A Robust Finger Knuckle Print Authentication using Topothesy and fractal dimension

Abstract

The finger knuckle based biometric authentication system using the approaches like, Gaussian smoothed high pass, Gaussian smoothed oriented derivative, and also the well known method for surface roughness measurement called the fractal profiles represented by Topothesy and fractal dimension which describe not only the roughness but also the affine self similarity is presented. Daisy descriptor for the representation of texture implemented. The results of fractal parameters along with the refined scores are comparable to those of the compcode and impcompcode.

Identification of soldiers and weapons in military armory based on comparison image processing and RFID tag

“…In terms of authentication of military personnel, in addition to RFID tags that would be embedded in them, biometrics can also be applied. Biometrics can be used for authentication to improve various systems as presented in (Kour et al, 2016), who see the application of biometrics as the key to the future of cyber security.…”

“…Algorithms that allow a text to be read from an image are machine learning algorithms and fall under the domain of Artificial Intelligence (AI). The authors in (Hanmandlu et al, 2017) used an image of a finger knuckle for the personnel authentication.…”

Evaluation of the surface quality of spun materials using topothesy

“…Russ mentions that this distance can be very small in real samples, making the physical interpretation often complicated, but that the topothesy has the advantage that it can be evaluated from a line profile, like in mechanical surface roughness measurements [8]. This fractal parameter has been successfully implemented, e.g., for fingerprint detection [9].…”