Eric Pirard

Multispectral imaging of ore minerals in optical microscopy

Abstract Multispectral imaging of ore minerals under the microscope is a logical extension of quantitative colour analysis and microspectrophotometric analysis of minerals. This paper describes, step by step, how the proper calibration of a scientific video camera can be performed in order to obtain precise reflectance measurements at each pixel within the field of view. After having reviewed the different sources of noise and aberration, practical formulae are presented that allow for the acquisition of a set of images at different wavelengths in the visible spectrum. The advantage of using a multispectral image acquisition system based on narrow bandwidth (10 nm) interference filters is discussed and quantitatively compared to colour imaging using tristimulus (red, green, blue) filters. Images taken from major sulphide parageneses are shown as examples of well contrasted multispectral images. Finally, the potential for automatic identification of ore minerals is discussed with reference to supervised multivariate image classification algorithms similar to those used in remote sensing. Additional comments on extending the principles for handling optical anisotropy and developing a multiradial imaging system are made.

Application and processing of geophysical images for mapping faults

This paper describes the application of geophysical prospecting techniques to locate the active faults in superficial Quaternary sediments. Both electrical tomography and seismic refraction tomography presented here were part of a geophysical campaign performed in the Roer Graben area as a reconnaissance tool before trenching for paleoseismological observations. The aim of this investigation was, in the first place, to determine the exact position of the active fault in order to determine the best emplacement of a later trench. An additional objective was to image the fault zone at shallow depth, allowing both a comparison with trench data, and a downward extrapolation of these direct observations. Both methods proved to be successful but generated relatively smooth images with a poor spatial resolution that were prone to a subjective interpretation by the operators. In order to restrict the interpretation of tomographies with quantitative measures of gradients, image analysis techniques were tested. This paper presents some preliminary results obtained on the use of crest line location methods issued from mathematical morphology. Synthetic models of simple resistivity anomalies along a faulted section were used to check the reliability of the image processing method.

Automatic landslide detection from remote sensing images using supervised classification methods

The creation of a landslide inventory map by manual interpretation of remote sensing images is very time-consuming. This study aims at developing an automated procedure for the detection of landslides from multi-spectral remote sensing images. According to the type of landslide, the parameters for detecting the slope instabilities will differ. In a first step, predefined input parameters derived from the images are incorporated in a supervised pixel classification algorithm. In this study, we use a maximum likelihood classification method, which shows positive preliminary results. In order to evaluate the accuracy and applicability of the method, the results are compared with ANN classification. Segmentation of the output image (containing likelihood values to be a landslide) into landslide and non-landslide areas is conducted by using the double threshold technique in combination with a histogram-based thresholding. Additional filtering of the detected blobs based on shape and geomorphologic properties allows to eliminate spurious areas. Validation of the results is done by comparison with manually defined landslides.

Testing for Sources of Errors in Quantitative Image Analysis

Because image analysis is subject to errors, this chapter advocates for the systematic performance of quality controls of the results. Errors can be reduced to a minimum, but to do so it is necessary to identify their cause. Since an image is the result of a long series of sampling and operations, many factors can introduce error. Each parameter can be tested by slightly varying that parameter while maintaining the other constant and monitoring their impact on the final measurement. Preparation (or acquisition) errors are easy to test but require performing some empirical trials. Integration errors (or sampling errors) can be substantially limited if basic rules are respected (Table 6). Analysis errors (or errors due to processing the images) require that the transformation applied to the image is fully understood by the operator. There is a great risk of bias if a processing algorithm is used as a magic black box. Finally, efforts should also be made to try to validate the results with external methods and correctly educate geoscientists in image processing and analysis.

Spreading segregation of blended fertilizers : influence of particles properties

The blending of solid granular fertilizers produces an almost infinite range of compounds with some raw materials. These can be specifically matched to a farmers needs at a reasonable cost. The main problem is that the blended fertilizers are exposed to the risk of segregation. With granular materials, the differences in physical properties can lead to the segregation of the particles. This study aims at analyzing and quantifying the particles influence on segregation during spreading of blended fertilizers. The experiment consisted of mixing two raw materials that differed by one characteristic: the size, the density, or the shape. The physical properties of each raw material were carefully measured. Twenty-six blends were spread on the field with a centrifugal spreader and samples were collected in order to measure segregation. The proportion of each component was calculated with the chemical content of the raw materials and blended samples. Two coefficients of segregation were determined. Great segregation in some cases was observed. The original proportion of 50% for each component can become 30/70 on the field. The analysis of the influence of each parameter shows that major effects occur with a difference of size and density. The influence of shape is minimal. A relationship was proposed between the differences of physical properties of the blend components and the spreading segregation.

