Recent Application in Biometrics

In the recent years, a number of recognition and authentication systems based on biometric measurements have been proposed. Algorithms and sensors have been developed to acquire and process many different biometric traits. Moreover, the biometric technology is being used in novel ways, with potential commercial and practical implications to our daily activities. The key objective of the book is to provide a collection of comprehensive references on some recent theoretical development as well as novel applications in biometrics. The topics covered in this book reflect well both aspects of development. They include biometric sample quality, privacy preserving and cancellable biometrics, contactless biometrics, novel and unconventional biometrics, and the technical challenges in implementing the technology in portable devices. The book consists of 15 chapters. It is divided into four sections, namely, biometric applications on mobile platforms, cancelable biometrics, biometric encryption, and other applications. The book was reviewed by editors Dr. Jucheng Yang and Dr. Norman Poh. We deeply appreciate the efforts of our guest editors: Dr. Girija Chetty, Dr. Loris Nanni, Dr. Jianjiang Feng, Dr. Dongsun Park and Dr. Sook Yoon, as well as a number of anonymous reviewers

Biometrics

Biometrics uses methods for unique recognition of humans based upon one or more intrinsic physical or behavioral traits. In computer science, particularly, biometrics is used as a form of identity access management and access control. It is also used to identify individuals in groups that are under surveillance. The book consists of 13 chapters, each focusing on a certain aspect of the problem. The book chapters are divided into three sections: physical biometrics, behavioral biometrics and medical biometrics. The key objective of the book is to provide comprehensive reference and text on human authentication and people identity verification from both physiological, behavioural and other points of view. It aims to publish new insights into current innovations in computer systems and technology for biometrics development and its applications. The book was reviewed by the editor Dr. Jucheng Yang, and many of the guest editors, such as Dr. Girija Chetty, Dr. Norman Poh, Dr. Loris Nanni, Dr. Jianjiang Feng, Dr. Dongsun Park, Dr. Sook Yoon and so on, who also made a significant contribution to the book

Biometric Person Identification Using Near-infrared Hand-dorsa Vein Images

Biometric recognition is becoming more and more important with the increasing demand for security, and more usable with the improvement of computer vision as well as pattern recognition technologies. Hand vein patterns have been recognised as a good biometric measure for personal identification due to many excellent characteristics, such as uniqueness and stability, as well as difficulty to copy or forge. This thesis covers all the research and development aspects of a biometric person identification system based on near-infrared hand-dorsa vein images. Firstly, the design and realisation of an optimised vein image capture device is presented. In order to maximise the quality of the captured images with relatively low cost, the infrared illumination and imaging theory are discussed. Then a database containing 2040 images from 102 individuals, which were captured by this device, is introduced. Secondly, image analysis and the customised image pre-processing methods are discussed. The consistency of the database images is evaluated using mean squared error (MSE) and peak signal-to-noise ratio (PSNR). Geometrical pre-processing, including shearing correction and region of interest (ROI) extraction, is introduced to improve image consistency. Image noise is evaluated using total variance (TV) values. Grey-level pre-processing, including grey-level normalisation, filtering and adaptive histogram equalisation are applied to enhance vein patterns. Thirdly, a gradient-based image segmentation algorithm is compared with popular algorithms in references like Niblack and Threshold Image algorithm to demonstrate its effectiveness in vein pattern extraction. Post-processing methods including morphological filtering and thinning are also presented. Fourthly, feature extraction and recognition methods are investigated, with several new approaches based on keypoints and local binary patterns (LBP) proposed. Through comprehensive comparison with other approaches based on structure and texture features as well as performance evaluation using the database created with 2040 images, the proposed approach based on multi-scale partition LBP is shown to provide the best recognition performance with an identification rate of nearly 99%. Finally, the whole hand-dorsa vein identification system is presented with a user interface for administration of user information and for person identification

Advancing the technology of sclera recognition

PhD ThesisEmerging biometric traits have been suggested recently to overcome some challenges and issues related to utilising traditional human biometric traits such as the face, iris, and fingerprint. In particu- lar, iris recognition has achieved high accuracy rates under Near- InfraRed (NIR) spectrum and it is employed in many applications for security and identification purposes. However, as modern imaging devices operate in the visible spectrum capturing colour images, iris recognition has faced challenges when applied to coloured images especially with eye images which have a dark pigmentation. Other issues with iris recognition under NIR spectrum are the constraints on the capturing process resulting in failure-to-enrol, and degradation in system accuracy and performance. As a result, the research commu- nity investigated using other traits to support the iris biometric in the visible spectrum such as the sclera. The sclera which is commonly known as the white part of the eye includes a complex network of blood vessels and veins surrounding the eye. The vascular pattern within the sclera has different formations and layers providing powerful features for human identification. In addition, these blood vessels can be acquired in the visible spectrum and thus can be applied using ubiquitous camera-based devices. As a consequence, recent research has focused on developing sclera recog- nition. However, sclera recognition as any biometric system has issues and challenges which need to be addressed. These issues are mainly related to sclera segmentation, blood vessel enhancement, feature ex- traction, template registration, matching and decision methods. In addition, employing the sclera biometric in the wild where relaxed imaging constraints are utilised has introduced more challenges such as illumination variation, specular reflections, non-cooperative user capturing, sclera blocked region due to glasses and eyelashes, variation in capturing distance, multiple gaze directions, and eye rotation. The aim of this thesis is to address such sclera biometric challenges and highlight the potential of this trait. This also might inspire further research on tackling sclera recognition system issues. To overcome the vii above-mentioned issues and challenges, three major contributions are made which can be summarised as 1) designing an efficient sclera recognition system under constrained imaging conditions which in- clude new sclera segmentation, blood vessel enhancement, vascular binary network mapping and feature extraction, and template registra- tion techniques; 2) introducing a novel sclera recognition system under relaxed imaging constraints which exploits novel sclera segmentation, sclera template rotation alignment and distance scaling methods, and complex sclera features; 3) presenting solutions to tackle issues related to applying sclera recognition in a real-time application such as eye localisation, eye corner and gaze detection, together with a novel image quality metric. The evaluation of the proposed contributions is achieved using five databases having different properties representing various challenges and issues. These databases are the UBIRIS.v1, UBIRIS.v2, UTIRIS, MICHE, and an in-house database. The results in terms of segmen- tation accuracy, Equal Error Rate (EER), and processing time show significant improvement in the proposed systems compared to state- of-the-art methods.Ministry of Higher Education and Scientific Research in Iraq and the Iraqi Cultural Attach´e in Londo

