Biometric Recognition Databases

Biometric Recognition Databases

1. Multi-Mode Database

   • Multimodal Biometrics: Multiple biometric traits Combined databases
   • Types: Independent samples Fusion of databases
   • Advantages: Better recognition Improved security

2. Single Mode Database

   • Face database
     • Face Recognition: Identify people Compare face images
     • Characteristics: Non-contact Scalable User-friendly
     • Requirements: Algorithms Databases
   • Fingerprint database
     • Fingerprint Recognition:Unique Stable Widely used
     • Advantages: Mature technology Reliable identification
     • Databases: FVC2004, NIST, CASIA-FingerprintV5
   • Iris database
     • Iris Recognition: Stable Accurate Non-invasive
     • Advantages: High security Difficult to forge
     • Databases: UBIRIS CASIA-IrisV4 UPOL BATH
   • Palm-print database
     • Palm-print Recognition: Genetic texture Stable features Human hand surface
     • Characteristics: Reliable identification, Keeps structure after friction
     • Databases: LPIDB PolyU CASIA-MS-PalmprintV1
   • Speech database
     • Speech Recognition: Voice signals, Text conversion, Command recognition
     • Importance: High-quality data Large-scale databases Research support
     • Databases: GRID BANCA AV@CAR CENSREC-1-AV IV2
   • Lip-reading database
     • Lip Recognition: Mouth analysis Speech support Biometric method
     • Technology: Computer vision Human-computer interaction
     • Databases: AVLetters OuluVS NDUTAVSC

3. Biometric Technology

   • Human Characteristics: Stability, Diversity Directness
   • Evaluation: Performance comparison Technology assessment

4. Conclusion

   • Databases: Single-mode Multi-mode
   • Biometric Data Collection: Time-consuming Requires equipment Needs cooperation
   • Important Issues: Privacy Data protection