Fusing iris colour and texture information for fast iris recognition on mobile devices

2016 ◽  
Author(s):  
Chiara Galdi ◽  
Jean-Luc Dugelay
Keyword(s):  
Mobile Devices ◽  
Iris Recognition ◽  
Texture Information ◽  
Iris Colour

Ubiquitous iris recognition by means of mobile devices

2015 ◽  
Vol 57 ◽  
pp. 66-73 ◽  
Author(s):  
Silvio Barra ◽  
Andrea Casanova ◽  
Fabio Narducci ◽  
Stefano Ricciardi
Keyword(s):  
Mobile Devices ◽  
Iris Recognition

scholarly journals An Accurate and Efficient User Authentication Mechanism on Smart Glasses Based on Iris Recognition

2017 ◽  
Vol 2017 ◽  
pp. 1-14 ◽  
Author(s):  
Yung-Hui Li ◽  
Po-Jen Huang
Keyword(s):  
Mobile Devices ◽  
Iris Recognition ◽  
Hamming Distance ◽  
User Authentication ◽  
Infrared Camera ◽  
Modern Society ◽  
Infrared Light ◽  
Recognition Mechanism ◽  
Authentication Mechanism ◽  
Smart Glasses

In modern society, mobile devices (such as smart phones and wearable devices) have become indispensable to almost everyone, and people store personal data in devices. Therefore, how to implement user authentication mechanism for private data protection on mobile devices is a very important issue. In this paper, an intelligent iris recognition mechanism is designed to solve the problem of user authentication in wearable smart glasses. Our contributions include hardware and software. On the hardware side, we design a set of internal infrared camera modules, including well-designed infrared light source and lens module, which is able to take clear iris images within 2~5 cm. On the software side, we propose an innovative iris segmentation algorithm which is both efficient and accurate to be used on smart glasses device. Another improvement to the traditional iris recognition is that we propose an intelligent Hamming distance (HD) threshold adaptation method which dynamically fine-tunes the HD threshold used for verification according to empirical data collected. Our final system can perform iris recognition with 66 frames per second on a smart glasses platform with 100% accuracy. As far as we know, this system is the world’s first application of iris recognition on smart glasses.

Kurtosis and skewness at pixel level as input for SOM networks to iris recognition on mobile devices

2017 ◽  
Vol 91 ◽  
pp. 37-43 ◽  
Author(s):  
Andrea F. Abate ◽  
Silvio Barra ◽  
Luigi Gallo ◽  
Fabio Narducci
Keyword(s):  
Mobile Devices ◽  
Iris Recognition

scholarly journals Local Binary Pattern Based Iris Recognition Model

2020 ◽  
pp. 19-22
Keyword(s):  
Human Physiology ◽  
Iris Recognition ◽  
Local Binary Pattern ◽  
Nearest Neighbor ◽  
Hamming Distance ◽  
Experimental Results ◽  
Recognition Model ◽  
Nearest Neighbor Classifier ◽  
Texture Information ◽  
Neighbor Classifier

Iris is a unique biometric tool, secure and reliable in recognizing an individual based on the texture information of human physiology. The Local Binary Pattern method uses descriptors based on histograms of Local Binary Pattern. In developed algorithm, Local Binary Pattern (LBP) histograms of iris images are extracted and concatenated into single enhanced histogram. It can be computed by nearest neighbor classifier and iris recognition is performed using Hamming distance as dissimilarity measure. We have conducted experimentation on CASIA dataset. From the experimental results, it is proved that the Robust LBP technique for iris recognition is more accurate than the conventional LBP.

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