Enticing general engineering undergrads into signal processing with Photo-Editing and image search

The University of Cambridge is unusual in that its Department of Engineering is a single department which covers virtually all branches of engineering under one roof. In their first two years of study, our undergrads study the full breadth of engineering topics and then have to choose a specialization area for the final two years of study. Here we describe part of a course, given towards the end of their second year, which is designed to entice these students to specialize in signal processing and information engineering topics for years 3 and 4. The course is based around a photo editor and an image search application, and it requires no prior knowledge of the z-transform or of 2-dimensional signal processing. It does assume some knowledge of 1-D convolution and basic Fourier methods and some prior exposure to Matlab. The subject of this paper, the photo editor, is written in standard Matlab m-files which are fully visible to the students and help them to see how specific algorithms are implemented in detail. © 2011 IEEE.

High order schemes on three-dimensional general polyhedral meshes - Application to the level set method

In this article, we detail the methodology developed to construct arbitrarily high order schemes - linear and WENO - on 3D mixed-element unstructured meshes made up of general convex polyhedral elements. The approach is tailored specifically for the solution of scalar level set equations for application to incompressible two-phase flow problems. The construction of WENO schemes on 3D unstructured meshes is notoriously difficult, as it involves a much higher level of complexity than 2D approaches. This due to the multiplicity of geometrical considerations introduced by the extra dimension, especially on mixed-element meshes. Therefore, we have specifically developed a number of algorithms to handle mixed-element meshes composed of convex polyhedra with convex polygonal faces. The contribution of this work concerns several areas of interest: the formulation of an improved methodology in 3D, the minimisation of computational runtime in the implementation through the maximum use of pre-processing operations, the generation of novel methods to handle complex 3D mixed-element meshes and finally the application of the method to the transport of a scalar level set. © 2012 Global-Science Press.

Color photometric stereo for multicolored surfaces

We present a multispectral photometric stereo method for capturing geometry of deforming surfaces. A novel photometric calibration technique allows calibration of scenes containing multiple piecewise constant chromaticities. This method estimates per-pixel photometric properties, then uses a RANSAC-based approach to estimate the dominant chromaticities in the scene. A likelihood term is developed linking surface normal, image intensity and photometric properties, which allows estimating the number of chromaticities present in a scene to be framed as a model estimation problem. The Bayesian Information Criterion is applied to automatically estimate the number of chromaticities present during calibration. A two-camera stereo system provides low resolution geometry, allowing the likelihood term to be used in segmenting new images into regions of constant chromaticity. This segmentation is carried out in a Markov Random Field framework and allows the correct photometric properties to be used at each pixel to estimate a dense normal map. Results are shown on several challenging real-world sequences, demonstrating state-of-the-art results using only two cameras and three light sources. Quantitative evaluation is provided against synthetic ground truth data. © 2011 IEEE.

Detecting air pockets for architectural concrete quality assessment using visual sensing

Air pockets, one kind of concrete surface defects, are often created on formed concrete surfaces during concrete construction. Their existence undermines the desired appearance and visual uniformity of architectural concrete. Therefore, measuring the impact of air pockets on the concrete surface in the form of air pockets is vital in assessing the quality of architectural concrete. Traditionally, such measurements are mainly based on in-situ manual inspections, the results of which are subjective and heavily dependent on the inspectors’ own criteria and experience. Often, inspectors may make different assessments even when inspecting the same concrete surface. In addition, the need for experienced inspectors costs owners or general contractors more in inspection fees. To alleviate these problems, this paper presents a methodology that can measure air pockets quantitatively and automatically. In order to achieve this goal, a high contrast, scaled image of a concrete surface is acquired from a fixed distance range and then a spot filter is used to accurately detect air pockets with the help of an image pyramid. The properties of air pockets (the number, the size, and the occupation area of air pockets) are subsequently calculated. These properties are used to quantify the impact of air pockets on the architectural concrete surface. The methodology is implemented in a C++ based prototype and tested on a database of concrete surface images. Comparisons with manual tests validated its measuring accuracy. As a result, the methodology presented in this paper can increase the reliability of concrete surface quality assessment

