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An optimal matching problem for the Euclidean distance
 SIAM J. Math. Anal
"... Abstract. We deal with an optimal matching problem, that is, we want to transport two measures to a given place, where they will match, minimizing the total transport cost that in our case is given by the sum of the Euclidean distance that each measure is transported. We show that such a problem ha ..."
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Cited by 9 (9 self)
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Abstract. We deal with an optimal matching problem, that is, we want to transport two measures to a given place, where they will match, minimizing the total transport cost that in our case is given by the sum of the Euclidean distance that each measure is transported. We show that such a problem
Statistical Modelling using Euclidean Distances
"... De Rooij and Heiser (2002a; 2002b) show how to use Euclidean distances as model terms in loglinear models for twoway contingency tables. The advantages of such an approach are that distance plots are easily interpretable, and instead of having a bunch of numbers all effects can be shown in a singl ..."
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De Rooij and Heiser (2002a; 2002b) show how to use Euclidean distances as model terms in loglinear models for twoway contingency tables. The advantages of such an approach are that distance plots are easily interpretable, and instead of having a bunch of numbers all effects can be shown in a
AntiAliased Euclidean Distance Transform
, 2010
"... We present a modified distance measure for use with distance transforms of antialiased, area sampled grayscale images of arbitrary binary contours. The modified measure can be used in any vectorpropagation Euclidean distance transform. Our test implementation in the traditional SSED8 algorithm sho ..."
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We present a modified distance measure for use with distance transforms of antialiased, area sampled grayscale images of arbitrary binary contours. The modified measure can be used in any vectorpropagation Euclidean distance transform. Our test implementation in the traditional SSED8 algorithm
Euclidean Distance Based Fingerprint Matching
"... Abstract — Forensic Science is an art and science of a print made by an impression of ridges in the skin of a finger, often used for biometric identification in criminal investigation. The law enforcement agencies uses system like AFIS (Automatic Fingerprint Identification System) where reference fi ..."
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filters for fingerprint identification. The fingerprint matching is done by extracting the Finger code from both reference and latent fingerprints and then finding the Euclidean distance between the two corresponding finger codes. After proper training the system, the result obtained provides 99 % rate
Speech Recognition Using Euclidean Distance
"... AbstractDigital processing of speech signal and voice recognition algorithm is very important for fast and accurate automatic voice recognition technology. The voice is a signal of infinite information. A direct analysis and synthesizing the complex voice signal is due to too much information conta ..."
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Cited by 3 (0 self)
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of spoken words. Verification is carried out using a weighted Euclidean distance. For speech recognition we implement the MFCC approach using software platform MatlabR2010b.
Linear Time Euclidean Distance Transform Algorithms
 IEEE Transactions on Pattern Analysis and Machine Intelligence
, 1995
"... Two linear time (and hence asymptotically optimal) algorithms for computing the Euclidean distance transform of a twodimensional binary image are presented. The algorithms are based on the construction and regular sampling of the Voronoi diagram whose sites consist of the unit (feature) pixels in t ..."
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Cited by 96 (0 self)
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Two linear time (and hence asymptotically optimal) algorithms for computing the Euclidean distance transform of a twodimensional binary image are presented. The algorithms are based on the construction and regular sampling of the Voronoi diagram whose sites consist of the unit (feature) pixels
Properties of Euclidean and nonEuclidean distance matrices
 LINEAR ALGEBRA APPL
, 1985
"... A distance matrix D of order n is symmetric with elements idfj, where d,, = 0. D is Euclidean when the in(n 1) quantities dij can be generated as the distances between a set of n points, X (n X p), in a Euclidean space of dimension p. The dimensionality of D is defined as the least value of p = r ..."
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Cited by 40 (1 self)
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A distance matrix D of order n is symmetric with elements idfj, where d,, = 0. D is Euclidean when the in(n 1) quantities dij can be generated as the distances between a set of n points, X (n X p), in a Euclidean space of dimension p. The dimensionality of D is defined as the least value of p
Fingerprint Matching of Normalized Image based on Euclidean Distance
"... Euclidean distance is one of the oldest methods for mapping distance between two points. It is highly demandable for matching process. Recently there are many techniques for matching fingerprints. Using Euclidean distance, minutiae based fingerprint matching gives accurate matching results. Euclidea ..."
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Euclidean distance is one of the oldest methods for mapping distance between two points. It is highly demandable for matching process. Recently there are many techniques for matching fingerprints. Using Euclidean distance, minutiae based fingerprint matching gives accurate matching results
Fast Exact Euclidean Distance (FEED) Transformation
"... Fast Exact Euclidean Distance (FEED) transformation is introduced, starting from the inverse of the distance transformation. The prohibitive computational cost of a naive implementation of traditional Euclidean Distance Transformation, is tackled by three operations: restriction of both the number ..."
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Cited by 2 (2 self)
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Fast Exact Euclidean Distance (FEED) transformation is introduced, starting from the inverse of the distance transformation. The prohibitive computational cost of a naive implementation of traditional Euclidean Distance Transformation, is tackled by three operations: restriction of both
Results 21  30
of
4,774