scholarly journals Estimating the Parameters of a Stochastic Geometrical Model for Multiphase Flow Images Using Local Measures

2021 ◽  
Vol 40 (3) ◽  
pp. 115-125
Author(s):  
Leo Theodon ◽  
Tatyana Eremina ◽  
Kassem Dia ◽  
Fabrice Lamadie ◽  
Jean-Charles Pinoli ◽  
...  
Keyword(s):  
Image Processing ◽  
Multiphase Flow ◽  
Numerical Experiments ◽  
Geometric Model ◽  
Geometrical Model ◽  
Boolean Model ◽  
Elongation Ratio ◽  
Flow Image ◽  
Local Measurements ◽  
Area And Perimeter

This paper presents a new method for estimating the parameters of a stochastic geometric model for multiphase flow image processing using local measures. Local measures differ from global measures in that they are only based on a small part of a binary image and consequently provide different information of certain properties such as area and perimeter. Since local measures have been shown to be helpful in estimating the typical grain elongation ratio of a homogeneous Boolean model, the objective of this study was to use these local measures to statistically infer the parameters of a more complex non-Boolean model from a sample of observations. An optimization algorithm is used to minimize a cost function based on the likelihood of a probability densityof local measurements. The performance of the model is analysed using numerical experiments and real observations. The errors relative to real images of most of the properties of the model-generated images are less than 2%. The covariance and particle size distribution are also calculated and compared.

scholarly journals An Overview of the Topological Gradient Approach in Image Processing: Advantages and Inconveniences

2010 ◽  
Vol 2010 ◽  
pp. 1-19 ◽  
Author(s):  
Lamia Jaafar Belaid
Keyword(s):  
Image Processing ◽  
Image Analysis ◽  
Numerical Experiments ◽  
Grey Level ◽  
Major Drawback ◽  
Topological Gradient ◽  
Boundary Measurements ◽  
Topological Asymptotic Expansion ◽  
Gradient Approach ◽  
Segmentation Problem

Image analysis by topological gradient approach is a technique based upon the historic application of the topological asymptotic expansion to crack localization problem from boundary measurements. This paper aims at reviewing this methodology through various applications in image processing; in particular image restoration with edge detection, classification and segmentation problems for both grey level and color images is presented in this work. The numerical experiments show the efficiency of the topological gradient approach for modelling and solving different image analysis problems. However, the topological gradient approach presents a major drawback: the identified edges are not connected and then the results obtained particularly for the segmentation problem can be degraded. To overcome this inconvenience, we propose an alternative solution by combining the topological gradient approach with the watershed technique. The numerical results obtained using the coupled method are very interesting.

scholarly journals A geometrical model for the evolution of spherical planetary nebulae based on thin-shell formalism

2021 ◽  
pp. 2150191
Author(s):  
Ibrahim Gullu ◽  
S. Habib Mazharimousavi ◽  
S. Danial Forghani
Keyword(s):  
Energy Density ◽  
Planetary Nebula ◽  
Thin Shell ◽  
Energy Momentum Tensor ◽  
Geometric Model ◽  
Geometrical Model ◽  
Momentum Tensor ◽  
Evolution Pattern ◽  
Simple Power Function ◽  
Curvature Tensors

A spherical planetary nebula is described as a geometric model. The nebula itself is considered as a thin-shell, which is visualized as a boundary of two spacetimes. The inner and outer curvature tensors of the thin-shell are found in order to get an expression of the energy-momentum tensor on the thin-shell. The energy density and pressure expressions are derived using the energy-momentum tensor. The time evolution of the radius of the thin-shell is obtained in terms of the energy density. The model is tested by using a simple power function for decreasing energy density and the evolution pattern of the planetary nebula is attained.

Change-driven data flow image processing architecture for optical flow computation

2007 ◽  
Vol 2 (4) ◽  
pp. 259-270 ◽  
Author(s):  
Julio C. Sosa ◽  
Jose A. Boluda ◽  
Fernando Pardo ◽  
Rocío Gómez-Fabela
Keyword(s):  
Image Processing ◽  
Optical Flow ◽  
Data Flow ◽  
Flow Computation ◽  
Flow Image ◽  
Optical Flow Computation ◽  
Processing Architecture

Image Denoising with Contour-Based Directionlet Transform

2014 ◽  
Vol 513-517 ◽  
pp. 3607-3611
Author(s):  
Huan An Xu ◽  
Guo Hua Peng ◽  
Zhe Liu
Keyword(s):  
Image Processing ◽  
Image Denoising ◽  
Numerical Experiments ◽  
Adaptive Threshold ◽  
Perceptual Quality ◽  
Laplacian Pyramid ◽  
Low Frequencies ◽  
Threshold Algorithm ◽  
Image Transform

A novel mutiscale and directionally adaptive image transform called contour based directionlet tansform is presented. Directionlet transform (DT) has shown its charming performance in image processing, but it has scrambled frequencies. Laplacian Pyramid is employed here to separate the low frequencies before applying DT for avoiding the drawback. And an adaptive threshold algorithm is proposed for denoising. Numerical experiments are performed to assess the applicability of the proposed method. The obtained results show that the proposed scheme outperforms Wavelet and Directionlet transforms in terms of numerical and perceptual quality.

