Toward accurate localization and high recognition performance for noisy iris images

Iris recognition plays an important role in biometrics. Until now, many scholars have made different efforts in this field. However, the recognition performances of most proposed methods degrade dramatically when the image contains some noise, which inevitably occurs during image acquisition such as...

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Bibliographic Details
Published in:Multimedia tools and applications 2014-08, Vol.71 (3), p.1411-1430
Main Authors: Wang, Ning, Li, Qiong, Abd El-Latif, Ahmed A., Zhang, Tiejun, Niu, Xiamu
Format: Article
Language:English
Subjects:
Accuracy
Algorithms
Analysis
Applied sciences
Artificial intelligence
Biometric identification
Computer Communication Networks
Computer Science
Computer science
control theory
systems
Computer systems and distributed systems. User interface
Data Structures and Information Theory
Exact sciences and technology
Eyes & eyesight
Illumination
Information systems. Data bases
Localization
Mathematical analysis
Memory and file management (including protection and security)
Memory organisation. Data processing
Methods
Multimedia computer applications
Multimedia Information Systems
Navier-Stokes equations
Noise
Object recognition
Pattern recognition. Digital image processing. Computational geometry
Position (location)
Reflection
Software
Special Purpose and Application-Based Systems
Spots
Studies
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Summary:Iris recognition plays an important role in biometrics. Until now, many scholars have made different efforts in this field. However, the recognition performances of most proposed methods degrade dramatically when the image contains some noise, which inevitably occurs during image acquisition such as reflection spots, inconsistent illumination, eyelid, eyelash, hair, etc. In this paper, an accurate iris localization and high recognition performance approach for noisy iris images is presented. After filling the reflection spots using the inpainting method which is based on Navier-Stokes (NS) equations, the Probable boundary (Pb) edge detection operator is used to detect pupil edge initially, which can eliminate the interference of inconsistent illumination, eyelid, eyelash and hair. Besides, the accurate circle parameters are obtained in delicately to reduce the input space of Hough transforms. The iris feature code is constructed based on 1D Log-Gabor filter. Our thorough experimental results on the challenging iris image database CASIA-Iris-Thousand achieve an EER of 1.8272 %, which outperforms the state-of-the-art methods.
ISSN:1380-7501
1573-7721
DOI:10.1007/s11042-012-1278-7