Al-Taie, Sarah A. Mohammed and Khaleel, Baydaa I. (2023) Palm Print Recognition Using Intelligent Techniques: A review. Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI), 9 (1). pp. 156-164.
![[thumbnail of 14-Palm Print Recognition Using Intelligent Techniques A review.pdf]](http://eprints.uad.ac.id/style/images/fileicons/text.png) |
Text
14-Palm Print Recognition Using Intelligent Techniques A review.pdf Download (409kB) |
Abstract
Hand or Palm print recognition systems are one of the efficient people recognition and authentication systems that provide high-security levels by approving the entering and exiting of people such as employees in the work field or companies. The basis for using palmprints lies in the fact that no two individuals have exactly the same palmprint pattern, moreover palmprints remain more or less stablethroughout the lifetime and are easily obtainable using standard imaging techniques. Palm print recognition systems process picture data from a photograph of a person's palm and compare it to a record for that person using a scanning device or camera-based application. There are numerous ways to obtain a palmprint image, including digital scanners. Researchers have taken palmprint photographs using video cameras, CCD-based scanners, and tripods. A CCD-based scanner may be used to take a high resolution image of a palmprint. A palm image can also be perfectly aligned with the user's hand thanks to the pegs on the CCD-based scanner The palmprint has a variety of natural ompositions that are rich in identifying characteristics like wrinkles, ridges, major lines, single, and minute points. Because of these, a palmprint is a distinctive biometric that is trustworthy for identifying humans As Artificial Intelligence (AI) methods and applications improved, the improvement of computer techniques and the usage of techniques increased in all fields including people recognition field. Many intelligent techniques are used to recognize people such as neural networks, the Genetic Algorithm, Particle Swarm Algorithm, and Deep Learning all these techniques are used and have almost the same recognition accuracy.
| Item Type: | Artikel Umum |
|---|---|
| Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering |
| Divisi / Prodi: | Faculty of Industrial Technology (Fakultas Teknologi Industri) > S1-Electrical Engineering (S1-Teknik Elektro) |
| Depositing User: | M.Eng. Alfian Ma'arif |
| Date Deposited: | 24 Mar 2023 03:15 |
| Last Modified: | 24 Mar 2023 03:15 |
| URI: | http://eprints.uad.ac.id/id/eprint/41477 |
Actions (login required)
 |
View Item |