Low-complexity iris recognition method using 2D Gauss-Hermite moments

@article{Rahman2013LowcomplexityIR,
  title={Low-complexity iris recognition method using 2D Gauss-Hermite moments},
  author={S. M. Mahbubur Rahman and M. Masud Reza and Q. M. Zubair Hasani},
  journal={2013 8th International Symposium on Image and Signal Processing and Analysis (ISPA)},
  year={2013},
  pages={142-146}
}
The authenticity and reliability of iris recognition-based biometric identification system is well-proven. Traditional iris recognition methods use expensive feature extraction algorithms and complex-valued IrisCodes that may hinder the development of a fast identification technique for multimodal biometric system. In this paper, a new set of computationally efficient real-valued features is proposed for recognition of iris patterns using the two dimensional higher-order Gauss-Hermite moments… CONTINUE READING

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Key Quantitative Results

  • It has been claimed that the complex-valued IrisCodes carrying binary phase information of the templates obtained by using the two dimensional (2D) Gabor filter and the Hamming distance-based dissimilarity measure of the IrisCodes may provide a recognition accuracy of more than 99%.

Citations

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References

Publications referenced by this paper.
SHOWING 1-10 OF 31 REFERENCES

DCT-Based Iris Recognition

  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • 2007
VIEW 11 EXCERPTS
HIGHLY INFLUENTIAL

Image analysis by Gaussian-Hermite moments

  • Signal Processing
  • 2011
VIEW 4 EXCERPTS
HIGHLY INFLUENTIAL

Correction method for nonideal iris recognition

  • 2012 19th IEEE International Conference on Image Processing
  • 2012
VIEW 1 EXCERPT

Iris Data Indexing Method Using Gabor Energy Features

  • IEEE Transactions on Information Forensics and Security
  • 2012
VIEW 1 EXCERPT