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  <titleInfo>
    <title>Polygonal approximation and scale-space analysis</title>
  </titleInfo>
  <name type="personal">
    <namePart>Ray, Kumar S.</namePart>
    <role>
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  <name type="personal">
    <namePart>Ray, Bimal K.</namePart>
  </name>
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  <originInfo>
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    <place>
      <placeTerm type="text">Oakville, Ont</placeTerm>
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    <place>
      <placeTerm type="text">Waretown, N.J</placeTerm>
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    <publisher>Apple Academic Press</publisher>
    <dateIssued>2013</dateIssued>
    <issuance>monographic</issuance>
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  <language>
    <languageTerm authority="iso639-2b" type="code">eng</languageTerm>
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  <physicalDescription>
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    <extent>376 p. : ill.</extent>
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  <tableOfContents>1. Polygonal approximation -- 2. A split and merge technique -- 3. A sequential one-pass method -- 4. Another sequential one-pass method -- 5. A data-driven method -- 6. Another data-driven method -- 7. A two-pass sequential method -- 8. Polygonal approximation using reverse engineering on bresenham's line drawing technique -- 9. Polygonal approximation as angle detection -- 10. Polygonal approximation as angle detection using asymmetric region of support -- 11. Scale space analysis with application to corner detection -- 12. Scale space analysis and corner detection on chain coded curves -- 13. Scale space analysis and corner detection using iterative gaussian smoothing with constant window size -- 14. Corner detection using bessel function as smoothing kernel -- 15. Adaptive smoothing using convolution with gaussian kernel -- 16. Application of polygonal approximation for pattern classification and object recognition -- 17. Polygonal dissimilarity and scale preserving smoothing -- 18. Matching polygon fragments -- 19. Polygonal approximation to recognize and locate partially occluded objects hypothesis generation and verification paradigm -- 20. Object recognition with belief revision : hypothesis generation and belief revision paradigm -- 21. Neuro-fuzzy reasoning for occluded object recognition : a learning paradigm through neuro-fuzzy concept -- 22. Conclusion.</tableOfContents>
  <note type="statement of responsibility">Kumar S. Ray and Bimal Kumar Ray.</note>
  <note>Includes bibliographical references (p. [361]-368) and index.</note>
  <note>Also available in print edition.</note>
  <note>Mode of access: World Wide Web.</note>
  <subject authority="lcsh">
    <topic>Curves</topic>
    <topic>Computer simulation</topic>
  </subject>
  <subject authority="lcsh">
    <topic>Geometry</topic>
    <topic>Data processing</topic>
  </subject>
  <subject authority="lcsh">
    <topic>Polygons</topic>
  </subject>
  <subject authority="lcsh">
    <topic>Approximation theory</topic>
  </subject>
  <subject authority="lcsh">
    <topic>Image processing</topic>
    <topic>Mathematics</topic>
  </subject>
  <subject authority="lcsh">
    <topic>Pattern recognition systems</topic>
    <topic>Mathematics</topic>
  </subject>
  <subject authority="lcsh">
    <topic>Computer vision</topic>
    <topic>Mathematics</topic>
  </subject>
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  <identifier type="isbn">9781466568891 (ebook : PDF)</identifier>
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