The main result of this paper is that simple (raster scan) sequential algorithms for computing Euclidean Distance Transforms can be implemented in an optimized manner from the point of view of numerical computations. We will show that these fast implementations have computational complexities comparable to the city block, chessboard and other simple chamfer Distance Transforms.

Re-distancing the implicit surface is time-consuming. We propose a fast implementation of the Chamfer distance which maintains the sub-voxel accuracy of the interface. This approximation to the Euclidean distance gives a reasonable accuracy while improving considerably the computation time.

statement of the problem: although all-ceramic restorations are broadly used, there is a lack of information concerning how their fit is affected by fabrication procedure and marginal configuration. purpose: the purpose of this study was to evaluate the marginal fit of zirconia cad/cam ceramic crowns before and after porcelain firing. the influence of finish line configuration on the marginal f...

Handwritten Chinese characters can be recognized by first extracting the basic shapes (radicals) of which they are composed. Radicals are described by nonlinear active shape models and optimal parameters found using the chamfer distance transform and a dynamic tunneling algorithm. The radical recognition rate is 96.5 percent correct (writer-independent) on 280,000 characters containing 98 radic...

This paper proposes active handwriting models, in which kernel principal component analysis is applied to capture nonlinear handwriting variations. In the recognition phase, the chamfer distance transform and a dynamic tunnelling algorithm (DTA) are employed to search for the optimal shape parameters. The proposed methodology is successfully applied to a novel radical decomposition approach to ...

A new region growing algorithm has recently been proposed for computing Euclidean Distance Maps in a time comparable to widely used chamfer DT. In this paper we show how this algorithm can be extended to more complex tasks such as the computation of distance maps on an-isotropic grids and the generation of a new type of Euclidean skeletons.

We present a practical vision-based robotic bin-picking system that performs detection and 3D pose estimation of objects in an unstructured bin using a novel camera design, picks up parts from the bin, and performs error detection and pose correction while the part is in the gripper. Two main innovations enable our system to achieve real-time robust and accurate operation. First, we use a multi...