Abstract
We describe a technique for improving the classification of fragmented cues for cracks. Evidence propagation on Bayesian networks represents search within the context of each cue. The algorithm was applied to a data-set of cracks, and results demonstrate that contextual classification of the cues leads to significantly improved error rates. © 1994.
| Original language | English |
|---|---|
| Pages (from-to) | 149-154 |
| Number of pages | 5 |
| Journal | Image and Vision Computing |
| Volume | 12 |
| Issue number | 3 |
| Publication status | Published - Apr 1994 |
Keywords
- Bayesian networks
- crack detection
- machine vision