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On the Euclidean distance of images
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2005We present a new Euclidean distance for images, which we call IMage Euclidean Distance (IMED). Unlike the traditional Euclidean distance, IMED takes into account the spatial relationships of pixels. Therefore, it is robust to small perturbation of images. We argue that IMED is the only intuitively reasonable Euclidean distance for images.
Liwei Wang, Jufu Feng
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An adaptive image Euclidean distance
Pattern Recognition, 2009zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Bao-Liang Lu
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Ridge points in Euclidean distance maps
Pattern Recognition Letters, 1992Abstract Two types of ridge points are identified on the Euclidean distance map of a digital object. From this set, which is connected, the skeleton of the object is derived as a unit width subset. The use of the Euclidean distance map guarantees obtaining a skeleton with structure sufficiently stable under object rotation, and placed where it is ...
Carlo Arcelli +1 more
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On Euclidean Distances and Sphere Representations
Graphs and Combinatorics, 2023zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Proceedings of the 2014 Symposium on Symbolic-Numeric Computation, 2014
The nearest point map of a real algebraic variety with respect to Euclidean distance is an algebraic function. For instance, for varieties of low rank matrices, the Eckart-Young Theorem states that this map is given by the singular value decomposition.
Draisma, J. +4 more
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The nearest point map of a real algebraic variety with respect to Euclidean distance is an algebraic function. For instance, for varieties of low rank matrices, the Eckart-Young Theorem states that this map is given by the singular value decomposition.
Draisma, J. +4 more
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Euclidean and Geodesic Distance Profiles
2017This paper presents a boundary-based, topological shape descriptor: the distance profile. It is inspired by the LBP (= local binary pattern) scale space – a topological shape descriptor computed by a filtration with concentric circles around a reference point.
Ines Janusch +2 more
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A Parallel Euclidean Distance Transformation Algorithm
Computer Vision and Image Understanding, 1996We present a parallel algorithm for the Euclidean distance transformation (EDT). It is a “divide-and-conquer” algorithm based on a fast sequential algorithm for the signed EDT (SEDT). The combining step that follows the local partial calculation of the SEDT can be done efficiently after reformulating the SEDT problem as the partial calculation of a ...
Hugo Embrechts, Dirk Roose
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A systolic algorithm for Euclidean distance transform
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2006The Euclidean distance transform is one of the fundamental operations in image processing. It has been widely used in computer vision, pattern recognition, morphological filtering, and robotics. This paper proposes a systolic algorithm that computes the Euclidean distance map of an N x N binary image in 3N clocks on 2N(2) processing cells.
Masafumi Miyazawa +3 more
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Efficient Computation of the Euclidean Distance Transform
Computer Vision and Image Understanding, 2000Summary: We present a simple algorithm for the Euclidean distance transform of a binary image that runs more efficiently than other algorithms in the literature. We show that our algorithm runs in optimal time for many architectures and has optimal cost for the RAM and EREW PRAM.
Laurence Boxer, Russ Miller
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