Security Enhancement of Dynamic Signature by Utilizing Local Features with Individual Threshold

2018 ◽  
Vol 24 (10) ◽  
pp. 7636-7642
Author(s):  
Suryanti Awang ◽  
Nor Faradilla Mohamed Idris ◽  
Junaida Sulaiman
Author(s):  
Suresha .M ◽  
. Sandeep

Local features are of great importance in computer vision. It performs feature detection and feature matching are two important tasks. In this paper concentrates on the problem of recognition of birds using local features. Investigation summarizes the local features SURF, FAST and HARRIS against blurred and illumination images. FAST and Harris corner algorithm have given less accuracy for blurred images. The SURF algorithm gives best result for blurred image because its identify strongest local features and time complexity is less and experimental demonstration shows that SURF algorithm is robust for blurred images and the FAST algorithms is suitable for images with illumination.


2014 ◽  
Vol 24 ◽  
pp. 47-52
Author(s):  
Joanna Putz-Leszczynska

This paper addresses template ageing in automatic signature verification systems. Handwritten signatures are a behavioral biometric sensitive to the passage of time. The experiments in this paper utilized a database that contains signature realizations captured in three sessions. The last session was captured seven years after the first one. The results presented in this paper show a potential risk of using an automatic handwriting verification system without including template ageing Purchase Article for $10 


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