Iris and Periocular Recognition using Deep Learning systematically explains the fundamental and most advanced techniques for ocular imprint-based human identification, with many applications in sectors such as healthcare, online education, e-business, metaverse, and entertainment. This is the first-ever book devoted to iris recognition that details cutting-edge techniques using deep neural networks. This book systematically introduces such algorithmic details with attractive illustrations, examples, experimental comparisons, and security analysis. It answers many fundamental questions about the most effective iris and periocular recognition techniques.
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Table of Contents
1. Advances in Iris and Ocular Recognition: An Insight into Trends 2. Unlocking the Full Potential of Iris Recognition with Deep Learning 3. Real-Time Online Framework for Accurate Detection, Segmentation, and Recognition of Irises 4. Enhancing Iris Recognition Accuracy through Dilated Residual Features 5. Iris Recognition with Deep Learning Across Spectrums 6. Semantics-Assisted Convolutional Neural Network for Accurate Periocular Recognition 7. Deep Neural Network with Focused Attention on Critical Periocular Regions 8. Dynamic Iris Recognition through Multi-Feature Collaboration 9. Position-Specific Convolutional Neural Network to Accurately Match Iris and Periocular Images 10. Securing the Metaverse with Egocentric Iris Recognition via AR/VR/MR Devices 11. Inference and Future Pathways: Reflections and Exploration of New Horizons
