Contactless fingerprint and palmprint fusion recognition based on quality assessment

Zhihua Liu; Bin Zhu; Yi Du

doi:10.1117/12.2681321

8 June 2023 Contactless fingerprint and palmprint fusion recognition based on quality assessment

Zhihua Liu, Bin Zhu, Yi Du

Proceedings Volume 12707, International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2023); 1270744 (2023) https://doi.org/10.1117/12.2681321
Event: International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2023), 2023, Changsha, China

Abstract

The quality problems of contactless fingerprint and palmprint samples due to sampling, itself and other factors lead to the decline of recognition efficiency. To improve the recognition efficiency, this paper proposed two kinds of fingerprint and palmprint image quality evaluation algorithms, LQA_S and GQA_L, based on SURF and ROI frequency domain intensity respectively, to evaluate the quality of target ROI from the local and global levels. Based on the evaluation algorithm, the contactless fingerprint and palmprint score-level fusion recognition was carried out, and the public reference data set was used for experimental verification. Through the analysis of the experimental data, it is proved that the contactless fingerprint and palmprint ROI quality evaluation algorithm can improve the accuracy of fingerprint and palmprint recognition, and the contactless fingerprint and palmprint fusion recognition accuracy based on this algorithm reaches 100%, which is superior to similar excellent methods in recent years.

Citation Download Citation

Zhihua Liu, Bin Zhu, and Yi Du "Contactless fingerprint and palmprint fusion recognition based on quality assessment", Proc. SPIE 12707, International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2023), 1270744 (8 June 2023); https://doi.org/10.1117/12.2681321

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