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  To Identify of Human Using Finger-Vein Imaging  
  Authors : Vandana Gajare S V Patil
  Cite as:

 

Biometric system has been actively emerging in various industries and continuing to roll to provide higher security features for access control system. The proposed system simultaneously acquires the finger surface and subsurface features from finger-vein and finger print images. This paper reviews the acquired finger vein and finger texture images are first subjected to pre-processing steps, which extract the region-of-interest (ROI). The enhanced and normalized ROI images employed to extract features and generate matching score. For this I will develop and investigate two new score-level combinations i.e. Gabour filter, Repeated line Tracking and Neural network comparatively evaluate them more popular score-level fusion approaches to ascertain their effectiveness in the proposed system. MATLAB software will be using for proposed work.

 

Published In : IJCSN Journal Volume 4, Issue 4

Date of Publication : August 2015

Pages : 655 - 658

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Publication Link : To Identify of Human Using Finger-Vein Imaging

 

 

 

Ms. Vandana Dilip Gajare : had completed her BE in E&TC and pursuing M.E. from the J.T. Mahajan college of Enginerering Faizpur. Maharashtra.

Mr. S. V. Patil : M.E.(Control & Instrumentation) working as a Sr. Lecturer in Dept of E&TC J.T. Mahajan College of Engineering, Faizpur. Maharashtra.

 

 

 

 

 

 

 

Finger-Vein Recognition

Gabour Filter

Repeated Line Tracking

Neural Network

This paper will present a complete finger image-matching framework by simultaneously utilizing the finger vein and finger texture features. It will present a new technique for the finger-vein identification that extract the features of finger image and obtain higher accuracy than previously proposed finger-vein identification approaches. Our authentification scheme will work more effectively in more realistic scenarios and leads to a more accurate performance, as will be demonstrated from the experimental results. We will examine a complete automated approach for the authentification of person by using finger surface texture images for the performance improvement.

 

 

 

 

 

 

 

 

 

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