Hand Image Segmentation by means of Gaussian Multiscale Aggregation for biometric applications

Applying biometrics to daily scenarios involves demanding requirements in terms of software and hardware. On the contrary, current biometric techniques are also being adapted to present-day devices, like mobile phones, laptops and the like, which are far from meeting the previous stated requirements. In fact, achieving a combination of both necessities is one of the most difficult problems at present in biometrics. Therefore, this paper presents a segmentation algorithm able to provide suitable solutions in terms of precision for hand biometric recognition, considering a wide range of backgrounds like carpets, glass, grass, mud, pavement, plastic, tiles or wood. Results highlight that segmentation accuracy is carried out with high rates of precision (F-measure 88%)), presenting competitive time results when compared to state-of-the-art segmentation algorithms time performance

Gaussian Multiscale Aggregation oriented to Hand Biometric Segmentation in Mobile Devices

New trends in biometrics are oriented to mobile devices in order to increase the overall security in daily actions like bank account access, e-commerce or even document protection within the mobile. However, applying biometrics to mobile devices imply challenging aspects in biometric data acquisition, feature extraction or private data storage. Concretely, this paper attempts to deal with the problem of hand segmentation given a picture of the hand in an unknown background, requiring an accurate result in terms of hand isolation. For the sake of user acceptability, no restrictions are done on background, and therefore, hand images can be taken without any constraint, resulting segmentation in an exigent task. Multiscale aggregation strategies are proposed in order to solve this problem due to their accurate results in unconstrained and complicated scenarios, together with their properties in time performance. This method is evaluated with a public synthetic database with 480000 images considering different backgrounds and illumination environments. The results obtained in terms of accuracy and time performance highlight their capability of being a suitable solution for the problem of hand segmentation in contact-less environments, outperforming competitive methods in literature like Lossy Data Compression image segmentation (LDC).

Gaussian Multiscale Aggregation Applied to Segmentation in Hand Biometrics

This paper presents an image segmentation algorithm based on Gaussian multiscale aggregation oriented to hand biometric applications. The method is able to isolate the hand from a wide variety of background textures such as carpets, fabric, glass, grass, soil or stones. The evaluation was carried out by using a publicly available synthetic database with 408,000 hand images in different backgrounds, comparing the performance in terms of accuracy and computational cost to two competitive segmentation methods existing in literature, namely Lossy Data Compression (LDC) and Normalized Cuts (NCuts). The results highlight that the proposed method outperforms current competitive segmentation methods with regard to computational cost, time performance, accuracy and memory usage.

Performance indices for robotic manipulators: a review of the state of the art

The performance indices are important tools for motion planning and design of robot manipulators. In this paper we present a collection of some of the performance indices that have generated interest in the robotics community. These indices are four different types: kinetostatic performance indices, dynamic performance indices, indices of joint limits, and finally global performance indices. In addition, we review the strategies that have been proposed to solve the problems that occur when the units of the Jacobian matrix elements are not homogeneous. At the end of this paper, we propose a set of global performance indices that can be useful in the design of robot manipulators.

Indices de desempeño de robots manipuladores: una revisión del estado del arte

Los índices de desempeño son importantes herramientas para la planificación de movimientos y el diseño de robots manipuladores. En este trabajo se presenta una colección de algunos de los índices de desempeño que mayor interés han generado en la comunidad dedicada a la robótica. Se presentan índices de desempeño cinetostático, dinámico, de lìmites articulares, e índices definidos sobre el espacio de trabajo. Además, se realiza una revisión sobre las estrategias que se han propuesto para solventar los problemas que aparecen cuando las unidades de los elementos de la matriz Jacobiana no son homogéneas. Al final de este trabajo, proponemos una serie índices de desempeño globales que pueden resultar útiles en el diseño de robots manipuladores.

Determining the effectiveness of three software evaluation techniques through informal aggregation

An accepted fact in software engineering is that software must undergo verification and validation process during development to ascertain and improve its quality level. But there are too many techniques than a single developer could master, yet, it is impossible to be certain that software is free of defects. So, it is crucial for developers to be able to choose from available evaluation techniques, the one most suitable and likely to yield optimum quality results for different products. Though, some knowledge is available on the strengths and weaknesses of the available software quality assurance techniques but not much is known yet on the relationship between different techniques and contextual behavior of the techniques. Objective: This research investigates the effectiveness of two testing techniques ? equivalence class partitioning and decision coverage and one review technique ? code review by abstraction, in terms of their fault detection capability. This will be used to strengthen the practical knowledge available on these techniques.

