Abstract
Palmprint recognition is a variant of fingerprint matching as both the systems share almost similar matching criteria and the minutiae feature extraction methods. However, there is a performance degradation with palmprint biometrics because of the failure of extracting genuine minutia points from the region of highly distorted ridge information with huge data. In this paper, we propose an efficient palmprint matching algorithm using nearest neighbor minutiae quadruplets. The representation of minutia points in the form of quadruplets improves the matching accuracy at nearest neighbors by discarding scope of the global matching on false minutia points. The proposed algorithm is evaluated on publicly available high resolution palmprint standard databases, namely, palmprint benchmark data sets (FVC ongoing) and Tsinghua palmprint database (THUPALMLAB). The experimental results demonstrate that the proposed palmprint matching algorithm achieves the state-of-the-art performance.
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Acknowledgements
We are sincerely thankful to FVC and Tsinghua university for providing data sets for research. The first author is thankful to Technobrain India Pvt Limited, for providing support in his research.
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Rao, A.T., Ramaiah, N.P., Mohan, C.K. (2017). Palmprint Recognition Based on Minutiae Quadruplets. In: Raman, B., Kumar, S., Roy, P., Sen, D. (eds) Proceedings of International Conference on Computer Vision and Image Processing. Advances in Intelligent Systems and Computing, vol 460. Springer, Singapore. https://doi.org/10.1007/978-981-10-2107-7_11
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DOI: https://doi.org/10.1007/978-981-10-2107-7_11
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