Area and Length Minimizing Flows for Shape Segmentation

— A number of active contour models have been proposed that unify the curve evolution framework with classical energy minimization techniques for segmentation, such as snakes. The essential idea is to evolve a curve (in two dimensions) or a surface (in three dimensions) under constraints from image forces so that it clings to features of interest in an intensity image. Recently, the evolution equation has been derived from first principles as the gradient flow that minimizes a modified length functional, tailored to features such as edges. However, because the flow may be slow to converge in practice, a constant (hyperbolic) term is added to keep the curve/surface moving in the desired direction. In this paper, we derive a modification of this term based on the gradient flow derived from a weighted area functional, with image dependent weighting factor. When combined with the earlier modified length gradient flow, we obtain a partial differential equation (PDE) that offers a ...

• Type: Conference
• Year: 1997
• Where: CVPR
• Authors: Kaleem Siddiqi, Steven W. Zucker, Yves Bérubé Lauzière, Allen Tannenbaum
• Keywords: Computer Vision, Curve Evolution Framework, CVPR 1997, Gradient flow, Modified Length