Publication Type:

Journal Article

Source:

International Journal of Pure and Applied Mathematics, Volume 117, Issue 10, p.37-41 (2017)

URL:

https://acadpubl.eu/jsi/2017-117-8-10/articles/10/7.pdf

Abstract:

The recognizable proof and authentication are finished by passwords, stick number, which is effectively broken by others. Biometrics is an effective and remarkable device in light of the useful and behavioral qualities of the individuals keeping in mind the end goal to demonstrate their authentication. One of the present patterns in biometric human recognizable proof is the improvement of new creating modalities.. For authentication four distinct modules are considered. This work diverse element as are considered to combination process highlight level combination used recognized the biometrics with help optimal Neural Network (NN), here shrouded layer and neuron optimization process Gray wolf optimization (GWO) system is utilized. From the process the trial results are contrasting with existing way to deal with demonstrate our proposed display as best for biometric authentication process.

Cite this Research Publication

N. Lalithamani, “Optimal NN Based Multimodal Biometric Authentication Using Palm and Finger Knuckle Images”, International Journal of Pure and Applied Mathematics, vol. 117, no. 10, pp. 37-41, 2017.