7.3.7 Distance Transforms, Distance Functions, Distance Measures

Rosenfeld, A., Pfaltz, J.L.,
Distance Functions on Digital Pictures,
PR(1), No. 1, July 1968, pp. 33-61.
Elsevier DOI Parallal distance. BibRef 6807

Jackson, D.M.[David M.], White, L.J.[Lee J.],
Effect of random errors on generalized distance computations,
PR(4), No. 3, October 1972, pp. 263-273.
Elsevier DOI 0309
BibRef

Fischler, M.A.[Martin A.],
Fast Algorithms for Two Maximal Distance Problems with Applications to Image Analysis,
PR(12), No. 1, 1980, pp. 35-40.
Elsevier DOI BibRef 8000

Yokoi, S., Toriwaki, J.I., Fukumura, T.,
On Generalized Distance Transformation of Digitized Pictures,
PAMI(3), No. 4, July 1981, pp. 424-443. BibRef 8107
Earlier:
Generalized Distance Transformation on Digitized Binary Images,
ICPR80(1201-1203). BibRef

Toriwaki, J.I., Naruse, T., Fukumura, T.,
Fundamental Properties of the Grey Weighted Distance Transformation of Grey Pictures,
IECE(60), 1977, pp. 1101-1108. BibRef 7700

Toriwaki, J.I.[Jun-Ichiro], Tanaka, M.[Masahiko], Fukumura, T.[Teruo],
A Generalized Distance Transformation of a Line Pattern with Grey Values and Its Application,
CGIP(20), No. 4, December 1982, pp. 319-346.
Elsevier DOI BibRef 8212
Earlier: ICPR80(35-37). BibRef

Danielsson, P.E.[Per-Erik],
Euclidean Distance Mapping,
CGIP(14), No. 3, November 1980, pp. 227-248.
Elsevier DOI How far is a point to some feature. BibRef 8011

Danielsson, P.E.[Per-Erik], Kruse, B.,
Distance Checking Algorithms,
CGIP(11), No. 4, December 1979, pp. 349-376.
Elsevier DOI
See also Process for Detecting Defects in Complicated Patterns, A. BibRef 7912

Roberts, S.J., Hanka, R.,
An interpretation of Mahalanobis distance in the dual space,
PR(15), No. 4, 1982, pp. 325-333.
Elsevier DOI 0309
BibRef

Krusinska, E.,
A valuation of state of object based on weighted Mahalanobis distance,
PR(20), No. 4, 1987, pp. 413-418.
Elsevier DOI 0309
Distance between object and multidimensional norm estimate. BibRef

Samet, H.,
Distance Transform for Images Represented by Quadtrees,
PAMI(4), No. 3, May 1982, pp. 298-303. BibRef 8205

Chazelle, B.,
An Improved Algorithm for the Fixed-Radius Neighbor Problem,
IPL(16), 1983, pp. 193-198. BibRef 8300

Bhattacharya, B.K., Toussaint, G.T.,
Efficient Algorithms for Computing the Maximum Distance,
Algorithms(4), 1983, pp. 121-126. BibRef 8300

Soille, P.,
Spatial Distributions from Contour Lines: An Efficient Methodology Based on Distance Transformations,
JVCIR(2), 1991, pp. 138-150. BibRef 9100

Soille, P.[Pierre],
Constrained Connectivity for Hierarchical Image Decomposition and Simplification,
PAMI(30), No. 7, July 2008, pp. 1132-1145.
IEEE DOI 0806
BibRef
Earlier:
On Genuine Connectivity Relations Based on Logical Predicates,
CIAP07(487-492).
IEEE DOI 0709
2 pixels are connected if the meet certain constraints, gray level differences over the connecting path. BibRef

Klein, F., Kubler, O.,
Euclidean Distance Transformations and Model-Guided Image Interpretation,
PRL(5), 1987, pp. 19-29. BibRef 8700

Das, P.P., Chakrabarti, P.P., Chatterji, B.N.,
Distance Functions in Digital Geometry,
IS(42), 1987, pp. 113-136. BibRef 8700

Das, P.P., Chatterji, B.N.,
Hyperspheres In Digital Geometry,
IS(50), 1990, pp. 73-91. BibRef 9000

Das, P.P., Chatterji, B.N.,
Knight's Distance in Digital Geometry,
PRL(7), 1988, pp. 215-226. BibRef 8800

Das, P.P.,
Counting Minimal Paths in Digital Geometry,
PRL(12), 1991, pp. 595-603. BibRef 9100
And:
An Algorithm for Computing the Number of the Minimal Paths in Digital Images,
PRL(9), 1989, pp. 107-116. BibRef

Das, P.P., Mukherjee, J.,
Metricity of Super-Knight's Distance in Digital Geometry,
PRL(11), 1990, pp. 601-604. BibRef 9000

Das, P.P., Chatterji, B.N.,
Octagonal Distances For Digital Pictures,
IS(50), 1990, pp. 123-150. BibRef 9000

Das, P.P., Chatterji, B.N.,
A Note on 'Distance Transformations in Arbitrary Dimensions',
CVGIP(43), No. 3, September 1988, pp. 368-385.
Elsevier DOI Proved the conjecture.
See also Distance Transformations in Arbitrary Dimensions. BibRef 8809

Das, P.P.,
Lattice of Octagonal Distances in Digital Geometry,
PRL(11), 1990, pp. 663-667. BibRef 9000

Das, P.P.,
More on Path Generated Digital Metrics,
PRL(10), 1989, pp. 25-31. BibRef 8900

Das, P.P.,
Metricity Preserving Transforms,
PRL(10), 1989, pp. 73-76. BibRef 8900

Rosenfeld, A.,
A Note on Average Distances in Digital Sets,
PRL(5), 1987, pp. 281-283. BibRef 8700

Borgefors, G.[Gunilla],
Distance Transformations in Digital Images,
CVGIP(34), No. 3, June 1986, pp. 344-371.
Elsevier DOI BibRef 8606
Earlier:
A New Distance Transformation Approximating the Euclidean Distance,
ICPR86(336-338). BibRef
And:
Another Comment on 'A Note on 'Distance Transformations in Digital Images'',
CVGIP(54), No. 2, September 1991, pp. 301-306.
Elsevier DOI
See also Note on Distance Transformations in Digital Images, A.
See also Comment on A Note on 'Distance Transformations in Digital Images', A. BibRef

Borgefors, G., Hartmann, T., Tanimoto, S.L.,
Parallel Distance Transforms on Pyramid Machines: Theory and Implementation,
SP(21), 1990, pp. 61-86. BibRef 9000

Vossepoel, A.M.[Albert M.],
A Note on 'Distance Transformations in Digital Images',
CVGIP(43), No. 1, July 1988, pp. 88-97.
Elsevier DOI
See also Distance Transformations in Digital Images.
See also Comment on A Note on 'Distance Transformations in Digital Images', A. BibRef 8807

Vossepoel, A.M.[Albert M.],
Estimating the size of circular pre-images from coarsely digitized representations,
ICPR92(III:365-368).
IEEE DOI 9208
probability of disks in set of pixels. BibRef

Beckers, A.L.D., Smeulders, A.W.M.,
A Comment on 'A Note on 'Distance Transformations in Digital Images'',
CVGIP(47), No. 1, July 1989, pp. 89-91.
Elsevier DOI
See also Note on Distance Transformations in Digital Images, A.
See also Distance Transformations in Digital Images. BibRef 8907

Yamashita, M.[Masafumi], Honda, N.[Namio],
Distance Functions Defined by Variable Neighborhood Sequences,
PR(17), No. 5, 1984, pp. 509-513.
Elsevier DOI 9611
BibRef

Yamashita, M.[Masafumi], Ibaraki, T.[Toshihide],
Distances Defined By Neighborhood Sequences,
PR(19), No. 3, 1986, pp. 237-246.
Elsevier DOI BibRef 8600

Piper, J.[Jim], Granum, E.[Erik],
Computing Distance Transformations in Convex and Non-Convex Domains,
PR(20), No. 6, 1987, pp. 599-615.
Elsevier DOI BibRef 8700

Verwer, B.J.H., Verbeek, P.W., Dekker, S.T.,
An Efficient Uniform Cost Algorithm Applied to Distance Transforms,
PAMI(11), No. 4, April 1989, pp. 425-429.
IEEE DOI BibRef 8904

Shih, F.Y., Wu, H.,
Optimization on Euclidean Distance Transformation Using Grayscale Morphology,
JVCIR(3), 1992, pp. 104-114. BibRef 9200

Shih, F.Y.[Frank Y.], Liu, J.J.[Jenny J.],
Size-invariant four-scan Euclidean distance transformation,
PR(31), No. 11, November 1998, pp. 1761-1766.
Elsevier DOI BibRef 9811

