Name
Title | ||
|---|---|---|
A framework for liveness detection for direct attacks in the visible spectrum for multimodal ocular biometrics |
Abstract | ||
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A new framework for liveness detection at the intra class level/user level.Proposed a more realistic database for liveness detection of ocular biometrics.A set of image quality features are proposed for liveness detection in ocular biometrics.To demonstrate the proposed framework, versatile spoofing techniques were explored.The proposed framework is more realistic and efficient compared to the state-of-the-art. In this research a new framework for software-based liveness detection for direct attacks in multimodal ocular biometrics across the visible spectrum is proposed. The framework aims to develop a more realistic method for liveness detection compared to previous frameworks proposed in the literature. To fulfil the above highlighted aims in this framework, intra-class level (i.e. user level) liveness detection is introduced. To detect liveness, a new set of image quality-based features is proposed for multimodal ocular biometrics in the visible spectrum. A variety of transformed domain (focus related) aspect and contrast-related quality features are employed to design the framework. Furthermore a new database is developed for liveness detection of multimodal ocular biometrics, which has the prominent presence of multimodal ocular traits (both sclera and iris). Moreover this database is comprised of a larger variety of fake images; those were prepared by employing versatile forging techniques which can be exhibited by imposters. Therefore the proposed schema has dealt with versatile categories of spoofing methods, which were not considered previously in the literature. The database contains a set of 500 fake and 500 genuine eye images acquired from 50 different eyes. An appreciable liveness detection result is achieved in the experiments. Furthermore, the experimental results conclude that this new framework is more efficient and competitive when compared to previous liveness detection schemes. Display Omitted |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1016/j.patrec.2015.11.016 | Pattern Recognition Letters |
Keywords | Field | DocType |
Biometrics,Sclera,Liveness,Iris,Visible spectrum | Computer vision,Pattern recognition,Spoofing attack,Image quality,Software,Artificial intelligence,Biometrics,Mathematics,Liveness | Journal |
Volume | Issue | ISSN |
82 | P2 | 0167-8655 |
Citations | PageRank | References |
2 | 0.35 | 17 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Abhijit Das | 1 | 62 | 9.71 |
| Umapada Pal | 2 | 1477 | 139.32 |
| Miquel Ferrer | 3 | 683 | 60.68 |
| Michael Blumenstein | 4 | 135 | 10.77 |