Dissimilarity Measures for Visual Pattern Partitioning

This version of the article has been accepted for publication, after peer review (when applicable) and is subject to Springer Nature’s AM terms of use, but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: http://dx.doi.org/10.1007/11492542_36We define a visual pattern as an image feature with frequency components in a range of bands that are aligned in phase. A technique to partition an image into its visual patterns involves clustering of the band-pass filtered versions of the image according to a measure of congruence in phase or, equivalently, alignment in the filter’s responses energy maxima. In this paper we study some measures of dissimilarity between images and discuss their suitability to the specific task of misalignment estimation between energy maps.The authors desire to acknowledge the Xunta de Galicia for their financial support of this work by means of the research project PGIDIT04TIC206005PR

Decomposition of 3D Medical Images into Visual Patterns

In this paper, we present a method for the decomposition of a volumetric image into its most relevant visual patterns , which we define as features associated to local energy maxima of the image. The method involves the clustering of a set of predefined bandpass energy filters according to their ability to segregate the different features in the image, thus generating a set of composite-feature detectors tuned to the specific visual patterns present in the data. Clustering is based on a measure of statistical dependence between pairs of frequency features. We will illustrate the applicability of the method to the initialization of a three-dimensional geodesic active model.This work was supported in part by the Xunta de Galicia under Grant PGIDIT04TIC206005PR2007-11-21S

Data-driven synthesis of composite-feature detectors for 3D image analysis

Most image analysis techniques are based upon low level descriptions of the data. It is important that the chosen representation is able to discriminate as much as possible among independent image features. In particular, this is of great importance in segmentation with deformable models, which must be guided to the target object boundary avoiding other image features. In this paper, we present a multiresolution method for the decomposition of a volumetric image into its most relevant visual patterns, which we define as features associated to local energy maxima of the image. The method involves the clustering of a set of predefined band-pass energy filters according to their ability to segregate the different features in the image. In this way, the method generates a set of composite-feature detectors tuned to the specific visual patterns present in the data. Clustering is accomplished by defining a distance metric between the frequency features that reflects the degree of alignment of their energy maxima. This distance is related to the mutual information of their responses' energy maps. As will be shown, the method is able to isolate the frequency components of independent visual patterns in 3D images. We have applied this composite-feature detection method to the initialization of active models. Among the visual patterns detected, those associated to the segmentation target are selected by user interaction to define the initial state of a geodesic active model. We will demonstrate that this initialization technique facilitates the evolution of the model to the proper boundary.S

Motion representation using composite energy features

This work tackles the segmentation of apparent-motion from a bottom-up perspective. When no information is available to build prior high-level models, the only alternative are bottom-up techniques. Hence, the whole segmentation process relies on the suitability of the low-level features selected to describe motion. A wide variety of low-level spatio-temporal features have been proposed so far. However, all of them suffer from diverse drawbacks. Here, we propose the use of composite energy features in bottom-up motion segmentation to solve several of these problems. Composite energy features are clusters of energy filters—pairs of band-pass filters in quadrature—each one sensitive to a different set of scale, orientation, direction of motion and speed. They are grouped in order to reconstruct independent motion patterns in a video sequence. A composite energy feature, this is, the response of one of these clusters of filters, can be built as a combination of the responses of the individual filters. Therefore, it inherits the desirable properties of energy filters but providing a more complete representation of motion patterns. In this paper, we will present our approach for integration of composite features based on the concept of Phase Congruence. We will show some results that illustrate the capabilities of this low-level motion representation and its usefulness in bottom-up motion segmentation and tracking.This work has been financially supported by the Ministry of Education and Science of the Spanish Government, through the Research Project TIN2006-08447.S

An automated design methodology of RF circuits by using Pareto-optimal fronts of EMsimulated inductors

