Abstract Currently frequent biometric scientific research such as with biometric applications like face, iris, voice, hand-based biometrics traits like palm print and fingerprint technique are utilized for spotting out the persons. These specific biometrics habits have their own improvement and weakness so that no particular biometrics can adequately opt for all terms like the accuracy and cost of all applications. In recent times, in addition, to distinct with the hand-based biometrics technique, Finger Knuckle Print (FKP) has been appealed to boom the attention among biometric researchers. The image template pattern formation of FKP embraces the report that is suitable for spotting the uniqueness of individuality. This FKP trait observes a person based on the knuckle print and the framework in the outer finger surface. This FKP feature determines the line anatomy and finger structures which are well established and persistent throughout the life of an individual. In this paper, a novel method for personal identification will be introduced, along with that data to be stored in a secure way has also been proposed. The authentication process includes the transformation of features using 2D Log Gabor filter and Eigen value representation of Multi-Manifold Discriminant Analysis (MMDA) of FKP. Finally, these features are grouped using k-means clustering for both identification and verification process. This proposed system is initialized based on the FKP framework without a template based on the fuzzy vault. The key idea of fuzzy vault storing is utilized to safeguard the secret key in the existence of random numbers as chaff pints.

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[14] Zhang L., https://www4.comp.polyu.edu.hk/~biometrics/F KP, Last Visited, 2018. Muthukumar Arunachalam received BE (ECE), ME (Applied Electronics) degrees from Madurai Kamaraj University and Anna University in 2004 and 2006 respectively and PhD from Kalasalingam University, India. He is an Associate Professor Electronics and Communication Engineering, in Kalasalingam University, India, where he has been since 2007. His area of interest is Image processing, signal processing, biometrics, and wireless communication. He is a life member of ISTE. Kavipriya Amuthan received BE (ECE) and ME (Digital Communication and Networking) degrees from Kalasalingam Academy of Research and Education, in 2013 and 2015 respectively. Currently, she is pursuing as PhD full-time scholar in ECE at Kalasalingam Academy of Research and Education, India. Her area of interest is Image processing, Biometrics, Cryptography and Network Security.