By Craig Fancourt, Luca Bogoni, Keith Hanna, Yanlin Guo, Richard Wildes, Naomi Takahashi (auth.), Takeo Kanade, Anil Jain, Nalini K. Ratha (eds.)

This booklet constitutes the refereed complaints of the fifth foreign convention on Audio- and Video-Based Biometric individual Authentication, AVBPA 2005, held in Hilton Rye city, big apple, united states, in July 2005.

The sixty six revised oral papers and 50 revised poster papers awarded have been conscientiously reviewed and chosen from a variety of submissions. The papers talk about all facets of biometrics together with iris, fingerprint, face, palm print, gait, gesture, speaker, and signature; theoretical and algorithmic matters are handled in addition to structures concerns. the commercial facet of biometrics is obvious from shows on shrewdpermanent playing cards, instant units, and architectural and implementation aspects.

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Extra resources for Audio- and Video-Based Biometric Person Authentication: 5th International Conference, AVBPA 2005, Hilton Rye Town, NY, USA, July 20-22, 2005. Proceedings

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Clearly this would require expanding the current hardware to a system capable of acquiring images from a moving subject. Second, further refinement of the current algorithms is needed for localizing, registering, and matching irises captured under very different environmental conditions. Acknowledgements This work was sponsored by the Defense Advanced Research Projects Agency under Department of Interior contract #DABT63-00-C-1042. Opinions, interpretations, conclusions, and recommendations are those of the authors and are not necessarily endorsed by the United States Government.

D. Bui and G. : Invariant Fourier-Wavelet Descriptor for Pattern Recognition. Vol. 32, no. 7. Pattern Recognition (1999) 1083-1088 6. R. N. : The Fourier Transform and Its Application. The McGraw-Hill Companies (2000) 7. D. Casasent and D. : Position, Rotation, and Scale Invariant Optical Correlation. Vol. 15, no. 7. App. Opt. (1976) 1795-1799 8. S. : A Wavelet Tour of Signal Processing. Academic Press Publishing Company (1998) 9. Institute of Automation, Chinese academy of Science, CASIA Iris Image Database.

Were acquired with a monochrome camera using NIR illumination. It is composed of 749 images from 107 different irises. For each iris, 7 images were captured in 2 sessions. The first session provides reference images (3 images) and the second session provides the test images, an each client. Fig. 7. The steps of our iris recognition system based on specific texture analysis, including iris segmentation, normalisation and enhancement (Step1), the texture extraction using Haar decomposition (Step 2) and the matching process to take the final decision For each client and for each test images, we keep the minimum value of its similarity measure to the three references images of the client.

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