On Multiview Analysis for Fingerprint Liveness Detection

• Published in: Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications Vol. 9423; pp. 143 - 150
• Main Authors: Toosi, Amirhosein, Cumani, Sandro, Bottino, Andrea
• Format: Book Chapter
• Language: English
• Published: Switzerland Springer International Publishing AG 2015; Springer International Publishing
• Series: Lecture Notes in Computer Science
• Subjects: Artificial intelligence; Image processing; Multi task learning; Multiview approach; Pattern recognition; Sparse reconstruction; Spoofing detection; SVM
• ISBN: 9783319257501; 3319257501
• ISSN: 0302-9743; 1611-3349
• DOI: 10.1007/978-3-319-25751-8_18

Fingerprint recognition systems, as any other biometric system, can be subject to attacks, which are usually carried out using artificial fingerprints. Several approaches to discriminate between live and fake fingerprint images have been presented to address this issue. These methods usually rely on the analysis of individual features extracted from the fingerprint images. Such features represent different and complementary views of the object in analysis, and their fusion is likely to improve the classification accuracy. However, very little work in this direction has been reported in the literature. In this work, we present the results of a preliminary investigation on multiview analysis for fingerprint liveness detection. Experimental results show the effectiveness of such approach, which improves previous results in the literature.