Visible, near infrared and thermal hand-based image biometric recognition

Biometric Recognition refers to the automatic identification of a person based on his or her anatomical characteristic or modality (i.e., fingerprint, palmprint, face) or behavioural (i.e., signature) characteristic. It is a fundamental key issue in any process concerned with security, shared resources, network transactions among many others. Arises as a fundamental problem widely known as recognition, and becomes a must step before permission is granted. It is supposed that protects key resources by only allowing those resources to be used by users that have been granted authority to use or to have access to them. Biometric systems can operate in verification mode, where the question to be solved is Am I who I claim I am? or in identification mode where the question is Who am I? Scientific community has increased its efforts in order to improve performance of biometric systems. Depending on the application many solutions go in the way of working with several modalities or combining different classification methods. Since increasing modalities require some user inconvenience many of these approaches will never reach the market. For example working with iris, face and fingerprints requires some user effort in order to help acquisition. This thesis addresses hand-based biometric system in a thorough way. The main contributions are in the direction of a new multi-spectral hand-based image database and methods for performance improvement. The main contributions are: A) The first multi-spectral hand-based image database from both hand faces: palmar and dorsal. Biometric database are a precious commodity for research, mainly when it offers something new like visual (VIS), near infrared (NIR) and thermography (TIR) images at a time. This database with a length of 100 users and 10 samples per user constitute a good starting point to check algorithms and hand suitability for recognition. B) In order to correctly deal with raw hand data, some image preprocessing steps are necessary. Three different segmentation phases are deployed to deal with VIS, NIR and TIR images specifically. Some of the tough questions to address: overexposed images, ring fingers and the cuffs, cold finger and noise image. Once image segmented, two different approaches are prepared to deal with the segmented data. These two approaches called: Holistic and Geometric define the main focus to extract the feature vector. These feature vectors can be used alone or can be combined in some way. Many questions can be stated: e.g. which approach is better for recognition?, Can fingers alone obtain better performance than the whole hand? and Is thermography hand information suitable for recognition due to its thermoregulation properties? A complete set of data ready to analyse, coming from the holistic and geometric approach have been designed and saved to test. Some innovative geometric approach related to curvature will be demonstrated. C) Finally the Biometric Dispersion Matcher (BDM) is used in order to explore how it works under different fusion schemes, as well as with different classification methods. It is the intention of this research to contrast what happen when using other methods close to BDM like Linear Discriminant Analysis (LDA). At this point, some interesting questions will be solved, e.g. by taking advantage of the finger segmentation (as five different modalities) to figure out if they can outperform what the whole hand data can teach us.El Reconeixement Biomètric fa referència a la identi cació automàtica de persones fent us d'alguna característica o modalitat anatòmica (empremta digital) o d'alguna característica de comportament (signatura). És un aspecte fonamental en qualsevol procés relacionat amb la seguretat, la compartició de recursos o les transaccions electròniques entre d'altres. És converteix en un pas imprescindible abans de concedir l'autorització. Aquesta autorització, s'entén que protegeix recursos clau, permeten així, que aquests siguin utilitzats pels usuaris que han estat autoritzats a utilitzar-los o a tenir-hi accés. Els sistemes biomètrics poden funcionar en veri cació, on es resol la pregunta: Soc jo qui dic que soc? O en identi cació on es resol la qüestió: Qui soc jo? La comunitat cientí ca ha incrementat els seus esforços per millorar el rendiment dels sistemes biomètrics. En funció de l'aplicació, diverses solucions s'adrecen a treballar amb múltiples modalitats o combinant diferents mètodes de classi cació. Donat que incrementar el número de modalitats, representa a la vegada problemes pels usuaris, moltes d'aquestes aproximacions no arriben mai al mercat. La tesis contribueix principalment en tres grans àrees, totes elles amb el denominador comú següent: Reconeixement biometric a través de les mans. i) La primera d'elles constitueix la base de qualsevol estudi, les dades. Per poder interpretar, i establir un sistema de reconeixement biomètric prou robust amb un clar enfocament a múltiples fonts d'informació, però amb el mínim esforç per part de l'usuari es construeix aquesta Base de Dades de mans multi espectral. Les bases de dades biomètriques constitueixen un recurs molt preuat per a la recerca; sobretot si ofereixen algun element nou com es el cas. Imatges de mans en diferents espectres electromagnètics: en visible (VIS), en infraroig (NIR) i en tèrmic (TIR). Amb un total de 100 usuaris, i 10 mostres per usuari, constitueix un bon punt de partida per estudiar i posar a prova sistemes multi biomètrics enfocats a les mans. ii) El segon bloc s'adreça a les dues aproximacions existents en la literatura per a tractar les dades en brut. Aquestes dues aproximacions, anomenades Holística (tracta la imatge com un tot) i Geomètrica (utilitza càlculs geomètrics) de neixen el focus alhora d'extreure el vector de característiques. Abans de tractar alguna d'aquestes dues aproximacions, però, és necessària l'aplicació de diferents tècniques de preprocessat digital de la imatge per obtenir les regions d'interès desitjades. Diferents problemes presents a les imatges s'han hagut de solucionar de forma original per a cadascuna de les tipologies de les imatges presents: VIS, NIR i TIR. VIS: imatges sobre exposades, anells, mànigues, braçalets. NIR: Ungles pintades, distorsió en forma de soroll en les imatges TIR: Dits freds La segona àrea presenta aspectes innovadors, ja que a part de segmentar la imatge de la ma, es segmenten tots i cadascun dels dits (feature-based approach). Així aconseguim contrastar la seva capacitat de reconeixement envers la ma de forma completa. Addicionalment es presenta un conjunt de procediments geomètrics amb la idea de comparar-los amb els provinents de l'extracció holística. La tercera i última àrea contrasta el procediment de classi cació anomenat Biometric Dispersion Matcher (BDM) amb diferents situacions. La primera relacionada amb l'efectivitat respecte d'altres mètode de reconeixement, com ara l'Anàlisi Lineal Discriminant (LDA) o bé mètodes com KNN o la regressió logística. Les altres situacions que s'analitzen tenen a veure amb múltiples fonts d'informació, quan s'apliquen tècniques de normalització i/o estratègies de combinació (fusió) per millorar els resultats. Els resultats obtinguts no deixen lloc per a la confusió, i són certament prometedors en el sentit que posen a la llum la importància de combinar informació complementària per obtenir rendiments superiors

