Iris and periocular biometric recognition
The book reviews developments in the following fields: periocular biometrics; robust iris image segmentation; iris image quality metrics; iris biometric indexing; biometric recognition; best periocular region identification; presentation attack resistant robust biometric ocular system; soft biometri...
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| Other Authors: | , |
|---|---|
| Format: | eBook |
| Language: | English |
| Published: |
London, UK :
The Institution of Engineering and Technology,
2017.
|
| Series: | IET security series ;
5. IET book series on advances in biometrics. |
| Subjects: | |
| ISBN: | 1785611690 9781785611698 9781523112319 152311231X 1785611682 9781785611681 |
| Physical Description: | 1 online resource : illustrations |
Cover
Table of contents
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| 001 | kn-on1004552347 | ||
| 003 | OCoLC | ||
| 005 | 20240717213016.0 | ||
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| 008 | 170922s2017 enka ob 001 0 eng d | ||
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| 020 | |a 1785611690 |q (electronic bk.) | ||
| 020 | |a 9781785611698 |q (electronic bk.) | ||
| 020 | |a 9781523112319 |q (electronic bk.) | ||
| 020 | |a 152311231X |q (electronic bk.) | ||
| 020 | |z 1785611682 | ||
| 020 | |z 9781785611681 | ||
| 035 | |a (OCoLC)1004552347 |z (OCoLC)1005965653 |z (OCoLC)1036294010 |z (OCoLC)1057434299 |z (OCoLC)1097098184 |z (OCoLC)1151924711 |z (OCoLC)1162916558 |z (OCoLC)1182856345 |z (OCoLC)1193149516 | ||
| 245 | 0 | 0 | |a Iris and periocular biometric recognition / |c edited by Christian Rathgeb and Christoph Busch. |
| 264 | 1 | |a London, UK : |b The Institution of Engineering and Technology, |c 2017. | |
| 300 | |a 1 online resource : |b illustrations | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 490 | 1 | |a IET Security Series ; |v 05 | |
| 490 | 1 | |a IET Book Series on Advances in Biometrics | |
| 504 | |a Includes bibliographical references at the end of each chapters and index. | ||
| 506 | |a Plný text je dostupný pouze z IP adres počítačů Univerzity Tomáše Bati ve Zlíně nebo vzdáleným přístupem pro zaměstnance a studenty | ||
| 520 | |a The book reviews developments in the following fields: periocular biometrics; robust iris image segmentation; iris image quality metrics; iris biometric indexing; biometric recognition; best periocular region identification; presentation attack resistant robust biometric ocular system; soft biometric classification; gender classification; near infrared iris images; age predictive biometrics; contact lens detection; software attacks; privacy protection; forensics; iris biometric template protection; privacy-preserving distance computation; IrisCodes; iris sensor identification; iris image matching; embedded systems; and mobile iris recognition. | ||
| 505 | 0 | 0 | |g Machine generated contents note: |g 1. |t Fundamentals in iris recognition -- |g 1.1. |t Introduction / |r Christoph Busch / |r Christian Rathgeb -- |g 1.2. |t Iris recognition processing chain / |r Christoph Busch / |r Christian Rathgeb -- |g 1.2.1. |t Image acquisition / |r Christoph Busch / |r Christian Rathgeb -- |g 1.2.2. |t Pre-processing / |r Christoph Busch / |r Christian Rathgeb -- |g 1.2.3. |t Feature extraction / |r Christoph Busch / |r Christian Rathgeb -- |g 1.2.4. |t Comparison / |r Christoph Busch / |r Christian Rathgeb -- |g 1.3. |t Status quo in research and industry / |r Christoph Busch / |r Christian Rathgeb -- |g 1.3.1. |t Databases, competitions and software / |r Christoph Busch / |r Christian Rathgeb -- |g 1.3.2. |t Standardization and deployments / |r Christoph Busch / |r Christian Rathgeb -- |g 