Paper Info
Title
Contactless finger knuckle identification using smartphones
Abstract
This paper details the development of a smartphone based online system to automatically identify a person by using their finger knuckle image. The key objective is to exploit user-friendly biometric, with least privacy concern, to enhance security of the data in smartphone. The final product from this research is a finger knuckle authentication smartphone application, which is developed under Android operating system with environment version 2.3.3. This paper has developed some specialized algorithms for the finger knuckle detection, image pre-processing and region segmentation. Automatically detected and segmented finger knuckle images are used to encode finger knuckle pattern phase information using a pair of log-Gabor filters. Efficient implementation of various modules is achieved in C/C++ programming language, with OpenCV library, for online application. We also developed a user-friendly graphical user interface for the users to enroll and authenticate themselves. The developed system can therefore acquire finger knuckle image from the smartphone camera and automatically authenticate the genuine users. This paper has also developed a new smartphone based finger knuckle image database of 561 finger knuckle images of 187 different fingers from 109 users, in real imaging environment. In the best of our knowledge, this is the first attempt to develop a mobile phone based finger knuckle identification which has shown highly promising results in automatically identifying the users from their finger knuckle images.
Year
Venue
Keywords
2012
BIOSIG
opencv library,image pre-processing,data privacy,c++ programming language,image segmentation,smartphone camera,region segmentation,operating systems (computers),finger knuckle detection,contactless finger knuckle identification,biometrics (access control),authorisation,graphical user interfaces,c++ language,automatic person identification,finger knuckle image,object detection,user-friendly biometric,log-gabor filters,privacy concern,online system,smart phones,android operating system version 2.3.3,finger knuckle pattern phase information encoding,user-friendly graphical user interface,finger knuckle authentication smartphone application,c programming language,data security enhancement
Field
DocType
ISSN
Computer vision,Object detection,Authentication,Android (operating system),Computer science,Image segmentation,Graphical user interface,Artificial intelligence,Biometrics,Mobile phone,Knuckle
Conference
1617-5468
ISBN
Citations 
PageRank 
978-1-4673-1010-9
14
0.70
References 
Authors
8
2
Name
Order
Citations
PageRank
KamYuen Cheng1140.70
Ajay Kumar2246.99