Development of a systematic computer vision-based method to analyse and compare images of false identity documents for forensic intelligence purposes-Part I: acquisition, calibration and validation issues

Following their detection and seizure by police and border guard authorities, false identity and travel documents are usually scanned, producing digital images. This research investigates the potential of these images to classify false identity documents, highlight links between documents produced by a same modus operandi or same source, and thus support forensic intelligence efforts. Inspired by previous research work about digital images of Ecstasy tablets, a systematic and complete method has been developed to acquire, collect, process and compare images of false identity documents. This first part of the article highlights the critical steps of the method and the development of a prototype that processes regions of interest extracted from images. Acquisition conditions have been fine-tuned in order to optimise reproducibility and comparability of images. Different filters and comparison metrics have been evaluated and the performance of the method has been assessed using two calibration and validation sets of documents, made up of 101 Italian driving licenses and 96 Portuguese passports seized in Switzerland, among which some were known to come from common sources. Results indicate that the use of Hue and Edge filters or their combination to extract profiles from images, and then the comparison of profiles with a Canberra distance-based metric provides the most accurate classification of documents. The method appears also to be quick, efficient and inexpensive. It can be easily operated from remote locations and shared amongst different organisations, which makes it very convenient for future operational applications. The method could serve as a first fast triage method that may help target more resource-intensive profiling methods (based on a visual, physical or chemical examination of documents for instance). Its contribution to forensic intelligence and its application to several sets of false identity documents seized by police and border guards will be developed in a forthcoming article (part II).

A measure of stability as a criterion for the verification and analysis of simulation models

The aim of this study is to define a new statistic, PVL, based on the relative distance between the likelihood associated with the simulation replications and the likelihood of the conceptual model. Our results coming from several simulation experiments of a clinical trial show that the PVL statistic range can be a good measure of stability to establish when a computational model verifies the underlying conceptual model. PVL improves also the analysis of simulation replications because only one statistic is associated with all the simulation replications. As well it presents several verification scenarios, obtained by altering the simulation model, that show the usefulness of PVL. Further simulation experiments suggest that a 0 to 20 % range may define adequate limits for the verification problem, if considered from the viewpoint of an equivalence test.

Validation of a computer-assisted system on classifying lower third molars

Objectives: The present study evaluates the reliability of the Radio Memory® software (Radio Memory; Belo Horizonte,Brasil.) on classifying lower third molars, analyzing intra- and interexaminer agreement of the results. Study Design: An observational, descriptive study of 280 lower third molars was made. The corresponding orthopantomographs were analyzed by two examiners using the Radio Memory® software. The exam was repeated 30 days after the first observation by each examiner. Both intra- and interexaminer agreement were determined using the SPSS v 12.0 software package for Windows (SPSS; Chicago, USA). Results: Intra- and interexaminer agreement was shown for both the Pell & Gregory and the Winter classifications, p<0.01, with 99% significant correlation between variables in all the cases. Conclusions: The use of Radio Memory® software for the classification of lower third molars is shown to be a valid alternative to the conventional method (direct evaluation on the orthopantomograph), for both clinical and investigational applications.

Accuracy of computer-aided ultrasound as compared with magnetic resonance imaging in the evaluation of nonalcoholic fatty liver disease in obese and eutrophic adolescents