1.4. |t Challenges in iris recognition / |r Christoph Busch / |r Christian Rathgeb -- |g 1.4.1. |t Visible wavelength and unconstrained conditions / |r Christoph Busch / |r Christian Rathgeb -- |g 1.4.2. |t Security and privacy protection / |r Christoph Busch / |r Christian Rathgeb -- |g 1.4.3. |t Cross-sensor and cross-spectral recognition / |r Christoph Busch / |r Christian Rathgeb -- |g 1.4.4. |t Soft biometrics and template ageing / |r Christoph Busch / |r Christian Rathgeb -- |g 1.4.5. |t Large-scale identification and iris biometric fusion / |r Christoph Busch / |r Christian Rathgeb -- |g 1.5. |t Summary / |r Christoph Busch / |r Christian Rathgeb -- |t References / |r Christoph Busch / |r Christian Rathgeb -- |g 2. |t overview of periocular biometrics / |r Christoph Busch / |r Christian Rathgeb -- |g 2.1. |t Acquisition of periocular images / |r Josef Bigun / |r Fernando Alonso-Fernandez -- |g 2.2. |t Detection of the periocular region / |r Josef Bigun / |r Fernando Alonso-Fernandez -- |g 2.3. |t Feature encoding and comparison / |r Josef Bigun / |r Fernando Alonso-Fernandez -- |g 2.4. |t Human performance evaluation / |r Josef Bigun / |r Fernando Alonso-Fernandez -- |g 2.5. |t Comparison of periocular with other modalities / |r Josef Bigun / |r Fernando Alonso-Fernandez -- |g 2.6. |t Other tasks using features from the periocular region / |r Josef Bigun / |r Fernando Alonso-Fernandez -- |g 2.7. |t Summary and future trends in periocular research / |r Josef Bigun / |r Fernando Alonso-Fernandez -- |t Acknowledgments / |r Josef Bigun / |r Fernando Alonso-Fernandez -- |t References / |r Josef Bigun / |r Fernando Alonso-Fernandez -- |g 3. |t Robust iris image segmentation / |r Josef Bigun / |r Fernando Alonso-Fernandez -- |g 3.1. |t Introduction / |r Peter Wild / |r Andreas Uhl / |r James Ferryman / |r Heinz Hofbauer -- |g 3.1.1. |t Segmentation accuracy / |r Peter Wild / |r Heinz Hofbauer / |r James Ferryman / |r Andreas Uhl -- |g 3.1.2. |t Iris segmentation quality / |r Peter Wild / |r Andreas Uhl / |r James Ferryman / |r Heinz Hofbauer -- |g 3.2. |t Advances in iris segmentation / |r Peter Wild / |r Andreas Uhl / |r James Ferryman / |r Heinz Hofbauer -- |g 3.2.1. |t From circular models to active contours / |r Peter Wild / |r Andreas Uhl / |r James Ferryman / |r Heinz Hofbauer -- |g 3.2.2. |t Near infrared vs. visible range segmentation / |r Peter Wild / |r Andreas Uhl / |r James Ferryman / |r Heinz Hofbauer -- |g 3.2.3. |t Learning-based techniques / |r Peter Wild / |r Andreas Uhl / |r James Ferryman / |r Heinz Hofbauer -- |g 3.2.4. |t Segmentation fusion / |r Peter Wild / |r Andreas Uhl / |r James Ferryman / |r Heinz Hofbauer -- |g 3.3. |t Experiments / |r Peter Wild / |r Andreas Uhl / |r James Ferryman / |r Heinz Hofbauer -- |g 3.3.1. |t Individual NIR vs. VIS performance / |r Peter Wild / |r Andreas Uhl / |r James Ferryman / |r Heinz Hofbauer -- |g 3.3.2. |t Impact of tuning / |r Peter Wild / |r Andreas Uhl / |r James Ferryman / |r Heinz Hofbauer -- |g 3.3.3. |t Combinations of segmentation performance / |r Peter Wild / |r Andreas Uhl / |r James Ferryman / |r Heinz Hofbauer -- |g 3.4. |t Conclusion and future work / |r Peter Wild / |r Andreas Uhl / |r James Ferryman / |r Heinz Hofbauer -- |t References / |r Peter Wild / |r Andreas Uhl / |r James Ferryman / |r Heinz Hofbauer -- |g 4. |t Iris image quality metrics with veto power and nonlinear importance tailoring / |r Peter Wild / |r Andreas Uhl / |r James Ferryman / |r Heinz Hofbauer -- |g 4.1. |t Introduction / |r Cathryn Downing / |r John Daugman -- |g 4.1.1. |t Related work / |r Cathryn Downing / |r John Daugman -- |g 4.2. |t Normalisation of individual quality measures / |r Cathryn Downing / |r John Daugman -- |g 4.3. |t Effectiveness of multiplying quality factors / |r Cathryn Downing / |r John Daugman -- |g 4.4. |t Importance tailoring / |r Cathryn Downing / |r John Daugman -- |g 4.5. |t Error reject curves / |r Cathryn Downing / |r John Daugman -- |g 4.6. |t Discipline in punishment / |r Cathryn Downing / |r John Daugman -- |g 4.7. |t Predictive value of the quality pseudonorm / |r Cathryn Downing / |r John Daugman -- |g 4.8. |t Testing and adoption into an ISO/IEC quality standard / |r Cathryn Downing / |r John Daugman -- |g 4.9. |t possible criticism of the method / |r Cathryn Downing / |r John Daugman -- |t Acknowledgement / |r Cathryn Downing / |r John Daugman -- |t References / |r Cathryn Downing / |r John Daugman -- |g 5. |t Iris biometric indexing / |r Cathryn Downing / |r John Daugman -- |g 5.1. |t Introduction / |r Jodo C. Neves / |r Hugo Proenca -- |g 5.2. |t State of the art / |r Jodo C. Neves / |r Hugo Proenca -- |g 5.3. |t Indexing/retrieving poorly separated data / |r Jodo C. Neves / |r Hugo Proenca -- |g 5.3.1. |t Indexing / |r Jodo C. Neves / |r Hugo Proenca -- |g 5.3.2. |t Retrieval / |r Jodo C. Neves / |r Hugo Proenca -- |g 5.3.3. |t Time complexity / |r Jodo C. Neves / |r Hugo Proenca -- |g 5.4. |t Performance comparison / |r Jodo C. Neves / |r Hugo Proenca -- |g 5.4.1. |t Synthetic IrisCodes / |r Jodo C. Neves / |r Hugo Proenca -- |g 5.4.2. |t Well separated near infra-red data / |r Jodo C. Neves / |r Hugo Proenca -- |g 5.4.3. |t Poorly separated visible wavelength data / |r Jodo C. Neves / |r Hugo Proenca -- |g 5.5. |t Conclusions / |r Jodo C. Neves / |r Hugo Proenca -- |t Acknowledgment / |r Jodo C. Neves / |r Hugo Proenca -- |t References / |r Jodo C. Neves / |r Hugo Proenca -- |g 6. |t Identifying the best periocular region for biometric recognition / |r Jodo C. Neves / |r Hugo Proenca -- |g 6.1. |t Introduction / |r B. VK. Vijaya Kumar / |r Jonathon M. Smereka -- |g 6.2. |t Experimental setup / |r B. VK. Vijaya Kumar / |r Jonathon M. Smereka -- |g 6.3. |t Results / |r B. VK. Vijaya Kumar / |r Jonathon M. Smereka -- |g 6.4. |t Summary / |r B. VK. Vijaya Kumar / |r Jonathon M. Smereka -- |t References / |r B. VK. Vijaya Kumar / |r Jonathon M. Smereka -- |g 7. |t Light field cameras for presentation attack resistant robust biometric ocular system / |r B. VK. Vijaya Kumar / |r Jonathon M. Smereka -- |g 7.1. |t Introduction / |r Raghavendra Ramachandra / |r Christoph Busch / |r Kiran B. Raja -- |g 7.2. |t Light-field imaging / |r Raghavendra Ramachandra / |r Christoph Busch / |r Kiran B. Raja -- |g 7.3. |t Scheme for iris and periocular verification / |r Raghavendra Ramachandra / |r Christoph Busch / |r Kiran B. Raja -- |g 7.3.1. |t Iris verification / |r Raghavendra Ramachandra / |r Christoph Busch / |r Kiran B. Raja -- |g 7.3.2. |t Periocular verification / |r Raghavendra Ramachandra / |r Christoph Busch / |r Kiran B. Raja -- |g 7.3.3. |t Combining iris and periocular characteristics / |r Raghavendra Ramachandra / |r Christoph Busch / |r Kiran B. Raja -- |g 7.3.4. |t Database, experiments and results / |r Raghavendra Ramachandra / |r Christoph Busch / |r Kiran B. Raja -- |g 7.4. |t Presentation attack resistant ocular biometrics in visible spectrum / |r Raghavendra Ramachandra / |r Christoph Busch / |r Kiran B. Raja -- |g 7.4.1. |t PAD algorithm employing the depth images from LFC / |r Raghavendra Ramachandra / |r Christoph Busch / |r Kiran B. Raja -- |g 7.4.2. |t Visible spectrum iris recognition system / |r Raghavendra Ramachandra / |r Christoph Busch / |r Kiran B. Raja -- |g 7.4.3. |t Presentation attack database / |r Raghavendra Ramachandra / |r Christoph Busch / |r Kiran B. Raja -- |g 7.4.4. |t Performance evaluation protocol / |r Raghavendra Ramachandra / |r Christoph Busch / |r Kiran B. Raja -- |g 7.4.5. |t Experiments and results / |r Raghavendra Ramachandra / |r Christoph Busch / |r Kiran B. Raja -- |g 7.5. |t Conclusion / |r Raghavendra Ramachandra / |r Christoph Busch / |r Kiran B. Raja -- |t References / |r Raghavendra Ramachandra / |r Christoph Busch / |r Kiran B. Raja -- |g 8. |t Gender classification from near infrared iris images / |r Raghavendra Ramachandra / |r Christoph Busch / |r Kiran B. |
