Efficient iris recognition by characterizing key local variations

@article{Ma2004EfficientIR,
  title={Efficient iris recognition by characterizing key local variations},
  author={Li Ma and Tieniu Tan and Yunhong Wang and Dexin Zhang},
  journal={IEEE Transactions on Image Processing},
  year={2004},
  volume={13},
  pages={739-750}
}
  • Li MaT. Tan Dexin Zhang
  • Published 1 June 2004
  • Computer Science
  • IEEE Transactions on Image Processing
Unlike other biometrics such as fingerprints and face, the distinct aspect of iris comes from randomly distributed features. This leads to its high reliability for personal identification, and at the same time, the difficulty in effectively representing such details in an image. This paper describes an efficient algorithm for iris recognition by characterizing key local variations. The basic idea is that local sharp variation points, denoting the appearing or vanishing of an important image… 
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1,068 Citations
Highly Influential Citations
68
Background Citations
313
Methods Citations
345
Results Citations
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1,068 Citations

Development of Local Feature Extraction and Reduction Schemes for Iris Biometrics

This thesis presents a salient keypoint detector called Salient Point of Interest using Entropy (SPIE), which reduces keypoints efficiently, by grouping all the closely placed keypoints into one using density-based clustering.

Iris Recognition based on Local sharp Variation Points

To characterize the most important features from two dimensional original iris images, a set of 1-D intensity signals which consist of most sharp variations is constructed and a dyadic wavelet transform is used to precisely locate the position of local sharp variations points which is recorded as features.

A New Encoding of Iris Images Employing Eight Quantization Levels

This work is proposing a new feature extraction method and new matching metric in order to find an effective threshold value to separate the intra and inter class distribution of the iris images of different people by using eight – level quantization.

PERSONAL IDENTIFICATION BASED ON ORDINAL MEASURES OF IRIS PATTERNS

Multilobe differential filters are developed to compute ordinal measures with flexible intralobe and interlobe parameters such as location, scale, orientation, and distance to characterize qualitative relationships between iris regions rather than precise measurements of iris image structures.

Recognition using SIFT and its Variants on Improved Segmented Iris

This thesis presents several SIFT based methods for extracting distinctive invariant features from iris that can be used to perform reliable matching between different views of an object or scene and provides a comparative analysis of these four methods.

Iris recognition using local texture analysis

This work presents an effective approach for iris recognition by analyzing iris patterns by dividing the normalized iris image into several regions to improve the rate of recognition and confirm the advantage of the proposed approach in terms of speed and accuracy.

Ordinal Measures for Iris Recognition

  • Zhenan SunT. Tan
  • Computer Science
    IEEE Transactions on Pattern Analysis and Machine Intelligence
  • 2009
This paper develops multilobe differential filters to compute ordinal measures with flexible intralobe and interlobe parameters such as location, scale, orientation, and distance and demonstrates the effectiveness of the proposed ordinal feature models.

Robust Iris Recognition based on Orientation Field

A robust iris recognition technique based on orientation field is presented and the performance of the implemented algorithms has been evaluated using Receiver Operating Characteristics (ROC) and experimental results are reported.

A new matching approach for local feature based iris recognition systems

This paper proposes a novel matching strategy with invariant properties, which is based on the possibilistic fuzzy clustering algorithm, to compare a pair of local feature sets and shows that the performance of the proposed approach is comparable to that of the well-known iris recognition systems.

Robust Iris Recognition based on Orientation Field

A robust iris recognition technique based on orientation field is presented and the performance of the implemented algorithms has been evaluated using Receiver Operating Characteristics (ROC) and experimental results are reported.
...

References

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