Minimization of Region-Scalable Fitting Energy for Image Segmentation
Vanderbilt University · Vanderbilt Health · +1 more institution
Abstract
Intensity inhomogeneities often occur in real-world images and may cause considerable difficulties in image segmentation. In order to overcome the difficulties caused by intensity inhomogeneities, we propose a region-based active contour model that draws upon intensity information in local regions at a controllable scale. A data fitting energy is defined in terms of a contour and two fitting functions that locally approximate the image intensities on the two sides of the contour. This energy is then incorporated into a variational level set formulation with a level set regularization term, from which a curve evolution equation is derived for energy minimization. Due to a kernel function in the data fitting…
Citation impact
- FWCI
- 60.33
- Percentile
- 100%
- References
- 35
Authors
4Topics & keywords
- Active contour model
- Level set (data structures)
- Image segmentation
- Regularization (linguistics)
- Level set method
- Artificial intelligence
- Segmentation
- Minification
- Affordable and clean energy