Shih, F.Y.[Frank Y.], Wu, Y.T.[Yi-Ta],
Fast Euclidean Distance Transformation in Two Scans Using a 3X3 Neighborhood,
CVIU(93), No. 2, February 2004, pp. 195-205.
Elsevier DOI 0402
Record relative X and Y and achieve distance in only 2 scans.
See also Fast Euclidean Distance Transformation by Propagation Using Multiple Neighborhoods.
See also Three-dimensional Euclidean distance transformation and its application to shortest path planning. BibRef

Shih, F.Y.[Frank Y.], Wu, Y.T.[Yi-Ta],
The Efficient Algorithms for Achieving Euclidean Distance Transformation,
IP(13), No. 8, August 2004, pp. 1078-1091.
IEEE DOI 0409
BibRef

Paglieroni, D.W.[David W.],
Distance Transforms: Properties and Machine Vision Applications,
GMIP(54), No. 1, January 1992, pp. 56-74. BibRef 9201

Paglieroni, D.W.,
A Unified Distance Transform Algorithm and Architecture,
MVA(5), 1992, pp. 47-55. BibRef 9200

Wang, X.L.[Xiao-Li], Bertrand, G.,
Some Sequential Algorithms for a Generalized Distance Transformation Based on Minkowski Operations,
PAMI(14), No. 11, November 1992, pp. 1114-1121.
IEEE DOI BibRef 9211
An Algorithm for a Generalized Distance Transformation Based on Minkowski Operations,
ICPR88(II: 1164-1168).
IEEE DOI BibRef

Ragnemalm, I.[Ingemar],
Neighborhoods for Distance Transformations Using Ordered Propagation,
CVGIP(56), No. 3, November 1992, pp. 399-409.
Elsevier DOI process only at the propagation front. BibRef 9211

Borgefors, G., Ragnemalm, I.[Ingemar], and Sanniti di Baja, G.[Gabriella],
Feature Extraction of the Euclidean Distance Transform,
CIAP91(115-122). BibRef 9100

Ragnemalm, I.,
The Euclidean Distance Transform in Arbitrary Dimensions,
PRL(14), 1993, pp. 883-888. BibRef 9300

Ragnemalm, I.,
Fast Erosion and Dilation by Contour Processing and Thresholding of Distance Maps,
PRL(13), 1992, pp. 161-166. BibRef 9200

Starovoitov, V.V.[Valery V.], Ablameyko, S.V.[Sergey V.], Ishikawa, S.[Seiji], Kawaguchi, E.[Eiji],
Binary Texture Border Extraction on Line Drawings Based on Distance Transform,
PR(26), No. 8, August 1993, pp. 1165-1176.
Elsevier DOI BibRef 9308

Breu, H., Gil, J., Kirkpatrick, D., Werman, M.,
Linear-Time Euclidean Distance Transform Algorithms,
PAMI(17), No. 5, May 1995, pp. 529-533.
IEEE DOI One theoretical algorithm and one practical algorithm, derive transform from a Voronoi diagram. BibRef 9505

Embrechts, H.[Hugo], Roose, D.[Dirk],
A Parallel Euclidean Distance Transformation Algorithm,
CVIU(63), No. 1, January 1996, pp. 15-26.
DOI Link BibRef 9601
Earlier:
Parallel algorithms for the distance transformation,
ECCV92(387-391).
Springer DOI 9205
BibRef

Starovoitov, V.V.,
A Clustering Technique Based on the Distance Transform,
PRL(17), No. 3, March 6 1996, pp. 231-239. BibRef 9603
Earlier:
Towards a measure of diversity between grey-scale images,
CAIP95(214-221).
Springer DOI 9509
BibRef

di Gesu, V.[Vito], Starovoitov, V.V.[Valery V.],
Distance-based functions for image comparison,
PRL(20), No. 2, February 1999, pp. 207-214. BibRef 9902

Starovoitov, V.V., Kose, C., Sankur, B.,
Generalized distance based matching of nonbinary images,
ICIP98(I: 803-807).
IEEE DOI 9810
BibRef

Toivanen, P.J.,
New Geodesic Distance Transforms for Gray-Scale Images,
PRL(17), No. 5, May 1 1996, pp. 437-450. 9606
BibRef
And: Correction: PRL(17), No. 13, November 25 1996, pp. 1411-1411. BibRef

Eggers, H.,
Parallel Euclidean Distance Transformations in Z(G)(N),
PRL(17), No. 7, June 10 1996, pp. 751-757. 9607
BibRef

Eggers, H.[Hinnik],
Two Fast Euclidean Distance Transformations in Z2 Based on Sufficient Propagation,
CVIU(69), No. 1, January 1998, pp. 106-116.
DOI Link BibRef 9801

Kiselman, C.O.,
Regularity Properties of Distance Transformations in Image-Analysis,
CVIU(64), No. 3, November 1996, pp. 390-398.
DOI Link 9612
BibRef

Chaudhuri, D., Murthy, C.A., Chaudhuri, B.B.,
A Modified Metric to Compute Distance,
PR(25), No. 7, July 1992, pp. 667-677.
Elsevier DOI Close to Euclidean, but more efficient. BibRef 9207

Huang, C.T.[C. Tony], Mitchell, O.R.[O. Robert],
A Euclidian Distance Transform Using Grayscale Morphology Decomposition,
PAMI(16), No. 4, April 1994, pp. 443-448.
IEEE DOI BibRef 9404
Earlier:
Rapid Euclidean Distance Transform Using Grayscale Morphology Decomposition,
CVPR91(695-697).
IEEE DOI
See also Threshold Decomposition of Gray-Scale Morphology into Binary Morphology. BibRef

Arcelli, C.[Carlo], Ramella, G.,
Sketching a Grey-Tone Pattern from Its Distance Transform,
PR(29), No. 12, December 1996, pp. 2033-2045.
Elsevier DOI 9701
BibRef

Coquin, D.[Didier], Bolon, P.[Philippe],
Discrete Distance Operator on Rectangular Grids,
PRL(16), 1995, pp. 911-923. BibRef 9500

Coquin, D.[Didier], Bolon, P.[Philippe],
Lower and Upper Bounds for Scaling Factors Used for Integer Approximation of 3D Anisotropic Chamfer Distance Operator,
DGCI09(457-468).
Springer DOI 0909
BibRef

Toivanen, P.J.,
Image Compression by Selecting Control Points Using Distance Function on Curved Space,
PRL(14), 1993, pp. 475-482. BibRef 9300

Rhodes, F.[Frank],
On the metrics of Chaudhuri, Murthy and Chaudhuri,
PR(28), No. 5, May 1995, pp. 745-752.
Elsevier DOI 0401
considers the approximation of Euclidean distance in n-dimensional space by linear combinations of the L1 and L-inf metrics.
See also Modified Metric to Compute Distance, A. BibRef

Rhodes, F.[Frank],
Some Characterizations of the Chessboard Metric and the City Block Metric,
PRL(11), 1990, pp. 669-675. BibRef 9000

Melter, R.A.,
Some Characterizations of City Block Distance,
PRL(6), 1987, pp. 235-240. BibRef 8700

Brown, R.L.,
The Fringe Distance Measure: An Easily Calculated Image Distance Measure with Recognition Results Comparable to Gaussian Blurring,
SMC(24), 1994, pp. 111-115. BibRef 9400

Lee, Y.H., Horng, S.J., Kao, T.W., Chen, Y.J.,
Parallel Computation of the Euclidean Distance transform on the Mesh of Trees and the Hypercube Computer,
CVIU(68), No. 1, October 1997, pp. 109-119.
DOI Link 9710
BibRef

Lee, Y.H.[Yu-Hua], Horng, S.J.[Shi-Jinn],
Optimal Computing the Chessboard Distance Transform on Parallel Processing Systems,
CVIU(73), No. 3, March 1999, pp. 374-390.
DOI Link BibRef 9903

Juffs, P., Beggs, E., Deravi, F.,
A Multiresolution Distance Measure for Images,
SPLetters(5), No. 6, June 1998, pp. 138-140.
IEEE Top Reference. 9806
BibRef

Butt, M.A., Maragos, P.,
Optimum Design of Chamfer Distance Transforms,
IP(7), No. 10, October 1998, pp. 1477-1484.
IEEE DOI BibRef 9810

Kaijser, T.,
Computing the Kantorovich Distance for Images,
JMIV(9), No. 2, September 1998, pp. 173-191.
DOI Link 9811
BibRef

Pennec, X., Ayache, N.J.,
Uniform Distribution, Distance and Expectation Problems for Geometric Features Processing,
JMIV(9), No. 1, July 1998, pp. 49-67.
DOI Link 9807
BibRef

