Abstract
We present an image analysis based automatic road crack detection method for conducting smooth driving on non-smooth road surfaces. In the new proposal, first the road surface areas which include cracks are extracted as crack images by analyzing the color variance on norm. Then cracks are extracted from those areas by introducing a method on discriminant analysis. According to experiments using the images of different road surfaces, the new proposal showed better performances than the conventional approaches.
| Original language | English |
|---|---|
| Pages (from-to) | 545-553 |
| Number of pages | 9 |
| Journal | International Journal of Machine Learning and Cybernetics |
| Volume | 6 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - 2015 Aug 24 |
| Externally published | Yes |
Keywords
- Cracks
- Discriminant analysis
- Image sample variance
- Smooth driving
ASJC Scopus subject areas
- Artificial Intelligence
- Software
- Computer Vision and Pattern Recognition
Fingerprint Dive into the research topics of 'Road crack detection using color variance distribution and discriminant analysis for approaching smooth vehicle movement on non-smooth roads'. Together they form a unique fingerprint.
Cite this
Premachandra, C., Premachandra, H. W. H., Parape, C. D., & Kawanaka, H. (2015). Road crack detection using color variance distribution and discriminant analysis for approaching smooth vehicle movement on non-smooth roads. International Journal of Machine Learning and Cybernetics, 6(4), 545-553. https://doi.org/10.1007/s13042-014-0240-6