Segmentation of Sedimentary Grain in Electron Microscopy Image

This paper describes a novel method developed for the segmentation of sedimentary grains in electron microscopy images. The algorithm utilizes the approach of region splitting and merging. In the splitting stage, the marker-based watershed segmentation is used. In the merging phase, the typical characteristics of grains in electron microscopy images are exploited for proposing special metrics, which are then used during the merging stage to obtain a correct grain segmentation. The metrics are based on the typical intensity changes on the grain borders and the compact shape of grains. The experimental part describes the optimal setting of parameter in the splitting stage and the overall results of the proposed algorithm tested on available database of grains. The results show that the proposed technique fulfills the requirements of its intended application

Quantitative textural analysis of sedimentary grains and basin subsidence modelling

Part 1: Quantitative textural analysis Shape analysis can provide important information regarding the origin, transport and deposition history of grains. Particle shape measurement has been an active area of research for sedimentologists since the 20th century. However, there is a lack of standardised methodology for quantitative characterisation of grain shapes. The main objective of this work is to develop methodologies that can be used by sedimentologists for quantitative textural analysis of grains such that the results obtained are comparable. A modular suite of code written in the Mathematica environment for the quantitative characterisation of sedimentary grains in 2- dimensions is presented. This image analysis package can be used to analyse consolidated as well as loose sediment samples. Using newly implemented image analysis methods, 20 loose sediment samples from four known depositional environments (beach, aeolian, glacial and fluvial) were analysed. This research aims to identify the most useful shape parameters for textural characterisation of populations of grains and determine the relative importance of the parameters. A key aspect of this study is to determine whether, in a particular sedimentary environment, textural maturity of the samples can be ranked based on their grain shape data. Furthermore, discrimination of sedimentary depositional environments is explored on the basis of grain shape. The available shape parameters suffer from a common shortcoming that particles, which are visually distinct, are not differentiated. To address this issue, the Inverse Radius of Curvature (IRC) plot which can be used to identify corners and measure their sharpness is introduced. Using the IRC plot, four shape parameters are proposed: number of corners, cumulative angularity, sharpest corner and straight fraction. This methodology is applied to a 4000 sand grain dataset. The textural analysis software package developed here allow users to quantitatively characterise large set of grains with a fast, cheap and robust methodology. This study indicate that textural maturity is readily categorised using automated grain shape parameter analysis. However, it is not possible to absolutely discriminate between different depositional environments on the basis of shape parameters alone. The four new shape parameters proposed here based on the IRC plot can be collectively used to quantitatively describe grains shape which correlates closely with visual perceptions. This work opens up the possibility of using detailed quantitative textural dataset of sediment grains along with other standard analyses (mineralogy, bulk composition, isotopic analysis, etc) for diverse sedimentary studies. Part 2: Basin modelling Subsidence modelling is an important part of basin analysis to better understand the tectonic evolution of sedimentary basins. The McKenzie model has been widely applied for subsidence modelling and stretching factor estimation for sedimentary basins formed in an extensional tectonic environment. In this contribution, a numerical model is presented that takes into account the effect of sedimentary cover on stretching factor estimation. Subsidence modelling requires values of physical parameters (crustal thickness, lithospheric thickness, stretching factor, etc.) which may not be always available. With a given subsidence history of a basin estimated using a stratigraphic backstripping method, these parameters can be estimated by quantitatively comparing the known subsidence curve with modelled subsidence curves. In this contribution, a method to compare known and modelled subsidence curves is presented aiming to constrain valid combinations of stretching factor, crustal thickness and lithospheric thickness of a basin. The parameter fitting method presented here is first applied to synthetically generated subsidence curves. Next, a case study using a known subsidence curve from the Campos Basin, offshore Brazil is considered. The range of stretching factors estimated for the Campos basin from this study is in accordance with previous work, with an additional estimate of corresponding lithospheric thickness. This study provides insights into the dependence of subsidence modelling methods on assumptions about input parameters as well as allowing for the estimation of valid combinations of physical lithospheric parameters, where the subsidence history is known

Marco de trabajo de rasgos biométricos en queiloscopía mediante el uso de machine learning

