Fingerprint, is considered one of the most crucial scientific tools in solving criminal cases. This biometric feature is composed of unique and distinctive patterns found on the fingertips of each individual. With advancing technology and progress in forensic sciences, fingerprint analysis plays a vital role in forensic investigations and the analysis of evidence at crime scenes. The fingerprint patterns of each individual start to develop in early stagesof life and never change thereafter. This fact makes fingerprints an exceptional means of identification. In criminal cases, fingerprint analysis is used to decipher traces, evidence, and clues at crime scenes. These analyses not only provide insights into how a crime was committed but also assist in identifying the culprits or individuals involved. Computer-based fingerprint identification systems yield faster and more accurate results compared to traditional methods, making fingerprint comparisons in large databases ...

Biometric recognition for a long time has been used in confined spaces, usually indoor, where security-critical operations required high accuracy recognition systems, e.g. in police stations, banks, companies, airports. Field activities, on the contrary, required more portability and flexibility leading to the development of devices for less constrained biometric traits acquisition and consequently of robust algorithms for biometric recognition in less constrained conditions. However, the application of "portable" biometric recognition, was still limited in specific fields e.g. for immigration control, and still required dedicated devices. A further step would be to spread the use of biometric recognition on personal devices, as personal computers, tablets and smartphones. Some attempts in this direction were made embedding fingerprint scanners in laptops or smartphones. So far biometric recognition on personal devices has been employed just for a limited set of tasks, as to unlock ...

In a world where security issues have been gaining explosive importance, face and ear recognition systems have attracted increasing attention in multiple application areas, ranging from forensics and surveillance to commerce and entertainment. While the recognition performance has been steadily improving, there are still challenging recognition scenarios and conditions, notably when facing large variations in the biometric data characteristics. Additionally, the widespread use of face and ear recognition solutions raises new security concerns, making the robustness against presentation attacks a very active field of research. Lenslet light field cameras have recently come into prominence as they are able to also capture the intensity of the light rays coming from multiple directions, thus offering a richer representation of the visual scene, notably spatio-angular information. To take benefit of this richer representation, light field cameras have recently been successfully applied, not only ...

Thermal imaging technology has significantly evolved during the last couple of decades, mostly thanks to thermal cameras having become more affordable and user friendly. However, and given that the exploration of thermal imagery is reasonably new, only a few public databases are available to the research community. This limitation consequently prevents the impact of deep learning technologies from generating improved and reliable face biometric systems that operate in the thermal spectrum. A possible solution relates to the development of technologies that bridge the gap between the visible and thermal spectrum. In attempting to respond to this necessity, the research presented in this dissertation aims to explore interspectral synthesis as a direction for efficient and prompt integration of thermal technology in already deployed face biometric systems. As a first contribution, a new database, containing paired visible and thermal face images acquired ...

This Thesis is focused on dealing with the variability factors in biometric recognition and applications of biometrics at a distance. In particular, this PhD Thesis explores the problem of variability factors assessment and how to deal with them by the incorporation of soft biometrics information in order to improve person recognition systems working at a distance. The proposed methods supported by experimental results show the benefits of adapting the system considering the variability of the sample at hand. Although being relatively young compared to other mature and long-used security technologies, biometrics have emerged in the last decade as a pushing alternative for applications where automatic recognition of people is needed. Certainly, biometrics are very attractive and useful for video surveillance systems at a distance, widely distributed in our lifes, and for the final user: forget about PINs and passwords, you ...

Biometric systems consist in the combination of devices, algorithms, and procedures used to recognize the individuals based on the characteristics, physical or behavioral, of their persons. These characteristics are called biometric traits. Nowadays, biometric technologies are becoming more and more widespread, and many people use biometric systems daily. However, in some cases the procedures used for the collection of the biometric traits need the cooperation of the user, controlled environments, illuminations perceived as unpleasant, too strong, or harmful, or the contact of the body with a sensor. For these reasons, techniques for the contactless and less-constrained biometric recognition are being researched, in order to increase the usability and social acceptance of biometric systems, and increase the fields of application of biometric technologies. In this context, the palmprint is a biometric trait whose acquisition is generally well accepted by the users. ...

This Thesis is focused on the quality assessment of biometric signals and its application to multimodal biometric systems. Since the establishment of biometrics as an specific research area in late 90s, the biometric community has focused its efforts in the development of accurate recognition algorithms and nowadays, biometric recognition is a mature technology that is used in many applications. However, we can notice recent studies that demonstrate how performance of biometric systems is heavily affected by the quality of biometric signals. Quality measurement has emerged in the biometric community as an important concern after the poor performance observed in biometric systems on certain pathological samples. We first summarize the state-of-the-art in the biometric quality problem. We present the factors influencing biometric quality, which mainly have to do with four issues: the individual itself, the sensor used in the acquisition, the ...

Absolute security does not exist: given funding, willpower and the proper technology, every security system can be compromised. However, the objective of the security community should be to develop such applications that the funding, the will, and the resources needed by the attacker to crack the system prevent him from attempting to do so. This Thesis is focused on the vulnerability assessment of biometric systems. Although being relatively young compared to other mature and long-used security technologies, biometrics have emerged in the last decade as a pushing alternative for applications where automatic recognition of people is needed. Certainly, biometrics are very attractive and useful for the final user: forget about PINs and passwords, you are your own key. However, we cannot forget that as any technology aimed to provide a security service, biometric systems are exposed to external attacks which ...

