Using the Number of Pores on Fingerprint Images to Detect Spoofing Attacks

Abstract-Due to the growing use of biometric technologies inour modern society, spoofing attacks are becoming a seriousconcern. Many solutions have been proposed to detect the use offake "fingerprints" on an acquisition device. In this paper, wepropose to take advantage of intrinsic features of friction ridgeskin: pores. The aim of this study is to investigate the potential ofusing pores to detect spoofing attacks.Results show that the use of pores is a promising approach. Fourmajor observations were made: First, results confirmed that thereproduction of pores on fake "fingerprints" is possible. Second,the distribution of the total number of pores between fake andgenuine fingerprints cannot be discriminated. Third, thedifference in pore quantities between a query image and areference image (genuine or fake) can be used as a discriminatingfactor in a linear discriminant analysis. In our sample, theobserved error rates were as follows: 45.5% of false positive (thefake passed the test) and 3.8% of false negative (a genuine printhas been rejected). Finally, the performance is improved byusing the difference of pore quantity obtained between adistorted query fingerprint and a non-distorted referencefingerprint. By using this approach, the error rates improved to21.2% of false acceptation rate and 8.3% of false rejection rate.

Early pattern recognition in severe perinatal asphyxia: a prospective MRI study.

On the basis of MRI examinations in 88 neonates and infants with perinatal asphyxia, we defined 6 different patterns on T2-weighted images: pattern A--scattered hyperintensity of both hemispheres of the telencephalon with blurred border zones between cortex and white matter, indicating diffuse brain injury; pattern B--parasagittal hyperintensity extending into the corona radiata, corresponding to the watershed zones; pattern C--hyper- and hypointense lesions in thalamus and basal ganglia, which relate to haemorrhagic necrosis or iron deposition in these areas; pattern D--periventricular hyperintensity, mainly along the lateral ventricles, i.e. periventricular leukomalacia (PVL), originating from the matrix zone; pattern E--small multifocal lesions varying from hyper--to hypointense, interpreted as necrosis and haemorrhage; pattern F--periventricular centrifugal hypointense stripes in the centrum semiovale and deep white matter of the frontal and occipital lobes. Contrast was effectively inverted on T1-weighted images. Patterns A, B and C were found in 17%, 25% and 37% of patients, and patterns D, E and F in 19%, 17% and 35%, respectively. In 49 patients a combination of patterns was observed, but 30% of the initial images were normal. At follow-up, persistent abnormalities were seen in all children with patterns A and D, but in only 52% of those with pattern C. Myelination was retarded most often in patients with diffuse brain injury and PVL (patterns A and D).

Atlas-based segmentation of pathological MR brain images using a model of lesion growth.

We propose a method for brain atlas deformation in the presence of large space-occupying tumors, based on an a priori model of lesion growth that assumes radial expansion of the lesion from its starting point. Our approach involves three steps. First, an affine registration brings the atlas and the patient into global correspondence. Then, the seeding of a synthetic tumor into the brain atlas provides a template for the lesion. The last step is the deformation of the seeded atlas, combining a method derived from optical flow principles and a model of lesion growth. Results show that a good registration is performed and that the method can be applied to automatic segmentation of structures and substructures in brains with gross deformation, with important medical applications in neurosurgery, radiosurgery, and radiotherapy.

The development of an automatic recognition system for earmark and earprint comparisons

The value of earmarks as an efficient means of personal identification is still subject to debate. It has been argued that the field is lacking a firm systematic and structured data basis to help practitioners to form their conclusions. Typically, there is a paucity of research guiding as to the selectivity of the features used in the comparison process between an earmark and reference earprints taken from an individual. This study proposes a system for the automatic comparison of earprints and earmarks, operating without any manual extraction of key-points or manual annotations. For each donor, a model is created using multiple reference prints, hence capturing the donor within source variability. For each comparison between a mark and a model, images are automatically aligned and a proximity score, based on a normalized 2D correlation coefficient, is calculated. Appropriate use of this score allows deriving a likelihood ratio that can be explored under known state of affairs (both in cases where it is known that the mark has been left by the donor that gave the model and conversely in cases when it is established that the mark originates from a different source). To assess the system performance, a first dataset containing 1229 donors elaborated during the FearID research project was used. Based on these data, for mark-to-print comparisons, the system performed with an equal error rate (EER) of 2.3% and about 88% of marks are found in the first 3 positions of a hitlist. When performing print-to-print transactions, results show an equal error rate of 0.5%. The system was then tested using real-case data obtained from police forces.

