Fingerprint Identification using Multiwavelet Transform | ||
| Al-Rafidain University College For Sciences | ||
| Article 1, Volume 0, Issue 23, March 2017, Pages 131-138 | ||
| Author | ||
| Enas Mohammed Hussein | ||
| Abstract | ||
| identification systems have been developed to achieve automatic identification of a person based on his physiological or behavioral characteristics. Biometric systems are critical in a wide range of applications such as banking system, E-commerce, smart cards, and access control to secure system. Automatic fingerprint identification is one of the most reliable biometric system, which is used for identifying persons. This study, aim is to design a fingerprint identification system, which is capable of identifying a fingerprint with high level of accuracy. Therefore, this system can be applied to a wide range of forensic applications. The proposed algorithm based upon multiwavelet transform (one level) as feature extraction and minimum distance classifier ( Euclidean distance) to make automatic fingerprint identification . The identification accuracy of this algorithm has been found to be 72%. | ||
| Keywords | ||
| Fingerprint | ||
|
Statistics Article View: 85 PDF Download: 51 |
||