Computer vision-based analysis of human facial video provides information regarding to expression, diseases symptoms, and physiological parameters such as heartbeat rate, blood pressure and respiratory rate. It also provides a convenient source of heartbeat signal to be used in biometrics and forensics. This thesis is a collection of works done in five themes in the realm of computer vision-based facial image analysis: Monitoring elderly patients at private homes, Face quality assessment, Measurement of physiological parameters, Contact-free heartbeat biometrics, and Decision support system for healthcare. The work related to monitoring elderly patients at private homes includes a detailed survey and review of the monitoring technologies relevant to older patients living at home by discussing previous reviews and relevant taxonomies, different scenarios for home monitoring solutions for older patients, sensing and data acquisition techniques, data processing and analysis techniques, available datasets for ...

The achievement of perfect security is out of the question. Even if we are not yet aware of them, every security aimed technology has weaknesses which attackers can exploit in order to circumvent the system. We should hence direct our efforts to the development of applications whose security level make it infeasible for computationally bound attackers to break the systems. This Thesis is focused on improving the security and privacy provided by biometric systems. With the increased need for reliable and automatic identity verification, biometrics have emerged in the last decades as a pushing alternative to traditional authentication methods. Certainly, biometrics are very attractive and useful for the general public: forget about PINs and passwords, you are your own key. However, the wide deployment of biometric recognition systems at both large-scale applications (e.g., border management at European level or national ...

This thesis contributes to motion characterization through inertial and physiological signals captured by wearable devices and analyzed using signal processing and deep learning techniques. This research leverages the possibilities of motion analysis for three main applications: to know what physical activity a person is performing (Human Activity Recognition), to identify who is performing that motion (user identification) or know how the movement is being performed (motor anomaly detection). Most previous research has addressed human motion modeling using invasive sensors in contact with the user or intrusive sensors that modify the user’s behavior while performing an action (cameras or microphones). In this sense, wearable devices such as smartphones and smartwatches can collect motion signals from users during their daily lives in a less invasive or intrusive way. Recently, there has been an exponential increase in research focused on inertial-signal processing to ...

Automatic ear recognition systems have seen increased interest over recent years due to multiple desirable characteristics. Ear images used in such systems can typically be extracted from profile head shots or video footage. The acquisition procedure is contactless and non-intrusive, and it also does not depend on the cooperation of the subjects. In this regard, ear recognition technology shares similarities with other image-based biometric modalities. Another appealing property of ear biometrics is its distinctiveness. Recent studies even empirically validated existing conjectures that certain features of the ear are distinct for identical twins. This fact has significant implications for security-related applications and puts ear images on a par with epigenetic biometric modalities, such as the iris. Ear images can also supplement other biometric modalities in automatic recognition systems and provide identity cues when other information is unreliable or even unavailable. In ...

Communicating with mobile devices has become an unavoidable part of our daily life. Unfortunately, the current user interface designs are mostly taken directly from desktop computers. This has resulted in devices that are sometimes hard to use. Since more processing power and new sensing technologies are already available, there is a possibility to develop systems to communicate through different modalities. This thesis proposes some novel computer vision approaches, including head tracking, object motion analysis and device ego-motion estimation, to allow efficient interaction with mobile devices. For head tracking, two new methods have been developed. The first method detects a face region and facial features by employing skin detection, morphology, and a geometrical face model. The second method, designed especially for mobile use, detects the face and eyes using local texture features. In both cases, Kalman filtering is applied to estimate ...

Single-pixel imaging is a recent paradigm that allows the acquisition of images at reasonably low cost by exploiting hardware compression of the data. The architecture of a single-pixel camera consists of only two elements: a spatial light modulator, and a single-point detector. The key idea is to measure the projection at the detector (i.e., the inner product) of the scene under view -the image- with some patterns. The post-processing of a sequence of measurements obtained with different patterns permits the restoring of the desired image. Single-pixel imaging has several advantages, which are of interest for different applications, and especially in the biomedical field. In particular, a time-resolved single-pixel imaging system benefits fluorescence lifetime sensing. Such a set-up can be coupled to a spectrometer, to supplement the lifetime with spectral information. However, the main limitation of single-pixel imaging is the speed ...

The number of cameras increases rapidly in squares, shopping centers, railway stations and airport halls. There are hundreds of cameras in the city center of Amsterdam. This is still modest compared to the tens of thousands of cameras in London, where citizens are expected to be filmed by more than three hundred cameras of over thirty separate Closed Circuit Television (CCTV) systems in a single day [84]. These CCTV systems include both publicly owned systems (railway stations, squares, airports) and privately owned systems (shops, banks, hotels). The main purpose of all these cameras is to detect, prevent and monitor crime and anti-social behaviour. Other goals of camera surveillance can be detection of unauthorized access, improvement of service, fire safety, etc. Since the terrorist attack on 9/11, detection and prevention of terrorist activities especially at high profiled locations such as airports, ...