LiveZilla Live Chat Software
Warning STRICT ERROR REPORTING IS ON
Deep Representation-Based Feature Extraction and Recovering for Finger-Vein Verification

Deep Representation-Based Feature Extraction and Recovering for Finger-Vein Verification

Starting at: Rs.4,500.00

4500 reward points

 Deep Representation-Based Feature Extraction and Recovering for Finger-Vein Verification

Finger-vein biometrics has been extensively investigated for personal verification. Despite recent advances in finger-vein verification, current solutions completely depend on domain knowledge and still lack the robustness to extract finger-vein features from raw images. This paper proposes a deep learning model to extract and recover vein features using limited a priori knowledge. First, based on a combination of the known state-of-the-art handcrafted finger-vein image segmentation techniques, we automatically identify two regions: a clear region with high separability between finger-vein patterns and background, and an ambiguous region with low separability between them. The first is associated with pixels on which all the above-mentioned segmentation techniques assign the same segmentation label (either foreground or background), while the second corresponds to all the remaining pixels. This scheme is used to automatically discard the ambiguous region and to label the pixels of the clear region as foreground or background. A training data set is constructed based on the patches centered on the labeled pixels. Second, a convolutional neural network (CNN) is trained on the resulting data set to predict the probability of each pixel of being foreground (i.e., vein pixel), given a patch centered on it. The CNN learns what a finger-vein pattern is by learning the difference between vein patterns and background ones. The pixels in any region of a test image can then be classified effectively. Third, we propose another new and original contribution by developing and investigating a fully convolutional network to recover missing finger-vein patterns in the segmented image. The experimental results on two public finger-vein databases show a significant improvement in terms of finger-vein verification accuracy.


 


ClickMyProject Specifications
 
 
Including Packages
 
Specialization
 
  * Supporting Softwares   * 24/7 Support
  * Complete Source Code   * Ticketing System
  * Complete Documentation   * Voice Conference
  * Complete Presentation Slides   * Video On Demand *
  * Flow Diagram   * Remote Connectivity *
  * Database File   * Code Customization **
  * Screenshots   * Document Customization **
  * Execution Procedure   * Live Chat Support
  * Readme File   * Toll Free Support *
  * Addons    
  * Video Tutorials    
       
 

*- PremiumSupport Service (Based on Service Hours) ** - Premium Development Service (Based on Requirements)


Add to Cart:

  • Model: PROJ8015
  • 999 Units in Stock
  • Manufactured by: ClickMyProjects

Please Choose:

Downloadable







This product was added to our catalog on Friday 08 June, 2018.

  0