Finger Vein Recognition Using Principle Component Analysis and Adaptive k-Nearest Centroid Neighbor Classifier

The k-nearest centroid neighbor kNCN classifier is one of the non-parametric classifiers which provide a powerful decision based on the geometrical surrounding neighborhood. Essentially, the main challenge in the kNCN is due to slow classification time that utilizing all training samples to find each nearest centroid neighbor. In this work, an adaptive k-nearest centroid neighbor (akNCN) is proposed as an improvement to the kNCN classifier. Two new rules are introduced to adaptively select the neighborhood size of the test sample. The neighborhood size for the test sample is changed through the following ways: 1) The neighborhood size, k will be adapted to j if the centroid distance of j-th nearest centroid neighbor is greater than the predefined boundary. 2) There is no need to look for further nearest centroid neighbors if the maximum number of samples of the same class is found among jth nearest centroid neighbor. Thus, the size of neighborhood is adaptively changed to j. Experimental results on theFinger Vein USM (FV-USM) image database demonstrate the promising results in which the classification time of the akNCN classifier is significantly reduced to 51.56% in comparison to the closest competitors, kNCN and limited-kNCN. It also outperforms its competitors by achieving the best reduction ratio of 12.92% whilemaintaining the classification accuracy

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

A single scale retinex based method for palm vein extraction

Palm vein recognition is a novel biometric identification technology. But how to gain a better vein extraction result from the raw palm image is still a challenging problem, especially when the raw data collection has the problem of asymmetric illumination. This paper proposes a method based on single scale Retinex algorithm to extract palm vein image when strong shadow presents due to asymmetric illumination and uneven geometry of the palm. We test our method on a multispectral palm image. The experimental result shows that the proposed method is robust to the influence of illumination angle and shadow. Compared to the traditional extraction methods, the proposed method can obtain palm vein lines with better visualization performance (the contrast ratio increases by 18.4%, entropy increases by 1.07%, and definition increases by 18.8%)

Affective modulation of cognitive control is determined by performance-contingency and mediated by ventromedial prefrontal and cingulate cortex

