Abstract
In many industrial applications, Fourier descriptors are commonly used when the description of the object shape is an important characteristic of the image. However, these descriptors are limited to single objects. We propose a general Fourier-based approach, called statistical Fourier descriptor (SFD), which computes shape statistics in grey level images. The SFD is computationally efficient and can be used for defect image classification. In a first example, we deployed the SFD to the inspection of welding seams with promising results.
| Original language | English |
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| Title of host publication | Proceedings of the 20th Int. Conference on Pattern Recognition (ICPR) |
| Number of pages | 4 |
| Publisher | IEEE |
| Publication date | 07.10.2010 |
| Pages | 4190-4193 |
| ISBN (Print) | 978-1-4244-7542-1 |
| ISBN (Electronic) | 978-1-4244-7541-4 |
| DOIs | |
| Publication status | Published - 07.10.2010 |
| Event | 2010 20th International Conference on Pattern Recognition - Istanbul, Turkey Duration: 23.08.2010 → 26.08.2010 |