| 505 | 0 | 0 | |r Raja -- |g 8.1. |t Introduction / |r Juan Tapia -- |g 8.2. |t Anatomy structure of the eye / |r Juan Tapia -- |g 8.3. |t Feature extraction / |r Juan Tapia -- |g 8.4. |t State of the art / |r Juan Tapia -- |g 8.5. |t Databases / |r Juan Tapia -- |g 8.5.1. |t BioSecure multimodal database / |r Juan Tapia -- |g 8.5.2. |t Gender from iris dataset (ND-GFI) / |r Juan Tapia -- |g 8.6. |t Feature selection / |r Juan Tapia -- |g 8.7. |t Research trends and challenges / |r Juan Tapia -- |g 8.7.1. |t Segmentation / |r Juan Tapia -- |g 8.7.2. |t Accuracy / |r Juan Tapia -- |g 8.7.3. |t Fragile bits / |r Juan Tapia -- |g 8.7.4. |t Sensors / |r Juan Tapia -- |g 8.7.5. |t Makeup / |r Juan Tapia -- |g 8.8. |t Concluding remarks / |r Juan Tapia -- |t Acknowledgments / |r Juan Tapia -- |t References / |r Juan Tapia -- |g 9. |t Periocular-based soft biometric classification / |r Juan Tapia -- |g 9.1. |t Introduction / |r Damon L. Woodard / |r Kalaivani Sundararajan / |r Nicole Tobias / |r Jamie Lyle -- |g 9.2. |t Approach / |r Damon L. Woodard / |r Jamie Lyle / |r Nicole Tobias / |r Kalaivani Sundararajan -- |g 9.2.1. |t Data / |r Nicole Tobias / |r Kalaivani Sundararajan / |r Damon L. Woodard / |r Jamie Lyle -- |g 9.2.2. |t Preprocessing / |r Damon L. Woodard / |r Jamie Lyle / |r Nicole Tobias / |r Kalaivani Sundararajan -- |g 9.2.3. |t Feature representations / |r Damon L. Woodard / |r Kalaivani Sundararajan / |r Nicole Tobias / |r Jamie Lyle -- |g 9.2.4. |t Classification / |r Damon L. Woodard / |r Kalaivani Sundararajan / |r Jamie Lyle / |r Nicole Tobias -- |g 9.3. |t Experiment results / |r Damon L. Woodard / |r Nicole Tobias / |r Kalaivani Sundararajan / |r Jamie Lyle -- |g 9.3.1. |t Experiment protocol / |r Damon L. Woodard / |r Kalaivani Sundararajan / |r Jamie Lyle / |r Nicole Tobias -- |g 9.3.2. |t Gender classification / |r Damon L. Woodard / |r Kalaivani Sundararajan / |r Nicole Tobias / |r Jamie Lyle -- |g 9.3.3. |t Ethnicity classification / |r Damon L. Woodard / |r Kalaivani Sundararajan / |r Jamie Lyle / |r Nicole Tobias. |
| 505 | 0 | 0 | |g Note continued: |g 9.3.4. |t Gender and ethnicity classification / |r Nicole Tobias / |r Kalaivani Sundararajan / |r Damon L. Woodard / |r Jamie Lyle -- |g 9.4. |t Summary / |r Nicole Tobias / |r Jamie Lyle / |r Damon L. Woodard / |r Kalaivani Sundararajan -- |t References / |r Damon L. Woodard / |r Kalaivani Sundararajan / |r Nicole Tobias / |r Jamie Lyle -- |g 10. |t Age predictive biometrics: predicting age from iris characteristics / |r Damon L. |
| 505 | 0 | 0 | |r Woodard / |r Kalaivani Sundararajan / |r Nicole Tobias / |r Jamie Lyle -- |g 10.1. |t Introduction / |r Marjory Da Costa-Abreu / |r Meryem Erbilek / |r Michael Fairhurst -- |g 10.2. |t Background discussion and related studies / |r Marjory Da Costa-Abreu / |r Michael Fairhurst / |r Meryem Erbilek -- |g 10.3. |t Predicting age in diverse scenarios / |r Michael Fairhurst / |r Marjory Da Costa-Abreu / |r Meryem Erbilek -- |g 10.4. |t Experimental infrastructure for iris-based predictive biometrics / |r Marjory Da Costa-Abreu / |r Meryem Erbilek / |r Michael Fairhurst -- |g 10.5. |t Experimental analysis of individual classification systems for iris-based predictive biometrics / |r Marjory