Maekawa, T.,
An overview of offset curves and surfaces,
CAD(31), No. 3, March 1999, pp. 165-173. BibRef 9903

Maekawa, T., Patrikalakis, N.M.,
Computation of singularities and intersections of offsets of planar curves,
CAGD(10), No. 5, 1993, pp. 407-429. BibRef 9300

Marchand-Maillet, S.[Stephane], Sharaiha, Y.M.[Yazid M.],
Euclidean Ordering via Chamfer Distance Calculations,
CVIU(73), No. 3, March 1999, pp. 404-413.
DOI Link BibRef 9903
And:
A Graph-Theoretic Algorithm for the Exact Generation of Euclidean Distance Maps,
SCIA97(xx-yy)
HTML Version. 9705
BibRef

Takala, J.H.[Jarmo H.], Viitanen, J.O.[Jouko O.],
Distance Transform Algorithm for Bit-Serial SIMD Architectures,
CVIU(74), No. 2, May 1999, pp. 150-161.
DOI Link BibRef 9905
Earlier: A2, A1:
SIMD parallel calculation of distance transformations,
ICIP94(III: 645-649).
IEEE DOI 9411
BibRef

Bloch, I.[Isabelle],
On fuzzy distances and their use in image processing under imprecision,
PR(32), No. 11, November 1999, pp. 1873-1895.
Elsevier DOI
See also Fuzzy Connectivity and Mathematical Morphology. BibRef 9911

Bloch, I.[Isabelle],
Geodesic balls in a fuzzy set and fuzzy geodesic mathematical morphology,
PR(33), No. 6, June 2000, pp. 897-905.
Elsevier DOI 0004
Fuzzy distances between fuzzy sets. BibRef

Bloch, I.[Isabelle],
On links between mathematical morphology and rough sets,
PR(33), No. 9, September 2000, pp. 1487-1496.
Elsevier DOI 0005
BibRef

Ramponi, G.,
Warped Distance for Space-Variant Linear Image Interpolation,
IP(8), No. 5, May 1999, pp. 629-639.
IEEE DOI BibRef 9905

Zhang, S., Karim, M.A.,
Euclidean Distance Transform by Stack Filters,
SPLetters(6), No. 10, October 1999, pp. 253.
IEEE Top Reference. BibRef 9910

Cuisenaire, O., Macq, B.,
Fast Euclidean Distance Transformation by Propagation Using Multiple Neighborhoods,
CVIU(76), No. 2, November 1999, pp. 163-172.
DOI Link 9911
Also use bucket sort. BibRef

Toivanen, P.J.[Pekka J.], Vepsäläinen, A.M.[Ari M.], Parkkinen, J.P.S.[Jussi P.S.],
Image Compression Using the Distance Transform on Curved Space (DTOCS) and Delaunay Triangulation,
PRL(20), No. 10, October 1999, pp. 1015-1026. 9911
BibRef
Earlier:
Image Compression Using the DTOCS and Delaunay Triangulation,
SCIA97(xx-yy)
HTML Version. 9705
BibRef

Pan, Y., Hamdi, M., Li, K.,
Euclidean Distance Transform for Binary Images on Reconfigurable Mesh-Connected Computers,
SMC-B(30), No. 1, February 2000, pp. 240-243.
IEEE Top Reference. 0004

See also Improved Constant-Time Algorithm for Computing the Radon and Hough Transforms on a Reconfigurable Mesh, An. BibRef

Gomes, J.[José], Faugeras, O.D.[Olivier D.],
Reconciling Distance Functions and Level Sets,
JVCIR(11), No. 2, June 2000, pp. 209-223. 0008
BibRef
Earlier: ScaleSpace99(70-81). BibRef

Gomes, J.[José], Faugeras, O.D.[Olivier D.],
The Vector Distance Functions,
IJCV(52), No. 2-3, May-June 2003, pp. 161-187.
DOI Link 0301
BibRef
Earlier:
Using the vector distance functions to evolve manifolds of arbitrary codimension,
ScaleSpace01(xx-yy). 0106
BibRef
Earlier:
Level Sets and Distance Functions,
ECCV00(I: 588-602).
Springer DOI 0003
BibRef

Mukherjee, J., Das, P.P., Kumar, M.A.[M. Aswatha], Chatterji, B.N.,
On approximating Euclidean metrics by digital distances in 2D and 3D,
PRL(21), No. 6-7, June 2000, pp. 573-582. 0006
BibRef

Chang, C.C., Chou, J.S., Chen, T.S.,
An Efficient Computation of Euclidean Distance Using Approximated Look-Up Table,
CirSysVideo(10), No. 4, June 2000, pp. 594-599.
IEEE Top Reference. 0006
BibRef

Boxer, L.[Laurence], Miller, R.[Russ],
Efficient Computation of the Euclidean Distance Transform,
CVIU(80), No. 3, December 2000, pp. 379-383.
DOI Link 0012
BibRef
And: Corrigendum: CVIU(86), No. 2, May 2002, pp. 137-140.
DOI Link 0301
BibRef

Sebe, N.[Nicu], Lew, M.S.[Michael S.], Huijsmans, D.P.[Dionysius P.],
Toward Improved Ranking Metrics,
PAMI(22), No. 10, October 2000, pp. 1132-1143.
IEEE DOI 0011
Evaluation. Distance Measures. Applied to contyent based retrieval, stereo matching and motion tracking. Comparison of various metrics (SSD, SAD, Cauchy, Kullback). Cauchy was better. BibRef

Satherley, R.[Richard], Jones, M.W.[Mark W.],
Vector-City Vector Distance Transform,
CVIU(82), No. 3, June 2001, pp. 238-254.
DOI Link City-block chamfer distance transform. 0108
BibRef

Maurer, C.R.[Calvin R.], Qi, R.S.[Ren-Sheng], Raghavan, V.[Vijay],
A linear time algorithm for computing exact euclidean distance transforms of binary images in arbitrary dimensions,
PAMI(25), No. 2, February 2003, pp. 265-270.
IEEE DOI 0301
For k-dimensional images. Based on dimensionality reduction and partial Voronoi diagram reconstructions. BibRef

Saha, P.K.[Punam K.], Wehrli, F.W.[Felix W.], Gomberg, B.R.[Bryon R.],
Fuzzy Distance Transform: Theory, Algorithms, and Applications,
CVIU(86), No. 3, June 2002, pp. 171-190.
DOI Link 0301
BibRef

Datta, A., Soundaralakshmi, S.,
Fast parallel algorithm for distance transform,
SMC-A(33), No. 4, July 2003, pp. 429-434.
IEEE Abstract. 0310
BibRef

Zhang, Y.G.[Yun Gang], Zhang, C.S.[Chang Shui], Zhang, D.[David],
Distance metric learning by knowledge embedding,
PR(37), No. 1, January 2004, pp. 161-163.
Elsevier DOI 0311
BibRef
And: Erratum: PR(37), No. 4, April 2004, pp. Page 855.
Elsevier DOI 0403
BibRef

Grevera, G.J.[George J.],
The 'dead reckoning' signed distance transform,
CVIU(95), No. 3, September 2004, pp. 317-333.
Elsevier DOI 0409
Modification to Chamfer distance based loosely on dead reckoning navigation. More efficient and accurate. BibRef

Ikonen, L.[Leena], Toivanen, P.J.[Pekka J.],
Shortest routes on varying height surfaces using gray-level distance transforms,
IVC(23), No. 2, 1 February 2004, pp. 133-141.
Elsevier DOI 0412
distance on curved space. BibRef

Ikonen, L.[Leena], Toivanen, P.J.[Pekka J.],
Distance and nearest neighbor transforms on gray-level surfaces,
PRL(28), No. 5, 1 April 2007, pp. 604-612.
Elsevier DOI 0703
Distance transforms; Gray-level distance transforms; Nearest neighbor transforms; Geodesic distances; Minimal geodesics; Surface roughness BibRef

Ikonen, L.[Leena], Toivanen, P.J.[Pekka J.], Tuominen, J.[Janne],
Shortest Route on Gray-Level Map Using Distance Transform on Curved Space,
SCIA03(305-310).
Springer DOI 0310
BibRef

Ikonen, L.[Leena],
Priority pixel queue algorithm for geodesic distance transforms,
IVC(25), No. 10, 1 October 2007, pp. 1520-1529.
Elsevier DOI 0709
Distance transforms; Gray-level distance transforms; Nearest neighbor transforms; Minimal geodesics; Pixel queue algorithms BibRef

Toivanen, P.J.[Pekka J.], Lenz, R.[Reiner],
On the Properties of Gray-scale Distance Transforms,
SCIA01(O-M4B). 0206
BibRef