La Queiloscopía es el estudio de las impresiones labiales que se producen a través del análisis de las líneas, fisuras, arrugas y estrías presentes en el labio. “Queilos” proviene del griego que significa labio y “scopia” examinar. Según Cardoso [3], fue el antropólogo R. Fischer el pionero en esta área. Éste describió los surcos en 1902, pero no fue hasta 1932 que Edmond Locard, reconocido criminalista francés, recomendó su uso para la identificación. No obstante, tuvieron que pasar veintiocho años para que en 1950 LeMonyne Snyder los utilice en un caso real. Aunque la Queiloscopía es un campo relativamente nuevo entre la gran cantidad de herramientas de identificación disponible para expertos forenses, de ésta se obtiene información sumamente útil como la identidad de una persona. Esto se debe a que permanecen relativamente estables y muestran diferencias en cuanto al género La Queiloscopía es un procedimiento manual donde se utilizan herramientas como lupas y escalas para analizar las huellas labiales. Esto lo convierte en una metodología propensa a errores humanos Para evitar esto y automatizarla, se precisa de un algoritmo. Por otro lado, Machine Learning (ML) es un subcampo de la Inteligencia Artificial (IA). Esta última se define como la inteligencia exhibida por una entidad artificial para resolver problemas complejos. Tal sistema generalmente supone ser una computadora o máquina . Dicho de otra forma, se puede decir que la IA es la habilidad que tiene dicha entidad de utilizar algoritmos para aprender de los datos y usar este conocimiento para tomar decisiones como lo haría un ser humano. A diferencia de este último, las máquinas que cuentan con IA corren con la ventaja de no precisar de descansos, analizar enormes cantidades de datos de forma simultánea y contar con una baja tasa de error . Si bien la IA y ML han estado presentes desde hace mucho tiempo, es solamente ahora que se cuenta con el poder computacional para efectivamente desarrollar Redes Neuronales Artificiales (RNA) lo suficientemente poderosas en un lapso de tiempo razonable . En el campo de la biometría, ML resalta por su capacidad de aumentar la precisión en el proceso de identificación. Las características biométricas tomadas en primera instancia no son siempre iguales a las tomadas una segunda vez. En consecuencia, el uso de técnicas de aprendizaje automático como neuronales, lógica difusa, informática evolutiva, etc., ha incrementado su demanda. En este contexto, el objetivo del proyecto es definir un marco de trabajo, utilizando ML, para determinar rasgos biométricos suaves de una persona, como el sexo y edad, a través de sus impresiones labiales.Red de Universidades con Carreras en Informátic

Análisis de calidad de arenas de fracturación mediante visión artificial y redes neuronales

La fracturación hidráulica realizada para extraer hidrocarburos de yacimientos no convencionales requiere de la inyección de arenas que actúan como apuntalantes de la fractura. La calidad de las arenas para cumplir dicha función se evalúa por la norma API19C, que establece medidas geométricas – esfericidad y redondez- más un porcentaje de fractura cuando la muestra es sometida a compresión. Todas estas mediciones deben encontrarse dentro de valores límites para asegurar la calidad de la arena. Según la norma, la inspección se realiza visualmente por un operador sobre un conjunto de 20 granos. Esto introduce un importante grado de subjetividad, y poca validez estadística. Para solucionar esto, la bibliografía refiere distintos métodos basados en visión artificial. Cada uno de estos métodos tiene ventajas y desventajas según la geometría, color de la partícula y la definición de la imagen usada. En este trabajo se presenta una metodología integrada a partir de varios métodos conocidos, más uno novedoso desarrollado por los autores para medir la redondez, que es la variable más difícil de medir. Las distintas medidas son tratadas por redes neuronales para dar una medida final de la redondez, que tiene un alto grado de correlación con la medida teórica de cada partícula considerada. Las medidas de esfericidad y porcentaje de fractura obtenidas también han dado valores consistentes. El método de visión artificial desarrollado es sumamente eficiente para determinar, a partir de las medidas obtenidas, la capacidad de una arena para actuar como apuntalante en una operación de fractura hidráulica.Red de Universidades con Carreras en Informátic

Sphericity and roundness computation for particles using the extreme vertices model

Shape is a property studied for many kinds of particles. Among shape parameters, sphericity and roundness indices had been largely studied to understand several processes. Some of these indices are based on length measurements of the particle obtained from its oriented bounding box (OBB). In this paper we follow a discrete approach based on Extreme Vertices Model and devise new methods to compute the OBB and the mentioned indices. We apply these methods to synthetic sedimentary rocks and to a real dataset of silicon nanocrystals (Si NC) to analyze the obtained results and compare them with those obtained with a classical voxel model.Peer ReviewedPostprint (author's final draft

From the primitive Ourthe to the primitive Meuse in the Lower Meuse of Liège - Part 1: Generalities and data

editorial reviewedThe gravel that covers the sub-flat surfaces above 180 m a.s.l. around Liège are the subject of a sedimentological study, in relation to the state of knowledge in terms of Oligocene stratigraphy taking into account the uplift/tilting of the NW flank of the Ardenne. This article reports the generalities and the field and laboratory data that have led to the construction of a new model of the morpho-sedimentary evolution of the hydrographic network of the Ourthe and the Meuse in the area of their current confluence. The interpretation of these data and the resulting model are published in the article that follows in this issue of the journa

