Skip to main content

Scale Invariant Gabor Descriptor-Based Noncooperative Iris Recognition

Abstract

A new noncooperative iris recognition method is proposed. In this method, the iris features are extracted using a Gabor descriptor. The feature extraction and comparison are scale, deformation, rotation, and contrast-invariant. It works with off-angle and low-resolution iris images. The Gabor wavelet is incorporated with scale-invariant feature transformation (SIFT) for feature extraction to better extract the iris features. Both the phase and magnitude of the Gabor wavelet outputs were used in a novel way for local feature point description. Two feature region maps were designed to locally and globally register the feature points and each subregion in the map is locally adjusted to the dilation/contraction/deformation. We also developed a video-based non-cooperative iris recognition system by integrating video-based non-cooperative segmentation, segmentation evaluation, and score fusion units. The proposed method shows good performance for frontal and off-angle iris matching. Video-based recognition methods can improve non-cooperative iris recognition accuracy.

Publisher note

To access the full article, please see PDF.

Author information

Affiliations

Authors

Corresponding author

Correspondence to Yingzi Du.

Rights and permissions

Open Access This article is distributed under the terms of the Creative Commons Attribution 2.0 International License (https://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Reprints and Permissions

About this article

Cite this article

Du, Y., Belcher, C. & Zhou, Z. Scale Invariant Gabor Descriptor-Based Noncooperative Iris Recognition. EURASIP J. Adv. Signal Process. 2010, 936512 (2010). https://doi.org/10.1155/2010/936512

Download citation

Keywords

  • Feature Extraction
  • Feature Point
  • Recognition Accuracy
  • Recognition Method
  • Iris Image
\