3 research outputs found
A Region-based Randers Geodesic Approach for Image Segmentation
The minimal path model based on the Eikonal partial differential equation has
served as a fundamental tool for the applications of image segmentation and
boundary detection in the passed two decades. However, the existing approaches
commonly only exploit the image edge-based features for computing minimal
paths, potentially limiting their performance in complicated segmentation
situations. In this paper, we introduce a new variational image segmentation
model based on the minimal path framework and the eikonal PDE, where the
region-based appearance term that defines then regional homogeneity features
can be taken into account for estimating the associated minimal paths. This is
done by constructing a Randers geodesic metric interpretation to the
region-based active contour energy. As a result, the minimization of the active
contour energy is transformed to finding the solution to the Randers eikonal
PDE.
We also suggest a practical interactive image segmentation strategy, where
the target boundary can be delineated by the concatenation of the piecewise
geodesic paths. We invoke the Finsler variant of the fast marching method to
estimate the geodesic distance map, yielding an efficient implementation of the
proposed Eikonal region-based active contour model. Experimental results on
both synthetic and real images exhibit that our model indeed achieves
encouraging segmentation performance
Anisotropic Edge-based Balloon Eikonal Active Contours
International audienc