Shape simulation of granular particles in concrete and applications in DEM

ABSTRACT Aggregate occupies at least three-quarters of the volume of concrete, so its impact on concrete’s properties is large. The sieve curve traditionally defines the aggregate size range. Another essential property is grain shape. Both, size and shape influence workability and the mechanical and durability properties of concrete. On the other hand, the shape of cement particles plays also an important role in the hydration process due to surface dissolution in the hardening process. Additionally, grain dispersion, shape and size govern the pore percolation process that is of crucial importance for concrete durability Discrete element modeling (DEM) is commonly employed for simulation of concrete structure. To be able doing so, the assessed grain shape should be implemented. The approaches for aggregate and cement structure simulation by a concurrent algorithm-based DEM system are discussed in this paper. Both aggregate and cement were experimentally analyzed by X-ray tomography method recently. The results provide a real experimental database, e.g. surface area versus volume distribution, for simulation of particles in concrete technology. Optimum solutions are obtained by different simplified shapes proposed for aggregate and cement, respectively. In this way, reliable concepts for aggregate structure and fresh cement paste can be simulated by a DEM system.

On the Shape Simulation of Aggregate and Cement Particles in a DEM System

Aggregate occupies at least three-quarters of the volume of concrete, so its impact on concrete’s properties is significant. Both size and shape of aggregate influence workability, mechanical properties, and durability of concrete. On the other hand, the shape of cement particles plays also an important role in the hydration process due to surface dissolution in the hardening process. Additionally, grain dispersion, shape, and size govern the pore percolation process that is of crucial importance for concrete durability. Discrete element modeling (DEM) is commonly employed for simulation of concrete structure. To be able to do so, the assessed grain shape should be implemented. The approaches for aggregate and cement structure simulation by a concurrent algorithm-based DEM system are discussed in this paper. Both aggregate and cement grains were experimentally analyzed by X-ray tomography method recently. The results provide a real experimental database, for example, surface area versus volume distribution, for simulation of particles in concrete technology. Optimum solutions are obtained by different simplified shapes proposed for aggregate and cement, respectively. In this way, more reliable concepts for aggregate structure and fresh cement paste can be simulated by a DEM system.

Particle Packing Density and Limestone Fillers for More Sustainable Cement

Cement blending with mineral admixtures, especially with byproduct or waste product powder, can effectively reduce consumption of cement and promote the ecology. Recently, an innovative concept was proposed to replace of coarse cement grains by the inert fillers for sustainable cement in the low w/c concrete cement. As a basic mechanism, particle packing plays an important role in such replacement or blending. In the first part of study, the paper discusses the particle packing aspect of cement grains, limestone filler (LF) and LF blended cement. The new developed wet packing method and a dry packing method are proposed for the evaluation purpose. The paper presents results of packing tests with the influences of PSD, cement type, vibration, mixing, blending proportions, etc. The advantages and limitations of two packing methods are also discussed in this paper.

New descriptor for skeletons of planar shapes: the calypter

The mathematical definition of the skeleton as the locus of centers of maximal inscribed discs is a nondigitizable one. The idea presented in this paper is to incorporate the skeleton information and the chain-code of the contour into a single descriptor by associating to each point of a contour the center and radius of the maximum inscribed disc tangent at that point. This new descriptor is called calypter. The encoding of a calypter is a three stage algorithm: (1) chain coding of the contour; (2) euclidean distance transformation, (3) climbing on the distance relief from each point of the contour towards the corresponding maximal inscribed disc center. Here we introduce an integer euclidean distance transform called the holodisc distance transform. The major interest of this holodisc transform is to confer 8-connexity to the isolevels of the generated distance relief thereby allowing a climbing algorithm to proceed step by step towards the centers of the maximal inscribed discs. The calypter has a cyclic structure delivering high speed access to the skeleton data. Its potential uses are in high speed euclidean mathematical morphology, shape processing, and analysis.

Design and calibration of a two-camera (visible to near-infrared and short-wave infrared) hyperspectral acquisition system for the characterization of metallic alloys from the recycling industry

Abstract. The conception of a prototype combining two hyperspectral cameras, one ranging from visible to near-infrared and the other covering short-wave infrared, is presented. The prototype aims at the characterization of millimeter-sized metallic alloys particles, originating from end-of-life vehicles and waste electrical and electronic equipment recycling. This paper is meant to serve as a support for a similar project by presenting difficulties encountered and available solutions. The calibration steps necessary to obtain quality reflectance data are also described. Classification results obtained on 100 metallic fragments dataset are finally presented.