Automatic computation of pebble roundness using digital imagery and discrete geometry

International audienceThe shape of sedimentary particles is an important property, from which geographical hypotheses related to abrasion, distance of transport, river behavior, etc. can be formulated. In this paper, we use digital image analysis, especially discrete geometry, to automatically compute some shape parameters such as roundness i.e. a measure of how much the corners and edges of a particle have been worn away. In contrast to previous works in which traditional digital images analysis techniques such as Fourier transform (Diepenbroek et al., 1992, Sedimentology, 39) are used, we opted for a discrete geometry approach that allowed us to implement Wadell's original index (Wadell, 1932, Journal of Geology, 40) which is known to be more accurate, but more time consuming to implement in the field (Pissart et al., 1998, Geomorphologie: relief, processus, environnement, 3). Our implementation of Wadell's original index is highly correlated (92%) with the round- ness classes of Krumbein's chart, used as a ground-truth (Krumbein, 1941, Journal of Sedimentary Petrology, 11, 2). In addition, we show that other geometrical parameters, which are easier to compute, can be used to provide good approximations of roundness. We also used our shape parameters to study a set of pebbles digital images taken from the Progo basin river network (Indonesia). The results we obtained are in agreement with previous works and open new possibilities for geomorphologists thanks to automatic computation

Development of image analysis techniques to assist evaluation of both air void structure and aggregate shape factors in concrete

Significant reduction in both strength and durability of concrete is brought about by voids left within the concrete once it has hardened. These voids can arise from a number of sources both intentional, in the case of air-entrained voids introduced by admixtures batched to provide a structure that can withstand frost attack and unintentional in the case of entrapped voids that arise due to characteristic of the sand and aggregates, excess water added and a lack of consolidation whilst plastic. Aggregate form, shape and texture are known to influence the way particles pack together and therefore the amount of space left between and amongst the particles. The second phase of this study has used desktop flat-bed scanning to record aggregate profiles, both raw particles and aggregate shape profiles taken from the curved surface of core samples, to classify the shape and then provide a protocol for defining the shape. This study has shown the photographs provided originally in Concrete Society Technical Report 11 and now recently re-introduced into the UK Annex of BS EN 12504-1:2009 Testing concrete in structures – Core specimens – Taking, examining and testing in compression, provide a misrepresentation of the curved surface of the core. A curved surface cannot be recorded faithfully by a 2D camera image. An accurate representation of the curved surface of concrete core samples has been obtained by the use of conventional desktop scanners, albeit using relatively high image resolution. By a novel yet simple modification, concrete core samples have been mechanically rolled above a modified flatbed desktop scanner driven by the crosshead so as to align directly above the cold cathode fluorescent (CCF) light source and the scanning charged coupled cross-head image recording device. A method of assessing the amount of voidage found within the curved surface of concrete core samples has been developed. A freely distributed software programme was used to process all images to determine percentage voidage and voids size distribution among other attributes. A second freely available statistics software package has been used to analyse the results. iii The second phase of the study has used the same scanning technique to classify 2D aggregate profile as used for voidage shape recognition taken from the curved surface of core samples. Three simple shape factors have been used, one developed specifically for this study. By means of Riley Circularity, Percentage Concavity and Aspect Ratio core surface aggregate profiles, raw aggregate shapes and voidage found on core samples have been classified. The objective being to determine if the aggregate within a sampled concrete has changed from that intended, possibly due to crushing oversize material or just changes within the source that would provide a means of assessing any influence aggregate shape change may have had on entrapped voidage and the effect that has had on the strength of the concrete. Scanner performance and calibration has been checked using high resolution calibration sheets. The image resolution was found to be accurate to 2.5% at 0.5mm diameter when scanned at 1200 dpi. This enabling the threshold to be investigated between entrained and entrapped air voids so as to allow discrimination between any combinations of the two found on a core sample. The equipment, equipment modifications, procedures, test protocols as well as the imaging software and statistical analyses packages included in this study have been chosen so as to allow others to utilise the benefits such analyses offers. The recent acceptance and drive to recycle materials for use as construction aggregate can benefit from classification by these procedures that until now have not been included in any published Standards. The procedures developed during this study have been published in the Magazine of Concrete Research, Dec 2010 and presentations given by invitation to joint meetings of the Concrete Society/Institute of Concrete Technology at Loughborough and in London, 2011

Actas del XXIV Workshop de Investigadores en Ciencias de la Computación: WICC 2022

Compilación de las ponencias presentadas en el XXIV Workshop de Investigadores en Ciencias de la Computación (WICC), llevado a cabo en Mendoza en abril de 2022.Red de Universidades con Carreras en Informátic