Abstract
It is shown how basic geometric notions can be used to extract an image signature independently of position, orientation and size. Simple primitives as lengths and slopes remain invariant by affine 2D similarity transformations. They can easily be used to define the invariant signature of an image. Contrary to the previous work in this area, images can be directly analyzed. This means that the extraction of interest points of the image is avoided. The method remains formal and no estimation or compression is needed. It is formally demonstrated that 100% of transformations are taken into consideration and that the signature of the image is totally invariant. The Quick Invariant Signature (QIS) extraction is a formal and fast method. It can be used either, only for signature extraction, or be integrated into a neural architecture for both extraction and classification. Unusual invariances such as cylindrical translation or toric translation are also defined by QIS.
| Original language | English |
|---|---|
| Title of host publication | IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2009 |
| Publisher | IEEE Press |
| Pages | 172-177 |
| Number of pages | 6 |
| ISBN (Print) | 9781424459506 |
| DOIs | |
| Publication status | Published - 2009 |
| Event | 9th IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2009 - Ajman, United Arab Emirates Duration: 14 Dec 2009 → 16 Dec 2009 |
Conference
| Conference | 9th IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2009 |
|---|---|
| Country/Territory | United Arab Emirates |
| City | Ajman |
| Period | 14 Dec 2009 → 16 Dec 2009 |
Keywords
- Binary
- Image signature
- Invariant descriptor
- Shape matching