Cyber Times International Journal of Technology & Management

Biometrics is one of traditional and effective method for verification and validation. While using biometrics for security purpose users do not need to remember passwords also no need for extra training. Fingerprints are commonly used for authentication as they are different for every person even two identical twins have diverse fingerprints. Also sensors for fingerprint take less space and flexible to use. With all above advantages there are some pitfalls, sometimes system may fail in authentication if condition of finger during verification is wrinkle and during enrollment is dry. This problem is generally faced by the people working in maritime environment. In such situations genuine person gets unauthenticated and the system performance gets degraded. Implemented system will improve performance of wrinkled fingerprints. Performance evaluation is using resilient back-propagation neural network. Wet Wrinkled Fingerprint (WWF) dataset verify performance of system. The data set consists sample of dry as well as wrinkled fingerprints of same person.