Localizing Region-Based Active Contours
Georgia Institute of Technology · Technion – Israel Institute of Technology
Abstract
In this paper, we propose a natural framework that allows any region-based segmentation energy to be re-formulated in a local way. We consider local rather than global image statistics and evolve a contour based on local information. Localized contours are capable of segmenting objects with heterogeneous feature profiles that would be difficult to capture correctly using a standard global method. The presented technique is versatile enough to be used with any global region-based active contour energy and instill in it the benefits of localization. We describe this framework and demonstrate the localization of three well-known energies in order to illustrate how our framework can be applied to any energy. We…
Citation impact
- FWCI
- 46.13
- Percentile
- 100%
- References
- 39
Authors
2Topics & keywords
- Active contour model
- Artificial intelligence
- Computer science
- Image segmentation
- Segmentation
- Energy (signal processing)
- Feature (linguistics)
- Computer vision
- Affordable and clean energy