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- W3176353923 abstract "Biometric authentication has been reported to be one of the most emerging research fields and its attainments are inseparable from the aid of a heterogeneity of single-modal and multi-modal biometric traits (e.g., fingerprint, hand geometry, iris, face, ear, gait, and so on). Normally, biometric traits are used as authentication information for the security system. Sometimes, the characteristics of biometric traits are difficult to acquire in an appropriate means, and it is essential to practice numerous pre-processing and post-processing algorithms to improve the feature of traits on the security system. In this case, this review paper presents a comprehensive overview of the biometric fusion system (BFS) with some pre-processing and post-processing approaches using the concept of artificial intelligence/machine learning techniques. In this regard, the following subject matters are discussed: 1. Biometric traits quality improvement techniques in the BFS. 2. Feature extraction and optimization approaches. 3. Analysis of classifiers to improve biometric fusion accuracy. 4. Existing challenges of BFS. Besides, a review of existing work based on their accuracy of classification is also discussed. The main aim of this survey is to make available a complete overview of BFS with the role of a different biometric trait in biometrics fusion. ." @default.
- W3176353923 created "2021-07-05" @default.
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- W3176353923 date "2021-01-01" @default.
- W3176353923 modified "2023-10-16" @default.
- W3176353923 title "A Comprehensive Overview of Quality Enhancement Approach-Based Biometric Fusion System Using Artificial Intelligence Techniques" @default.
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- W3176353923 doi "https://doi.org/10.1007/978-981-16-1089-9_8" @default.
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