Biometric image discrimination technologies
"Biometric Image Discrimination Technologies addresses highly relevant issues to many fundamental concerns of both researchers and practitioners of biometric image discrimination (BID) in biometric applications. This book describes the basic concepts necessary for a good understanding of BID and answers some important introductory questions about BID." "Biometric Image Discrimination Technologies covers the theories which are the foundations of basic BID technologies, while developing new algorithms which are verified to be more effective in biometrics authentication. This book will assist students new to the field and will also be useful to senior researchers in this area."--BOOK JACKET.
71 pages matching approach in this book
Results 1-3 of 71
What people are saying - Write a review
We haven't found any reviews in the usual places.
An Introduction to Biometrics Image Discrimination BID
11 other sections not shown
2DPCA algorithm Analysis and Machine approach BDPCA BDPCA+LDA Belhumeur between-class scatter BID technologies biometrics Chapter CKFD classifier CLDA Computer Vision Copying or distributing corresponding covariance matrix dimension dimensional discriminant analysis discriminant features discriminatory information distributing in print DLDA eigenface eigenface method eigenspace eigenvalues eigenvectors electronic forms Equation face images face recognition facial feature extraction feature space feature vector Fisher criterion Fisher discriminant fisherface method forms without written Frangi gait Hespanha high-dimensional Idea Group Inc identification IEEE IEEE Transactions iris iris recognition KPCA Kriegman LDA algorithm linear discriminant Machine Intelligence Mika nonlinear number of training obtain optimal discriminant vectors ORL database palmprint database palmprint images palmprint recognition Pattern Analysis Pattern Recognition PCA plus LDA Pentland performance principal components print or electronic problem Ratsch recognition rates scatter matrix SchOlkopf Smola subspace technique training samples Transactions on Pattern UODV Wang within-class scatter matrix written Figure Zhang