Multimodal biometric identification based on overlapped fingerprints, palm prints, and finger knuckles using BM-KMA and CS-RBFNN techniques in forensic applications-Reference-Cited by-同舟云学术

Multimodal biometric identification based on overlapped fingerprints, palm prints, and finger knuckles using BM-KMA and CS-RBFNN techniques in forensic applications

Published:2023-08-12 Issue: Volume: Page:
ISSN:0178-2789
Container-title:The Visual Computer
language:en
Short-container-title:Vis Comput

Author:

Johnson Jyothi,Chitra R.

Publisher

Springer Science and Business Media LLC

Subject

Computer Graphics and Computer-Aided Design,Computer Vision and Pattern Recognition,Software

Link

https://link.springer.com/content/pdf/10.1007/s00371-023-03023-5.pdf

Reference30 articles.

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2. Kaushikp, S., Singh, R.: A new hybrid approach for palm print recognition in nPCA based palm print recognition system. In: 5th International conference on reliability, infocom technologies and optimization. (2016). http://dx.doi.org/https://doi.org/10.1109/ICRITO.2016.7784958

3. Anitha, M.L., Radhakrishna Rao, K.A.: A novel bimodal biometric identification system based on finger geometry and palm print. In: 19th International conference on digital signal processing. 20–23 Aug 2014, Hong Kong, China. (2014). https://doi.org/10.1109/ICDSP.2014.6900730

4. Choudhury Surabhi, H., Kumar, A., Laskar Shahedul, H.: Adaptive management of multimodal biometrics a deep learning and metaheuristic approach. Appl. Soft Comput. 106(8), 1–20 (2021). https://doi.org/10.1016/j.asoc.2021.107344

5. George, A., Karthick, G., Harikumar, R.: An efficient system for palm print recognition using ridges. Int. Conf. Intell. Comput. Appl. (2014). https://doi.org/10.1109/ICICA.2014.60

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