A New Method for Sclera Vessel Recognition using OLBP

No Thumbnail Available
File version
Author(s)
Das, Abhijit
Pal, Umapada
A. Ferrer Ballester, Miguel
Blumenstein, Michael
Griffith University Author(s)
Primary Supervisor
Other Supervisors
Editor(s)
Zhenan Sun
Date
2013
Size
File type(s)
Location
Jinan, China
License
Abstract

This paper proposes a new sclera vessel recognition technique. The vesselpatterns of sclera are unique for each individual and this can be utilized to identify a person uniquely. In this research we have used a time adaptive active contour-based region growing technique for sclera segmentation. Prior to that, we have made some tonal and illumination correction to get a clearer sclera area without the distributing vessel structure. This is because the presence of complex vessel structures occasionally affects the region-growing process. The sclera vessels are not prominent in the images, so in order to make them clearly visible, a local image enhancement process using a Haar high pass filter is incorporated. To get the total orientation of the vessels, we have used Orientated Local Binary Pattern (OLBP). The OLBP images of each class are used for template matching for classification by calculating the minimum Hamming Distance. We have used the UBIRIS version 1 dataset for the experimentation of our research. The proposed approach has achieved high recognition accuracy employing the above-mentioned dataset.

Journal Title
Conference Title
Biometric Recognition : 8th Chinese Conference, CCBR 2013 : Proceedings
Book Title
Edition
Volume
Issue
Thesis Type
Degree Program
School
Patent number
Funder(s)
Grant identifier(s)
Rights Statement
Rights Statement
Item Access Status
Note
Access the data
Related item(s)
Subject
Computer vision
Information and computing sciences
Persistent link to this record
Citation