Comparison and validation of tissue modelization and statistical classification methods in T1-weighted MR brain images.

This paper presents a validation study on statistical nonsupervised brain tissue classification techniques in magnetic resonance (MR) images. Several image models assuming different hypotheses regarding the intensity distribution model, the spatial model and the number of classes are assessed. The methods are tested on simulated data for which the classification ground truth is known. Different noise and intensity nonuniformities are added to simulate real imaging conditions. No enhancement of the image quality is considered either before or during the classification process. This way, the accuracy of the methods and their robustness against image artifacts are tested. Classification is also performed on real data where a quantitative validation compares the methods' results with an estimated ground truth from manual segmentations by experts. Validity of the various classification methods in the labeling of the image as well as in the tissue volume is estimated with different local and global measures. Results demonstrate that methods relying on both intensity and spatial information are more robust to noise and field inhomogeneities. We also demonstrate that partial volume is not perfectly modeled, even though methods that account for mixture classes outperform methods that only consider pure Gaussian classes. Finally, we show that simulated data results can also be extended to real data.

Inbreeding avoidance through kin recognition: choosy females boost male dispersal.

Inbreeding avoidance is predicted to induce sex biases in dispersal. But which sex should disperse? In polygynous species, females pay higher costs to inbreeding and thus might be expected to disperse more, but empirical evidence consistently reveals male biases. Here, we show that theoretical expectations change drastically if females are allowed to avoid inbreeding via kin recognition. At high inbreeding loads, females should prefer immigrants over residents, thereby boosting male dispersal. At lower inbreeding loads, by contrast, inclusive fitness benefits should induce females to prefer relatives, thereby promoting male philopatry. This result points to disruptive effects of sexual selection. The inbreeding load that females are ready to accept is surprisingly high. In absence of search costs, females should prefer related partners as long as delta<r/(1+r) where r is relatedness and delta is the fecundity loss relative to an outbred mating. This amounts to fitness losses up to one-fifth for a half-sib mating and one-third for a full-sib mating, which lie in the upper range of inbreeding depression values currently reported in natural populations. The observation of active inbreeding avoidance in a polygynous species thus suggests that inbreeding depression exceeds this threshold in the species under scrutiny or that inbred matings at least partly forfeit other mating opportunities for males. Our model also shows that female choosiness should decline rapidly with search costs, stemming from, for example, reproductive delays. Species under strong time constraints on reproduction should thus be tolerant of inbreeding.

Images in clinical urology. Nail of glans penis.

A 56-year-old man presented with a "nail" growing at the base of his glans penis. The tumor was locally excised, and microscopic examination revealed papillomatosis and hyperkeratosis of the malpighian epithelium, with a strong inflammatory reaction of the chorion and signs of local microinvasion, as well as the presence of well-differentiated squamous epithelial cells. The surgical margins were negative. The differential diagnosis was made between a benign papillomatous proliferation and verrucous carcinoma.

Automatic Mallampati Classification Using Active Appearance Models

Difficult tracheal intubation assessment is an important research topic in anesthesia as failed intubations are important causes of mortality in anesthetic practice. The modified Mallampati score is widely used, alone or in conjunction with other criteria, to predict the difficulty of intubation. This work presents an automatic method to assess the modified Mallampati score from an image of a patient with the mouth wide open. For this purpose we propose an active appearance models (AAM) based method and use linear support vector machines (SVM) to select a subset of relevant features obtained using the AAM. This feature selection step proves to be essential as it improves drastically the performance of classification, which is obtained using SVM with RBF kernel and majority voting. We test our method on images of 100 patients undergoing elective surgery and achieve 97.9% accuracy in the leave-one-out crossvalidation test and provide a key element to an automatic difficult intubation assessment system.

Brittle cornea syndrome: recognition, molecular diagnosis and management.

