A Cosmic Watershed: the WVF Void Detection Technique

On megaparsec scales the Universe is permeated by an intricate filigree of clusters, filaments, sheets and voids, the Cosmic Web. For the understanding of its dynamical and hierarchical history it is crucial to identify objectively its complex morphological components. One of the most characteristic aspects is that of the dominant underdense Voids, the product of a hierarchical process driven by the collapse of minor voids in addition to the merging of large ones. In this study we present an objective void finder technique which involves a minimum of assumptions about the scale, structure and shape of voids. Our void finding method, the Watershed Void Finder (WVF), is based upon the Watershed Transform, a well-known technique for the segmentation of images. Importantly, the technique has the potential to trace the existing manifestations of a void hierarchy. The basic watershed transform is augmented by a variety of correction procedures to remove spurious structure resulting from sampling noise. This study contains a detailed description of the WVF. We demonstrate how it is able to trace and identify, relatively parameter free, voids and their surrounding (filamentary and planar) boundaries. We test the technique on a set of Kinematic Voronoi models, heuristic spatial models for a cellular distribution of matter. Comparison of the WVF segmentations of low noise and high noise Voronoi models with the quantitatively known spatial characteristics of the intrinsic Voronoi tessellation shows that the size and shape of the voids are succesfully retrieved. WVF manages to even reproduce the full void size distribution function.Comment: 24 pages, 15 figures, MNRAS accepted, for full resolution, see http://www.astro.rug.nl/~weygaert/tim1publication/watershed.pd

An Efficient Image Segmentation Approach through Enhanced Watershed Algorithm

Image segmentation is a significant task for image analysis which is at the middle layer of image engineering. The purpose of segmentation is to decompose the image into parts that are meaningful with respect to a particular application. The proposed system is to boost the morphological watershed method for degraded images. Proposed algorithm is based on merging morphological watershed result with enhanced edge detection result obtain on pre processing of degraded images. As a post processing step, to each of the segmented regions obtained, color histogram algorithm is applied, enhancing the overall performance of the watershed algorithm. Keywords – Segmentation, watershed, color histogra

3D + t Morphological Processing: Applications to Embryogenesis Image Analysis

We propose to directly process 3D + t image sequences with mathematical morphology operators, using a new classi?cation of the 3D+t structuring elements. Several methods (?ltering, tracking, segmentation) dedicated to the analysis of 3D + t datasets of zebra?sh embryogenesis are introduced and validated through a synthetic dataset. Then, we illustrate the application of these methods to the analysis of datasets of zebra?sh early development acquired with various microscopy techniques. This processing paradigm produces spatio-temporal coherent results as it bene?ts from the intrinsic redundancy of the temporal dimension, and minimizes the needs for human intervention in semi-automatic algorithms

New foreground markers for Drosophila cell segmentation using marker-controlled watershed

Image segmentation consists of partitioning the image into different objects of interest. For a biological image, the segmentation step is important to understand the biological process. However, it is a challenging task due to the presence of different dimensions for cells, intensity inhomogeneity, and clustered cells. The marker-controlled watershed (MCW) is proposed for segmentation, outperforming the classical watershed. Besides, the choice of markers for this algorithm is important and impacts the results. For this work, two foreground markers are proposed: kernels, constructed with the software Fiji and Obj.MPP markers, constructed with the framework Obj.MPP. The new proposed algorithms are compared to the basic MCW. Furthermore, we prove that Obj.MPP markers are better than kernels. Indeed, the Obj.MPP framework takes into account cell properties such as shape, radiometry, and local contrast. Segmentation results, using new markers and illustrated on real Drosophila dataset, confirm the good performance quality in terms of quantitative and qualitative evaluation

On morphological hierarchical representations for image processing and spatial data clustering

Hierarchical data representations in the context of classi cation and data clustering were put forward during the fties. Recently, hierarchical image representations have gained renewed interest for segmentation purposes. In this paper, we briefly survey fundamental results on hierarchical clustering and then detail recent paradigms developed for the hierarchical representation of images in the framework of mathematical morphology: constrained connectivity and ultrametric watersheds. Constrained connectivity can be viewed as a way to constrain an initial hierarchy in such a way that a set of desired constraints are satis ed. The framework of ultrametric watersheds provides a generic scheme for computing any hierarchical connected clustering, in particular when such a hierarchy is constrained. The suitability of this framework for solving practical problems is illustrated with applications in remote sensing

Two-phase flow in rocks : new insights from multi-scale pore network modeling and fast pore scale visualization

