• DocumentCode
    1945211
  • Title

    A Nonparametric Approach for Active Contours

  • Author

    Ozertem, Umut ; Erdogmus, Deniz

  • Author_Institution
    Oregon Health & Sci. Univ., Portland
  • fYear
    2007
  • fDate
    12-17 Aug. 2007
  • Firstpage
    1407
  • Lastpage
    1410
  • Abstract
    Active contours are commonly used in many image segmentation applications. There are different active contour definitions, but all active contour definitions in the literature use parametric forms to determine the shape priors or adjust the weighting of internal and external forces acting on the active contour. However, the evaluation or estimation of the optimal values of these parameters is impossible in a general sense, and the algorithms are run with different parameters until a satisfactory result is obtained. To get rid of this exhaustive parameter search, we approach the same problem in a nonparametric way to translate the problem of seeking good values of these unknown parameters into seeking for a good density estimate. We tested the proposed method and compared with earlier approaches and obtained better results.
  • Keywords
    image segmentation; search problems; active contours; exhaustive parameter search; image segmentation; nonparametric approach; Active contours; Image edge detection; Image processing; Image segmentation; Kernel; Neural networks; Object recognition; Shape; Testing; Video coding;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 2007. IJCNN 2007. International Joint Conference on
  • Conference_Location
    Orlando, FL
  • ISSN
    1098-7576
  • Print_ISBN
    978-1-4244-1379-9
  • Electronic_ISBN
    1098-7576
  • Type

    conf

  • DOI
    10.1109/IJCNN.2007.4371164
  • Filename
    4371164