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03616nam a22004575i 4500 |
| 003 - CONTROL NUMBER IDENTIFIER |
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| control field |
OSt |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
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| control field |
20140310143351.0 |
| 007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION |
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cr nn 008mamaa |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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120417s2012 gw | s |||| 0|eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
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| International Standard Book Number |
9783642284571 |
|
978-3-642-28457-1 |
| 082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER |
|---|
| Classification number |
006.3 |
| Edition number |
23 |
| 264 #1 - |
|---|
| -- |
Berlin, Heidelberg : |
| -- |
Springer Berlin Heidelberg, |
| -- |
2012. |
| 912 ## - |
|---|
| -- |
ZDB-2-ENG |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Liu, Chengjun. |
| Relator term |
author. |
| 245 10 - IMMEDIATE SOURCE OF ACQUISITION NOTE |
|---|
| Title |
Cross Disciplinary Biometric Systems |
| Medium |
[electronic resource] / |
| Statement of responsibility, etc |
by Chengjun Liu, Vijay Kumar Mago. |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
XVI, 228p. 112 illus., 58 illus. in color. |
| Other physical details |
online resource. |
| 440 1# - SERIES STATEMENT/ADDED ENTRY--TITLE |
|---|
| Title |
Intelligent Systems Reference Library, |
| International Standard Serial Number |
1868-4394 ; |
| Volume number/sequential designation |
37 |
| 505 0# - FORMATTED CONTENTS NOTE |
|---|
| Formatted contents note |
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. |
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc |
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 the cross disciplinary technologies, face recognition systems, fingerprint recognition systems, iris recognition systems, as well as image search systems all benefit in terms of recognition performance. Take face recognition for an example, which is not only the most natural way human beings recognize the identity of each other, but also the least privacy-intrusive means because people show their face publicly every day. Face recognition systems display superb performance when they capitalize on the innovative ideas across color science, mathematics, and computer science (e.g., pattern recognition, machine learning, and image processing). The novel ideas lead to the development of new color models and effective color features in color science; innovative features from wavelets and statistics, and new kernel methods and novel kernel models in mathematics; new discriminant analysis frameworks, novel similarity measures, and new image analysis methods, such as fusing multiple image features from frequency domain, spatial domain, and color domain in computer science; as well as system design, new strategies for system integration, and different fusion strategies, such as the feature level fusion, decision level fusion, and new fusion strategies with novel similarity measures. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Engineering. |
|
|---|
| Topical term or geographic name as entry element |
Artificial intelligence. |
|
|---|
| Topical term or geographic name as entry element |
Optical pattern recognition. |
|
|---|
| Topical term or geographic name as entry element |
Biometrics. |
|
|---|
| Topical term or geographic name as entry element |
Engineering. |
|
|---|
| Topical term or geographic name as entry element |
Computational Intelligence. |
|
|---|
| Topical term or geographic name as entry element |
Biometrics. |
|
|---|
| Topical term or geographic name as entry element |
Pattern Recognition. |
|
|---|
| Topical term or geographic name as entry element |
Artificial Intelligence (incl. Robotics). |
| 700 1# - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Mago, Vijay Kumar. |
| Relator term |
author. |
| 710 2# - ADDED ENTRY--CORPORATE NAME |
|---|
| Corporate name or jurisdiction name as entry element |
SpringerLink (Online service) |
| 773 0# - HOST ITEM ENTRY |
|---|
| Title |
Springer eBooks |
| 776 08 - ADDITIONAL PHYSICAL FORM ENTRY |
|---|
| Display text |
Printed edition: |
| International Standard Book Number |
9783642284564 |
| 856 40 - ELECTRONIC LOCATION AND ACCESS |
|---|
| Uniform Resource Identifier |
http://dx.doi.org/10.1007/978-3-642-28457-1 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Source of classification or shelving scheme |
|
| Item type |
E-Book |
