Enhance the classification and Score level Fusion Multi-model Biometric System Based on Fingerprint and Speech Recognition - Sharma, Shubhleen; Kumar, Dinesh (International Journal of Computer Sciences and Engineering, 2019)
Biometric is the technique for the recognition of the physiological and biological features which are the face, iris, and fingerprint and pattern analysis. Biometric is the method of identifying the biometric features. Some issues in the uni-modal biometric scheme that reduced performance and accuracy. To overcome the effect in the uni-modal biometric, biometric fusion can be used through a multimodal biometric system. Biometric fusion is a method of using multiple biometric information and steps for the processing of the information to improve the biometric system. Multi-model biometric systems meet various security issues and sometimes un-acceptance false rejection errors, false rejection rate, and error rates. Some of these problems can be reduced by setting up multi-model biometric systems. It supports joining twice biometric traits in a verification system to enhance the accuracy rate and Specificity. However, features of different biometrics have to be independent. In this research work, proposes a multi-modal biometric recognized using fingerprint and speech recognition. In the proposed approach, a Novel, user authentication system, based on a combined acquisition of Fingerprint and Speech with high accuracy rate, Precision, false acceptance rate, and false rejection rate. In fingerprint using Minutiae method and Speech using MFCC method used for feature extraction method. In this research work, develop a project application in MATLAB 2016a simulation tool and has developed a score level fusion of various or multiple biometrics help to reduce the system error rates.