, a comprehensive survey of closest point search methods for lattices without a regular structure is presented. The existing search strategies are described in a unified framework, and differences between them are elucidated. An efficient closest point search algorithm, based on the Schnorr–Euchner variation of the Pohst method, is implemented. Given an arbitrary point...

This work presents a method for the registration of three-dimensional (3-D) shapes. The method is based on the iterative closest point (ICP) algorithm and improves it through the use of a 3-D volume containing the shapes to be registered. The Voronoi diagram of the "model" shape points is first constructed in the volume. Then this is used for the calculation of the closest point operator. This ...

Probabilistic atlas has broad applications in medical image segmentation and registration. The most common problem building a probabilistic atlas is picking a target image upon which to map the rest of the training images. Here we present a method to choose a target image that is the closest to the mean geometry of the population under consideration as determined by bending energy. Our approach...

We discuss how methods based on hidden Markov models performed in the fold-recognition section of the CASP2 experiment. Hidden Markov models were built for a representative set of just over 1,000 structures from the Protein Data Bank (PDB). Each CASP2 target sequence was scored against this library of HMMs. In addition, an HMM was built for each of the target sequences and all of the sequences ...

We compare several decision rules for allocating subjects to dosages that are based on sequential isotonic estimates of a monotone dose-toxicity curve. We conclude that the decision rule in which the next assignment is to the dose having probability of toxicity closest to target does not work well. The best rule in our comparison is given by the cumulative cohort design. According to this desig...