rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    non sort: A
    title: Contrario Line Segment Detection
  name:
    name part: Grompone von Gioi, Rafael.
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: xxu
    date issued: 2014
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: VIII, 90 p. 60 illus. online resource.
  abstract: The reliable detection of low-level image structures is an old and still challenging problem in computer vision. This book leads a detailed tour through the LSD algorithm, a line segment detector designed to be fully automatic. Based on the a contrario framework, the algorithm works efficiently without the need of any parameter tuning. The design criteria are thoroughly explained and the algorithm's good and bad results are illustrated on real and synthetic images. The issues involved, as well as the strategies used, are common to many geometrical structure detection problems and some possible extensions are discussed.
  table of contents: Introduction -- A Contrario Detection -- The LSD Algorithm -- Experiments -- Extensions.
  note: by Rafael Grompone von Gioi.
  subject:
    topic: Computer science
  subject:
    topic: Artificial intelligence
  subject:
    topic: Computer graphics
  subject:
    topic: Computer Science
  subject:
    topic: Computer Imaging, Vision, Pattern Recognition and Graphics
  subject:
    topic: Artificial Intelligence (incl. Robotics)
  classification: T385
  classification: TA1637-1638
  classification: TK7882.P3
  classification: 006.6
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: SpringerBriefs in Computer Science
  identifier: 9781493905751
  identifier: http://dx.doi.org/10.1007/978-1-4939-0575-1
  record info:
    record creation date: 140320
    record change date: 20151204160337.0
    record identifier: 978-1-4939-0575-1