Using image processing to performing biometric authentication applied on microcomputer based hand- wrist vein patterns
By: Khalaf, Ahmed Othman
.
Contributor(s): Salah, Shaimaa Khudhair.
Publisher: Haryana IOSR - International Organization of Scientific Research 2023Edition: Vol.25(4), Jul-Aug.Description: 50-54p.Subject(s): Computer EngineeringOnline resources: Click here
In:
IOSR Journal of Computer Engineering (IOSR-JCE)Summary: A kind of biometric recognition called vein identification systems uses vascular architecture to identify people.
One of these approaches is identification based on hand-wrist vein pattern. Hand-wrist vein pictures acquired
from persons utilizing an infrared light source with a wavelength of 850 nm were segmented in this research by
running them through several image processing techniques. The scale-independent feature transformation
(SURF) approach was used to extract critical points from segmented pictures. The SURF approach produces
characteristics such as rotation, camera angle, ambient light intensity, and so on. This strategy has been chosen
since it is unaffected by circumstances. During the identification procedure, the retrieved key points were
utilized to calculate the Euclidean distance. The accuracy rate was judged to be 97% as a consequence of the
matching operations employing the database's hand-wrist vein patterns.
| Item type | Current location | Call number | Status | Date due | Barcode | Item holds |
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Articles Abstract Database
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School of Engineering & Technology Archieval Section | Not for loan | 2023-1554 |
A kind of biometric recognition called vein identification systems uses vascular architecture to identify people.
One of these approaches is identification based on hand-wrist vein pattern. Hand-wrist vein pictures acquired
from persons utilizing an infrared light source with a wavelength of 850 nm were segmented in this research by
running them through several image processing techniques. The scale-independent feature transformation
(SURF) approach was used to extract critical points from segmented pictures. The SURF approach produces
characteristics such as rotation, camera angle, ambient light intensity, and so on. This strategy has been chosen
since it is unaffected by circumstances. During the identification procedure, the retrieved key points were
utilized to calculate the Euclidean distance. The accuracy rate was judged to be 97% as a consequence of the
matching operations employing the database's hand-wrist vein patterns.
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