A Unified Geometric Model for Virtual Slide Image Processing and Classification

2016 ◽  
Vol 10 (1) ◽  
pp. 151-160
Author(s):  
Matthieu Toutain ◽  
Abderrahim Elmoataz ◽  
Xavier Desquesnes ◽  
Jean-Hugues Pruvot
Keyword(s):  
Image Processing ◽  
Virtual Slide ◽  
Geometric Model ◽  
Slide Image

scholarly journals The Glory of the Past and Geometrical Concurrency

10.29007/klcl ◽  
2018 ◽  
Author(s):  
Cristian Prisacariu
Keyword(s):  
Modal Logic ◽  
Geometric Model ◽  
Expressive Power ◽  
Geometrical Model ◽  
Geometrical Aspect ◽  
Fine Grained ◽  
The Past ◽  
Action Refinement ◽  
Higher Dimensional ◽  
Natural Way

This paper contributes to the general understanding of the "geometrical model of concurrency" that was named higher dimensional automata (HDAs) by Pratt and van Glabbeek. In particular we provide some understanding of the modal logics for such models and their expressive power in terms of the bisimulation that can be captured.The geometric model of concurrency is interesting from two main reasons: its generality and expressiveness, and the natural way in which autoconcurrency and action refinement are captured.Logics for this model, though, are not well investigated, where a simple, yet adequate, modal logic over HDAs was only recently introduced.As this modal logic, with two existential modalities, "during" and "after", captures only split bisimulation, which is rather low in the spectrum of van Glabbeek and Vaandrager, the immediate question was what small extension of this logic could capture the more fine-grained hereditary history preserving bisimulation (hh)?In response, the work in this paper provides several insights. One is the fact that the geometrical aspect of HDAs makes it possible to use for capturing the hh-bisimulation, a standard modal logic that does not employ event variables, opposed to the two logics (over less expressive models) that we compare with. The logic that we investigate here uses standard backward-looking modalities (i.e., past modalities) and extends the previously introduced logic (called HDML) that had only forward, action-labelled, modalities.Since the direct proofs are rather intricate, we try to understand better the above issues by introducing a related model that we call ST-configuration structures, which extend the configuration structures of van Glabbeek and Plotkin. We relate this model to HDAs, and redefine and prove the earlier results in the light of this new model. These offer a different view on why the past modalities and geometrical concurrency capture the hereditary history preserving bisimulation.Additional correlating insights are also gained.

scholarly journals Multiphase Flow Control with Embedded System and Color Image Processing

2017 ◽  
Vol 10 (39) ◽  
pp. 1-8 ◽  
Author(s):  
Maqsood Jan Mohammad ◽  
Tahir Qadri ◽  
Shakil Ahmed ◽  
◽  
◽  
...  
Keyword(s):  
Image Processing ◽  
Multiphase Flow ◽  
Embedded System ◽  
Flow Control ◽  
Color Image ◽  
Color Image Processing

Geometric Model of the Interaction of the Grinding Wheel and Workpiece during Surface Grinding with the Periphery of a Straight Wheel

2015 ◽  
Vol 756 ◽  
pp. 41-46 ◽  
Author(s):  
Aleksandr A. Dyakonov ◽  
Leonid V. Shipulin
Keyword(s):  
Geometric Model ◽  
Translational Motion ◽  
Geometrical Model ◽  
Surface Grinding ◽  
Polished Surface ◽  
Grinding Wheel ◽  
Experimental Check ◽  
Basic Parameters

Results of development of geometrical model of a shaping of a polished surface at surface grinding by the periphery of a wheel are presented in article. The developed model allows to predict a roughness of the processed surface depending on basic parameters of operation: speeds of rotation of the tool and translational motion of workpiece, wheel parameters – granularity and structure, depth of cutting and other parameters. Results of experimental check of the developed model are given in article.

Application of Modal Wavelets to Multiphase Flow Image

2003 ◽  
Vol 2003.16 (0) ◽  
pp. 105-106
Author(s):  
Teruyoshi YAMAZAKI ◽  
Masahiro TAKEI ◽  
Mitsuaki OCHI ◽  
Yoshifuru SAITO
Keyword(s):  
Multiphase Flow ◽  
Flow Image
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