IS = { zkontrolovano 10 Jan 2012 },
  UPDATE  = { 2011-04-11 },
  author   = { Lemaitre, Cedric and
               Per{\v d}och, Michal and
               Rahmoune, Abdul and
               Matas, Ji{\v r}{\' i} and
               Miteran, Johel },
  title =    { Detection and matching of curvilinear structures },
  journal =  { Pattern Recognition },
  year =     { 2011 },
  volume =   { 44 },
  number =   { 7 },
  month =    { July },
  pages =    { 1514-1527 },
  project =  { GACR 102/07/1317, FP7-ICT-270138 DARWIN},
  keywords = { Curvilinear structures, Wiry objects, Descriptor,
                Detector, Segmentation, Matching },
  annote = { We propose an approach to curvilinear and wiry object
    detection and matching based on a new curvilinear region detector
    (CRD) and a shape context-like descriptor (COH).  Standard methods
    for local patch detection and description are not directly
    applicable to wiry objects and curvilinear structures, such as
    roads, railroads and rivers in satellite and aerial images,
    vessels and veins in medical images, cables, poles and fences in
    urban scenes, stems and tree branches in natural images, since
    they assume the object is compact, i.e. that most elliptical
    patches around features cover only the object. However, wiry
    objects often have no flat parts and most neighborhoods include
    both foreground and background.  The detection process is first
    evaluated in terms of segmentation quality of curvilinear
    regions. The repeatability of the detection is then assessed using
    the protocol introduced in Mikolajczyk et al. [1].  Experiments
    show that the CRD is at least as robust as to several image
    acquisition conditions changes (viewpoint, scale, illumination,
    compression, blur) as the commonly used affine-covariant
    detectors.  The paper also introduces an image collection
    containing wiry objects and curvilinear structures (the W?CS
    dataset). },
  psurl      = {http://doi:10.1016/j.patcog.2011.01.005},
  issn       = {0031-3203},
  publisher  = {Elsevier},
  address    = {Amsterdam, Netherlands},
  authorship = {20-20-20-20-20},