Abstract
Biometric traits such as fingerprint, retina scan, and palm-prints are used to identify a person at attendance monitoring, banking, passport, travel, and many other applications. Biometric-based person identification is the only method that never changes according to time, and no one can copy it without knowledge. Footprint-based biometric is one way to recognize a person based on different features associated with human footprints. For example, some places, such as airports, nanotechnology laboratories, silicon industries, temples, and public areas, require high security. It is necessary to add a footprint-based biometric trait for such high alert areas. The number of subjects taken by existing footprint-based methods is limited to very few subjects. The above research gaps motivate to add more subjects for this study. The proposed algorithm utilizes the fuzzy logic-based method for personal identification. Considerably 220 subjects with temporal aspects are taken into account to fill the existing methods gap. Three approaches, Fine Gaussian SVM (FSVM), Fine KNN (FKNN), and Fuzzy Ensemble Subspace Discriminant (FESD), have been utilized to create the enhanced human footprint matcher. The Fine Gaussian SVM approach exhibits an accuracy of 84.7%, the FKNN approach results in an accuracy of 92.3%, and the FESD approach gives an accuracy of 98.89%. FESD approach rectifies the recognition rate(to reach the required accuracy of 98.88%) False Match Rate (FMR, the rate of falsely as genuine classified imposters) at 0.01, False Non-Match Rate at 0.093 which is the rate of falsely as imposter classified genuine users) to a set of different matchers for the identification task. It improves the speed of recognition with 220 subjects by implementing the prototype schemes for footprint biometric to evaluate system properties, including accuracy and performance.
Highlights
There are many biometric matching techniques available for identification
The objective of the research work was to meet all aspects of existing biometric characteristics to a new biometric modality human footprint
Universality is every subject in the system holds some features and human footprints hold a high number of features like minutiae, toeprint, the area of footprint, centroid and so forth
Summary
There are many biometric matching techniques available for identification. Footprint-based biometric is a considerably newer technique for personal identification. Some other methods based on smart cards are available. One can intrude the methods based on smart cards. Most of the means for personal identification are used for attendance. The associate editor coordinating the review of this manuscript and approving it for publication was Guitao Cao. monitoring. The footprint-based matching technique does not propose it as a method for attendance monitoring though it has the capability for the same. In cases where a person without hands can use this technique for attendance monitoring. Aadhar in India is such a card that stores biometric data of face, retina, palm, and fingers but not the footprint [1]–[4]
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