Scaling-robust fingerprint verification with smartphone camera in real-life scenarios

@article{Raghavendra2013ScalingrobustFV,
  title={Scaling-robust fingerprint verification with smartphone camera in real-life scenarios},
  author={Ramachandra Raghavendra and Christoph Busch and Bian Yang},
  journal={2013 IEEE Sixth International Conference on Biometrics: Theory, Applications and Systems (BTAS)},
  year={2013},
  pages={1-8}
}
We propose a new scheme for accurate contactless fingerprint recognition captured with smartphone cameras under various real-life scenarios. The proposed scheme can be structured using three building blocks namely: (1) finger segmentation (2) pre-processing and scaling (3) minutiae extraction and comparison. The proposed finger segmentation scheme is based on Mean Shift Segmentation (MSS) algorithm followed by multiple metrics to accurately segment the finger from the background. We then… CONTINUE READING

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Key Quantitative Results

  • The experimental results have shown the effectiveness of the proposed scheme on various complex backgrounds with an Equal Error Rate of 3.74% noted on Samsung S1 smartphone camera.
  • Extensive experiments carried out on this dataset shows that, the proposed segmentation method has achieved a remarkable accuracy with 94.66%, 96.50% and 98.21% on the samples captured with Nokia N8, iPhone 4 and Samsung S1 respectively.
  • Further, the proposed scaling scheme has also showed high performance with an accuracy of 97.42%, 98.43% and 97.25% on the samples captured with Nokia N8, iPhone 4 and Samsung S1 respectively that further indicates the robustness to various rotation and translation errors that can be encountered in real-life scenario.

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