Browsing by Author "Imtiaz Ahmad Bhat"

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    Automated fingerprint identification system
    (UMT Lahore, 2024-07-04) Mohammad Asad Sheikh; Abdul Basit; Imtiaz Ahmad Bhat; Tahir Mehmood Bhutta
    Accurate automatic personal identification is critical in a variety of applications in our electronically interconnected society. Biometrics, which refers to identification based on physical or behavioral characteristics, is being increasingly adopted to provide positive identification with a high degree of confidence. Among all the biometric techniques, fingerprint-based authentication systems have received the most attention because of the long history of fingerprints and their extensive use in forensics. However, the numerous fingerprint systems currently available still do not meet the stringent performance requirements of several important civilian applications. A critical step in automatic fingerprint matching is to automatically and reliably extract minutiae from the input fingerprint images. However, the performance of a minutiae extraction algorithm relies heavily on the quality of the input fingerprint images. In order to ensure that the performance of an automatic fingerprint identification and verification system is robust with respect to the quality of input fingerprint images, it is essential to incorporate a fingerprint enhancement algorithm in the minutiae extraction module. We present a fast fingerprint enhancement algorithm that can adaptively improve the clarity of ridge and furrow structures of input fingerprint images based on the estimated local ridge orientation and frequency. A fingerprint classification algorithm is presented in this paper. Fingerprints are classified into five categories: arch, tented arch, left loop, right loop, and whorl. The algorithm extracts singular points (cores and deltas) in a fingerprint image and performs classification based on the number and locations of the detected singular points. The fine-level matching is performed by extracting ridge endings and branching points, called minutiae, from a fingerprint image. The similarity between two fingerprints is determined by comparing the two sets of minutiae points.