Multimodal Biometric Verification

The focus of this book is on developing user
interfaces that identify and verify legitimate users
in real-time due to their biometric characteristics.
Face and hand geometry are the biometric
identifiers that are used in the applications.
Application programs using these biometric
identifiers are developed in unimodal and multimodal
cases. In this book, six Java applications are
developed to capture users'' hand and face images in
real-time, to enroll, to verify and identify them.
All of the applications are designed as wizard
applications and are built upon the same scenario. In
the face recognition, Gabor jets are used to extract
feature values of the face images. Matching
the person is done according to the Gabor based
feature vectors. In the hand recognition task, hand
shape-based approach is applied on the hands. Hand
segmentation, normalization and feature extraction
are the important steps of this approach. Performance
evaluation of the system is done by both empirical
and observational methods.

Autorentext

Elif SURER is a Ph.D student at University of Bologna, Italy. She received her BSc and MSc from Bogazici University, Turkey. Lale AKARUN has been a full professor at Computer Engineering department of Bogazici University, Turkey since 2002. Besides guiding many dissertations, she has published professional articles in refereed journals.

Klappentext

The focus of this book is on developing user interfaces that identify and verify legitimate users in real-time due to their biometric characteristics. Face and hand geometry are the biometric identifiers that are used in the applications. Application programs using these biometricidentifiers are developed in unimodal and multimodalcases. In this book, six Java applications aredeveloped to capture users' hand and face images inreal-time, to enroll, to verify and identify them.All of the applications are designed as wizardapplications and are built upon the same scenario. Inthe face recognition, Gabor jets are used to extractfeature values of the face images. Matching the person is done according to the Gabor based feature vectors. In the hand recognition task, hand shape-based approach is applied on the hands. Hand segmentation, normalization and feature extraction are the important steps of this approach. Performanceevaluation of the system is done by both empiricaland observational methods.