Multi-Mode Detection and Identification of Biometric Using Multilevel Scaler SVM

Abstract

the face, iris and fingerprint are most promising biometric authentication system that can be identify and analysis a person as their unique features that can be quickly extracted during the recognition process. to ensure the actual presence of a real legitimate trait in difference to a fake self-pretended synthetic or reconstructed sample is aimportant problem in biometric verification, which needs the development of new and efficient protection measures. biometric systems are susceptible to spoofing attack. a dependable and efficient remedy is needed to attack the epidemic growth in identity theft. the biometric system deals with non-ideal scenarios such as blurred images, reflections etc. which are faked by others. due to this image quality assessment approaches to implement fake detection method in multimodal biometric systems. image quality assessment approach is used to prepare the feature vector which contains quality parameters such as blur level, color diversity, reflection, error rate, noise rate, similarity values and so on. then implement multi level support vector machine classification algorithm to detect fake biometrics by storing these features as vectors in database.

Authors and Affiliations

P Appala Naidu, Dr. CH GVN Prasad

Keywords

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  • EP ID EP24591
  • DOI -
  • Views 373
  • Downloads 11

How To Cite

P Appala Naidu, Dr. CH GVN Prasad (2017). Multi-Mode Detection and Identification of Biometric Using Multilevel Scaler SVM. International Journal for Research in Applied Science and Engineering Technology (IJRASET), 5(6), -. https://www.europub.co.uk/articles/-A-24591