Globally optimal geodesic active contours

Appleton, Ben and Talbot, Hugues (2005) Globally optimal geodesic active contours. Journal of Mathematical Imaging and Vision, 23 1: 67-86. doi:10.1007/s10851-005-4968-1

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Author Appleton, Ben
Talbot, Hugues
Title Globally optimal geodesic active contours
Journal name Journal of Mathematical Imaging and Vision   Check publisher's open access policy
ISSN 0924-9907
1573-7683
Publication date 2005-07-01
Sub-type Article (original research)
DOI 10.1007/s10851-005-4968-1
Open Access Status File (Author Post-print)
Volume 23
Issue 1
Start page 67
End page 86
Total pages 20
Place of publication Secaucus, NJ, U.S.A.
Publisher Springer New York LLC
Language eng
Subject 280208 Computer Vision
080104 Computer Vision
C1
Abstract An approach to optimal object segmentation in the geodesic active contour framework is presented with application to automated image segmentation. The new segmentation scheme seeks the geodesic active contour of globally minimal energy under the sole restriction that it contains a specified internal point p_int. This internal point selects the object of interest and may be used as the only input parameter to yield a highly automated segmentation scheme. The image to be segmented is represented as a Riemannian space S with an associated metric induced by the image. The metric is an isotropic and decreasing function of the local image gradient at each point in the image, encoding the local homogeneity of image features. Optimal segmentations are then the closed geodesics which partition the object from the background with minimal similarity across the partitioning. An efficient algorithm is presented for the computation of globally optimal segmentations and applied to cell microscopy, x-ray, magnetic resonance and cDNA microarray images.
Keyword Geodesic active contour
Circular shortest path
Optimal segmentation
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Excellence in Research Australia (ERA) - Collection
School of Information Technology and Electrical Engineering Publications
 
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Citation counts: TR Web of Science Citation Count  Cited 42 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 49 times in Scopus Article | Citations
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Created: Mon, 07 Mar 2005, 10:00:00 EST by Ben Appleton on behalf of School of Information Technol and Elec Engineering