Patterns Identification of Finger Outer Knuckles by Utilizing Local Directional Number

Abstract

Finger Outer Knuckle (FOK) is a distinctive biometric that has grown in popularity recently. This results from its inborn qualities such as stability, protection, and specific anatomical patterns. Applications for the identification of FOK patterns include forensic investigations, access control systems, and personal identity. In this study, we suggest a method for identifying FOK patterns using Local Directional Number (LDN) codes produced from gradient-based compass masks. For the FOK pattern matching, the suggested method uses two asymmetric masks—Kirsch and Gaussian derivative—to compute the edge response and extract LDN codes. To calculate edge response on the pattern, an asymmetric compass mask made from the Gaussian derivative mask is created by rotating the Kirsch mask by 45 degrees to provide edge response in eight distinct directions. The edge response of each mask and the combination of dominating vector numbers are examined during the LDN code-generating process. A distance metric can be used to compare the LDN code's condensed representation of the FOK pattern to the original for matching purposes. On the Indian Institute of Technology Delhi Finger Knuckle (IITDFK) database, the efficiency of the suggested procedure is assessed. The data show that the suggested strategy is effective, with an Equal Error Rate (EER) of 10.78%. This value performs better than other EER values when compared to different approaches.