Iris and Periocular Biometric Recognition

✍ Scribed by Christian Rathgeb, Christoph Busch

Publisher: The Institution of Engineering and Technology
Year: 2017
Tongue: English
Leaves: 497
Series: Iet Security
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

This book covers iris and periocular recognition, a prominent field in Biometrics Recognition and Identity Science in the areas of security, computing, and communications research and technologies. Selected topics cover a wide spectrum of current research, focusing on periocular recognition to augment the biometric performance of the iris in unconstrained environments, paving the way for multi-spectral biometric recognition on mobile devices. Divided into three parts, this text covers the most recent research and future directions as well as security related topics

✦ Table of Contents

Content: Part I: Introduction to iris and periocular recognitionChapter 1: Fundamentals of iris biometric recognitionChapter 2: An overview of periocular biometrics Part II: Issues and challengesChapter 3: Robust iris image segmentationChapter 4: Iris image quality metrics with veto power and nonlinear importance tailoringChapter 5: Iris biometric indexingChapter 6: Identifying the best periocular region for biometric recognitionChapter 7: Light field cameras for presentation attack resistant robust biometric ocular system Part III: Soft biometric classificationChapter 8: Gender classification from near infrared iris imagesChapter 9: Periocular-based soft biometric classificationChapter 10: Age predictive biometrics: predicting age from iris characteristics Part IV: Security aspectsChapter 11: Presentation attack detection in iris recognitionChapter 12: Contact lens detection in iris imagesChapter 13: Software attacks on iris recognition systems Part V: Privacy protection and forensicsChapter 14: Iris biometric template protectionChapter 15: Privacy-preserving distance computation for IrisCodesChapter 16: Identifying iris sensors from iris imagesChapter 17: Matching iris images against face images using a joint dictionary-based sparse representation scheme Part VI: Future trendsChapter 18: Iris biometrics for embedded systemsChapter 19: Mobile iris recognitionChapter 20: Future trends in iris recognition: an industry perspective

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