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 Volume 5, Issue 2 (February 2018), Pages: 103-107


 Original Research Paper

 Title: A combined score level fusion approach for multi model biometric system using left and right palm print

 Author(s): B. Baron Sam *, M. Saravanan


 School of Computing, Sathyabama University, Chennai, India

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Biometrics is the art of setting up the character of an individual in view of the physical, concoction or behavioral properties of the individual. Palm Print recognizable proof is an imperative individual ID innovation and it has pulled in much consideration. The palm print contains standard bends and wrinkles as well as rich surface and miniscule focuses, so the palm print ID can accomplish a high exactness. We propose a novel structure of joining the left with right palm print at the coordinating (matching) score level. In the system, three sorts of coordinating (matching) scores, which are separately acquired by the left palm print coordinating, right palm print coordinating and crossing coordinating between the left query and right training palm print, are fused to make the final decision. The structure not only combines the left and right palm print images for identification, additionally appropriately abuses the comparability between the left and right palm print of a similar subject. The proposed strategy accurately takes the method for the left and right palm print pictures into record, and plans estimation to survey the relation between them. In additament, by using this nearness, the proposed weighted cumulation scheme uses a system to facilitate the three sorts of scores incited from the left and right palm print pictures. 

 © 2017 The Authors. Published by IASE.

 This is an open access article under the CC BY-NC-ND license (

 Keywords: Biometrics, Palm print, Matching score

 Article History: Received 1 August 2017, Received in revised form 2 December 2017, Accepted 10 December 2017

 Digital Object Identifier:


 Sam BB and Saravanan M (2018). A combined score level fusion approach for multi model biometric system using left and right palm print. International Journal of Advanced and Applied Sciences, 5(2): 103-107

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