Cross Disciplinary Biometric Systems

Cross disciplinary biometric systems help boost the performance of the conventional systems. Not only is the recognition accuracy significantly improved, but also the robustness of the systems is greatly enhanced in the challenging environments, such as varying illumination conditions. By leveraging...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Liu, Chengjun (Autor), Mago, Vijay Kumar (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2012.
Edición:1st ed. 2012.
Colección:Intelligent Systems Reference Library, 37
Temas:
Computational intelligence.
Biometric identification.
Pattern recognition systems.
Artificial intelligence.
Computational Intelligence.
Biometrics.
Automated Pattern Recognition.
Artificial Intelligence.
Acceso en línea:Texto Completo
Tabla de Contenidos:
  • Feature Local Binary Patterns
  • New Color Features for Pattern Recognition
  • Gabor-DCT Features with Application to Face Recognition
  • Frequency and Color Fusion for Face Verification
  • Mixture of Classifiers for Face Recognition Across Pose
  • Wavelet Features for 3D Face Recognition
  • Minutiae-based Fingerprint Matching
  • Iris segmentation: state of the art and innovative methods
  • Various Discriminatory Features for Eye Detection
  • LBP and Color Descriptors for Image Classification.

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