Improving Texture Categorization with Biologically Inspired Filtering

Within the domain of texture classification, a lot of effort has been spent on local descriptors, leading to many powerful algorithms. However, preprocessing techniques have received much less attention despite their important potential for improving the overall classification performance. We address this question by proposing a novel, simple, yet very powerful biologically-inspired filtering (BF) which simulates the performance of human retina. In the proposed approach, given a texture image, after applying a DoG filter to detect the "edges", we first split the filtered image into two "maps" alongside the sides of its edges. The feature extraction step is then carried out on the two "maps" instead of the input image. Our algorithm has several advantages such as simplicity, robustness to illumination and noise, and discriminative power. Experimental results on three large texture databases show that with an extremely low computational cost, the proposed method improves significantly the performance of many texture classification systems, notably in noisy environments. The source codes of the proposed algorithm can be downloaded from https://sites.google.com/site/nsonvu/code.Comment: 11 page

Toughening and hardening in double-walled carbon nanotube/nanostructured magnesia composites

Dense double-walled carbon nanotube (DWCNT)/nanostructured MgO composites were prepared using an in situ route obviating any milling step for the synthesis of powders and consolidation by spark-plasma-sintering. An unambiguous increase in both toughness and microhardness is reported. The mechanisms of crack-bridging on an unprecedented scale, crack-deflection and DWCNT pullout have been evidenced. The very long DWCNTs, which appear to be mostly undamaged, are very homogeneously dispersed at the grain boundaries of the matrix, greatly inhibiting the grain growth during sintering. These results arise because the unique microstructure (low content of long DWCNTs, nanometric matrix grains and grain boundary cohesion) provides the appropriate scale of the reinforcement to make the material tough

Facial image processing

[No abstract available

PixelTrack: A Fast Adaptive Algorithm for Tracking Non-rigid Objects

International audienceIn this paper, we present a novel algorithm for fast tracking of generic objects in videos. The algorithm uses two components: a detector that makes use of the generalised Hough transform with pixel-based descriptors, and a probabilistic segmentation method based on global models for foreground and background. These components are used for tracking in a combined way, and they adapt each other in a co-training manner. Through effective model adaptation and segmentation, the algorithm is able to track objects that undergo rigid and non-rigid deformations and considerable shape and appearance variations. The proposed tracking method has been thoroughly evaluated on challenging standard videos, and outperforms state-of-theart tracking methods designed for the same task. Finally, the proposed models allow for an extremely efficient implementation, and thus tracking is very fast

Spark-plasma-sintering of double-walled carbon nanotube–magnesia nanocomposites

A double-walled carbon nanotube–MgO powder is prepared without any mixing. The applied pressure is the main parameter acting on densification. Increasing the maximum temperature and holding time is marginally beneficial. The nanotubes are blocking the matrix grain growth. The nanocomposite prepared using the most severe spark plasma sintering conditions (1700 °C, 150 MPa) shows mostly undamaged nanotubes and a higher microhardness than the other materials, reflecting a better bonding between nanotubes and matrix. The electrical conductivity of all nanocomposites is over 12 S/cm

Synthesis of Fe-ZrO2 nanocomposite powders by reduction in H2 of a nanocrystalline (Zr, Fe)O2 solid solution

The formation of Fe-ZrO2 nanocomposite powders by reduction in hydrogen of a nanocrystalline totally stabilized Zr0.9Fe0.1O1.95 solid solution was investigated by X-ray diffraction (XRD), field-emission-gun scanning electron microscopy (FEG-SEM) and Mössbauer spectroscopy. The reduction of the stabilized Zr0.9Fe0.1O1.95 solid solution and the formation of metallic particles precedes the transformation of zirconia into the monoclinic phase, which becomes the major zirconia phase upon reduction at 950 °C. α-Fe particles with a size distribution slightly increasing from 10–50 to 20–70 nm upon the increase in reduction temperature are observed and a second population of smaller (<5 nm) γ-Fe nanoparticles is also noticed when the reduction is performed at 1000 °C. Another metallic phase with a hyperfine field of not, vert, similar200 kOe at RT (not, vert, similar250 kOe at 80 K) is detected, which could account for an Fe/Zr phase. It could be formed by the reduction on an Fe2+-rich transient phase incorporating a small fraction of the Zr4+ ions, formed by a phase partitioning process superimposed to the reduciton processes

The exchanges on the coastline of the southern Gaul in the first Iron Age: from “Hellenisation” concept to “Mediterraneisation”

International audienc

Conduite d'un Robot Mobile Opto-guidé Par Logiciels Temps-Réel Open-Source Démonstrateur du projet RNTL Cléopatre

National audienceLe travail présenté ici a été réalisé dans le cadre du projet Cléopatre1, projet national de R&D dans le domaine des technologies logicielles dédiées aux applications temps-réel, terminé en juin 2005. Ce projet avait pour finalité la conception d'un système d'exploitation temps réel baptisé « système Cléopatre » à code source ouvert, gratuit et téléchargeable à partir d'un site public de façon à en faciliter la diffusion. Ce système d'exploitation temps réel a la particularité de se présenter sous forme d'un assemblage de composants sélectionnables par l'utilisateur. Ces derniers peuvent être définis comme des briques logicielles disponibles sur les étagères d'une bibliothèque et implémentant des mécanismes novateurs principalement issus de la recherche en ordonnancement temps réel. Nous présentons le démonstrateur de ce projet, un AGV (Automated Guided Vehicle) conduit en temps-réel par l'O.S. Cléopatre. L'objectif était d'évaluer ses performances d'un point de vue temporel, le gain engendré par l'approche composant en termes d'empreinte mémoire et d'accessibilité mais aussi vérifier l'inter-opérabilité des composants logiciels développés. L'application mise en œuvre consiste à conduire cet AGV opto-guidé muni de son informatique embarquée, en exécutant en temps-réel des ordres de mission émis par une liaison sans fil à partir d'une station de supervision