Name
Abstract | ||
|---|---|---|
Iris authentication/recognition on mobile devices is feasible.Spatial histograms can be exploited for iris features extraction and matching.Performance of iris segmentation/recognition algorithms is strongly affected by capture conditions.Imaging sensor's resolution alone does not necessarily result in higher recognition accuracy. The worldwide diffusion of latest generations mobile devices, namely smartphones and tablets, represents the technological premise to a new wave of applications for which reliable owner identification is becoming a key requirement. This crucial task can be approached by means of biometrics (face, iris or fingerprint) by exploiting high resolution imaging sensors typically built-in on this class of devices, possibly resulting in a ubiquitous platform to verify owner identity during any kind of transaction involving the exchange of sensible data. Among the aforementioned biometrics, iris is known for its inherent invariance and accuracy, though only a few works have explored this topic on mobile devices. In this paper a comprehensive method for iris authentication on mobiles by means of spatial histograms is described. The proposed approach has been tested on the MICHE-I iris dataset, featuring subjects captured indoor and outdoor under controlled and uncontrolled conditions by means of built-in cameras aboard three among the most diffused smartphones/tablets on the market. The experimental results collected, provide an interesting insight about the readiness of mobile technology with regard to iris recognition. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1016/j.patrec.2014.10.011 | Pattern Recognition Letters |
Keywords | Field | DocType |
Biometrics,Iris recognition,Mobile devices | Mobile technology,Iris recognition,Computer vision,Authentication,Segmentation,Fingerprint,Mobile device,Artificial intelligence,Iris flower data set,Biometrics,Mathematics | Journal |
Volume | Issue | ISSN |
57 | C | 0167-8655 |
Citations | PageRank | References |
24 | 0.78 | 19 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Silvio Barra | 1 | 24 | 0.78 |
| Andrea Casanova | 2 | 40 | 5.58 |
| Fabio Narducci | 3 | 86 | 14.75 |
| Stefano Ricciardi | 4 | 141 | 20.57 |