Hybrid analysis of nonlinear circuits: DAE models with indices zero and one

We extend in this paper some previous results concerning the differential-algebraic index of hybrid models of electrical and electronic circuits. Specifically, we present a comprehensive index characterization which holds without passivity requirements, in contrast to previous approaches, and which applies to nonlinear circuits composed of uncoupled, one-port devices. The index conditions, which are stated in terms of the forest structure of certain digraph minors, do not depend on the specific tree chosen in the formulation of the hybrid equations. Additionally, we show how to include memristors in hybrid circuit models; in this direction, we extend the index analysis to circuits including active memristors, which have been recently used in the design of nonlinear oscillators and chaotic circuits. We also discuss the extension of these results to circuits with controlled sources, making our framework of interest in the analysis of circuits with transistors, amplifiers, and other multiterminal devices.

Dietary and lifestyle quality indices with/without physical activity and markers of insulin resistance in European adolescents: the HELENA study

Resistencia a la insulina en adolescentes

Genetic algorithms and Gaussian Bayesian networks to uncover the predictive core set of bibliometric indices

The diversity of bibliometric indices today poses the challenge of exploiting the relationships among them. Our research uncovers the best core set of relevant indices for predicting other bibliometric indices. An added difficulty is to select the role of each variable, that is, which bibliometric indices are predictive variables and which are response variables. This results in a novel multioutput regression problem where the role of each variable (predictor or response) is unknown beforehand. We use Gaussian Bayesian networks to solve the this problem and discover multivariate relationships among bibliometric indices. These networks are learnt by a genetic algorithm that looks for the optimal models that best predict bibliometric data. Results show that the optimal induced Gaussian Bayesian networks corroborate previous relationships between several indices, but also suggest new, previously unreported interactions. An extended analysis of the best model illustrates that a set of 12 bibliometric indices can be accurately predicted using only a smaller predictive core subset composed of citations, g-index, q2-index, and hr-index. This research is performed using bibliometric data on Spanish full professors associated with the computer science area.

Quantitative analysis of morphological changes in yeast colonies growing on solid medium: the eccentricity and Fourier indices

The colony shape of four yeast species growing on agar medium wasmeasured for 116 days by image analysis. Initially, all the colonies are circular, with regular edges. The loss of circularity can be quantitatively estimated by the eccentricity index, Ei, calculated as the ratio between their orthogonal vertical and horizontal diameters. Ei can increase from 1 (complete circularity) to a maximum of 1.17–1.30, depending on the species. One colony inhibits its neighbour only when it has reached a threshold area. Then, Ei of the inhibited colony increases proportionally to the area of the inhibitory colony. The initial distance between colonies affects those threshold values but not the proportionality, Ei/area; this inhibition affects the shape but not the total surface of the colony. The appearance of irregularities in the edges is associated, in all the species, not with age but with nutrient exhaustion. The edge irregularity can be quantified by the Fourier index, Fi, calculated by the minimum number of Fourier coefficients that are needed to describe the colony contour with 99% fitness. An ad hoc function has been developed in Matlab v. 7.0 to automate the computation of the Fourier coefficients. In young colonies, Fi has a value between 2 (circumference) and 3 (ellipse). These values are maintained in mature colonies of Debaryomyces, but can reach values up to 14 in Saccharomyces.All the species studied showed the inhibition of growth in facing colony edges, but only three species showed edge irregularities associated with substrate exhaustion. Copyright © 2014 John Wiley & Sons, Ltd.

Application of Vegetation Indices to Estimate Acorn Production at Iberian

The Iberian pig valued natural resources of the pasture when fattened in mountain. The variability of acorn production is not contained in any line of Spanish agricultural insurance. However, the production of arable pasture is covered by line insurance number 133 for loss of pasture compensation. This scenario is only contemplated for breeding cows and brave bulls, sheep, goats and horses, although pigs are not included. This insurance is established by monitoring ten-day composites Normalized Difference Vegetation Index (NDVI) measured by satellite over treeless pastures, using MODIS TERRA satellite. The aim of this work is to check if we can use a satellite vegetation index to estimate the production of acorns.

Co-aggregation ability of cell Wall components of Saccharomyces cerevisiae to pathogenic bacteria

Autoaggregation in bacteria is the phenomenon of aggregation between cells of the same strain, whereas coaggregation is due to aggregation occurring among different species. Aggregation ability of prebiotic bacteria is related to adhesion ability, which is a prerequisite for the colonization and protection of the gastrointestinal tract in all animal species; however, coaggregation ability of prebiotic bacteria offers a possibility of close interaction with pathogenic bacteria.