AbstractObjective:To compare the accuracy of computer-aided ultrasound (US) and magnetic resonance imaging (MRI) by means of hepatorenal gradient analysis in the evaluation of nonalcoholic fatty liver disease (NAFLD) in adolescents.Materials and Methods:This prospective, cross-sectional study evaluated 50 adolescents (aged 11–17 years), including 24 obese and 26 eutrophic individuals. All adolescents underwent computer-aided US, MRI, laboratory tests, and anthropometric evaluation. Sensitivity, specificity, positive and negative predictive values and accuracy were evaluated for both imaging methods, with subsequent generation of the receiver operating characteristic (ROC) curve and calculation of the area under the ROC curve to determine the most appropriate cutoff point for the hepatorenal gradient in order to predict the degree of steatosis, utilizing MRI results as the gold-standard.Results:The obese group included 29.2% girls and 70.8% boys, and the eutrophic group, 69.2% girls and 30.8% boys. The prevalence of NAFLD corresponded to 19.2% for the eutrophic group and 83% for the obese group. The ROC curve generated for the hepatorenal gradient with a cutoff point of 13 presented 100% sensitivity and 100% specificity. As the same cutoff point was considered for the eutrophic group, false-positive results were observed in 9.5% of cases (90.5% specificity) and false-negative results in 0% (100% sensitivity).Conclusion:Computer-aided US with hepatorenal gradient calculation is a simple and noninvasive technique for semiquantitative evaluation of hepatic echogenicity and could be useful in the follow-up of adolescents with NAFLD, population screening for this disease as well as for clinical studies.

Classifier combination for in vivo magnetic resonance spectra of brain tumours

In this paper we present a multi-stage classifier for magnetic resonance spectra of human brain tumours which is being developed as part of a decision support system for radiologists. The basic idea is to decompose a complex classification scheme into a sequence of classifiers, each specialising in different classes of tumours and trying to reproducepart of the WHO classification hierarchy. Each stage uses a particular set of classification features, which are selected using a combination of classical statistical analysis, splitting performance and previous knowledge.Classifiers with different behaviour are combined using a simple voting scheme in order to extract different error patterns: LDA, decision trees and the k-NN classifier. A special label named "unknown¿ is used when the outcomes of the different classifiers disagree. Cascading is alsoused to incorporate class distances computed using LDA into decision trees. Both cascading and voting are effective tools to improve classification accuracy. Experiments also show that it is possible to extract useful information from the classification process itself in order to helpusers (clinicians and radiologists) to make more accurate predictions and reduce the number of possible classification mistakes.

Shared feature extraction for nearest neighbor face recognition

In this paper, we propose a new supervised linearfeature extraction technique for multiclass classification problemsthat is specially suited to the nearest neighbor classifier (NN).The problem of finding the optimal linear projection matrix isdefined as a classification problem and the Adaboost algorithmis used to compute it in an iterative way. This strategy allowsthe introduction of a multitask learning (MTL) criterion in themethod and results in a solution that makes no assumptions aboutthe data distribution and that is specially appropriated to solvethe small sample size problem. The performance of the methodis illustrated by an application to the face recognition problem.The experiments show that the representation obtained followingthe multitask approach improves the classic feature extractionalgorithms when using the NN classifier, especially when we havea few examples from each class

A Hierarchical Approach for Multi-task Logistic Regression

Peer-reviewed

Cinética não-isotérmica na análise térmica de sólidos

In this work, a computer program called Thermal Kinetics was implemented to simulate thermal analysis experiments by numerical integration of the kinetics equations. The computer program was tested in two different examples: non-isothermal transformation of a Cu-Al alloy and non-isothermal decomposition of calcium oxalate monohydrated. In spite of the rather crude approximations of the model, the simulated profiles are very similar to the experimental curves. Both, the dalpha /dt and the dalpha /dT profiles reproduce the experimental transition temperatures with an error smaller than 25%.

Interfície gràfica per a la valoració d'operadors de preprocessat d'imatge en imatges d'ultrasò