Defects Detection and Assessment in Concrete Surfaces

Aside from cracks, the impact of other surface defects, such as air pockets and discoloration, can be detrimental to the quality of concrete in terms of strength, appearance and durability. For this reason, local and national codes provide standards for quantifying the quality impact of these concrete surface defects and owners plan for regular visual inspections to monitor surface conditions. However, manual visual inspection of concrete surfaces is a qualitative (and subjective) process with often unreliable results due to its reliance on inspectors’ own criteria and experience. Also, it is labor intensive and time-consuming. This paper presents a novel, automated concrete surface defects detection and assessment approach that addresses these issues by automatically quantifying the extent of surface deterioration. According to this approach, images of the surface shot from a certain angle/distance can be used to automatically detect the number and size of surface air pockets, and the degree of surface discoloration. The proposed method uses histogram equalization and filtering to extract such defects and identify their properties (e.g. size, shape, location). These properties are used to quantify the degree of impact on the concrete surface quality and provide a numerical tool to help inspectors accurately evaluate concrete surfaces. The method has been implemented in C++ and results that validate its performance are presented.

On representing chemical environments

We review some recently published methods to represent atomic neighbourhood environments, and analyse their relative merits in terms of their faithfulness and suitability for fitting potential energy surfaces. The crucial properties that such representations (sometimes called descriptors) must have are differentiability with respect to moving the atoms, and invariance to the basic symmetries of physics: rotation, reflection, translation, and permutation of atoms of the same species. We demonstrate that certain widely used descriptors that initially look quite different are specific cases of a general approach, in which a finite set of basis functions with increasing angular wave numbers are used to expand the atomic neighbourhood density function. Using the example system of small clusters, we quantitatively show that this expansion needs to be carried to higher and higher wave numbers as the number of neighbours increases in order to obtain a faithful representation, and that variants of the descriptors converge at very different rates. We also propose an altogether new approach, called Smooth Overlap of Atomic Positions (SOAP), that sidesteps these difficulties by directly defining the similarity between any two neighbourhood environments, and show that it is still closely connected to the invariant descriptors. We test the performance of the various representations by fitting models to the potential energy surface of small silicon clusters and the bulk crystal.

Direction and polarisation estimation using polarised cylindrical conformal arrays

In this study, the authors describe two-dimensional direction finding and signal polarisation estimation from a cylindrical conformal array consisting of directional and polarised antenna elements. Firstly, a simple and general transformation procedure, based on the mathematical framework of geometric algebra, is presented for arbitrary conformal arrays with polarised and directional antennas. Subsequently, the authors utilise the symmetry of cylindrical arrays to estimate signal parameters via rotational invariance techniques. The authors show how to iteratively estimate the azimuth and elevation angles of the incident signal, as well as its polarisation. To illustrate the versatility of this method, the results of simulations on a 3×4 cylindrical conformal array are shown and discussed. © 2012 The Institution of Engineering and Technology.

The role of the surfaces in the photon absorption in Ge nanoclusters embedded in silica.

The usage of semiconductor nanostructures is highly promising for boosting the energy conversion efficiency in photovoltaics technology, but still some of the underlying mechanisms are not well understood at the nanoscale length. Ge quantum dots (QDs) should have a larger absorption and a more efficient quantum confinement effect than Si ones, thus they are good candidate for third-generation solar cells. In this work, Ge QDs embedded in silica matrix have been synthesized through magnetron sputtering deposition and annealing up to 800°C. The thermal evolution of the QD size (2 to 10 nm) has been followed by transmission electron microscopy and X-ray diffraction techniques, evidencing an Ostwald ripening mechanism with a concomitant amorphous-crystalline transition. The optical absorption of Ge nanoclusters has been measured by spectrophotometry analyses, evidencing an optical bandgap of 1.6 eV, unexpectedly independent of the QDs size or of the solid phase (amorphous or crystalline). A simple modeling, based on the Tauc law, shows that the photon absorption has a much larger extent in smaller Ge QDs, being related to the surface extent rather than to the volume. These data are presented and discussed also considering the outcomes for application of Ge nanostructures in photovoltaics.PACS: 81.07.Ta; 78.67.Hc; 68.65.-k.