tc18_bib.bib

@ARTICLE{normand2008pr,
  AUTHOR = {Normand, Nicolas and Evenou, Pierre},
  JOURNAL = {Pattern Recognition},
  PAGES = {20 pages},
  TITLE = {Medial Axis Lookup Table and Test Neighborhood Computation for 3{D} Chamfer Norms},
  NOTE = {To appear},
  YEAR = {2008}
}


@INPROCEEDINGS{DEBL_1995,
  AUTHOR = {I. Debled-Rennesson and J.-P. Reveill{\`e}s},
  TITLE = {A linear algorithm for segmentation of digital
                  curves},
  BOOKTITLE = {International Journal on Pattern Recognition and Artificial Intelligence},
  PAGES = {635--662},
  YEAR = 1995,
  VOLUME = 9
}


@INPROCEEDINGS{KENMO_2000,
  AUTHOR = {Y. Kenmochi and R. Klette},
  TITLE = {Surface area estimation for digitized regular solids},
  BOOKTITLE = {Proc. Vision Geometry IX},
  PAGES = {100--111},
  YEAR = 2000,
  MONTH = {Oct.},
  EDITOR = {L. J. Latecki and D. M. Mount and A. Y. Wu},
  PUBLISHER = {SPIE},
  VOLUME = 4117
}


@INPROCEEDINGS{KLETTE_2001,
  AUTHOR = {R. Klette and H.~J. Sun},
  TITLE = {Digital planar segment based polyhedrization for surface area estimation},
  BOOKTITLE = {International Workshop on Visual Form 4},
  SERIES = {Lect. Notes Comput. Sci.},
  PAGES = {356--366},
  YEAR = 2001,
  EDITOR = {C. Arcelli and L. P. Cordella and G. {Sanniti di Baja}},
  VOLUME = 2059,
  PUBLISHER = {Springer-Verlag},
  ANNOTE = {Capri, Italy}
}


@ARTICLE{FOUARD_2005,
  AUTHOR = {C\'eline Fouard and Gr\'egoire Malandain},
  JOURNAL = {Image and Vision Computing},
  TITLE = {3-D chamfer distances and norms in anisotropic grids},
  YEAR = {2005},
  MONTH = {February},
  OPTNOTE = {},
  NUMBER = {2},
  PAGES = {143--158},
  VOLUME = {23},
  KEYWORDS = {chamfer distance, anisotropic lattice, Farey triangulation},
  PDF = {ftp://ftp-sop.inria.fr/epidaure/Publications/Fouard/Fouard_Malandain_IVC_2004.pdf},
  ABSTRACT = {Chamfer distances are widely used in image analysis and many 
authors have investigated the computation of optimal chamfer mask 
coefficients. Unfortunately, these methods are not systematized: 
calculations have to be conducted manually for every mask size or image 
anisotropy. Since image acquisition (e.g. medical imaging) can lead to 
discrete anisotropic grids with unpredictable anisotropy value, 
automated calculation of chamfer mask coefficients becomes mandatory for 
e cient distance map computations. This article presents an automatic 
construction for chamfer masks of arbitrary sizes. This allows, first, 
to derive analytically the relative error with respect to the Euclidean 
distance, in any 3-D anisotropic lattice, and second, to compute optimal 
chamfer coefficients. In addition, the resulting chamfer map verifies 
discrete norm conditions.}
}


@TECHREPORT{MALANDAIN_2005,
  AUTHOR = {Gr\'egoire Malandain and C\'eline Fouard},
  INSTITUTION = {INRIA},
  TITLE = {On optimal chamfer masks and coefficients},
  YEAR = {2005},
  OPTADDRESS = {},
  OPTMONTH = {},
  OPTNOTE = {},
  NUMBER = {5566},
  TYPE = {Research Report},
  ABSTRACT = { This report describes the calculation of local errors
    in Chamfer masks both in two- and in three-dimensional anisotropic
    spaces. For these errors, closed forms are given that can be
    related to the Chamfer mask geometry.  Thanks to these calculation,
    it can be obsrved that the usual Chamfer masks ({\em i.e.} 3x3x3 or
    5x5x5) have an inhomogeneously distributed error. Moreover, it
    allows us to design dedicated Chamfer masks by controlling either
    the complexity of the computation of the distance map (or
    equivalently the number of vectors in the mask), or the error of
    the mask in $\mathbb{Z}^2$ or in $\mathbb{Z}^3$.  Last, since
    Chamfer distances are usually computed with integer weights (and
    approximate the Euclidean distance up to a multiplicative factor),
    we demonstrate that the knowledge of the local errors allows a very
    efficient computation of these weights.},
  KEYWORDS = {Chamfer distance, anisotropic lattice, Farey 
triangulation},
  OPTURL = {http://www.inria.fr/rrrt/rr-5566.html},
  OPTPDF = {ftp://ftp.inria.fr/INRIA/publication/publi-pdf/RR/RR-5566.pdf}
}


@INPROCEEDINGS{GERARD_2003,
  AUTHOR = {Y. G{\'e}rard},
  TITLE = {A fast and elementary algorithm for digital planes recognition},
  BOOKTITLE = {International Workshop on Combinatorial Image Analysis},
  YEAR = 2003,
  ADDRESS = {Palermo, Italy}
}


@ARTICLE{SAITO_1994,
  AUTHOR = {T. Saito and J.~I. Toriwaki},
  TITLE = {New algorithms for {E}uclidean distance
                 transformations of an {$n$}-dimensional digitized
                 picture with applications},
  JOURNAL = {Pattern Recognition},
  YEAR = 1994,
  VOLUME = 27,
  PAGES = {1551--1565}
}


@ARTICLE{HIRATA_1996,
  AUTHOR = {T. Hirata},
  TITLE = {A unified linear-time algorithm for computing distance
                 maps},
  JOURNAL = {Information Processing Letters},
  VOLUME = {58},
  NUMBER = {3},
  PAGES = {129--133},
  DAY = {13},
  MONTH = MAY,
  YEAR = {1996},
  CODEN = {IFPLAT},
  ISSN = {0020-0190},
  MRCLASS = {68U10},
  MRNUMBER = {97j:68137},
  BIBDATE = {Wed Nov 11 12:16:26 MST 1998},
  ACKNOWLEDGEMENT = ACK-NHFB,
  CLASSIFICATION = {C1250 (Pattern recognition); C4240C (Computational
                 complexity); C5260B (Computer vision and image
                 processing techniques)},
  CORPSOURCE = {Fac. of Eng., Nagoya Univ., Japan},
  KEYWORDS = {binary image; chamfer; chessboard; city block;
                 computational complexity; computer vision; distance
                 maps; Euclidean; Euclidean distance; Euclidean distance
                 transform; image processing; machine vision; matrix
                 searching; octagonal},
  TREATMENT = {T Theoretical or Mathematical}
}


@INPROCEEDINGS{MEIJSTER_2000,
  AUTHOR = {A. Meijster and J.B.T.M. Roerdink and W. H. Hesselink},
  TITLE = { A general algorithm for computing distance transforms in linear time},
  BOOKTITLE = {Mathematical Morphology and its Applications to Image and Signal Processing},
  PAGES = {331--340},
  YEAR = 2000,
  PUBLISHER = {Kluwer}
}