Fouard, C.[Céline], Malandain, G.[Grégoire],
3-D chamfer distances and norms in anisotropic grids,
IVC(23), No. 2, 1 February 2004, pp. 143-158.
Elsevier DOI 0412
BibRef
Earlier:
Automatic calculation of chamfer mask coefficients for large masks and anisotropic images pages.,
INRIARR-4792, Mars 2003.
HTML Version. 0306
BibRef

Ong, E.J.[Eng-Jon], Bowden, R.[Richard],
Learning multi-kernel distance functions using relative comparisons,
PR(38), No. 12, December 2005, pp. 2653-2657.
Elsevier DOI 0510
BibRef
And:
Learning Distances for Arbitrary Visual Features,
BMVC06(II:749).
PDF File. 0609
BibRef
And:
Learning Wormholes for Sparsely Labelled Clustering,
ICPR06(I: 916-919).
IEEE DOI 0609

See also Learning Sequential Patterns for Lipreading. BibRef

Miyazawa, M., Zeng, P.F.[Pei-Feng], Iso, N., Hirata, T.,
A Systolic Algorithm for Euclidean Distance Transform,
PAMI(28), No. 7, July 2006, pp. 1127-1134.
IEEE DOI 0606
Computes the Euclidean distance map of an NXN binary image in 3N clocks on 2N^2 processing cells. BibRef

Nayak, A.[Arvind], Trucco, E.[Emanuele], Thacker, N.A.[Neil A.],
When are Simple LS Estimators Enough? An Empirical Study of LS, TLS, and GTLS,
IJCV(68), No. 2, June 2006, pp. 203-216.
Springer DOI 0606
least squares; total least squares; generalized total least squares. Study the various errors to determine whether simpler model can be used. BibRef

Guderlei, R., Klenk, S., Mayer, J., Schmidt, V., Spodarev, E.,
Algorithms for the computation of the Minkowski functionals of deterministic and random polyconvex sets,
IVC(25), No. 4, April 2007, pp. 464-474.
Elsevier DOI 0702
Binary image; Intrinsic volume; Querma[ss] integral; Minkowski functional; Area; Boundary length; Euler-Poincare characteristic; Stationary random closed set; Random field; Volume fraction; Steiner formula; Principal kinematic formula; Parallel set BibRef

Lee, D.J.[Dah-Jye], Archibald, J.[James], Xu, X.Q.[Xiao-Qian], Zhan, P.C.[Peng-Cheng],
Using distance transform to solve real-time machine vision inspection problems,
MVA(18), No. 2, April 2007, pp. 85-93.
Springer DOI 0704
BibRef

Fouard, C.[Celine], Strand, R.[Robin], Borgefors, G.[Gunilla],
Weighted distance transforms generalized to modules and their computation on point lattices,
PR(40), No. 9, September 2007, pp. 2453-2474.
Elsevier DOI 0705
Weighted distance; Distance transform; Chamfer algorithm; Non-standard grids BibRef

Rauber, T.W., Braun, T., Berns, K.,
Probabilistic distance measures of the Dirichlet and Beta distributions,
PR(41), No. 2, February 2008, pp. 637-645.
Elsevier DOI 0711
Probabilistic distance measures; Chernoff distance; Bhattacharyya distance; Dirichlet distribution; Beta distribution BibRef

Rauber, T.W., Conci, A., Braun, T., Berns, K.,
Bhattacharyya probabilistic distance of the Dirichlet density and its application to Split-and-Merge image segmentation,
WSSIP08(145-148).
IEEE DOI 0806
BibRef

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A Fast Marching Method for the Area Based Affine Distance,
JMIV(30), No. 1, January 2008, pp. 1-12.
Springer DOI 0801
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McCane, B.[Brendan], Albert, M.[Michael],
Distance functions for categorical and mixed variables,
PRL(29), No. 7, 1 May 2008, pp. 986-993.
Elsevier DOI 0804
Categorical data; Mahalanobis distance; Distance functions BibRef

Fabbri, R.[Ricardo], da Fontoura Costa, L.[Luciano], Torelli, J.C.[Julio C.], Bruno, O.M.[Odemir M.],
2D Euclidean distance transform algorithms: A comparative survey,
Surveys(40), No. 1, February 2008, pp. 1-44.
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IJIG(1), No. 4, October 2001, pp. 635-645. 0110
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PR(42), No. 3, March 2009, pp. 349-357.
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Image similarity; Image Euclidean distance; Image metric; Gender classification BibRef

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New sequential exact Euclidean distance transform algorithms based on convex analysis,
IVC(27), No. 1-2, January 2009, pp. 37-44.
Elsevier DOI 0811
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A Linear Euclidean Distance Transform Algorithm Based on the Linear-Time Legendre Transform,
CRV05(262-267).
IEEE DOI 0505
Distance transform; Euclidean distance; Feature transform; Fast Legendre transform; Legendre-Fenchel transform; Fenchel conjugate; Moreau envelope; Moreau-Yosida approximate; Computational convex analysis BibRef

Cardenes, R.[Ruben], Alberola-Lopez, C.[Carlos], Ruiz-Alzola, J.[Juan],
Fast and accurate geodesic distance transform by ordered propagation,
IVC(28), No. 3, March 2010, pp. 307-316.
Elsevier DOI 1001
Distance transform; Geodesic distance transform; Geodesic metric; Hidden pixels; Ordered propagation; Visibility BibRef

Cardenes, R., Warfield, S.K., Mewes, A.J.U., Ruiz-Alzola, J.,
K-voronoi diagrams computing in arbitrary domains,
ICIP03(II: 941-944).
IEEE DOI 0312
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Cardenes, R., Warfield, S.K., Macias, E., Ruiz-Alzola, J.,
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Zhao, Q.[Qi], Yang, Z.[Zhi], Tao, H.[Hai],
Differential Earth Mover's Distance with Its Applications to Visual Tracking,
PAMI(32), No. 2, February 2010, pp. 274-287.
IEEE DOI 1001
Simplified computational model for EMD. BibRef

Son, J.[Joken], Inoue, N.[Naoya], Yamashtia, Y.[Yukihiko],
Geometrically local isotropic independence and numerical analysis of the Mahalanobis metric in vector space,
PRL(31), No. 8, 1 June 2010, pp. 709-716.
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Numerical analysis of Mahalanobis metric in vector space,
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Mahalanobis metric; Mahalanobis distance; Manifold; Geometrically local isotropic independence; Newton-Raphson method. Probabilistic distance for non-normal distribution. BibRef

Ma, Y.[Yu], Gu, X.D.[Xiao-Dong], Wang, Y.Y.[Yuan-Yuan],
Histogram similarity measure using variable bin size distance,
CVIU(114), No. 8, August 2010, pp. 981-989.
Elsevier DOI 1007
Variable bin size distance (VBSD); Histogram similarity; Histogram distance; Image retrieval BibRef

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Local Distance Functions: A Taxonomy, New Algorithms, and an Evaluation,
PAMI(33), No. 4, April 2011, pp. 794-806.
IEEE DOI 1103
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IEEE DOI 0909
Survey, Distance Functions. Classify by how, where and when they estimate geodesic distance defined by the metric tensor. BibRef

Mukherjee, J.[Jayanta],
On approximating Euclidean metrics by weighted t-cost distances in arbitrary dimension,
PRL(32), No. 6, 15 April 2011, pp. 824-831.
Elsevier DOI 1103
Digital geometry; t-cost distances; Euclidean norm; m-Neighbor distances; Octagonal distances; Hypersphere BibRef

Mukherjee, J.[Jayanta],
Hyperspheres of weighted distances in arbitrary dimension,
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Elsevier DOI 1212
Weighted distance; Euclidean distance; Octagonal distance; Hypersphere BibRef

Mukherjee, J.[Jayanta],
Linear combination of weighted t-cost and chamfering weighted distances,
PRL(40), No. 1, 2014, pp. 72-79.
Elsevier DOI 1403
Chamfering weighted distance BibRef

Mukherjee, J.[Jayanta],
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Maximum relative error (MRE) BibRef

Ciesielski, K.C.[Krzysztof Chris], Chen, X.J.[Xin-Jian], Udupa, J.K.[Jayaram K.], Grevera, G.J.[George J.],
Linear Time Algorithms for Exact Distance Transform,
JMIV(39), No. 3, March 2011, pp. 193-209.
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PR(43), No. 10, October 2010, pp. 3348-3358.
Elsevier DOI 1007
Squared Euclidean distance transformation; Irregular grids; Quadtree; Run length encoding; Voronoi diagram; Medial axis extraction BibRef

