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Biomolecular Detection employing the Interferometric Reflectance Imaging Sensor (IRIS)
Published on: May 3, 2011
A novel iris localization algorithm based on the gray distributions of eye images
Weiqi Yuan1, Lu Xu, Zhonghua Lin
1Computer Vision Group, Shenyang University of Technology, Box 29, No.1, South Thirteenth Road, Tiexi District, Shenyang 110023, China. yuan60@126.com.
Summary
This study introduces a new iris localization algorithm using gray image features for accurate pupil and iris boundary detection. Experiments show it outperforms traditional methods like Daugman's algorithm.
Area of Science:
- Computer Vision
- Biometrics
- Image Processing
Background:
- Accurate iris localization is crucial for reliable biometric identification.
- Existing iris localization algorithms have limitations in speed and accuracy.
Purpose of the Study:
- To propose a novel iris localization algorithm.
- To improve the accuracy and speed of iris localization.
Main Methods:
- Utilizing gray distributions and features of eye images.
- Employing a gray value summing operator to find a point inside the pupil.
- Using a boundary detection template to identify inner and outer iris boundaries.
- Calculating circle parameters from detected boundary points.
Main Results:
- The proposed algorithm accurately localizes the iris.
- Achieved superior accuracy and speed compared to Daugman's algorithm and Hough transform.
- Validated on the CASIA iris image database.
Conclusions:
- The novel iris localization algorithm offers enhanced performance.
- Gray feature-based approach provides an effective method for iris localization.
- The algorithm is a promising advancement in iris recognition technology.