Da Costa-Abreu / |r Michael Fairhurst / |r Meryem Erbilek -- |g 10.6. |t Experimental analysis of iris-based multiclassifier systems / |r Marjory Da Costa-Abreu / |r Michael Fairhurst / |r Meryem Erbilek -- |g 10.7. |t Experimental analysis of multiagent intelligent systems for iris-based predictive biometrics / |r Marjory Da Costa-Abreu / |r Michael Fairhurst / |r Meryem Erbilek -- |g 10.8. |t Discussion / |r Marjory Da Costa-Abreu / |r Michael Fairhurst / |r Meryem Erbilek -- |g 10.9. |t Experimental analysis of multimodal iris-based predictive systems / |r Michael Fairhurst / |r Marjory Da Costa-Abreu / |r Meryem Erbilek -- |g 10.10. |t Final remarks / |r Marjory Da Costa-Abreu / |r Michael Fairhurst / |r Meryem Erbilek -- |t References / |r Marjory Da Costa-Abreu / |r Meryem Erbilek / |r Michael Fairhurst -- |g 11. |t Presentation attack detection in iris recognition / |r Marjory Da Costa-Abreu / |r Meryem Erbilek / |r Michael Fairhurst -- |g 11.1. |t Introduction / |r Marta Gomez-Barrero / |r Javier Galbally -- |g 11.2. |t Presentation attacks in iris recognition / |r Marta Gomez-Barrero / |r Javier Galbally -- |g 11.3. |t Presentation attack detection in iris recognition / |r Marta Gomez-Barrero / |r Javier Galbally -- |g 11.3.1. |t Sensor-level approaches / |r Marta Gomez-Barrero / |r Javier Galbally -- |g 11.3.2. |t Feature-level approaches / |r Marta Gomez-Barrero / |r Javier Galbally -- |g 11.4. |t Evaluation of presentation attack detection methods / |r Marta Gomez-Barrero / |r Javier Galbally -- |g 11.5. |t Conclusion / |r Marta Gomez-Barrero / |r Javier Galbally -- |t References / |r Marta Gomez-Barrero / |r Javier Galbally -- |g 12. |t Contact lens detection in iris images / |r Marta Gomez-Barrero / |r Javier Galbally -- |g 12.1. |t Introduction / |r Jukka Komulainen / |r Matti Pietikiiinen / |r Abdenour Hadid -- |g 12.2. |t Literature review on contact lens detection / |r Jukka Komulainen / |r Matti Pietikiiinen / |r Abdenour Hadid -- |g 12.2.1. |t Textured contact lens detection / |r Jukka Komulainen / |r Matti Pietikiiinen / |r Abdenour Hadid -- |g 12.2.2. |t Classification of contact lens type / |r Jukka Komulainen / |r Matti Pietikiiinen / |r Abdenour Hadid -- |g 12.3. |t Case study: generalised software-based textured contact lens detection / |r Jukka Komulainen / |r Matti Pietikiiinen / |r Abdenour Hadid -- |g 12.3.1. |t Pre-processing / |r Jukka Komulainen / |r Matti Pietikiiinen / |r Abdenour Hadid -- |g 12.3.2. |t Texture description / |r Jukka Komulainen / |r Matti Pietikiiinen / |r Abdenour Hadid -- |g 12.3.3. |t Experimental analysis / |r Jukka Komulainen / |r Matti Pietikiiinen / |r Abdenour Hadid -- |g 12.4. |t Discussion / |r Jukka Komulainen / |r Matti Pietikiiinen / |r Abdenour Hadid -- |g 12.4.1. |t Further work on generalised textured contact lens detection / |r Jukka Komulainen / |r Matti Pietikiiinen / |r Abdenour Hadid -- |g 12.4.2. |t role of pre-processing in contact lens detection / |r Jukka Komulainen / |r Matti Pietikiiinen / |r Abdenour Hadid -- |g 12.4.3. |t On the evaluation of contact lens detection algorithms / |r Matti Pietikiiinen / |r Abdenour Hadid / |r Jukka Komulainen -- |g 12.5. |t Conclusions / |r Jukka Komulainen / |r Matti Pietikiiinen / |r Abdenour Hadid -- |t Acknowledgement / |r Jukka Komulainen / |r Matti Pietikiiinen / |r Abdenour Hadid -- |t References / |r Jukka Komulainen / |r Matti Pietikiiinen / |r Abdenour Hadid -- |g 13. |t Software attacks on iris recognition systems / |r Jukka Komulainen / |r Matti Pietikiiinen / |r Abdenour Hadid -- |g 13.1. |t Introduction / |r Marta Gomez-Barrero / |r Javier Galbally -- |g 13.2. |t Hill-climbing based attacks / |r Javier Galbally / |r Marta Gomez-Barrero -- |g 13.3. |t