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Shape Regularized Active Contour using Iterative Global Search and Local Optimization
 

Summary: Shape Regularized Active Contour using Iterative Global Search
and Local Optimization
Tianli Yu1
, Jiebo Luo2
, and Narendra Ahuja1
1
Beckman Institute & ECE Department 2
Kodak Research Laboratories
Univ. of Illinois at Urbana-Champaign Eastman Kodak Company
Urbana, IL 61801 Rochester, NY 14650-1816
Abstract
Recently, nonlinear shape models have been shown to
improve the robustness and flexibility of segmentation. In
this paper, we propose Shape Regularized Active Contour
(ShRAC) that incorporates existing nonlinear shape mod-
els into the classical active contour approach. ShRAC uses
a discrete representation of the contour to allow efficient
combinatorial search. The search for optimal contour is
performed by a coarse-to-fine algorithm that iterates be-
tween combinatorial search and gradient-based local op-

  

Source: Ahuja, Narendra - Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign

 

Collections: Computer Technologies and Information Sciences; Engineering