Efficient Iris Identification with Improved Segmentation Techniques

View Sample PDF

Author(s): Abhishek Verma (New Jersey Institute of Technology, USA)and Chengjun Liu (New Jersey Institute of Technology, USA)
Copyright: 2012
Pages: 17
Source title: Cross-Disciplinary Applications of Artificial Intelligence and Pattern Recognition: Advancing Technologies
Source Author(s)/Editor(s): Vijay Kumar Mago (Simon Fraser University, Canada)and Nitin Bhatia (DAV College, India)
DOI: 10.4018/978-1-61350-429-1.ch009

Keywords: Artificial Intelligence / Computer Science & IT / Information Science Reference

Purchase

View Efficient Iris Identification with Improved Segmentation Techniques on the publisher's website for pricing and purchasing information.

Abstract

In this chapter, the authors propose and implement an improved iris recognition method based on image enhancement and heuristics. They make major improvements in the iris segmentation phase. In particular, the authors implement the raised to power operation for more accurate detection of the pupil region. Additionally, with their technique they are able to considerably reduce the candidate limbic boundary search space; this leads to a significant increase in the accuracy and speed of the segmentation. Furthermore, the authors selectively detect the limbic circle having center within close range of the pupil center. The effectiveness of the proposed method is evaluated on a grand challenge, large scale database: the Iris Challenge Evaluation (ICE) dataset.

The IRMA Community

Research IRM

Efficient Iris Identification with Improved Segmentation Techniques

Purchase

Abstract

Related Content

IRMA Sponsors