A novel approach on cluster-based indexing technique for level-1 and level-2 fingerprint features. (25th January 2015)

• Record Type: Journal Article
• Authors: Poonguzhali, N.; Ezhilarasan, M.
• Is Part Of: International journal of computational intelligence studies. Volume 3:Number 4(2014)
• Page Start: 320
• Page End: 328
• Publication Date: 2015-01-25
• Subjects: biometrics -- indexing -- feature extraction -- fingerprint matching -- ridges -- minutiae -- k-means; Computational intelligence -- Periodicals; 006.305
• Languages: English
• ISSNs: 1755-4985

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.