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The 2020 International Joint Conference on Biometrics (IJCB 2020) combines two major biometrics research conferences, the Biometrics Theory, Applications and Systems (BTAS) conference and the International Conference on Biometrics (ICB) The blending of these two conferences in 2020 is through special agreement between the IEEE Biometrics Council and the IAPR TC 4, and should present an exciting event for the entire worldwide biometrics research community.

Biometric identification

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In many cases of serious crime, images of a hand can be the only evidence available for the forensic identification of the offender. As well as placing them at the scene, such images and video evidence offer proof of the offender committing the crime. The knuckle creases of the human hand have emerged as an effective biometric trait and been used to identify the perpetrators of child abuse in forensic investigations. However, manual utilization of knuckle creases for identification is highly time consuming and can be subjective, requiring the expertise of experienced forensic anthropologists whose availability is very limited. Hence, there arises a need for an automated approach for localization and comparison of knuckle patterns. In this paper, we present a fully automatic end-to-end approach which localizes the minor, major and base knuckles in images of the hand, and effectively uses them for identification achieving state-of-the-art results. This work improves on existing approaches and allows us to strengthen cases further by objectively combining multiple knuckles and knuckle types to obtain a holistic matching result for comparing two hands. This yields a stronger and more robust multi-unit biometric and facilitates the large-scale examination of the potential of knuckle-based identification. Evaluated on two large landmark datasets, the proposed framework achieves equal error rates (EER) of 1.0-1.9%, rank-1 accuracies of 99.3-100% and decidability indices of 5.04-5.83. We make the full results available via a novel online GUI to raise awareness with the general public and forensic investigators about the identifiability of various knuckle regions. These strong results demonstrate the value of our holistic approach to hand identification from knuckle patterns and their utility in forensic investigations.

Biometric identification

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Biometric identification

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"Iris recognition has been widely recognized as one of the most performing biometric system. The accuracy performance of iris recognition system is measured by FRR (False Reject Rate). FRR measures the genuine user who is incorrectly denied by the system due to the changes in iris features (such as aging and health condition) and external factors that affected the iris image to be high in noise rate. The external factors such as technical fault, occlusion, and source of lighting caused the image acquisition to produce distorted iris images problem hence incorrectly rejected by the biometric system. The current way of reducing FRR are wavelets and Gabor filters, cascaded classifiers, ordinal measure, multiple biometric modality and selection of unique iris features. Nonetheless, in the long duration of matching process, the previous methods unable to identify the user as a genuine since the iris structure itself produce a template changed due to aging. In facts, iris consists of unique features such as crypts, furrows, collarette, pigment blotches, freckles and pupil that are distinguishable among human. Previous research has been done in selecting the unique iris features however it shows low accuracy performance. Therefore, a new way of identifying and matching the iris template using nature-inspired algorithm is proposed in this book. As a conclusion, this book entitled as "Swarm Intelligence for Iris Recognition" brings an overview of iris recognition that naturally based on nature-inspired environment technology and provides benefits to the reader"-- Provided by publisher.

Biometric identification. --- Swarm intelligence.

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This book focuses on fusion in biometric systems. It discusses the present level, the limitations, and proposed methods to improve performance. It describes the fundamental concepts, current research, and security related issues.

Biometric identification --- Law and legislation. --- Data processing.