Reconocimiento de objetos multi-clase basado en descriptores de forma

Este trabajo presenta un sistema para detectar y clasificar objetos binarios según la forma de éstos. En el primer paso del procedimiento, se aplica un filtrado para extraer el contorno del objeto. Con la información de los puntos de forma se obtiene un descriptor BSM con características altamente descriptivas, universales e invariantes. En la segunda fase del sistema se aprende y se clasifica la información del descriptor mediante Adaboost y Códigos Correctores de Errores. Se han usado bases de datos públicas, tanto en escala de grises como en color, para validar la implementación del sistema diseñado. Además, el sistema emplea una interfaz interactiva en la que diferentes métodos de procesamiento de imágenes pueden ser aplicados.

Shape complexity based on mutual information

Shape complexity has recently received attention from different fields, such as computer vision and psychology. In this paper, integral geometry and information theory tools are applied to quantify the shape complexity from two different perspectives: from the inside of the object, we evaluate its degree of structure or correlation between its surfaces (inner complexity), and from the outside, we compute its degree of interaction with the circumscribing sphere (outer complexity). Our shape complexity measures are based on the following two facts: uniformly distributed global lines crossing an object define a continuous information channel and the continuous mutual information of this channel is independent of the object discretisation and invariant to translations, rotations, and changes of scale. The measures introduced in this paper can be potentially used as shape descriptors for object recognition, image retrieval, object localisation, tumour analysis, and protein docking, among others

Role of Particle Shape on the Stress Propagation in Granular Packings

We present an experimental and numerical study on the influence that particle aspect ratio has on the mechanical and structural properties of granular packings. For grains with maximal symmetry (squares), the stress propagation in the packing localizes forming chainlike forces analogous to the ones observed for spherical grains. This scenario can be understood in terms of stochastic models of aggregation and random multiplicative processes. As the grains elongate, the stress propagation is strongly affected. The interparticle normal force distribution tends toward a Gaussian, and, correspondingly, the force chains spread leading to a more uniform stress distribution reminiscent of the hydrostatic profiles known for standard liquids

Predictability of music descriptor time series and its application to cover song detection

Intuitively, music has both predictable and unpredictable components. In this work we assess this qualitative statement in a quantitative way using common time series models fitted to state-of-the-art music descriptors. These descriptors cover different musical facets and are extracted from a large collection of real audio recordings comprising a variety of musical genres. Our findings show that music descriptor time series exhibit a certain predictability not only for short time intervals, but also for mid-term and relatively long intervals. This fact is observed independently of the descriptor, musical facet and time series model we consider. Moreover, we show that our findings are not only of theoretical relevance but can also have practical impact. To this end we demonstrate that music predictability at relatively long time intervals can be exploited in a real-world application, namely the automatic identification of cover songs (i.e. different renditions or versions of the same musical piece). Importantly, this prediction strategy yields a parameter-free approach for cover song identification that is substantially faster, allows for reduced computational storage and still maintains highly competitive accuracies when compared to state-of-the-art systems.

Micropatterning of single endothelial cell shape reveals a tight coupling between nuclear volume in G1 and proliferation

Shape-dependent local differentials in cell proliferation are considered to be a major driving mechanism of structuring processes in vivo, such as embryogenesis, wound healing, and angiogenesis. However, the specific biophysical signaling by which changes in cell shape contribute to cell cycle regulation remains poorly understood. Here, we describe our study of the roles of nuclear volume and cytoskeletal mechanics in mediating shape control of proliferation in single endothelial cells. Micropatterned adhesive islands were used to independently control cell spreading and elongation. We show that, irrespective of elongation, nuclear volume and apparent chromatin decondensation of cells in G1 systematically increased with cell spreading and highly correlated with DNA synthesis (percent of cells in the S phase). In contrast, cell elongation dramatically affected the organization of the actin cytoskeleton, markedly reduced both cytoskeletal stiffness (measured dorsally with atomic force microscopy) and contractility (measured ventrally with traction microscopy), and increased mechanical anisotropy, without affecting either DNA synthesis or nuclear volume. Our results reveal that the nuclear volume in G1 is predictive of the proliferative status of single endothelial cells within a population, whereas cell stiffness and contractility are not. These findings show that the effects of cell mechanics in shape control of proliferation are far more complex than a linear or straightforward relationship. Our data are consistent with a mechanism by which spreading of cells in G1 partially enhances proliferation by inducing nuclear swelling and decreasing chromatin condensation, thereby rendering DNA more accessible to the replication machinery.

Entropy change of martensitic transformations in Cu-based shape-memory alloys

We have investigated the different contributions to the entropy change at the martensitic transition of different families of Cu-based shape-memory alloys. The total entropy change has been obtained through calorimetric measurements. By measuring the evolution of the magnetic susceptibility with temperature, the entropy change associated with conduction electrons has been evaluated. The contribution of the anharmonic vibrations of the lattice has also been estimated using various parameters associated with the anharmonic behavior of these alloys, collected from the literature. The results found in the present work have been compared to values published for the martensitic transition of group-IV metals. For Cu-based alloys, both electron and anharmonic contributions have been shown to be much smaller than the overall entropy change. This finding demonstrates that the harmonic vibrations of the lattice are the most relevant contribution to the stability of the bcc phase in Cu-based alloys.

Vibrational behaviour of bcc Cu-based shape memory alloys close to the martensitic transition

Experimental data from ultrasonic and inelastic neutron scattering measurements are analyzed for different families of Cu-based shape-memory alloys. It is shown that the transition occurs at a value, independent of composition and alloy family, of the ratio between the elastic constants associated with the two shears necessary to accomplish the lattice distortion from the bcc to the close-packed structure. The zone boundary frequency of the TA2[110] branch evaluated at the transition point (TM), weakly depends, for each family, on composition. A linear relationship between this frequency and the inverse of the elastic constant C', both quantities evaluated at TM, has been found, in agreement with the prediction of a Landau model proposed for martensitic transformations.

On the stability of the bcc phase in Cu-Al-Mn shape memory alloys

Measurements of the entropy change at the martensitic transition of two composition-related sets of Cu-Al-Mn shape-memory alloys are reported. It is found that most of the entropy change has a vibrational origin, and depends only on the particular close-packed structure of the low-temperature phase. Using data from the literature for other Cu-based alloys, this result is shown to be general. In addition, it is shown that the martensitic structure changes from 18R to 2H when the ratio of conduction electrons per atom reaches the same value as the eutectoid point in the equilibrium phase diagram. This finding indicates that the structure of the metastable low-temperature phase is reminiscent of the equilibrium structure.