Cognitive control requires a fine balance between stability, the protection of an on-going task-set, and flexibility, the ability to update a task-set in line with changing contingencies. It is thought that emotional processing modulates this balance, but results have been equivocal regarding the direction of this modulation. Here, we tested the hypothesis that a crucial determinant of this modulation is whether affective stimuli represent performance-contingent or task-irrelevant signals. Combining functional magnetic resonance imaging with a conflict task-switching paradigm, we contrasted the effects of presenting negative- and positive-valence pictures on the stability/flexibility trade-off in humans, depending on whether picture presentation was contingent on behavioral performance. Both the behavioral and neural expressions of cognitive control were modulated by stimulus valence and performance contingency: in the performance-contingent condition, cognitive flexibility was enhanced following positive pictures, whereas in the nonperformance-contingent condition, positive stimuli promoted cognitive stability. The imaging data showed that, as anticipated, the stability/flexibility trade-off per se was reflected in differential recruitment of dorsolateral frontoparietal and striatal regions. In contrast, the affective modulation of stability/flexibility shifts was mirrored, unexpectedly, by neural responses in ventromedial prefrontal and posterior cingulate cortices, core nodes of the “default mode” network. Our results demonstrate that the affective modulation of cognitive control depends on the performance contingency of the affect-inducing stimuli, and they document medial default mode regions to mediate the flexibility-promoting effects of performance-contingent positive affect, thus extending recent work that recasts these regions as serving a key role in on-task control processes

Neural Correlates of Spontaneous BOLD Fluctuations: A Simultaneous LFP-fMRI Investigation In The Non-human Primate

Resting-state functional magnetic resonance imaging (rs-fMRI) is widely used to explore functional connectivity (FC) between brain regions across neurological and psychiatric diseases. However, the neural basis of spontaneous low frequency blood-oxygen level dependent (BOLD) fluctuations is poorly understood. Here, we acquired rs-fMRI data in macaque monkeys together with simultaneous recordings of local field potentials (LFPs) in prefrontal cortex area 9/46d. We first evaluated the correlation between LFPs (1-100 Hz) and BOLD signals and found unique frequency power correlates of positive and negative FC. Anti-correlation of high and low power envelopes indicated that ongoing cross-frequency interactions are a neural correlate of FC. On the other hand, seed-based analysis of the BOLD signal from the vicinity of electrode revealed the same spatial topology when using the power envelopes of high frequency bands of LFPs in the regression analysis. Variations of the canonical hemodynamic response function (HRF) in distinct cortical areas were also investigated to find the optimal HRF that can best fit in model analysis and estimate the BOLD response. While we found the optimal HRF that yields the highest correlation, the HRF shape was consistent within subjects and between brain regions. Our results suggest that intrinsic connectivity networks may be specifically driven by unique LFP profiles and these profiles contribute differently to BOLD FC. This study provides insight into the neural correlates of spontaneous BOLD FC at rest

Investigation of the modulation of spatial frequency preferences with attentional load within human visual cortex

Performance in visual tasks improves with attention, and this improvement has been shown to stem, in part, from changes in sensory processing. However, the mechanism by which attention affects perception remains unclear. Considering that neurons within the visual areas are selective for basic image statistics, such as orientation or spatial frequency (SF), it is plausible that attention modulates these sensory preferences by altering their so-called ‘tuning curves’. The goal of this project is to investigate this possibility by measuring and comparing the SF tuning curves across a range of attentional states in humans. In Experiment 1, a model-driven approach to fMRI analysis was introduced that allows for fast and efficient estimation of population spatial frequency tuning (pSFT) for individual voxels within human visual cortices. Using this method, I estimated pSFTs within early visual cortices of 8 healthy, young adults. Consistent with previous studies, the estimated SF optima showed a decline with retinotopic eccentricity. Moreover, my results suggested that the bandwidth of pSFT depends on eccentricity, and that populations with lower SF peaks possess broader bandwidths. In Experiment 2, I proposed a new visual task, coined the Numerosity Judgement Paradigm (NJP), for fine-grained parametric manipulation of attentional load. Eight healthy, young adults performed this task in an MRI scanner, and the analysis of the BOLD signal indicated that the activity within the putative dorsal attention network was precisely modulated as a function of the attentional load of the task. In Experiment 3, I used the NJP to modulate attentional load, and exploited the model-based approach to estimate pSFTs under different attentional states. fMRI results of 9 healthy, young adults did not reveal any changes in either peak or the bandwidth of the pSFTs with attentional load. This study yields a full visuocortical map of spatial frequency sensitivity and introduces a new paradigm for modulating attentional load. Although under this paradigm I did not find any changes in SF preferences within human visual areas with attentional load, I cannot preclude the possibility that changes emerge under different attentional manipulations