Synthetic iris generation / |r Javier Galbally / |r Marta Gomez-Barrero -- |g 13.3.1. |t False acceptance attacks based on fully synthetic iris / |r Javier Galbally / |r Marta Gomez-Barrero -- |g 13.3.2. |t Inverse biometrics attacks / |r Javier Galbally / |r Marta Gomez-Barrero -- |g 13.4. |t Software attacks on biometric template protection schemes / |r Javier Galbally / |r Marta Gomez-Barrero -- |g 13.4.1. |t Stolen key-inversion attacks / |r Javier Galbally / |r Marta Gomez-Barrero -- |g 13.4.2. |t Attacks via record multiplicity / |r Javier Galbally / |r Marta Gomez-Barrero -- |g 13.5. |t Countermeasures to software attacks / |r Javier Galbally / |r Marta Gomez-Barrero -- |g 13.6. |t Conclusions / |r Javier Galbally / |r Marta Gomez-Barrero -- |t References / |r Javier Galbally / |r Marta Gomez-Barrero -- |g 14. |t Iris biometric template protection / |r Javier Galbally / |r Marta Gomez-Barrero -- |g 14.1. |t Introduction / |r Christian Rathgeb / |r Christoph Busch / |r Johannes Wagner -- |g 14.2. |t Iris template protection schemes / |r Christian Rathgeb / |r Christoph Busch / |r Johannes Wagner -- |g 14.2.1. |t Iris-biometric cryptosystems / |r Christian Rathgeb / |r Christoph Busch / |r Johannes Wagner -- |g 14.2.2. |t Cancelable iris biometrics / |r Christian Rathgeb / |r Christoph Busch / |r Johannes Wagner -- |g 14.3. |t Implementation of iris template protection schemes / |r Christian Rathgeb / |r Christoph Busch / |r Johannes Wagner -- |g 14.3.1. |t Iris fuzzy vault / |r Christian Rathgeb / |r Christoph Busch / |r Johannes Wagner -- |g 14.3.2. |t Bin-combo for iris-codes / |r Christian Rathgeb / |r Christoph Busch / |r Johannes Wagner -- |g 14.4. |t Experimental evaluations / |r Christian Rathgeb / |r Christoph Busch / |r Johannes Wagner -- |g 14.4.1. |t Performance evaluation / |r Christian Rathgeb / |r Christoph Busch / |r Johannes Wagner -- |g 14.4.2. |t Discussion / |r Christian Rathgeb / |r Christoph Busch / |r Johannes Wagner -- |g 14.5. |t Summary and research directions / |r Christian Rathgeb / |r Christoph Busch / |r Johannes Wagner -- |t References / |r Christian Rathgeb / |r Christoph Busch / |r Johannes Wagner -- |g 15. |t Privacy-preserving distance computation for IrisCodes / |r Christian Rathgeb / |r Christoph Busch / |r Johannes Wagner -- |g 15.1. |t Introduction / |r Julien Bringer / |r Constance Morel / |r Herve Chabanne -- |g 15.2. |t Secure distance computation in the semi-honest model / |r Julien Bringer / |r Constance Morel / |r Herve Chabanne -- |g 15.2.1. |t Oblivious transfer / |r Julien Bringer / |r Constance Morel / |r Herve Chabanne -- |g 15.2.2. |t Yao's garbled circuits / |r Julien Bringer / |r Constance Morel / |r Herve Chabanne -- |g 15.2.3. |t GSHADE in the semi-honest model / |r Julien Bringer / |r Herve Chabanne / |r Constance Morel -- |g 15.2.4. |t Privacy-preserving distance computation for IrisCodes in the semi-honest model / |r Julien Bringer / |r Constance Morel / |r Herve Chabanne -- |g 15.3. |t Secure distance computation in the malicious model / |r Julien Bringer / |r Constance Morel / |r Herve Chabanne -- |g 15.3.1. |t Yao's garbled circuits in the malicious setting / |r Julien Bringer / |r Constance Morel / |r Herve Chabanne -- |g 15.3.2. |t GSHADE in the malicious setting / |r Julien Bringer / |r Constance Morel / |r Herve Chabanne -- |g 15.3.3. |t Privacy-preserving distance computation for IrisCodes in the malicious model / |r Julien Bringer / |r Constance Morel / |r Herve Chabanne -- |g 15.4. |t Application to other iris representations / |r Julien Bringer / |r Constance Morel / |r Herve Chabanne -- |g 15.5. |t Conclusion / |r Julien Bringer / |r Constance Morel / |r Herve Chabanne -- |t Acknowledgments / |r Julien Bringer / |r Constance Morel / |r Herve Chabanne -- |t References / |r Julien Bringer / |r Constance Morel / |r Herve Chabanne -- |g 16. |t Identifying iris sensors from iris images / |r Julien Bringer / |r Constance Morel / |r Herve Chabanne -- |g 16.1. |t Techniques for sensor identification/dataset classification / |r Luca Debiasi / |r Andreas Uhl / |r Christof Kauba -- |g 16.1.1. |t PRNU-based sensor identification (PSI) / |r Luca Debiasi / |r Andreas Uhl / |r Christof Kauba -- |g 16.1.2. |t Iris texture classification (ITC) / |r Luca. |