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2D Subquadratic Separable Distance Transformation for Path-Based Norms,
DGCI14(75-87).
Springer DOI 1410
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Earlier:
Distance transformation, reverse distance transformation and discrete medial axis on toric spaces,
ICPR08(1-4).
IEEE DOI 0812
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Vacavant, A.[Antoine], Coeurjolly, D.[David], Tougne, L.[Laure],
Separable algorithms for distance transformations on irregular grids,
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Elsevier DOI 1101
BibRef
Earlier:
A Novel Algorithm for Distance Transformation on Irregular Isothetic Grids,
DGCI09(469-480).
Springer DOI 0909
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Earlier:
Distance Transformation on Two-Dimensional Irregular Isothetic Grids,
DGCI08(xx-yy).
Springer DOI 0804
BibRef
Earlier:
Dynamic Reconstruction of Complex Planar Objects on Irregular Isothetic Grids,
ISVC06(II: 205-214).
Springer DOI 0611
BibRef
Earlier: Dymanic extension of:
Topological and geometrical reconstruction of complex objects on irregular isothetic grids,
DGCI06(xx-yy). Squared Euclidean distance transformation; Irregular grids; Quadtree; Voronoi diagrams BibRef

Rabin, J.[Julien], Delon, J.[Julie], Gousseau, Y.[Yann],
Transportation Distances on the Circle,
JMIV(41), No. 1-2, September 2011, pp. 147-167.
WWW Link. 1108
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Earlier:
Circular Earth Mover's Distance for the comparison of local features,
ICPR08(1-4).
IEEE DOI 0812
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Twining, C.J.[Carole J.], Taylor, C.J.[Christopher J.],
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PAMI(33), No. 12, December 2011, pp. 2492-2505.
IEEE DOI 1110
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Specificity as a Graph-Based Estimator of Cross-Entropy and KL Divergence,
BMVC06(II:59).
PDF File. 0609
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Celebi, M.E.[M. Emre], Kingravi, H.A.[Hassan A.], Celiker, F.[Fatih],
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PRL(33), No. 10, 15 July 2012, pp. 1422-1425.
Elsevier DOI 1205
Euclidean distance; Weighted t-cost distance; Norm approximation
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Antón-Canalís, L.[Luis], Hernández-Tejera, M.[Mario], Sánchez-Nielsen, E.[Elena],
Distance Maps from Unthresholded Magnitudes,
PR(45), No. 9, September 2012, pp. 3125-3130.
Elsevier DOI 1206
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Earlier: IbPRIA11(92-99).
Springer DOI 1106
BibRef
Earlier:
Analysis of Relevant Maxima in Distance Transform. An Application to Fast Coarse Image Segmentation,
IbPRIA07(I: 97-104).
Springer DOI 0706
Distance transform; Distance map; Pseudodistance BibRef

Lagerstrom, R.[Ryan], Buckley, M.[Michael],
An attribute weighted distance transform,
PRL(33), No. 16, 1 December 2012, pp. 2141-2147.
Elsevier DOI 1210
Euclidean distance transform; Mathematical morphology; Adaptive filtering BibRef

Ni, B.B., Yan, S.C., Wang, M., Kassim, A.A., Tian, Q.,
High-Order Local Spatial Context Modeling by Spatialized Random Forest,
IP(22), No. 2, February 2013, pp. 739-751.
IEEE DOI 1302
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Feng, J.S.[Jia-Shi], Ni, B.B.[Bing-Bing], Tian, Q.[Qi], Yan, S.C.[Shui-Cheng],
Geometric LP-norm feature pooling for image classification,
CVPR11(2609-2704).
IEEE DOI 1106
aggregate local features. Average and Max are common, but not best. Perserve geometric information. BibRef

Normand, N.[Nicolas], Strand, R.[Robin], Evenou, P.[Pierre], Arlicot, A.[Aurore],
Minimal-delay distance transform for neighborhood-sequence distances in 2D and 3D,
CVIU(117), No. 4, April 2013, pp. 409-417.
Elsevier DOI 1303
BibRef
Earlier:
Path-Based Distance with Varying Weights and Neighborhood Sequences,
DGCI11(199-210).
Springer DOI 1104
Distance transform; Neighborhood-sequence distance; Minkowski Sum; Lambek-Moser inverse; Beatty sequence BibRef

Normand, N.[Nicolas], Strand, R.[Robin], Evenou, P.[Pierre], Arlicot, A.[Aurore],
A Streaming Distance Transform Algorithm for Neighborhood-Sequence Distances,
IPOL(2014), No. 2014, pp. 196-203.
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Nagy, B.[Benedek], Strand, R.[Robin], Normand, N.[Nicolas],
Distance Functions Based on Multiple Types of Weighted Steps Combined with Neighborhood Sequences,
JMIV(60), No. 8, October 2018, pp. 1209-1219.
Springer DOI 1810
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Normand, N.[Nicolas], Strand, R.[Robin], Evenou, P.[Pierre],
Digital Distances and Integer Sequences,
DGCI13(169-179).
Springer DOI 1304
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Strand, R.[Robin], Ciesielski, K.C.[Krzysztof Chris], Malmberg, F.[Filip], Saha, P.K.[Punam K.],
The minimum barrier distance,
CVIU(117), No. 4, April 2013, pp. 429-437.
Elsevier DOI 1303
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The Minimum Barrier Distance: A Summary of Recent Advances,
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Springer DOI 1711
Image processing; Distance function; Distance transform; Fuzzy subset; Path strength BibRef

Strand, R.[Robin], Malmberg, F.[Filip], Saha, P.K.[Punam K.], Linnér, E.[Elisabeth],
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Springer DOI 1410
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Ciesielski, K.C.[Krzysztof Chris], Strand, R.[Robin], Malmberg, F.[Filip], Saha, P.K.[Punam K.],
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Elsevier DOI 1405
Image processing BibRef

Jiang, L.X.[Liang-Xiao], Li, C.Q.[Chao-Qun],
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Elsevier DOI 1306
Value Difference Metric; The memory-based reasoning transform; The attribute independence assumption; Distance measure BibRef

Mukherjee, J.[Jayanta],
Linear combination of norms in improving approximation of Euclidean norm,
PRL(34), No. 12, 1 September 2013, pp. 1348-1355.
Elsevier DOI 1306
Weighted distance; t-Cost distance; Weighted-t-cost distance; Euclidean distance BibRef

Sun, C.S.[Chen-Sheng], Lam, K.M.[Kin-Man],
Multiple-Kernel, Multiple-Instance Similarity Features for Efficient Visual Object Detection,
IP(22), No. 8, 2013, pp. 3050-3061.
IEEE DOI 1307
coarse-to-fine learning; kernel machines BibRef

Lindblad, J.[Joakim], Sladoje, N.[Nataša],
Linear Time Distances Between Fuzzy Sets With Applications to Pattern Matching and Classification,
IP(23), No. 1, January 2014, pp. 126-136.
IEEE DOI 1402
BibRef
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Exact Linear Time Euclidean Distance Transforms of Grid Line Sampled Shapes,
ISMM15(645-656).
Springer DOI 1506
fuzzy set theory BibRef

Öfverstedt, J.[Johan], Sladoje, N.[Nataša], Lindblad, J.[Joakim],
Distance Between Vector-Valued Fuzzy Sets Based on Intersection Decomposition with Applications in Object Detection,
ISMM17(395-407).
Springer DOI 1706
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Sladoje, N.[Nataša], Lindblad, J.[Joakim],
Distance Between Vector-Valued Representations of Objects in Images with Application in Object Detection and Classification,
IWCIA17(243-255).
Springer DOI 1706
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And:
Estimation of Moments of Digitized Objects with Fuzzy Borders,
CIAP05(188-195).
Springer DOI 0509
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Jing, Y.S.[Yu-Shi], Covell, M., Tsai, D., Rehg, J.M.,
Learning Query-Specific Distance Functions for Large-Scale Web Image Search,
MultMed(15), No. 8, December 2013, pp. 2022-2034.
IEEE DOI 1402
Internet BibRef

Schouten, T.E.[Theo E.], van den Broek, E.L.[Egon L.],
Fast Exact Euclidean Distance (FEED): A New Class of Adaptable Distance Transforms,
PAMI(36), No. 11, November 2014, pp. 2159-2172.
IEEE DOI 1410
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Earlier:
Incremental Distance Transforms (IDT),
ICPR10(237-240).
IEEE DOI 1008
BibRef
Earlier:
Fast exact euclidean distance (FEED) transformation,
ICPR04(III: 594-597).
IEEE DOI 0409
Algorithm design and analysis BibRef

Zhang, Y.[Yu], Wu, J.X.[Jian-Xin], Cai, J.F.[Jian-Fei], Lin, W.Y.[Wei-Yao],
Flexible Image Similarity Computation Using Hyper-Spatial Matching,
IP(23), No. 9, September 2014, pp. 4112-4125.
IEEE DOI 1410
computer vision BibRef

