Abstract
Fingerprint recognition has emerged asone of the mostimportant methods for personal recognition. Though, owing to the skin conditions, some feature points are hard to extract, so some fingerprints could not be identified by feature based techniques. In order to address this limitation, this research explores an efficient algorithm for fingerprint recognition based on hybrid features of Discrete Cosine Transform (DCT), Discrete Wavelet Transform (DWT), and moment methods. The proposed technique can be applied for high accuracy fingerprint recognition task in biometric systems.
| Original language | English |
|---|---|
| Title of host publication | 2017 24th Iranian Conference on Biomedical Engineering and 2017 2nd International Iranian Conference on Biomedical engineering (ICBME) |
| Editors | Sara Barati |
| Place of Publication | Piscataway NJ USA |
| Publisher | IEEE, Institute of Electrical and Electronics Engineers |
| Pages | 41-46 |
| Number of pages | 6 |
| ISBN (Electronic) | 9781538636091 |
| ISBN (Print) | 9781538636107 |
| DOIs | |
| Publication status | Published - 2017 |
| Externally published | Yes |
| Event | National and International Iranian Conference on Biomedical Engineering 2017 - Tehran, Iran Duration: 30 Nov 2017 → 1 Dec 2017 Conference number: 24th/2nd https://ieeexplore.ieee.org/xpl/conhome/8412772/proceeding (Proceedings) |
Conference
| Conference | National and International Iranian Conference on Biomedical Engineering 2017 |
|---|---|
| Abbreviated title | ICBME 2017 |
| Country/Territory | Iran |
| City | Tehran |
| Period | 30/11/17 → 1/12/17 |
| Internet address |
Keywords
- DCT
- DWT
- fingerprint
- hybrid feature extraction
- moment invarients