Attractable snakes based on the greedy algorithm for contour extraction

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

52 Scopus Citations
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Author(s)

Detail(s)

Original languageEnglish
Pages (from-to)791-806
Journal / PublicationPattern Recognition
Volume35
Issue number4
Publication statusPublished - Apr 2002
Externally publishedYes

Abstract

While most improved snakes were built under the original variational scheme, this paper presents an attractable snake based on the greedy snake (Williams and Shah, CVGIP: Image Understanding 55(1) (1992) 14-26). By use of a direct feedback mechanism that is seamlessly consistent with the search strategy of the greedy algorithm, the proposed approach is capable of inheriting the simplicity and efficiency of that algorithm and performing competitively with related snakes. To avoid undesirable local minima, an overall optimal edge detector is designed. A suitable synthetic convergent criterion is proposed which enables snakes to converge normally or oscillatingly on target objects. An adaptive interpolation scheme that encourages snakes to accurately sense the details of object shapes is also described. This model is applied to extract contours from various images with encouraging results. © 2002 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved.

Research Area(s)

  • Active contour, Edge detection, Greedy algorithm, Optimization, Segmentation, Snakes