Publication

Abstract : Objectives: To apply Multimodal Biometrics in the authentication process in hospital suites, fusing two Biometric traits namely face and fingerprint at the feature level to improve the security. Methods/Statistical analysis: This paper deals with using face and fingerprints, which are fused at the feature level and processed further. Majorly, techniques for pre-processing include Histogram Equalization for face, and Skeletonizing and thinning for fingerprints. In the next stage, Feature Extraction techniques like PCA (Principal Component Analysis) for face and Ridge Endings and Bifurcation extractions for fingerprint are used. Then once fused at feature level, shuffling is done and the fusion vectors are encrypted. These are used for authentication in hospital suites. Findings: In general, Multimodal Biometrics offers higher security than Unimodal when implemented efficiently. This concept can be used in hospital suites, where security is prime importance and a breach of the same can endanger the lives of patients. Application/Improvements: As mentioned, this concept can be highly useful in hospital suites, where close monitoring of access to VIP suites is necessary. Since a breach of security can be very sensitive in such places, it is important to employ maximum protection for the authentic-cation process. Areas where it could be improved further can be in increasing the number of traits for tighter security, and exploring apt fusion methods for the same to improve efficiency. Also, in future different encryption algorithms can be tested and tried.