Handbook of Vascular Biometrics

This open access handbook provides the first comprehensive overview of biometrics exploiting the shape of human blood vessels for biometric recognition, i.e. vascular biometrics, including finger vein recognition, hand/palm vein recognition, retina recognition, and sclera recognition. After an introductory chapter summarizing the state of the art in and availability of commercial systems and open datasets/open source software, individual chapters focus on specific aspects of one of the biometric modalities, including questions of usability, security, and privacy. The book features contributions from both academia and major industrial manufacturers

Biometric Systems

Because of the accelerating progress in biometrics research and the latest nation-state threats to security, this book's publication is not only timely but also much needed. This volume contains seventeen peer-reviewed chapters reporting the state of the art in biometrics research: security issues, signature verification, fingerprint identification, wrist vascular biometrics, ear detection, face detection and identification (including a new survey of face recognition), person re-identification, electrocardiogram (ECT) recognition, and several multi-modal systems. This book will be a valuable resource for graduate students, engineers, and researchers interested in understanding and investigating this important field of study

Vascular Innovation Science

Vascular Innovation science are a standout amongst the most approaching innovations which is very secure. In this paperi introduces a study of machine learning techniques utilized for Vascular innovation development applications, and distinguishes significant exploration issues. Basic mission assets and applications require instruments to recognize when honest to goodness clients attempt to abuse their benefits; unquestionably biometrics serves to give such administrations

The way we walk

Mark Nixon and John Carter reveal how developments in biometrics could mean the increasing use of biometric evidence such ear shape and gait to identify defendants

Infrared face recognition: a comprehensive review of methodologies and databases

Automatic face recognition is an area with immense practical potential which includes a wide range of commercial and law enforcement applications. Hence it is unsurprising that it continues to be one of the most active research areas of computer vision. Even after over three decades of intense research, the state-of-the-art in face recognition continues to improve, benefitting from advances in a range of different research fields such as image processing, pattern recognition, computer graphics, and physiology. Systems based on visible spectrum images, the most researched face recognition modality, have reached a significant level of maturity with some practical success. However, they continue to face challenges in the presence of illumination, pose and expression changes, as well as facial disguises, all of which can significantly decrease recognition accuracy. Amongst various approaches which have been proposed in an attempt to overcome these limitations, the use of infrared (IR) imaging has emerged as a particularly promising research direction. This paper presents a comprehensive and timely review of the literature on this subject. Our key contributions are: (i) a summary of the inherent properties of infrared imaging which makes this modality promising in the context of face recognition, (ii) a systematic review of the most influential approaches, with a focus on emerging common trends as well as key differences between alternative methodologies, (iii) a description of the main databases of infrared facial images available to the researcher, and lastly (iv) a discussion of the most promising avenues for future research.Comment: Pattern Recognition, 2014. arXiv admin note: substantial text overlap with arXiv:1306.160

Towards a General Definition of Biometric Systems

A foundation for closing the gap between biometrics in the narrower and the broader perspective is presented trough a conceptualization of biometric systems in both perspectives. A clear distinction between verification, identification and classification systems is made as well as shown that there are additional classes of biometric systems. In the end a Unified Modeling Language model is developed showing the connections between the two perspectives

Using a Bayesian averaging model for estimating the reliability of decisions in multimodal biometrics

The issue of reliable authentication is of increasing importance in modern society. Corporations, businesses and individuals often wish to restrict access to logical or physical resources to those with relevant privileges. A popular method for authentication is the use of biometric data, but the uncertainty that arises due to the lack of uniqueness in biometrics has lead there to be a great deal of effort invested into multimodal biometrics. These multimodal biometric systems can give rise to large, distributed data sets that are used to decide the authenticity of a user. Bayesian model averaging (BMA) methodology has been used to allow experts to evaluate the reliability of decisions made in data mining applications. The use of decision tree (DT) models within the BMA methodology gives experts additional information on how decisions are made. In this paper we discuss how DT models within the BMA methodology can be used for authentication in multimodal biometric systems