A Hybrid Model of Multimodal Biometrics System using Fingerprint and Face as Traits
Sonam Shukla1 Pradeep Mishra2
1Sonam Shukla, M. Tech Scholar, Shri Shankaracharya Group of Institutions, Bhilai, India.
2Pradeep Mishra, Department of Computer Science And Engineering, Shri Shankaracharya Group of Institutions, Bhilai, India.
Manuscript received on February 15, 2012. | Revised Manuscript received on February 20, 2012. | Manuscript published on March 05, 2012. | PP: 406-410 | Volume-2 Issue-1, March 2012. | Retrieval Number: A0464022112 /2012©BEIESP
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The issues associated with identity usurpation are currently at the heart of numerous concerns in our modern society. Establishing the identity of individuals is recognized as fundamental to the numerous administrative operations. Identity documents (IDs) are tools that permit the bearers to prove or confirm their identity with a high degree of certainty. In response to the dangers posed by theft or fraudulent use of identity documents and security threats, a wide range of biometric technologies is emerging, covering e.g. face, fingerprint and iris. They are also proposed to enforce border control and check-in procedures. These are positive developments and they offer specific solutions to enhance document integrity and ensure that the bearer designated on the document is truly the person holding it. Biometric identifiers – conceptually unique attributes – are today portrayed as the panacea for identity verification. Biometrics is the science and technology of measuring and analyzing biological data of human body, extracting a feature set from the acquired data, and comparing this set against to the template set in the database. Experimental studies show that Unimodal biometric systems had many disadvantages regarding performance and accuracy. Multimodal biometric systems perform better than unimodal biometric systems and are popular even more complex also. We examine the accuracy and performance of multimodal biometric authentication systems using state of the art Commercial Off- The-Shelf (COTS) products. Here we discuss fingerprint and face biometric systems, decision and fusion techniques used in these systems. We also discuss their advantage over unimodal biometric systems.
Keywords: Fingerprint Recognition; Binarization; Block Filter Method; Matching score and Minutia; Face Recognition; Face Mask; Mask Fitting and Warping.