Brittle cornea syndrome (BCS) is an autosomal recessive disorder characterised by extreme corneal thinning and fragility. Corneal rupture can therefore occur either spontaneously or following minimal trauma in affected patients. Two genes, ZNF469 and PRDM5, have now been identified, in which causative pathogenic mutations collectively account for the condition in nearly all patients with BCS ascertained to date. Therefore, effective molecular diagnosis is now available for affected patients, and those at risk of being heterozygous carriers for BCS. We have previously identified mutations in ZNF469 in 14 families (in addition to 6 reported by others in the literature), and in PRDM5 in 8 families (with 1 further family now published by others). Clinical features include extreme corneal thinning with rupture, high myopia, blue sclerae, deafness of mixed aetiology with hypercompliant tympanic membranes, and variable skeletal manifestations. Corneal rupture may be the presenting feature of BCS, and it is possible that this may be incorrectly attributed to non-accidental injury. Mainstays of management include the prevention of ocular rupture by provision of protective polycarbonate spectacles, careful monitoring of visual and auditory function, and assessment for skeletal complications such as developmental dysplasia of the hip. Effective management depends upon appropriate identification of affected individuals, which may be challenging given the phenotypic overlap of BCS with other connective tissue disorders.

Recognition of RNA virus by RIG-I results in activation of CARD9 and inflammasome signaling for interleukin 1 beta production.

Interleukin 1 beta (IL-1 beta) is a potent proinflammatory factor during viral infection. Its production is tightly controlled by transcription of Il1b dependent on the transcription factor NF-kappaB and subsequent processing of pro-IL-1 beta by an inflammasome. However, the sensors and mechanisms that facilitate RNA virus-induced production of IL-1 beta are not well defined. Here we report a dual role for the RNA helicase RIG-I in RNA virus-induced proinflammatory responses. Whereas RIG-I-mediated activation of NF-kappaB required the signaling adaptor MAVS and a complex of the adaptors CARD9 and Bcl-10, RIG-I also bound to the adaptor ASC to trigger caspase-1-dependent inflammasome activation by a mechanism independent of MAVS, CARD9 and the Nod-like receptor protein NLRP3. Our results identify the CARD9-Bcl-10 module as an essential component of the RIG-I-dependent proinflammatory response and establish RIG-I as a sensor able to activate the inflammasome in response to certain RNA viruses.

Theoretical study on receptor-G protein recognition: new insights into the mechanisms of the alpha1b-adrenergic recptor activation

This work compares the structural/dynamics features of the wild-type alb-adrenergic receptor (AR) with those of the D142A active mutant and the agonist-bound state. The two active receptor forms were compared in their isolated states as well as in their ability to form homodimers and to recognize the G alpha q beta 1 gamma 2 heterotrimer. The analysis of the isolated structures revealed that, although the mutation- and agonist-induced active states of the alpha 1b-AR are different, they, however, share several structural peculiarities including (a) the release of some constraining interactions found in the wild-type receptor and (b) the opening of a cytosolic crevice formed by the second and third intracellular loops and the cytosolic extensions of helices 5 and 6. Accordingly, also their tendency to form homodimers shows commonalties and differences. In fact, in both the active receptor forms, helix 6 plays a crucial role in mediating homodimerization. However, the homodimeric models result from different interhelical assemblies. On the same line of evidence, in both of the active receptor forms, the cytosolic opened crevice recognizes similar domains on the G protein. However, the docking solutions are differently populated and the receptor-G protein preorientation models suggest that the final complexes should be characterized by different interaction patterns.

Characteristic reflection patterns in the southeast Canadian cordillera, northern Appalachians and Swiss Alps

There are some striking similarities and some differences between the seismic reflection sections recorded across the fold and thrust belts of the southeast Canadian Cordillera, Quebec-Maine Appalachians and Swiss Alps. In the fold and thrust belts of all three mountain ranges, seismic reflection surveys have yielded high-quality images of. (1) nappes (thin thrust sheets) stacked on top of ancient continental margins; (2) ramp anticlines in the hanging walls of faults that have ramp-flat or listric geometries; (3) back thrusts and back folds that developed during the terminal phases of orogeny; and (4) tectonic wedges and regional decollements. A principal result of the Cordilleran and Appalachian deep crustal studies has been the recognition of master decollements along which continental margin strata have been transported long distances, whereas a principal result of the Swiss Alpine deep crustal program has been the identification of the Adriatic indenter, a crustal-scale wedge that caused delamination of the European lithosphere. Significant crustal roots are observed beneath the fold and thrust belts of the Alps, southeast Canadian Cordillera and parts of the southern Appalachians, but such structures beneath the northern Appalachians have probably been removed by post-orogenic collapse and/or crustal attenuation associated with the Mesozoic opening of the Atlantic Ocean.