A Novel Authentication Using Multimodal Biometrics System

Regular price
Sale price
Regular price
Sold out
Unit price
Shipping calculated at checkout.


The data or information must be stored and retrieved securely in Airports, Militaries, etc. Whenever access to data is considered, secure authentication is a must. The secure authentication is required for secure accessing of the business information at any period of time. Different conventional techniques are available such as passwords of alphanumeric and symbols for avoiding the fraudulent access activities. However, the security of the system is less due to some weak passwords and symbols which are easily hacked by the attackers. Thus, multi-modal bio-metric system is developed in which multiple bio-metrics such as iris, face, and fingerprint of an individual is utilized as password in order to access the system. The integration of the multiple bio-metrics information is achieved by different fusion level techniques such as feature-level, score-level and decision-level fusion. Nowadays, multi-modal bio-metric authentication system is developed by using modern techniques. However, the efficiency and recognition rate of the authentication are still not effectively improved.


Angeline Prasanna Gopalan


Dr. G. Angeline Prasanna, Associate Professor and Head, Department of CS. she has completed her B.Sc(CT), M.Sc(CS)., M.C.A., M.Phil., and Ph.D, in Bharathiar University. She completed her Doctorial Degree in January 2018. She produced 23 M.Phil Scholars under her Guidance. She published more than 15 papers in International and National Journals.

Number of Pages:


Book language:


Published On:




Publishing House:

LAP LAMBERT Academic Publishing


iris, Face, fingerprint, SCI, Visual Information Fidelity, Sparse Concentration IndexSLF, Score-Level FusionSMBR, Sparse feature based Multimodal Biometric RecognitionSME, Spectral Magnitude ErrorSMO, Sequential Minimal OptimizationSNR, Signal-to-Noise RatioSOC, System-On-ChipSPE, Spectral Phase ErrorSSIM, Structural Similarity IndexSVM, Support Vector MachineTCD, Total Corner DifferenceTED, Total Edge DifferenceUBM, Universal Background ModelUCN, Unconstrained Cohort NormalisationVIF

Product category:

COMPUTERS / Networking / General