Abstract
We apply to edge detection a recently introduced method for computing geometric structures in a digital image, without any a priori information. According to a basic principle of perception due to Helmholtz, an observed geometric structure is perceptually "meaningful" if its number of occurences would be very small in a random situation: in this context, geometric structures are characterized as large deviations from randomness. This leads us to define and compute edges and boundaries (closed edges) in an image by a parameter-free method. Maximal detectable boundaries and edges are defined, computed, and the results compared with the ones obtained by classical algorithms.
| Original language | English |
|---|---|
| Pages (from-to) | 271-284 |
| Number of pages | 14 |
| Journal | Journal of Mathematical Imaging and Vision |
| Volume | 14 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - May 2001 |
| Externally published | Yes |
Keywords
- Edge detection
- Helmholtz principle
- Image analysis
- Large deviations
- Perception