Many geological applications involve the flow of multiple fluids through porous geological materials, e.g. environmental remediation of polluted ground water resources, carbon dioxide storage in geological reservoirs and petroleum recovery. Commonly, to model these applications, the geological materials in question are treated as continuous porous media with effective material properties. Since these properties are a manifestation of what goes on in the pores of the material, we have to study the transport processes at the pore scale to understand why and how they vary over space and time in different rocks and under different conditions. As the high cost of acquiring and testing samples in many of these applications is often a limiting factor, numerical modelling at the pore scale is becoming a key technology to gain new insights in this field. This could be crucial in reducing uncertainties in field scale projects. The work presented in this thesis focuses on the investigation of two-phase flow in sedimentary rocks, and is an integrated numerical and experimental study. It deals primarily with two outstanding issues. First, image-based pore scale simulation methods have difficulties with representing the multiple pore scales in rocks with wide pore size distributions, due to a trade-off in the size and resolution of both modeling and imaging methods. Therefore, performing two-phase flow simulations in a number of important rock types, such as many carbonates and tight, clay-baring sandstones has remained an outstanding challenge. To tackle this problem, a new numerical model was developed to calculate capillary pressure, relative permeability and resistivity index curves during drainage and imbibition processes in such materials. The multi-scale model was based on information obtained from 3D micro-computed tomography images of the internal pore structure, complemented with information on the pores that are unresolved with this technique. In this method, pore network models were first extracted from resolved pores in the images, by using a maximal ball network extraction algorithm. Then, pores which touched regions with unresolved porosity were connected with a special type of network element called micro-links. In the quasi-static simulations that were performed on these network models, the micro-links carried average properties of the unresolved porosity. In contrast to most previous models, the new approach to taking into account unresolved porosity therefore allowed efficient simulations on images of complex rocks, with sizes comparable to single-scale pore network models. It was able to reproduce most of the behaviour of a fully resolved pore network model, for both drainage and imbibition processes, and for different pore scale wettability distributions (water-wet, oil-wet and different mixed-wet distributions). Furthermore, simulations on images of carbonate rocks showed good agreement to experiments. A sensitivity study on carbonate rocks and tight, clay-bearing sandstones produced results that were in qualitative agreement with experiments, and allowed to analyse how the two-phase flow behaviour of these rocks is influenced by their pore scale properties. The second issue which is treated in this thesis is related to the validation of pore scale models. Comparing predicted effective properties to experimentally measured values is useful and necessary, but is complicated by the typical difference in size between the model and the experiment. Furthermore, it does not always give a clear indication of the reasons for an observed mismatch between models and experiments. Comparing two-phase flow models to pore scale experiments in which the evolution of the fluid distributions is visualized is thus extremely useful. However, this requires to image the two-phase flow process while it is taking place in a rock, and it is necessary to do this with time resolutions on the order of tens of seconds and spatial resolutions on the order of micrometers. Previous experimental approaches used synchrotron beam lines to achieve this. In this thesis, we show that such experiments are also possible using laboratory-based micro-computed tomography scanners, which are orders of magnitude cheaper and therefore more accessible than synchrotrons. An experiment in which kerosene was pumped into a water-saturated sandstone is presented, showing that individual Haines jumps (pore filling events) could be visualized during this drainage process. Because the image quality is lower than at synchrotrons, care had to be taken to adapt the image analysis work flow to deal with high image noise levels. The work flow was designed to allow to track the fluid filling state of individual pores. The results indicate that the dynamic effects due to viscous and inertial forces during Haines jumps do not significantly impact the evolution of the fluid distributions during drainage, which may thus be adequately described by quasi-static models

Impact Of Fines On Gas Relative Permeability Through Sand Using Pore Networks From 3d Synchrotron Micro-Computed Tomography

Fines migration and transport in sand systems have huge influence on vital applications, including the storage and recovery of water and energy resources from the subsurface. Multi-phase flow of gas through saturated unconsolidated media takes place between the pores of sediments, physical phenomenon at the pore-scale control the flow properties. Given a sandy sediment media, gas permeability is highly affected by fine particles due to migration, clogging and bridging reducing gas flow or causing sand particles to displace creating fractures. There is a knowledge gap of fines effects on gas production from sandy sediments, especially at the pore-scale. Therefore, there is a need to model and quantify effects of fines in multi-phase flow using pore networks to better understand gas recovery systems. Three-dimensional, synchrotron micro-computed tomography images of sand sediments were obtained at Argonne National Laboratory at a resolution of 3.89 micron per voxel. Kaolinite and Montmorillonite fine particles were added in varied concentrations in six soil specimens, each system was scanned at four stages with varied saturations of brine and CO2, resulting in 20 systems. Micro-computed tomography images were processed for 3D visualization, quantification and pore network modeling. Pore Network Models were generated, and relative permeability properties were then computed for each system. Findings revealed that fines accumulate at sand-brine and brine-gas interfaces. As fines concentration increased, gas percolation decreased. Further increase in fines concentrations resulted in blocking local gas flow causing pressure variations enough to create fractures that allows gas to escape and permeability to increase back. Pore Networks and Computer-Based Two-Phase Flow Simulations can effectively be used to characterize flow in porous media. In unconsolidated media the pore space geometry will change due to sand grains movements. At high concentrations, different fines type produces altered gas flow regimes, Kaolinite resulted in fractures while montmorillonite resulted in detached gas ganglia. Generally, increasing fines reduces gas percolation and further injection of gas reduced permeability. The finds herein are critical in understanding the impact of fines migration during gas flow in sand, they can be applied to characterizing and predicting two phase properties of unconsolidated sediments