Efficient approach for iris recognition. Issue 7 (October 2016)
- Record Type:
- Journal Article
- Title:
- Efficient approach for iris recognition. Issue 7 (October 2016)
- Main Title:
- Efficient approach for iris recognition
- Authors:
- Hamouchene, Izem
Aouat, Saliha - Abstract:
- Abstract Iris texture is a natural password that has great advantages such as variability, stability, unique features for each person, and its importance in the security field. This makes an iris recognition system upper of other biometric methods used for human identification. Recent science is interested to develop intelligent systems able to identify persons based on the texture of their iris. We proposed a new feature extraction method based on local and directional texture information. The proposed feature extraction method gets both local and global relevant information and faster than commonly used method. In the experimental parts, our system is compared to other famous and recent iris recognition systems using CASIA iris dataset. Experiments demonstrate that the proposed system gives better recognition rate (99.96 %) compared to other systems.
- Is Part Of:
- Signal, image and video processing. Volume 10:Issue 7(2016)
- Journal:
- Signal, image and video processing
- Issue:
- Volume 10:Issue 7(2016)
- Issue Display:
- Volume 10, Issue 7 (2016)
- Year:
- 2016
- Volume:
- 10
- Issue:
- 7
- Issue Sort Value:
- 2016-0010-0007-0000
- Page Start:
- 1361
- Page End:
- 1367
- Publication Date:
- 2016-10
- Subjects:
- Image processing -- Pattern recognition -- Iris recognition -- Texture analysis
Signal processing -- Digital techniques -- Periodicals
Image processing -- Digital techniques -- Periodicals
Digital video -- Periodicals
621.3822 - Journal URLs:
- http://www.springerlink.com/content/120512/ ↗
http://www.springerlink.com/openurl.asp?genre=journal&issn=1863-1703 ↗
http://www.springer.com/gb/ ↗ - DOI:
- 10.1007/s11760-016-0900-y ↗
- Languages:
- English
- ISSNs:
- 1863-1703
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 8275.985203
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 9992.xml