Title: A novel approach on cluster-based indexing technique for level-1 and level-2 fingerprint features
Authors: N. Poonguzhali; M. Ezhilarasan
Addresses: Department of Computer Science and Engineering, Pondicherry Engineering College, Puducherry 605 014, India ' Department of Information Technology, Pondicherry Engineering College, Puducherry 605 014, India
Abstract: In recent years, automated fingerprint identification system (AFIS) plays a predominant role in personal authentication and verification. Fingerprint indexing is still a challenging issue in an AFIS as the size of database nowadays is huge. This paper proposes a cluster-based indexing on fingerprint features. The feature extraction of a fingerprint image is at three levels: level-1, level-2 and level-3. Fingerprint indexing is broadly classified as correlation-based matching, minutiae-based matching and non-minutiae-based matching. The fingerprint database is clustered using k-means algorithm. The fingerprint indexing methodology projected in this work is based on a combination of level-1 and level-2 features.
Keywords: biometrics; feature extraction; fingerprint matching; ridges; minutiae; k-means clustering; cluster-based indexing; fingerprint features; fingerprint indexing; fingerprint identification; fingerprint images.
International Journal of Computational Intelligence Studies, 2014 Vol.3 No.4, pp.320 - 328
Available online: 19 Jan 2015 *Full-text access for editors Access for subscribers Purchase this article Comment on this article