Development a New Algorithm for Iris Biometric Recognition

@article{Hentati2012DevelopmentAN,
  title={Development a New Algorithm for Iris Biometric Recognition},
  author={Raida Hentati and Manel Hentati and Mohamed Abid},
  journal={International Journal of Computer and Communication Engineering},
  year={2012},
  pages={283-286}
}
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16 Citations
Background Citations
8
Methods Citations
3

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16 Citations

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Hierarchical Convolutional Neural Network based Iris Segmentation and Recognition System for Biometric Authentication

A new real time bio-metric model based on Deep Learning (DL) architecture called Hierarchical Convolutional Neural Network (HCNN) is presented, which provides the boundaries of actual iris with the help of learned features.

SIP-SegNet: A Deep Convolutional Encoder-Decoder Network for Joint Semantic Segmentation and Extraction of Sclera, Iris and Pupil based on Periocular Region Suppression

A novel deep learning framework called SIP-SegNet is presented, which performs the joint semantic segmentation of ocular traits (sclera, iris and pupil) in unconstrained scenarios with greater accuracy and extracts the periocular information using adaptive thresholding and employs the fuzzy filtering technique to suppress this information.

The Implementation of an Intelligent Algorithm Hybrid Biometric Identification for the Exemplary Hardware Platforms

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A multi-biometric iris recognition system based on a deep learning approach

An efficient and real-time multimodal biometric system is proposed based on building deep learning representations for images of both the right and left irises of a person, and fusing the results obtained using a ranking-level fusion method.

Iris Normalization using Circular Masking

The proposed method uses circular masking technique for iris normalization and the results obtained are satisfactory compared to regular irisnormalization techniques.

Modify k-medoids Algorithm with New Efficiency Method for Biometric Database Classification

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References

SHOWING 1-6 OF 6 REFERENCES

A machine-vision system for iris recognition

A prototype system for personnel verification based on automated iris recognition for noninvasive biometric measurement is described, in which the system exhibits flawless performance in the evaluation of 520 iris images.

Analysis of textual images using the Hough transform

Methods for handling several discretization problems that arise in mapping the rectangular image space to the (ρ, Θ) accumulator array are described.

Iris Feature Extraction Using 2D Phase Congruency

  • Xiaoyan YuanP. Shi
  • Computer Science
    Third International Conference on Information Technology and Applications (ICITA'05)
  • 2005
This paper made some experimental try to extract the iris feature using the 2D phase congruency, which invariant to changes in intensity or contrast, to try to avoid those problems of natural illumination or other variant conditions.

The Human Iris Structure and Its Usages

This paper is devoted to the human iris structure and to the practical usages of the knowledge of its structure, which are identiication of a person and iridology.

A human identification technique using images of the iris and wavelet transform

A new approach for recognizing the iris of the human eye is presented, and the resulting one-dimensional signals are compared with model features using different dissimilarity functions.

Person Identification Technique Using Human Iris Recognition

A new iris recognition system that implements (i) gradient decomposed Hough transform / integro-differential operators combination for iris localization and (ii) the "analytic image" concept (2D Hilbert transform) to extract pertinent information from iris texture is examined.