| 505 | 0 | 0 | |r Debiasi / |r Andreas Uhl / |r Christof Kauba -- |g 16.2. |t Datasets / |r Luca Debiasi / |r Andreas Uhl / |r Christof Kauba -- |g 16.3. |t Experimental setup / |r Luca Debiasi / |r Andreas Uhl / |r Christof Kauba -- |g 16.4. |t Experimental results / |r Luca Debiasi / |r Andreas Uhl / |r Christof Kauba -- |g 16.5. |t Practical discussion / |r Luca Debiasi / |r Andreas Uhl / |r Christof Kauba -- |g 16.6. |t Conclusion / |r Luca Debiasi / |r Andreas Uhl / |r Christof Kauba -- |t References / |r Luca Debiasi / |r Andreas Uhl / |r Christof Kauba -- |g 17. |t Matching iris images against face images using a joint dictionary-based sparse representation scheme / |r Christof Kauba / |r Luca Debiasi / |r Andreas Uhl -- |g 17.1. |t Introduction / |r Arun Ross / |r Raghavender Jillela -- |g 17.2. |t Database / |r Arun Ross / |r Raghavender Jillela -- |g 17.2.1. |t Challenges / |r Arun Ross / |r Raghavender Jillela -- |g 17.3. |t Outline of experiments / |r Arun Ross / |r Raghavender Jillela -- |g 17.4. |t Iris recognition / |r Arun Ross / |r Raghavender Jillela -- |g 17.4.1. |t Open source algorithm / |r Arun Ross / |r Raghavender Jillela -- |g 17.4.2. |t Commercial algorithm / |r Arun Ross / |r Raghavender Jillela -- |g 17.5. |t Ocular recognition / |r Arun Ross / |r Raghavender Jillela -- |g 17.5.1. |t Baseline-local binary patterns / |r Raghavender Jillela / |r Arun Ross -- |g 17.5.2. |t Normalized gradient correlation / |r Arun Ross / |r Raghavender Jillela -- |g 17.6. |t Ocular matching using joint dictionary approach / |r Arun Ross / |r Raghavender Jillela. |
| 505 | 0 | 0 | |g Note continued: |g 17.6.1. |t Sparse representation framework / |r Arun Ross / |r Raghavender Jillela -- |g 17.6.2. |t Joint dictionary approach / |r Arun Ross / |r Raghavender Jillela -- |g 17.6.3. |t Dictionary learning and matching / |r Arun Ross / |r Raghavender Jillela -- |g 17.7. |t Computational details / |r Arun Ross / |r Raghavender Jillela -- |g 17.8. |t Score-level fusion / |r Arun Ross / |r Raghavender Jillela -- |g 17.9. |t Summary / |r Arun Ross / |r Raghavender Jillela -- |t References / |r Arun Ross / |r Raghavender Jillela -- |g 18. |t Iris biometrics for embedded systems / |r Arun Ross / |r Raghavender Jillela -- |g 18.1. |t Introduction to embedded systems / |r Raul Sanchez-Reillo / |r Judith Liu-Jimene -- |g 18.2. |t Design strategies for developing embedded systems / |r Raul Sanchez-Reillo / |r Judith Liu-Jimene -- |g 18.2.1. |t General architecture of an embedded system / |r Raul Sanchez-Reillo / |r Judith Liu-Jimene -- |g 18.2.2. |t Architecture alternatives / |r Raul Sanchez-Reillo / |r Judith Liu-Jimene -- |g 18.3. |t Biometric requirements for embedded systems / |r Raul Sanchez-Reillo / |r Judith Liu-Jimene -- |g 18.3.1. |t Functional requirements / |r Raul Sanchez-Reillo / |r Judith Liu-Jimene -- |g 18.3.2. |t Security requirements / |r Raul Sanchez-Reillo / |r Judith Liu-Jimene -- |g 18.4. |t Iris biometrics analysis for embedded systems / |r Raul Sanchez-Reillo / |r Judith Liu-Jimene -- |g 18.4.1. |t Data capture / |r Raul Sanchez-Reillo / |r Judith Liu-Jimene -- |g 18.4.2. |t Preprocessing / |r Raul