Multimodal Fusion of Iris and Fingerprint
Using Hybrid Wavelets Type I & Type II based Feature Vector
(Sprache: Englisch)
Biometrics systems perform authentication based on human body features, systems based on only one kind of biometric trait are generally called as unimodal biometric systems. The performance and scalability of a biometric system can be increased by combining...
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Biometrics systems perform authentication based on human body features, systems based on only one kind of biometric trait are generally called as unimodal biometric systems. The performance and scalability of a biometric system can be increased by combining more than one biometric trait. Such systems are called as multimodal biometric systems. Being less intrusive and universal fingerprint based systems serve as good option for access control and surveillance. Iris recognition enjoys universality, high degree of uniqueness and moderate user co-operation. This makes Fingerprint & Iris recognition systems unavoidable in emerging security & authentication mechanisms. This book is focusing on a multimodal implementation of Fingerprint & Iris. Fingerprint and Iris features are extracted using multilevel decomposition of captured image data using a new family of wavelet called Hybrid Wavelet type-I and type-II. Feature vector of iris and fingerprint are combined using decision fusion technique and their performance is studied here.
Bibliographische Angaben
- Autoren: Bhavesh Pandya , Vinayak Bharadi , Hemchandra Kekre
- 2014, 104 Seiten, Maße: 22 cm, Kartoniert (TB), Englisch
- Verlag: LAP Lambert Academic Publishing
- ISBN-10: 3848432439
- ISBN-13: 9783848432431
Sprache:
Englisch
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