scholarly journals Iris Recognition on Low Computational Power Mobile Devices

10.5772/16228 ◽  
2011 ◽  
Author(s):  
Huiqi Lu ◽  
Chris R. ◽  
Rupert C.D.
Keyword(s):  
Mobile Devices ◽  
Iris Recognition ◽  
Computational Power

Applications Suitability on PvC Environments

2007 ◽  
pp. 57-62
Author(s):  
A . Flores ◽  
M. Polo Usaola
Keyword(s):  
Human Computer Interaction ◽  
Ubiquitous Computing ◽  
Mobile Devices ◽  
Operating Systems ◽  
Heterogeneous Computing ◽  
Computational Power ◽  
Human Environment ◽  
Memory Space ◽  
E Mail ◽  
Or Applications

Pervasive computing (PvC) environments should support the continuity of users’ daily tasks across dynamic changes of operative contexts. Pervasive or ubiquitous computing implies computation becoming part of the environment. Many different protocols and operating systems, as well as a variety of heterogeneous computing devices, are interrelated to allow accessing information anywhere, anytime in a secure manner (Weiser, 1991; Singh, Puradkar, & Lee, 2005; Ranganathan & Campbell, 2003).According to the initial considerations by Weiser (1991), a PvC environment should provide the feeling of an enhanced natural human environment, which makes the computers themselves vanish into the background. Such a disappearance should be fundamentally a consequence not of technology but of human psychology, since whenever people learn something sufficiently well, they cease to be aware of it. This means that the user’s relationship to computation changes to an implicit human-computer interaction. Instead of thinking in terms of doing explicit tasks “on the computer”—creating documents, sending e-mail, and so on—on PvC environments individuals may behave as they normally do: moving around, using objects, seeing and talking to each other. The environment is in charge of facilitating these actions, and individuals may come to expect certain services which allow the feeling of “continuity” on their daily tasks (Wang & Garlan, 2000).Users should be allowed to change their computational tasks between different operative contexts, and this could imply the use of many mobile devices that help moving around into the environment. As a result, the underlying resources to run the required applications may change from wide memory space, disk capacity, and computational power, to lower magnitudes. Such situations could make a required service or application inappropriate in the new context, with a likely necessity of supplying a proper adjustment. However, users should not perceive the surrounding environment as something that constraints their working/living activities. There should be a continuous provision of proper services or applications. Hence the environment must be provided with a mechanism for dynamic applications suitability (Flores & Polo, 2006).

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 A Contextual Data Offloading Service With Privacy Support

2019 ◽  
Author(s):  
Francisco Gomes ◽  
Lincoln Rocha ◽  
Fernando Trinta
Keyword(s):  
Mobile Devices ◽  
Mobile Device ◽  
Context Aware ◽  
Computational Power ◽  
Context Model ◽  
Data Offloading ◽  
Contextual Data ◽  
Data History ◽  
Remote Environment ◽  
The Impact

Mobile and context-aware applications are now a reality thanks to the increased capabilities of mobile devices. In the last twenty years, researchers had proposed several software infrastructures to help the development of context-aware applications. We verified that most of them do not store contextual data history and that few of these infrastructures take into account the privacy of contextual data. This article presents a service named COP (Contextual data Offloading service with Privacy support) to mitigate these problems. Its foundations are: (i) a context model; (ii) a privacy policies; and (iii) a list of synchronization policies. The COP aims at storing and processing the contextual data generated from several mobile devices, using the computational power of the cloud. We have implemented one experiment evaluated the impact of contextual filter processing in the mobile device and the remote environment. In this experiment, we measured the processing time and the energy consumption of COP approach. The analysis detected that the migration of data from mobile device to a remote environment is advantageous.

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 On SOMA Parallelization with Android Devices

2019 ◽  
Vol 3 (3) ◽  
pp. 441
Author(s):  
Michal Bukáček
Keyword(s):  
Open Access ◽  
Mobile Devices ◽  
Original Work ◽  
Computational Power ◽  
Creative Commons ◽  
Advantages And Disadvantages ◽  
Left Behind ◽  
Desktop Computers ◽  
Common Task ◽  
Open Access Article

Today's world is full of new, small, personal handhelds. They are called smartphones or tablets. The machines themselves always have less power than desktop computers or even mainframes which were left behind. Their computational power can be increased when they are joined together in a group and are addressing one common task. To check and demonstrate the possibility of the use of mobile devices being joined to a group, the SOMA algorithm was chosen. The well as known functions, for example; De Jong, Rosenbrock, Rastrigin or Schwefel will be used and their extremes (minimums) will be realized. The goal is to test the speed of these mobile devices to realize the extremes of more dimensional functions. The advantages and disadvantages of this swarm linking will be shown. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium provided the original work is properly cited.

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