Werner, D.[Diana], Werner, P.[Philipp], Al-Hamadi, A.[Ayoub],
Quantitative Analysis of Surface Reconstruction Accuracy Achievable with the TSDF Representation,
CVS15(167-176).
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Earlier: A1, A3, A2:
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Wei, J.[Jie],
On Markov Earth Mover's Distance,
IJIG(14), No. 04, 2014, pp. 1450016.
DOI Link 1412
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Mishchenko, Y.[Yuriy],
A fast algorithm for computation of discrete Euclidean distance transform in three or more dimensions on vector processing architectures,
SIViP(9), No. 1, January 2015, pp. 19-27.
WWW Link. 1503
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Mennucci, A.C.G., Duci, A.,
Banach-Like Distances and Metric Spaces of Compact Sets,
SIIMS(8), No. 1, 2015, pp. 19-66.
DOI Link 1503
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Baum, M., Willett, P., Hanebeck, U.D.,
On Wasserstein Barycenters and MMOSPA Estimation,
SPLetters(22), No. 10, October 2015, pp. 1511-1515.
IEEE DOI 1506
Barycenter: a measure of similarity between images. Minimum Mean Optimal Sub-Pattern Assignment for tracking. approximation theory BibRef

Harel, M., Mannor, S.,
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PAMI(37), No. 10, October 2015, pp. 2119-2130.
IEEE DOI 1509
Complexity theory. Descrepancy measure between 2 distributions. BibRef

Taha, A.A.[Abdel Aziz], Hanbury, A.[Allan],
An Efficient Algorithm for Calculating the Exact Hausdorff Distance,
PAMI(37), No. 11, November 2015, pp. 2153-2163.
IEEE DOI 1511
computational complexity BibRef

Correa-Morris, J.[Jyrko], Martínez-Díaz, Y.[Yoanna], Hernández, N.[Noslen], Méndez-Vázquez, H.[Heydi],
Novel histograms kernels with structural properties,
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Histogram similarity BibRef

Jin, C.[Cong], Jin, S.W.[Shu-Wei],
Image distance metric learning based on neighborhood sets for automatic image annotation,
JVCIR(34), No. 1, 2016, pp. 167-175.
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Automatic image annotation
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Jin, C.[Cong], Jin, S.W.[Shu-Wei],
Content-based image retrieval model based on cost sensitive learning,
JVCIR(55), 2018, pp. 720-728.
Elsevier DOI 1809
Content-based image retrieval, Distance metric learning, Cost sensitive learning, Classification performance, Class imbalance
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El Moataz, A.[Abderrahim], Toutain, M.[Matthieu], Tenbrinck, D.[Daniel],
On the p-Laplacian and inf-Laplacian on Graphs with Applications in Image and Data Processing,
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Alvarez, L.[Luis], Cuenca, C.[Carmelo], Esclarín, J.[Julio], Mazorra, L.[Luis], Morel, J.M.[Jean-Michel],
Affine Invariant Distance Using Multiscale Analysis,
JMIV(55), No. 2, June 2016, pp. 199-209.
Springer DOI 1604
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Toutain, M.[Matthieu], Elmoataz, A.[Abderrahim], Lozes, F.[François], Mansouri, A.[Alamin],
Non-local Discrete INF-Poisson and Hamilton Jacobi Equations,
JMIV(55), No. 2, June 2016, pp. 229-241.
Springer DOI 1604
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Genctav, M.[Murat], Genctav, A.[Asli], Tari, S.[Sibel],
NonLocal via Local-NonLinear via Linear: A New Part-coding Distance Field via Screened Poisson Equation,
JMIV(55), No. 2, June 2016, pp. 242-252.
Springer DOI 1604
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Režnáková, M.[Marta], Tencer, L.[Lukas], Cheriet, M.[Mohamed],
Incremental Similarity for real-time on-line incremental learning systems,
PRL(74), No. 1, 2016, pp. 61-67.
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Incremental learning BibRef

Wang, K.[Ke], Yong, B.[Bin],
Application of the Frequency Spectrum to Spectral Similarity Measures,
RS(8), No. 4, 2016, pp. 344.
DOI Link 1604
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Zhai, Y.H.[Yuan-Hao], Neuhoff, D.L.[David L.],
Similarity of Scenic Bilevel Images,
IP(25), No. 11, November 2016, pp. 5063-5076.
IEEE DOI 1610
image processing BibRef

Peng, J.T.[Jiang-Tao], Zhang, L.[Lefei], Li, L.Q.[Luo-Qing],
Regularized set-to-set distance metric learning for hyperspectral image classification,
PRL(83, Part 2), No. 1, 2016, pp. 143-151.
Elsevier DOI 1609
Hyperspectral image classification BibRef

Xavier, E.M.A.[Emerson M. A.], Ariza-López, F.J.[Francisco J.], Ureña-Cámara, M.A.[Manuel A.],
A Survey of Measures and Methods for Matching Geospatial Vector Datasets,
Surveys(48), No. 3, February 2016, pp. 39.
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Survey, Geospatial Matching. Survey of procedures to find the correspondences between two vector datasets and similarity measures. BibRef

Ruiz-Lendínez, J.J.[Juan J.], Ureña-Cámara, M.A.[Manuel A.], Ariza-López, F.J.[Francisco J.],
A Polygon and Point-Based Approach to Matching Geospatial Features,
IJGI(6), No. 12, 2017, pp. xx-yy.
DOI Link 1801
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Chen, Y.L.[Yi-Lin], He, F.[Fazhi], Wu, Y.[Yiqi], Hou, N.[Neng],
A local start search algorithm to compute exact Hausdorff Distance for arbitrary point sets,
PR(67), No. 1, 2017, pp. 139-148.
Elsevier DOI 1704
Hausdorff Distance BibRef

Wei, D.[Dennis],
k-quantiles: L1 distance clustering under a sum constraint,
PRL(92), No. 1, 2017, pp. 49-55.
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Proportional data BibRef

Rodrigues, É.O.,
Combining Minkowski and Cheyshev: New distance proposal and survey of distance metrics using k-nearest neighbours classifier,
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Elsevier DOI 1806
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Mustafa, A.A.Y.[Adnan A.Y.],
Probabilistic binary similarity distance for quick binary image matching,
IET-IPR(12), No. 10, October 2018, pp. 1844-1856.
DOI Link 1809
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A modified hamming distance measure for quick detection of dissimilar binary images,
ICCVIA15(1-6)
IEEE DOI 1603
image matching BibRef

Mustafa, A.A.Y.[Adnan A.Y.],
An Image Mapping Approach for Quick Dissimilarity Detection of Binary Images,
IVCNZ19(1-4)
IEEE DOI 2004
image matching, probability, image pixels, dissimilar detection via mapping, image correlation BibRef

Firozjaei, M.K.[Mohammad Karimi], Daryaei, I.[Iman], Sedighi, A.[Amir], Weng, Q.H.[Qi-Hao], Alavipanah, S.K.[Seyed Kazem],
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Texture and spectral information. BibRef

Kosub, S.[Sven],
A note on the triangle inequality for the Jaccard distance,
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Elsevier DOI 1904
Jaccard index, Set distance, Submodularity BibRef

Karam, C., Sugimoto, K., Hirakawa, K.,
Fast Convolutional Distance Transform,
SPLetters(26), No. 6, June 2019, pp. 853-857.
IEEE DOI 1906
computational complexity, convolution, fast Fourier transforms, filtering theory, Gaussian processes, distance transform BibRef

Manduhu, M., Jones, M.W.,
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IP(28), No. 11, November 2019, pp. 5322-5335.
IEEE DOI 1909
Graphics processing units, Phase change random access memory, Approximation algorithms, Parallel algorithms, Transforms, binary operations on GPU BibRef

Guo, Q.[Qi], Su, X.[XunLi],
Almost Regular Metrics on Groups and Lipschitz-Continuity of Distance Transforms,
JMIV(61), No. 9, November 2019, pp. 1235-1242.
Springer DOI 1911
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Shamai, G.[Gil], Zibulevsky, M.[Michael], Kimmel, R.[Ron],
Efficient Inter-Geodesic Distance Computation and Fast Classical Scaling,
PAMI(42), No. 1, January 2020, pp. 74-85.
IEEE DOI 1912
Manifolds, Complexity theory, Interpolation, Matrix decomposition, Surface reconstruction, Shape, Laplace equations, fast classical scaling BibRef

Shamai, G.[Gil], Aflalo, Y.[Yonathan], Zibulevsky, M.[Michael], Kimmel, R.[Ron],
Classical Scaling Revisited,
ICCV15(2255-2263)
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Complexity theory. evaluation of distances between data points. BibRef