A new design methodology for radiofrequency circuits is presented that includes electromagnetic (EM) simulation of the inductors into the optimization flow. This is achieved by previously generating the Pareto-optimal front (POF) of the inductors using EM simulation. Inductors are selected from the Pareto front and their S-parameter matrix is included in the circuit netlist that is simulated using an RF simulator. Generating the EM-simulated POF of inductors is computationally expensive, but once generated, it can be used for any circuit design. The methodology is illustrated both for a singleobjective and a multiobjective optimization of a low noise amplifierMinisterio de Economía y Competitividad TEC2013-45638-C3-3-R, TEC2013-40430-RJunta de Andalucía PIC12-TIC-1481Consejo Superior de Investigaciones Científicas 201350E05

OBIA System for Identifying Mesoscale Oceanic Structures in SeaWiFS and MODIS-Aqua Images

The ocean covers over 70% of the surface of our planet and plays a key role in the global climate. Most ocean circulation is mesoscale (scales of 50–500 km and 10–100 days), and the energy in mesoscale circulation is at least one order of magnitude greater than general circulation; therefore, the study of mesoscale oceanic structures (MOS) is crucial to ocean dynamics, making it especially useful for analyzing global changes. The detection of MOS, such as upwellings or eddies, from satellites images is significant for marine environmental studies and coastal resource management. In this paper, we present an object-based image analysis (OBIA) system which segments and classifies regions contained in sea-viewing field-of-view sensor (SeaWiFS) and Moderate Resolution Imaging Spectro-radiometer (MODIS)-Aqua sensor satellite images into MOS. After color clustering and hierarchical data format (HDF) file processing, the OBIA system segments images and extracts image descriptors, producing primary regions. Then, it merges regions, recalculating image descriptors for MOS identification and definition. First, regions are labeled by a human-expert, who identifies MOS: upwellings, eddies, cool, and warm eddies. Labeled regions are then classified by learning algorithms (i.e., decision tree, Bayesian network, artificial neural network, genetic algorithm, and near neighbor algorithm) from selected features. Finally, the OBIA system enables images to be queried from the user interface and retrieved by means of fuzzy descriptors and oceanic structures. We tested our system with images from the Canary Islands and the North West African coast

A location-based approach to the classification of mesoscale oceanic structures in SeaWiFS and Aqua-MODIS images of Northwest Africa

This study presents a different approach to the classification of Mesoscale Oceanic Structures (MOS) present in the Northwest African area, based on their location. The main improvement stems from the partition of this area in four large zones perfectly differentiated by their morphological characteristics, with attention to seafloor topography and coastal relief. This decomposition makes it easier to recognize structures under adverse conditions, basically the presence of clouds partly hiding them. This is observed particularly well in upwellings, which are usually very large structures with a different morphology and genesis in each zone. This approach not only improves the classification of the upwellings, but also makes it possible to analyse changes in the MOS over time, thereby improving the prediction of its morphological evolution. To identify and label the MOS classified in the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) and Aqua-MODIS (Moderate Resolution Imaging Spectroradiometer) chlorophyll-a and temperature images, we used a tool specifically designed by our group for this purpose and which has again shown its validity in this new proposal

High-temperature superconducting fault current microlimiters

High-temperature superconducting microbridges implemented with YBa(2)Cu(3)O(7-delta) thin-films are shown to be possible fault current limiters for microelectronic devices with some elements working at temperatures below the superconducting critical temperature and, simultaneously, under very low power conditions (below 1W). This is the case in the important applications of superconductors as SQUID based electronics, and technologies for communication or infrared detectors. In this paper it is shown that the good thermal behavior of these microlimiters allows working in a regime where even relatively small faults induce their transition to highly dissipative states, dramatically increasing their limitation efficiency. The conditions for optimal refrigeration and operation of these microlimiters are also proposed.Comment: 10 pages, 3 figures. LaTeX and EPS file

Análisis de las actividades del programa Clic en contextos de enseñanza-aprendizaje

