3D Experimental investigation of the hygro-mechanical behaviour of wood at cellular and sub-cellular scale: detection of local deformations

The swelling/shrinkage of spruce wood samples (Picea Abies) is documented with high resolution XRay Tomography and advanced image analysis tools. We report the reversible moisture-induced global and local deformations at the cellular and sub-cellular scales. In particular, we present sophisticated methods for detecting local deformations in the cell wall. Insight is given on the hygromechanical behaviour of wood cell material and on the role of ultra-cellular components in wood, such as bordered pits and rays

Zero-Crossing Statistics for Non-Markovian Time Series

In applications spaning from image analysis and speech recognition, to energy dissipation in turbulence and time-to failure of fatigued materials, researchers and engineers want to calculate how often a stochastic observable crosses a specific level, such as zero. At first glance this problem looks simple, but it is in fact theoretically very challenging. And therefore, few exact results exist. One exception is the celebrated Rice formula that gives the mean number of zero-crossings in a fixed time interval of a zero-mean Gaussian stationary processes. In this study we use the so-called Independent Interval Approximation to go beyond Rice's result and derive analytic expressions for all higher-order zero-crossing cumulants and moments. Our results agrees well with simulations for the non-Markovian autoregressive model

Dynamic Block-Based Parameter Estimation for MRF Classification of High-Resolution Images

International audienceA Markov random field is a graphical model that is commonly used to combine spectral information and spatial context into image classification problems. The contributions of the spatial versus spectral energies are typically defined by using a smoothing parameter, which is often set empirically. We propose a new framework to estimate the smoothing parameter. For this purpose, we introduce the new concepts of dynamic blocks and class label co-occurrence matrices. The estimation is then based on the analysis of the balance of spatial and spectral energies computed using the spatial class co-occurrence distribution and dynamic blocks. Moreover, we construct a new spatially weighted parameter to preserve the edges, based on the Canny edge detector. We evaluate the performance of the proposed method on three data sets: a multispectral DigitalGlobe WorldView-2 and two hyperspectral images, recorded by the AVIRIS and the ROSIS sensors, respectively. The experimental results show that the proposed method succeeds in estimating the optimal smoothing parameter and yields higher classification accuracies when compared to the state-of-the-art methods

Computer vision techniques applied to the quality control of ceramic plates

This paper presents a system, based on computer vision techniques, that detects and quantifies different types of defects in ceramic plates. It was developed in collaboration with the industrial ceramic sector and consequently it was focused on the defects that are considered more quality depreciating by the Portuguese industry. They are of three main types: cracks; granules and relief surface. For each type the development was specific as far as image processing techniques and illumination are concerned. The system was tested in pre industrial conditions showing the efficiency of the several developed algorithms and also revealing the perspective of its evolution to an industrial automatic inspection system

PILOT: Password and PIN Information Leakage from Obfuscated Typing Videos

This paper studies leakage of user passwords and PINs based on observations of typing feedback on screens or from projectors in the form of masked characters that indicate keystrokes. To this end, we developed an attack called Password and Pin Information Leakage from Obfuscated Typing Videos (PILOT). Our attack extracts inter-keystroke timing information from videos of password masking characters displayed when users type their password on a computer, or their PIN at an ATM. We conducted several experiments in various attack scenarios. Results indicate that, while in some cases leakage is minor, it is quite substantial in others. By leveraging inter-keystroke timings, PILOT recovers 8-character alphanumeric passwords in as little as 19 attempts. When guessing PINs, PILOT significantly improved on both random guessing and the attack strategy adopted in our prior work [4]. In particular, we were able to guess about 3% of the PINs within 10 attempts. This corresponds to a 26-fold improvement compared to random guessing. Our results strongly indicate that secure password masking GUIs must consider the information leakage identified in this paper

The recognition and modelling of a backbone and its deformity

In this article the authors present a method for the backbone recognition and modelling. The process of recognition combines some classical techniques (Hough transformation, GVF snakes) with some new (authors present a method for initial curvature detection, which they call the Falling Ball method). The result enables us to identify high-quality features of the spine and to detect the major deformities of backbone: the intercrestal line, centre sacral vertical line, C7 plumbline; as well as angles: proximal thoracic curve, main thoracic curve, thoracolumbar/lumbar. These features are used for measure in adolescent idiopathic scoliosis, especially in the case of treatment. Input data are just radiographic images, meet in everyday practice