Synthesis of Palm Print in Feature Fusion Techniques for Multimodal Biometric Recognition System Online Signature

Author:

T. Vijayakumar

Abstract

Biometric identification technology is widely utilized in our everyday lives as a result of the rising need for information security and safety laws throughout the world. In this aspect, multimodal biometric recognition (MBR) has gained significant research attention due to its ability to overcome several important constraints in unimodal biometric systems. Henceforth, this research article utilizes multiple features such as an iris, face, finger vein, and palm print for obtaining the highest accuracy to identify the exact person. The utilization of multiple features from the person improves the accuracy of biometric system. In many developed countries, palm print features are employed to provide the most accurate identification of an actual individual as fast as possible. The proposed system can be very suitable for the person who dislikes answering many questions for security authentication. Moreover, the proposed system can also be used to minimize the extra questionnaire by achieving a highest accuracy than other existing multimodal biometric systems. Finally, the results are computed and tabulated in this research article.

Publisher

Inventive Research Organization

Cited by 47 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Deep learning-powered multimodal biometric authentication: integrating dynamic signatures and facial data for enhanced online security;Neural Computing and Applications;2024-04-15

2. HGSSA-bi LSTM: A Secure Multimodal Biometric Sensing Using Optimized Bi-Directional Long Short-Term Memory with Self-Attention;ECS Sensors Plus;2024-01-24

3. A Research Study into Palm Print Based Biometric System;2023 International Conference on Computer Science and Emerging Technologies (CSET);2023-10-10

4. Security system based on hand geometry and palmprint for user authentication in E-correction system;International Journal of Information Technology;2023-09-13

5. Biometric Fusion Approaches Based on Deep Convolutional Neural Network;2023 Al-Sadiq International Conference on Communication and Information Technology (AICCIT);2023-07-04

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