En este trabajo, examinamos uno de los programas utilizados por el profesorado: el Clic. Una herramienta de creación de actividades educativas multimedia para alumnos. Además de describirlo, dando cuenta de sus características técnicas, potencialidades, posibles usos y su valor pedagógico con relación a otros recursos didácticos (en especial el libro de texto), nos centramos en un caso concreto: un centro educativo de primaria. En este estudio de caso, enmarcado en una investigación más amplia, analizamos los modos o las experiencias de utilización de las actividades del Clic. Experiencias en este caso desarrolladas tanto en aulas ordinarias como en aulas específicas (aulas de informática). La información de la que disponemos para el análisis de estas experiencias ha sido recogida mediante entrevistas formales e informales, observación participante y no participante, notas de campo, informes y diarios de campo, etc.En aquest treball examinem un dels programes utilitzats pel professorat: el Clic. Una eina de creació d'activitats educatives multimèdia per a alumnes. A més de descriure'l, oferint les seves característiques tècniques, potencialitats, possibles usos i el seu valor pedagògic en relació amb altres recursos didàctics (especialment el llibre de text), ens centrem en un cas concret: un centre educatiu de primària. En aquest estudi de cas, emmarcat en una investigació més àmplia, vam analitzar les maneres o experiències d'utilització de les activitats del Clic. Experiències en aquest cas desenvolupades tant en aules ordinàries com en aules específiques (aules d'informàtica). La informació de la qual disposem per a l'anàlisi d'aquestes experiències ha estat recollida mitjançant entrevistes formals i informals, observació participant i no participant, notes de camp, informes i diaris de camp, etc.Along this article, we examine one of the computer programmes used by teachers: Clic. This is a tool for creating multimedia educational activities for students. Apart from describing this programme -specifying its technical characteristics, potentialities, possible uses and its pedagogical value in relation to other didactic resources (particularly the text book)- we refer to a concrete case in a Primary School. In this case study, which is part of a broader research, we analyse the ways or experiences of use of the Clic activities. These experiences take place both in mainstream classrooms and specific classrooms (computer classrooms). The information we have for the analysis of these experiences was obtained out of formal and informal interviews, participant and non-participant information, field notes, reports and field diaries, etc

May the NAO index be used to forecast rain in Spain?

This paper studies the influence of the North Atlantic Oscillation (NAO) on monthly, seasonal and annual precipitation regimes in continental Spain. The data used for this study include the monthly rain series of 325 meteorological stations distributed homogeneously over the study zone, and the monthly NAO indices from 1961 to 1998. A total of 5525 rain series were employed for the analysis. Simple and multiple linear correlations were established between these variables in different combinations. The main aim was to check whether monthly, seasonal or annual precipitation data could be predicted using earlier precipitation data and the NAO index. The geographical areas where the stations have shown a statistically significant correlation have been represented on maps. The results differ depending on the correlation, but, in general, the best results have been found in the fall and winter months. Finally, a practical application of the method was carried out in the Ebro Valley and it was observed that the combination of the NAO index for spring and summer and the precipitation registered in those two seasons may be useful to forecast rain in the fall.Este trabajo estudia la influencia de la Oscilación del Atlántico Norte (NAO) en el régimen de precipitaciones mensuales, estacionales y anuales de la España Peninsular. Para ello se han utilizado los datos mensuales de precipitación de 325 estaciones pluviométricas repartidas homogéneamente y los índices mensuales del índice NAO desde 1961 a 1998; se han usado un total de 5525 series de precipitación. El estudio se ha realizado mediante correlaciones lineales simples o múltiples entre estas variables utilizando diferentes combinaciones. Se trata de ver si se podría predecir la precipitación mensual, estacional o bien anual a partir de datos previos de precipitación y del índice NAO. Se han representado espacialmente las zonas geográficas cuyos observatorios manifiestan una correlación estadísticamente significativa. Los resultados difieren del tipo de correlación elegido, pero en general los mejores resultados se encuentran en los meses de invierno. Por último, se ha aplicado esta metodología al Valle del Ebro y se ha observado que una combinación del índice NAO de primavera y verano, junto con la precipitación registrada en esas dos estaciones podría ser útil para predecir la precipitación de otoño.publishe