El càncer de mama és una de les causes de més mortalitat entreles dones dels països desenvolupats. És tractat d'una maneramés eficient quan es fa una detecció precoç, on les tècniques d'imatge són molt importants. Una de les tècniques d'imatge més utilitzades després dels raigs-X són els ultrasons. A l'hora de fer un processat d'imatges d'ultrasò, els experts en aquest camp es troben amb una sèrie de limitacions en el moment d'utilitzar uns filtrats per les imatges, quan es fa ús de determinades eines. Una d'aquestes limitacions consisteix en la falta d'interactivitat que aquestes ens ofereixen. Per tal de solventar aquestes limitacions, s'ha desenvolupat una eina interactiva que permet explorar el mapa de paràmetres visualitzant el resultat del filtrat en temps real, d'una manera dinàmica i intuïtiva. Aquesta eina s'ha desenvolupat dins l'entorn de visualització d'imatge mèdica MeVisLab. El MeVisLab és un entorn molt potent i modular pel desenvolupament d'algorismes de processat d'imatges, visualització i mètodes d'interacció, especialment enfocats a la imatge mèdica. A més del processament bàsic d'imatges i de mòduls de visualització, inclou algorismes avançats de segmentació, registre i moltes análisis morfològiques i funcionals de les imatges.S'ha dut a terme un experiment amb quatre experts que, utilitzantl'eina desenvolupada, han escollit els paràmetres que creien adientsper al filtrat d'una sèrie d'imatges d'ultrasò. En aquest experiments'han utilitzat uns filtres que l'entorn MeVisLab ja té implementats:el Bilateral Filter, l'Anisotropic Difusion i una combinació d'un filtrede Mediana i un de Mitjana.Amb l'experiment realitzat, s'ha fet un estudi dels paràmetres capturats i s'han proposat una sèrie d'estimadors que seran favorables en la majoria dels casos per dur a terme el preprocessat d'imatges d'ultrasò

Estudio de las técnicas de reconocimiento facial en obras de arte a través de la visión por computador

El objetivo de esta investigación es comprobar la utilidad de las técnicas actuales de reconocimiento facial a través de la visión por computador en entornos museísticos. Para alcanzar este fin, he seguido las estrategias de diseño y creación para crear una aplicación que me permita posteriormente realizar una serie de experimentos, los cuales me proporcionarán los datos necesarios con los que evaluar la funcionalidad de estas técnicas existentes en obras de arte, en mi caso concretamente, sobre cuadros.

Drag force and frictional resistances in vertically vibrated dense granular media

The objective of this thesis is to shed light on the vertical vibration of granular materials for potential interest in the power generation industry. The main focus is investigating the drag force and frictional resistance that influence the movement of a granular material (in the form of glass beads) contained in a vessel, which is subjected to sinusoidal oscillation. The thesis is divided into three parts: theoretical analysis, experiments and computer simulations. The theoretical part of this study presents the underlying physical phenomena of the vibration of granular materials. Experiments are designed to determine fundamental parameters that contribute to the behavior of vibrating granular media. Numerical simulations include the use of three different software applications: FLUENT, LS-DYNA and ANSYS Workbench. The goal of these simulations is to test theoretical and semiempirical models for granular materials in order to validate their compatibility with the experimental findings, to assist in predicting their behavior, and to estimate quantities that are hard to measure in laboratory.

Role of Selected Spectral Attributes in the Perception of Synthetic Vowels

This thesis is an experimental study regarding the identification and discrimination of vowels, studied using synthetic stimuli. The acoustic attributes of synthetic stimuli vary, which raises the question of how different spectral attributes are linked to the behaviour of the subjects. The spectral attributes used are formants and spectral moments (centre of gravity, standard deviation, skewness and kurtosis). Two types of experiments are used, related to the identification and discrimination of the stimuli, respectively. The discrimination is studied by using both the attentive procedures that require a response from the subject, and the preattentive procedures that require no response. Together, the studies offer information about the identification and discrimination of synthetic vowels in 15 different languages. Furthermore, this thesis discusses the role of various spectral attributes in the speech perception processes. The thesis is divided into three studies. The first is based only on attentive methods, whereas the other two concentrate on the relationship between identification and discrimination experiments. The neurophysiological methods (EEG recordings) reveal the role of attention in processing, and are used in discrimination experiments, while the results reveal differences in perceptual processes based on the language, attention and experimental procedure.