Footprint-Based Personal Recognition Using Dactyloscopy Technique

The uniqueness of human footprint has drawn attention of academia and industry in recent years and is emerging as a latest biometric trait for biometric authentication. A robust technique to be used for identification and recognition of an individual using footprint as a biometric trait has been proposed in this work. Most of the footprint recognition methods require segmentation or connected component analysis. The determinant values that produce the features of the human footprint are generally utilized in the recognition processes. Static footprint images of 94 individuals (57 males and 37 females) of different regions of North India between age group 15–25 years have been acquired using Dactyloscopy technique. Biometric performance parameters such as false accept rate, false reject rate, genuine accept rate, half total error rate, and accuracy have been computed. The experimental results show that the performance parameters computed for Dactyloscopy technique could be used for biometric authentication. This study could be of potential use for forensic and non-forensic purposes and researchers working in foot biometrics.