Sanchez-Reillo / |r Judith Liu-Jimene -- |g 18.4.3. |t Feature extraction / |r Raul Sanchez-Reillo / |r Judith Liu-Jimene -- |g 18.4.4. |t Comparison / |r Raul Sanchez-Reillo / |r Judith Liu-Jimene -- |g 18.5. |t Existing implementations / |r Raul Sanchez-Reillo / |r Judith Liu-Jimene -- |g 18.5.1. |t Custom hardware-FPGA / |r Raul Sanchez-Reillo / |r Judith Liu-Jimene -- |g 18.5.2. |t Software implementations / |r Raul Sanchez-Reillo / |r Judith Liu-Jimene -- |g 18.6. |t Conclusions / |r Raul Sanchez-Reillo / |r Judith Liu-Jimene -- |t References / |r Raul Sanchez-Reillo / |r Judith Liu-Jimene -- |g 19. |t Mobile iris recognition / |r Raul Sanchez-Reillo / |r Judith Liu-Jimene -- |g 19.1. |t Background / |r Takashi Shinzaki / |r Akira Yonenaga -- |g 19.2. |t Mobile iris authentication / |r Takashi Shinzaki / |r Akira Yonenaga -- |g 19.3. |t Technologies for the future / |r Takashi Shinzaki / |r Akira Yonenaga -- |g 19.4. |t Summary / |r Takashi Shinzaki / |r Akira Yonenaga -- |t References / |r Takashi Shinzaki / |r Akira Yonenaga -- |g 20. |t Future trends in iris recognition: an industry perspective / |r Takashi Shinzaki / |r Akira Yonenaga -- |g 20.1. |t Customer requirements / |r Daniel Hartung / |r Gunther Mull / |r Sven Utcke / |r Ji-Young Lim -- |g 20.1.1. |t Robustness / |r Daniel Hartung / |r Gunther Mull / |r Sven Utcke / |r Ji-Young Lim -- |g 20.1.2. |t Performance / |r Daniel Hartung / |r Gunther Mull / |r Sven Utcke / |r Ji-Young Lim -- |g 20.1.3. |t Usability / |r Daniel Hartung / |r Gunther Mull / |r Sven Utcke / |r Ji-Young Lim -- |g 20.1.4. |t Choosing a modality / |r Daniel Hartung / |r Gunther Mull / |r Sven Utcke / |r Ji-Young Lim -- |g 20.2. |t Development process / |r Daniel Hartung / |r Gunther Mull / |r Sven Utcke / |r Ji-Young Lim -- |g 20.2.1. |t Bias and variability / |r Daniel Hartung / |r Gunther Mull / |r Sven Utcke / |r Ji-Young Lim -- |g 20.2.2. |t Parameter optimisation / |r Daniel Hartung / |r Gunther Mull / |r Sven Utcke / |r Ji-Young Lim -- |g 20.2.3. |t Evaluation and tools / |r Daniel Hartung / |r Gunther Mull / |r Sven Utcke / |r Ji-Young Lim -- |g 20.3. |t Future trends and challenges / |r Daniel Hartung / |r Gunther Mull / |r Sven Utcke / |r Ji-Young Lim -- |g 20.3.1. |t Sensor-related trends / |r Daniel Hartung / |r Gunther Mull / |r Sven Utcke / |r Ji-Young Lim -- |g 20.3.2. |t Presentation attack detection / |r Daniel Hartung / |r Gunther Mull / |r Sven Utcke / |r Ji-Young Lim -- |g 20.3.3. |t Deep learning / |r Daniel Hartung / |r Gunther Mull / |r Sven Utcke / |r Ji-Young Lim -- |g 20.3.4. |t Standards / |r Daniel Hartung / |r Gunther Mull / |r Sven Utcke / |r Ji-Young Lim -- |g 20.4. |t Summary / |r Daniel Hartung / |r Gunther Mull / |r Sven Utcke / |r Ji-Young Lim -- |t Acknowledgement / |r Daniel Hartung / |r Gunther Mull / |r Sven Utcke / |r Ji-Young Lim -- |t References / |r Daniel Hartung / |r Gunther Mull / |r Sven Utcke / |r Ji-Young Lim. |
| 590 | |a Knovel |b Knovel (All titles) | ||
| 650 | 0 | |a Biometric identification. | |
| 655 | 7 | |a elektronické knihy |7 fd186907 |2 czenas | |
| 655 | 9 | |a electronic books |2 eczenas | |
| 700 | 1 | |a Rathgeb, Christian, |e editor. | |
| 700 | 1 | |a Busch, Christoph, |e editor. | |
| 776 | 0 | 8 | |i Print version: |t Iris and periocular biometric recognition. |d Stevenage, UNKNOWN : The Institution of Engineering and Technology, 2017 |z 9781785611681 |z 1785611682 |
| 830 | 0 | |a IET security series ; |v 5. | |
| 830 | 0 | |a IET book series on advances in biometrics. | |
| 856 | 4 | 0 | |u https://proxy.k.utb.cz/login?url=https://app.knovel.com/hotlink/toc/id:kpIPBR0004/iris-and-periocular?kpromoter=marc |y Full text |
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