Contactless multiple finger segments based identity verification using information fusion from higher order spectral invariants

A methodology for identity verification from contactless finger images using ridge orientation profiles and bispectral invariant features is extended to use fusion at data, feature levels and combination of both levels using multiple finger segments. Performance is evaluated on 1341 images (selected 24 Megapixel video frames obtained with the finger to camera distance between 12 and 20cms, reduced to finger regions of about 1250 x 3000 pixels) from 41 individuals of different ethnicities. Features are extracted from profiles along key lines between landmarks that facilitate segmentation. The methodology is designed by means of the segmentation procedure, the invariant features and fusion techniques to be robust to geometric and photometric transformations and partial occlusion. Feature fusion, data fusion and a combination of the two are tested. The methodology yields around 5% EER with a combination of data and feature fusion providing the best performance. It can be applied to soft, on-the-move biometric systems

Participative Urban Health and Healthy Aging in the Age of AI

This open access book constitutes the refereed proceedings of the 18th International Conference on String Processing and Information Retrieval, ICOST 2022, held in Paris, France, in June 2022. The 15 full papers and 10 short papers presented in this volume were carefully reviewed and selected from 33 submissions. They cover topics such as design, development, deployment, and evaluation of AI for health, smart urban environments, assistive technologies, chronic disease management, and coaching and health telematics systems

Humanoid Robots

For many years, the human being has been trying, in all ways, to recreate the complex mechanisms that form the human body. Such task is extremely complicated and the results are not totally satisfactory. However, with increasing technological advances based on theoretical and experimental researches, man gets, in a way, to copy or to imitate some systems of the human body. These researches not only intended to create humanoid robots, great part of them constituting autonomous systems, but also, in some way, to offer a higher knowledge of the systems that form the human body, objectifying possible applications in the technology of rehabilitation of human beings, gathering in a whole studies related not only to Robotics, but also to Biomechanics, Biomimmetics, Cybernetics, among other areas. This book presents a series of researches inspired by this ideal, carried through by various researchers worldwide, looking for to analyze and to discuss diverse subjects related to humanoid robots. The presented contributions explore aspects about robotic hands, learning, language, vision and locomotion

Remote measurements of heart valve sounds for health assessment and biometric identification

Heart failure will contribute to the death of one in three people who read this thesis; and one in three of those who don't. Although in order to diagnose patients’ heart condition cardiologists have access to electrocardiograms, chest X-rays, ultrasound imaging, MRI, Doppler techniques, angiography, and transesophageal echocardiography, these diagnostic techniques require a cardiologist’s visit, are expensive, the examination time is long and so are the waiting lists. Furthermore abnormal events might be sporadic and thus constant monitoring would be needed to avoid fatalities. Therefore in this thesis we propose a cost effective device which can constantly monitor the heart condition based on the principles of phonocardiography, which is a cost-effective method which records heart sounds. Manual auscultation is not widely used to diagnose because it requires considerable training, it relies on the hearing abilities of the clinician and specificity and sensitivity for manual auscultation are low since results are qualitative and not reproducible. However we propose a cheap laser-based device which is contactless and can constantly monitor patients’ heart sounds with a better SNR than the digital stethoscope. We also propose a Machine Learning (ML) aided software trained on data acquired with our device which can classify healthy from unhealthy heart sounds and can perform biometric authentication. This device might allow development of gadgets for remote monitoring of cardiovascular health in different settings

Европейский и национальный контексты в научных исследованиях

В настоящем электронном сборнике «Европейский и национальный контексты в научных исследованиях. Технология» представлены работы молодых ученых по геодезии и картографии, химической технологии и машиностроению, информационным технологиям, строительству и радиотехнике. Предназначены для работников образования, науки и производства. Будут полезны студентам, магистрантам и аспирантам университетов.=In this Electronic collected materials “National and European dimension in research. Technology” works in the fields of geodesy, chemical technology, mechanical engineering, information technology, civil engineering, and radio-engineering are presented. It is intended for trainers, researchers and professionals. It can be useful for university graduate and post-graduate students