Visible to the public Multimodal Biometrics Feature Level Fusion for Iris and Hand Geometry Using Chaos-based Encryption Technique

TitleMultimodal Biometrics Feature Level Fusion for Iris and Hand Geometry Using Chaos-based Encryption Technique
Publication TypeConference Paper
Year of Publication2019
Conference Name2019 Fifth International Conference on Image Information Processing (ICIIP)
Date Publishednov
Keywordsbehavioral attributes, biometric encryption, chaos, Chaos encryption, chaos-based encryption technique, computational geometry, cryptography, false acceptance rate, false rejection rate, feature extraction, genuine acceptance rate, Hand geometry, hand geometry features, image fusion, image matching, Iris, iris features, Iris recognition, matching process, Metrics, Moments, morphological operations, multimodal biometric system, multimodal biometrics feature level fusion, Multimodal system, pattern recognition system, physiological attributes, pubcrawl, resilience, Resiliency, Scalability
AbstractBiometrics has enormous role to authenticate or substantiate an individual's on the basis of their physiological or behavioral attributes for pattern recognition system. Multimodal biometric systems cover up the limitations of single/ uni-biometric system. In this work, the multimodal biometric system is proposed; iris and hand geometry features are fused at feature level. The iris features are extracted by using moments and morphological operations are used to extract the features of hand geometry. The Chaos-based encryption is applied in order to enhance the high security on the database. Accuracy is predicted by performing the matching process. The experimental result shows that the overall performance of multimodal system has increased with accuracy, Genuine Acceptance Rate (GAR) and reduces with False Acceptance Rate (FAR) and False Rejection Rate (FRR) by using chaos with iris and hand geometry biometrics.
Citation Keykaur_multimodal_2019