preprintNov 19, 2002Closed access

Gradient flows and geometric active contour models

University of Minnesota

Indexed incrossref

Abstract

In this paper, we analyze the geometric active contour models discussed previously from a curve evolution point of view and propose some modifications based on gradient flows relative to certain new feature-based Riemannian metrics. This leads to a novel snake paradigm in which the feature of interest may be considered to lie at the bottom of a potential well. Thus the snake is attracted very naturally and efficiently to the desired feature. Moreover, we consider some 3-D active surface models based on these ideas.>

Citation impact

660
total citations
FWCI
71.08
Percentile
100%
References
28
Citations per year

Authors

5

Topics & keywords

Keywords
  • Feature (linguistics)
  • Active contour model
  • Point (geometry)
  • Artificial intelligence
  • Computer science
  • Computer vision
  • Image (mathematics)
  • Pattern recognition (psychology)
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