Topic
Distance transform
About: Distance transform is a research topic. Over the lifetime, 2886 publications have been published within this topic receiving 59481 citations.
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TL;DR: A shape-independent surface-matching algorithm gives a rigid body transformation, which allows the transfer of information between both modalities in the fast registration of positron emission tomography and magnetic resonance images of the brain.
Abstract: We propose a fully nonsupervised methodology dedicated to the fast registration of positron emission tomography (PET) and magnetic resonance images of the brain. First, discrete representations of the surfaces of interest (head or brain surface) are automatically extracted from both images. Then, a shape-independent surface-matching algorithm gives a rigid body transformation, which allows the transfer of information between both modalities. A three-dimensional (3D) extension of the chamfer-matching principle makes up the core of this surface-matching algorithm. The optimal transformation is inferred from the minimization of a quadratic generalized distance between discrete surfaces, taking into account between-modality differences in the localization of the segmented surfaces. The minimization process is efficiently performed via the precomputation of a 3D distance map. Validation studies using a dedicated brain-shaped phantom have shown that the maximum registration error was of the order of the PET pix...
100 citations
TL;DR: Performance of the proposed algorithm is compared to those of conventional coverage techniques to demonstrate its completeness of coverage, energy and time efficiency, and robustness to the environment shape or the initial robot pose.
100 citations
TL;DR: A parallel procedure is described which, applied to a connected image, originates a connected skeleton made by the union of simple digital arcs that ensures the possibility of recovering the original image by means of a reverse distance transform.
Abstract: In picture processing it is often convenient to deal with a stick-like version (skeleton) of binary digital images. Although skeleton connectedness is not necessary for storage and retrieval purposes, this property is desirable when a structural description of images is of interest. In this paper a parallel procedure is described which, applied to a connected image, originates a connected skeleton made by the union of simple digital arcs. The procedure involves a step by step propagation of the background over the image. At every step, contour elements either belonging to the significant convex regions of the current image or being local maxima of the original image are selected as skeleton elements. Since the final set so obtained is not ensured to be connected, the configurations in correspondence of which disconnections appear are investigated and the procedures to avoid this shortcoming are given. The presence of the whole set of local maxima among the skeleton elements ensures the possibility of recovering the original image by means of a reverse distance transform. The details of the program implementing the proposed algorithm on a parallel processor are finally included.
99 citations
TL;DR: In this paper, a gray image is considered as a two-dimensional surface, and the neighbor distance deduced from the oriented distance in differential geometry is used as a measure of pixel's sharpness, where the smooth image surface is restored by kernel regression.
97 citations
ARCO1
TL;DR: The skeletonization algorithm includes a beautifying step and a pruning step, which favour the use of the skeleton for shape analysis tasks, and is driven by the Euclidean distance map of the pattern.
97 citations