A new method for the detection of singular points in fingerprint images

• Type: Article in International Conference Proceedings Book
• Date: 2009

Authors

Filipe Tiago Alves de Magalhães (Author) FEUP; Hélder P. de Oliveira (Author) FEUP; Aurélio C. Campilho (Author) FEUP

Conference proceedings International

Title: Proceedings of the IEEE Workshop on Applications of Computer Vision

Pages: 157-162

Snowbird, Utah, USA, 7 a 8 de Dezembro de 2009

Indexing

Scopus - 7 Citations

INSPEC

Scientific classification

FOS: Engineering and technology > Electrical engineering, Electronic engineering, Information engineering

CORDIS: Technological sciences > Technology > Computer technology > Image processing

Other information

Authenticus ID: P-007-T0A

DOI: 10.1109/WACV.2009.5403106

Abstract (EN): Automatic biometric identification based on fingerprints is still one of the most reliable identification method in criminal and forensic applications. A critical step in fingerprint analysis without human intervention is to automatically and reliably extract singular points from the input fingerprint images. These singular points (cores and deltas) not only represent the characteristics of local ridge patterns but also determine the topological structure (i.e., fingerprint type) and largely influence the orientation field. Poincaré Indexbased methods are one of the most common for singular points detection. However, these methods usually result in many spurious detections. Therefore, we propose an enhanced version of the method presented by Zhou et al. [13] that introduced a feature called DORIC to improve the detection. Our principal contribution lies in the adoption of a smoothed orientation field and in the formulation of a new algorithm to analyze the DORIC feature. Experimental results show that the proposed algorithm is accurate and robust, giving better results than the best reported results so far, with improvements in the range of 5% to 7%.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 6