Liu, C.Y.[Chuan-Yi], Wang, J.Q.[Jun-Qian], Duan, S.M.[Shao-Ming], Xu, Y.[Yong],
Combining dissimilarity measures for image classification,
PRL(128), 2019, pp. 536-543.
Elsevier DOI 1912
Image classification, Distance measures, Fusion distance BibRef

Li, Q.[Qiude], Xiong, Q.Y.[Qing-Yu], Ji, S.F.[Sheng-Fen], Wen, J.H.[Jun-Hao], Gao, M.[Min], Yu, Y.[Yang], Xu, R.[Rui],
Using fine-tuned conditional probabilities for data transformation of nominal attributes,
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Elsevier DOI 1912
Conditional probability transformation, Fine-tuning algorithm, MIC-based feature selection, Data transformation, Distance measure BibRef

Lu, S.[Shan], Zhang, J.[Jun], Gao, Y.[Ying],
Learning a minimum similarity projection and lowest correlation representation for image classification,
IET-IPR(14), No. 4, 27 March 2020, pp. 782-788.
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Efficient distance transformation for path-based metrics,
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Elsevier DOI 2005
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Ishihara, M.[Makio], Kawashima, R.[Ryo],
Multi-Distance Function Trilateration over k-NN Fingerprinting for Indoor Positioning and Its Evaluation,
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Springer DOI 2007
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Wang, L.L.[Liang-Liang], Rajan, D.[Deepu],
An image similarity descriptor for classification tasks,
JVCIR(71), 2020, pp. 102847.
Elsevier DOI 2009
Image similarity, Similarity representation, Deep features selection, Correlational descriptor BibRef

Iwata, K.[Kazunori],
Revisiting a Nearest Neighbor Method for Shape Classification,
IEICE(E103-D), No. 12, December 2020, pp. 2649-2658.
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And:
Reducing the computational cost of shape matching with the distance set,
ICPR16(1506-1511)
IEEE DOI 1705
Computational efficiency, Computers, Cost function, Euclidean distance, Minimization, Shape, Sorting, Hilbert distance, distance set, local descriptor of shape, shape matching BibRef

Tao, J.[Jiong], Zhang, J.Y.[Ju-Yong], Deng, B.L.[Bai-Lin], Fang, Z.[Zheng], Peng, Y.[Yue], He, Y.[Ying],
Parallel and Scalable Heat Methods for Geodesic Distance Computation,
PAMI(43), No. 2, February 2021, pp. 579-594.
IEEE DOI 2101
On triangular meshes. Optimization, Linear systems, Memory management, Computational modeling, Heat recovery, Approximation algorithms, parallel algorithm BibRef

Ryu, J.[Jegoon], Kamata, S.I.[Sei-Ichiro],
An efficient computational algorithm for Hausdorff distance based on points-ruling-out and systematic random sampling,
PR(114), 2021, pp. 107857.
Elsevier DOI 2103
Hausdorff distance, Computational complexity, Point matching, 3-D point sets BibRef

Vaz, C.[Colin], Narayanan, S.[Shrikanth],
Extending the Beta divergence to complex values,
PRL(144), 2021, pp. 105-111.
Elsevier DOI 2103
Information theory, KL divergence, Objective function, Young's inequality BibRef

Cheng, C.P.[Cui-Ping], Xiao, F.Y.[Fu-Yuan],
A distance for belief functions of orderable set,
PRL(145), 2021, pp. 165-170.
Elsevier DOI 2104
Belief function, Distance metric, Orderable sets, Hesitant fuzzy linguistic set BibRef

Rodrigues, É.O.[Érick Oliveira],
An efficient and locality-oriented Hausdorff distance algorithm: Proposal and analysis of paradigms and implementations,
PR(117), 2021, pp. 107989.
Elsevier DOI 2106
Hausdorff distance, Mathematical morphology, Similarity, Registration, Parallelism BibRef

Antol, M.[Matej], Jánošová, M.[Miriama], Dohnal, V.[Vlastislav],
Metric hull as similarity-aware operator for representing unstructured data,
PRL(149), 2021, pp. 91-98.
Elsevier DOI 2108
Similarity operators, Metric space, Data aggregation BibRef

Terlep, T.A.[T. Arthur], Bell, M.R.[Mark R.], Talavage, T.M.[Thomas M.], Smith, D.L.[Douglas L.],
Euclidean Distance Approximations From Replacement Product Graphs,
IP(31), 2022, pp. 125-137.
IEEE DOI 2112
Games, Garnets, Graph theory, Topology, Tools, Standards, Space heating, Chamfer, euclidean distance, distance approximation, Dijkstra's algorithm BibRef

Cai, T.J.[Tian-Ji], Cheng, J.Y.[Jun-Yi], Schmitzer, B.[Bernhard], Thorpe, M.[Matthew],
The Linearized Hellinger-Kantorovich Distance,
SIIMS(15), No. 1, 2022, pp. 45-83.
DOI Link 2204
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Kazemi, M.[Meysam], Wecker, L.[Lakin], Samavati, F.[Faramarz],
Efficient Calculation of Distance Transform on Discrete Global Grid Systems,
IJGI(11), No. 6, 2022, pp. xx-yy.
DOI Link 2206
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Beier, F.[Florian], Beinert, R.[Robert], Steidl, G.[Gabriele],
On a Linear Gromov-Wasserstein Distance,
IP(31), 2022, pp. 7292-7305.
IEEE DOI 2212
Extraterrestrial measurements, Level measurement, Shape, Task analysis, Shape measurement, Minimization, Ear, shape spaces BibRef

Aziz, Y.[Yasir], Memon, K.H.[Kashif Hussain],
Fast geometrical extraction of nearest neighbors from multi-dimensional data,
PR(136), 2023, pp. 109183.
Elsevier DOI 2301
Nearest neighbors, Classification, Hashing, Windowing operation BibRef

Turgay, N.D.[Neset Deniz], Nagy, B.[Benedek], Kovács, G.[Gergely], Vizvári, B.[Béla],
Weighted distances in the Cairo pattern,
PRL(166), 2023, pp. 105-111.
Elsevier DOI 2302
Cairo pattern, Tiling, Minimal path, Linear programming, Chamfer distances BibRef

Alvarez, S.A.[Sergio A.],
Gaussian RBF Centered Kernel Alignment (CKA) in the Large-Bandwidth Limit,
PAMI(45), No. 5, May 2023, pp. 6587-6593.
IEEE DOI 2304
Similarity measure between kernels. Kernel, Bandwidth, Symmetric matrices, Convergence, Encoding, Behavioral sciences, Watermarking, Nonlinear kernels, similarity BibRef

Zhao, L.J.[Long-Jiao], Wang, Y.[Yu], Kato, J.[Jien], Ishikawa, Y.[Yoshiharu],
Learning Local Similarity with Spatial Interrelations on Content-Based Image Retrieval,
IEICE(E106-D), No. 5, May 2023, pp. 1069-1080.
WWW Link. 2305
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Blanco-Mallo, E.[Eva], Morán-Fernández, L.[Laura], Remeseiro, B.[Beatriz], Bolón-Canedo, V.[Verónica],
Do all roads lead to Rome? Studying distance measures in the context of machine learning,
PR(141), 2023, pp. 109646.
Elsevier DOI 2306
Distance measures, Similarity measures, Classification, Clustering, Machine learning BibRef

Beinert, R.[Robert], Heiss, C.[Cosmas], Steidl, G.[Gabriele],
On Assignment Problems Related to Gromov-Wasserstein Distances on the Real Line,
SIIMS(16), No. 2, 2023, pp. 1028-1032.
DOI Link 2307
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Rezaei, M.[Mina], Soleymani, F.[Farzin], Bischl, B.[Bernd], Azizi, S.[Shekoofeh],
Deep Bregman divergence for self-supervised representations learning,
CVIU(235), 2023, pp. 103801.
Elsevier DOI 2310
Self-supervised learning, Deep metric learning, Bregman divergences, Non-Euclidean geometry BibRef

van de Velden, M.[Michel], d'Enza, A.I.[Alfonso Iodice], Markos, A.[Angelos], Cavicchia, C.[Carlo],
A general framework for implementing distances for categorical variables,
PR(153), 2024, pp. 110547.
Elsevier DOI 2405
Categorical data, Distance, Cluster analysis, Classification, K-NN BibRef

Franzoni, V.[Valentina], Biondi, G.[Giulio], Liu, Y.[Yang], Milani, A.[Alfredo],
Evolving meta-correlation classes for binary similarity,
PR(157), 2025, pp. 110871.
Elsevier DOI 2409
Evolutionary computation, Network topology, Complex networks, Link prediction, Binary similarity BibRef

