Topic
Distance transform
About: Distance transform is a research topic. Over the lifetime, 2886 publications have been published within this topic receiving 59481 citations.
Papers published on a yearly basis
Papers
More filters
TL;DR: A new method for detecting linear bands in gray-scale images using a modified Hough transform and a new line segment detection method, which is practical and robust.
25 citations
Patent•
11 Mar 1999TL;DR: In this paper, an edge detection method employing binary morphological erosion is presented, where a structure element is guided in a step-by-step manner across the binary image and generates an eroded binary image in accordance with an erosion rule.
Abstract: An edge detection method employs binary morphological erosion. A binary image is generated from the gray-scale-value input image. A structure element is guided in a step-by-step manner across the binary image and generates an eroded binary image in accordance with an erosion rule. By forming the difference between the binary image and the eroded binary image, an output image containing the edges is generated. An output image which contains masked edges is generated through the use of a further erosion rule. The further erosion rule is based on a gray-scale value threshold and is applied to the eroded binary image to form a twice-eroded binary image. The difference between the twice-eroded binary image and the binary image forms the image which contains masked edges.
25 citations
28 Oct 2002
TL;DR: The proposed method is fast because much of the computation required to convert the line-of-sight range distances to Euclidean distances can be done during a pre-processing step in the 2D coordinate space of each range image.
Abstract: Several existing algorithms for reconstructing 3D models from range data first approximate the object's 3D distance field to provide an implicit representation of the scanned object and then construct a surface model of the object using this distance field. In these existing approaches, computing and storing 3D distance values from range data contribute significantly to the computational and storage requirements. This paper presents an efficient method for estimating the 3D Euclidean distance field from 2D range images that can be used by any of these algorithms. The proposed method uses Adaptively Sampled Distance Fields to minimize the number of distance evaluations and significantly reduce storage requirements of the sampled distance field. The method is fast because much of the computation required to convert the line-of-sight range distances to Euclidean distances can be done during a pre-processing step in the 2D coordinate space of each range image.
25 citations
TL;DR: In this paper, the authors presented different improvements of ODSIM methodology for simulating more realistic shapes in the particular case of karst, using a custom distance field computed with a fast marching method.
25 citations
TL;DR: This study proposes a method that is based on the Iterative Closest Point algorithm and a pre-computed closest point map obtained with a slight modification of the fast marching method proposed by Sethian and shows that on these data sets this registration method leads to accuracy numbers that are comparable to those obtained with voxel-based methods.
25 citations