Lei, B.[Bohan], Zhuang, Y.T.[Yue-Ting], Xu, X.Y.[Xiao-Yin], Zhang, M.[Min],
An Optimal Transport-Based Method for Medical Image Generation,
ICIP24(3640-3646)
IEEE DOI 2411
Training, Image resolution, Image synthesis, Extraterrestrial phenomena, Memory management, optimal transport BibRef

Zhou, J.S.[Jun-Sheng], Zhang, W.Q.[Wei-Qi], Ma, B.R.[Bao-Rui], Shi, K.[Kanle], Liu, Y.S.[Yu-Shen], Han, Z.Z.[Zhi-Zhong],
UDiFF: Generating Conditional Unsigned Distance Fields with Optimal Wavelet Diffusion,
CVPR24(21496-21506)
IEEE DOI Code:
WWW Link. 2410
Wavelet transforms, Visualization, Wavelet domain, Shape, Surface waves, Benchmark testing, Diffusion models, 3D shape generation BibRef

Fainstein, M.[Miguel], Siless, V.[Viviana], Iarussi, E.[Emmanuel],
DUDF: Differentiable Unsigned Distance Fields with Hyperbolic Scaling,
CVPR24(4484-4493)
IEEE DOI 2410
Training, Surface reconstruction, Accuracy, Computational modeling, Level set, Neural networks, Neural implicit representations, eikonal equation BibRef

Chou, G.[Gene], Bahat, Y.[Yuval], Heide, F.[Felix],
Diffusion-SDF: Conditional Generative Modeling of Signed Distance Functions,
ICCV23(2262-2272)
IEEE DOI Code:
WWW Link. 2401
BibRef

Liu, W.X.[Wei-Xiao], Wu, Y.W.[Yu-Wei], Ruan, S.[Sipu], Chirikjian, G.S.[Gregory S.],
Marching-Primitives: Shape Abstraction from Signed Distance Function,
CVPR23(8771-8780)
IEEE DOI 2309
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Ma, B.R.[Bao-Rui], Zhou, J.S.[Jun-Sheng], Liu, Y.S.[Yu-Shen], Han, Z.Z.[Zhi-Zhong],
Towards Better Gradient Consistency for Neural Signed Distance Functions via Level Set Alignment,
CVPR23(17724-17734)
IEEE DOI 2309
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Rosa, N.[Nicholas], Drummond, T.[Tom], Harandi, M.[Mehrtash],
A Differentiable Distance Approximation for Fairer Image Classification,
ACCV22(VI:218-234).
Springer DOI 2307
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Huberman, S.[Saar], Bracha, A.[Amit], Kimmel, R.[Ron],
Deep Accurate Solver for the Geodesic Problem,
SSVM23(288-300).
Springer DOI 2307
Distance on surface. BibRef

Ouasfi, A.[Amine], Boukhayma, A.[Adnane],
Few 'Zero Level Set'-Shot Learning of Shape Signed Distance Functions in Feature Space,
ECCV22(XXXII:561-578).
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Potamias, R.A.[Rolandos Alexandros], Neofytou, A.[Alexandros], Bintsi, K.M.[Kyriaki Margarita], Zafeiriou, S.P.[Stefanos P.],
GraphWalks: Efficient Shape Agnostic Geodesic Shortest Path Estimation,
DLGC22(2967-2976)
IEEE DOI 2210
Shape, Pipelines, Estimation, Approximation algorithms BibRef

Krayer, B.[Bastian], Müller, S.[Stefan],
Hierarchical Point Distance Fields,
ISVC21(II:435-446).
Springer DOI 2112
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Hu, C.S.[Chuan-Shen], Lawson, A.[Austin], Chung, Y.M.[Yu-Min], Keegan, K.[Kaitlin],
Two-parameter Persistence for Images via Distance Transform,
TAG-CV21(4159-4167)
IEEE DOI 2112
Data analysis, Filtration, Digital images, Transforms, Gray-scale BibRef

Hartman, E.[Emmanuel], Sukurdeep, Y.[Yashil], Charon, N.[Nicolas], Klassen, E.[Eric], Bauer, M.[Martin],
Supervised deep learning of elastic SRV distances on the shape space of curves,
Diff-CVML21(4420-4428)
IEEE DOI 2109
Square Root Velocity. Computable distance between spatial curves. Training, Deep learning, Shape, Transforms, Tools BibRef

Nunez, E.[Elvis], Lizarraga, A.[Andrew], Joshi, S.H.[Shantanu H.],
SrvfNet: A Generative Network for Unsupervised Multiple Diffeomorphic Functional Alignment,
CVSports21(4476-4484)
IEEE DOI 2109
Deep learning, Magnetic resonance imaging, Computational modeling, Training data, Computer architecture BibRef

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Towards Efficient Time Stepping for Numerical Shape Correspondence,
SSVM21(165-176).
Springer DOI 2106
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Sun, W., Shan, Z., Liu, F., Qiao, M., Gui, H., Li, X.,
Similarity Measure for Binary Function Based on Graph Mover's Distance,
CVIDL20(255-259)
IEEE DOI 2102
computational complexity, graph theory, image matching, neural nets, similarity measure, graph matching, Binary Similarity. BibRef

Chakraborty, R.[Rudrasis], Xing, Y.F.[Yi-Fei], Duan, M.X.[Min-Xuan], Yu, S.X.[Stella X.],
C-SURE: Shrinkage Estimator and Prototype Classifier for Complex-Valued Deep Learning,
PBVS20(360-367)
IEEE DOI 2008
Manifolds, Maximum likelihood estimation, Frequency modulation, Gaussian distribution, Prototypes, Covariance matrices, Measurement BibRef

Khrulkov, V.[Valentin], Mirvakhabova, L.[Leyla], Ustinova, E.[Evgeniya], Oseledets, I.[Ivan], Lempitsky, V.[Victor],
Hyperbolic Image Embeddings,
CVPR20(6417-6427)
IEEE DOI 2008
Task analysis, Visualization, Natural language processing, Geometry, Extraterrestrial measurements BibRef

Yuan, T.T.[Tong-Tong], Deng, W.H.[Wei-Hong], Tang, J.[Jian], Tang, Y.[Yinan], Chen, B.H.[Bing-Hui],
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CVPR19(4810-4819).
IEEE DOI 2002
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Dahl, V.A.[Vedrana Andersen], Dahl, A.B.[Anders Bjorholm],
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SSVM19(357-368).
Springer DOI 1909
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Nagy, B.[Benedek], Strand, R.[Robin], Normand, N.[Nicolas],
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DGCI19(62-74).
Springer DOI 1905
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Öfverstedt, J.[Johan], Lindblad, J.[Joakim], Sladoje, N.[Nataša],
Stochastic Distance Transform,
DGCI19(75-86).
Springer DOI 1905
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Gabdulkhakova, A.[Aysylu], Kropatsch, W.G.[Walter G.],
Confocal Ellipse-based Distance and Confocal Elliptical Field for polygonal shapes,
ICPR18(3025-3030)
IEEE DOI 1812
Shape, Skeleton, Transforms, Image processing, Euclidean distance, Pattern recognition BibRef

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Multi-view Harmonized Bilinear Network for 3D Object Recognition,
CVPR18(186-194)
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Object recognition, Feature extraction, Kernel, Shape BibRef

Li, D.C.[Dong-Chang], La Torre, D.[Davide], Vrscay, E.R.[Edward R.],
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ICIP17(1117-1121)
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Binary codes, Containers, Hamming distance, Indexing, Search problems, Binary Code, Index, Trie BibRef

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ICPR16(3103-3108)
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Noyel, G.[Guillaume], Jourlin, M.[Michel],
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And:
Spatio-Colour Asplünd's Metric and Logarithmic Image Processing for Colour Images (LIPC),
CIARP16(36-43).
Springer DOI 1703
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Earlier:
Asplünd's metric defined in the logarithmic image processing (LIP) framework for colour and multivariate images,
ICIP15(3921-3925)
IEEE DOI 1512
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Jia, D.[Di], Xiao, C.L.[Cheng-Long], Sun, J.G.[Jin-Guang],
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Earlier:
An Optimal Greedy Approximate Nearest Neighbor Method in Statistical Pattern Recognition,
PReMI15(236-245).
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Earlier:
Nonlinear Transformation of the Distance Function in the Nearest Neighbor Image Recognition,
CompIMAGE14(261-266).
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MCPR15(103-112).
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Earlier:
An Effective Permutant Selection Heuristic for Proximity Searching in Metric Spaces,
MCPR14(102-111).
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Distance between Separating Circles and Points,
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ICPR08(1-4).
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Chapter on 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture continues in
Three Dimensional Distance Transforms and Distance Functions .