Publications from the Center of Mathematical Morphology

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F. Willot, B. Abdallah, D. Jeulin (2016): The Permeability of Boolean Sets of Cylinders. Oil & Gas Science and Technology - Revue d'IFP Energies nouvelles 71(4).
Numerical and analytical results on the permeability of Boolean models of randomly-oriented cylinders with circular cross-section are reported. The present work investigates cylinders of prolate (highly-elongated) and oblate (nearly flat) types. The fluid flows either inside or outside of the cylinders. The Stokes flow is solved using full-fields Fourier-based computations on 3D binarized microstructures. The permeability is given for varying volume fractions of pores. A new upper-bound is derived for the permeability of the Boolean model of oblate cylinders. The behavior of the permeability...

G. Noyel, D. Jeulin, E. Parra-Denis, M. Bilodeau (2016): 在轮胎的内部表面上的浮凸元素特征的快速分析方法.
Method of fast analysis of the relief elements featuring on the interior surface of a tyre, said method comprising the steps in the course of which: A- the three dimensional image of said surface is captured by assigning each pixel of the image a grey level value proportional to the topographical elevation of this point, so as to obtain a starting image, B- the image of the surface captured is transformed into an orthogonal reference frame (OXY) in which the abscissa axis (OX) represents the circumferential values, and the ordinate axis (OY) represents the radial values, C- each pixel of the...

G. Franchi (2016): Spatial machine learning applied to multivariate and multimodal images.
This thesis focuses on multivariate spatial statistics and machine learning applied to hyperspectral and multimodal and images in remote sensing and scanning electron microscopy (SEM). In this thesis the following topics are considered: Fusion of images: SEM allows us to acquire images from a given sample using different modalities. The purpose of these studies is to analyze the interest of fusion of information to improve the multimodal SEM images acquisition. We have modeled and implemented various techniques of image fusion of information, based in particular on spatial regression theory....

G. Franchi, J. Angulo, D. Sejdinovic (2016): Hyperspectral Image Classification with Support Vector Machines on Kernel Distribution Embeddings. 2016 IEEE International Conference on Image Processing (ICIP), Phoenix (United States).
We propose a novel approach for pixel classification in hyperspectral images, leveraging on both the spatial and spectral information in the data. The introduced method relies on a recently proposed framework for learning on distributions - by representing them with mean elements in reproducing kernel Hilbert spaces (RKHS) and formulating a classification algorithm therein. In particular, we associate each pixel to an empirical distribution of its neighbouring pixels, a judicious representation of which in an RKHS, in conjunction with the spectral information contained in the pixel itself,...

G. Franchi, J. Angulo (2016): A deep spatial/spectral descriptor of hyperspectral texture using scattering transform. 2016 IEEE International Conference on Image Processing (ICIP), Phoenix (United States).
A technique to describe the spatial / spectral features of hyperspectral images is introduced. These descriptors aim at representing the content of the image while considering invariances related to the texture and to its geometric transformations, so called spatial invariances. Moreover, we also consider spectral invariances which are related to the composition of the pixels. Our approach is based on the scattering transform, which provides an useful framework for deep learning classification. The goal through these descriptors is to improve pixel-wise classification of hyperspectral images.

J. Corvo, J. Angulo, J. Breugnot, S. Bordes, B. Closs (2016): Common reduced spaces of representation applied to multispectral texture analysis in cosmetology. Multimodal Biomedical Imaging XI, San Francisco (United States).

E. Chevallier, T. Forget, F. Barbaresco, J. Angulo (2016): Kernel Density Estimation on the Siegel Space with an Application to Radar Processing. Entropy 18(11).

G. Franchi, J. Angulo (2016): Morphological Principal Component Analysis for Hyperspectral Image Analysis. ISPRS International Journal of Geo-Information 5(6).

E. Chevallier, J. Angulo (2016): The Irregularity Issue of Total Orders on Metric Spaces and Its Consequences for Mathematical Morphology. Journal of Mathematical Imaging and Vision 54(3) 344 — 357.

E. Chevallier, A. Chevallier, J. Angulo (2016): N-ary Mathematical Morphology. Mathematical Morphology - Theory and Applications 1(1).

O. Burgy, G. Wettstein, P. Bellaye, N. Decologne, C. Racoeur, F. Goirand, G. Beltramo, J.F. Hernandez, A. Kenani, P. Camus, A. Bettaieb, C. Garrido, P. Bonniaud (2016): Deglycosylated bleomycin has the antitumor activity of bleomycin without pulmonary toxicity. Science Translational Medicine 8(326) 326ra20 — 326ra20.
Bleomycin (BLM) is a potent anticancer drug used to treat different malignancies, mainly lymphomas, germ cell tumors, and melanomas. Unfortunately, BLM has major, dose-dependent, pulmonary toxicity that affects 20% of treated individuals. The most severe form of BLM-induced pulmonary toxicity is lung fibrosis. Deglyco-BLM is a molecule derived from BLM in which the sugar residue D-mannosyl-L-glucose disaccharide has been deleted. The objective of this study was to assess the anticancer activity and lung toxicity of deglyco-BLM. We compared the antitumor activity and pulmonary toxicity of...

B. Figliuzzi, W.H.R. Chan, C.R. Buie, J.L. Moran (2016): Nonlinear electrophoresis in the presence of dielectric decrement. Physical Review E 94(2).
The nonlinear phenomena that occur in the electric double layer (EDL) that forms at charged surfaces strongly influence electrokinetic effects, including electro-osmosis and electrophoresis. In particular, saturation effects due to either dielectric decrement or ion crowding effects are of paramount importance. Dielectric decrement significantly influences the ionic concentration in the EDL at high ζ potential, leading to the formation of a condensed layer near the particle's surface. In this article, we present a model incorporating both steric effects due to the finite size of ions and...

D. Jeulin (2016): Morphological probabilistic hierarchies for texture segmentation. Mathematical Morphology - Theory and Applications 1(Issue 1) 216—234.
A general methodology is introduced for texture segmentation in binary, scalar, or multispectral images. Textural information is obtained from morphological operations on images. Starting from a fine partition of the image in regions, hierarchical segmentations are designed in a probabilistic framework by means of probabilistic distances conveying the textural information, and of random markers accounting for the morphological content of the regions and of their spatial arrangement. The probabilistic hierarchies are built from binary or multiple fusion of regions.

D. Jeulin (2016): Iterated Boolean random varieties and application to fracture statistics models. Applications of Mathematics Volume 61, Issue 4 pp 363–386.
Models of random sets and of point processes are introduced to simulate some specific clustering of points, namely on random lines in R2 and R3 and on random planes in R3. The corresponding point processes are special cases of Cox processes. The generating distribution function of the probability distribution of the number of points in a convex set K and the Choquet capacity T (K) are given. A possible application is to model point defects in materials with some degree of alignment. Theoretical results on the probability of fracture of convex specimens in the framework of the weakest link...

S. Drouyer, S. Beucher, M. Bilodeau, M. Moreaud, L. Sorbier (2016): A morphological approach for texture detection, application to SEM stereo reconstruction. The 16th European Microscopy Congress 2016, Lyon (France).

B. Figliuzzi, M. Bilodeau, J. Angulo, S. Velasco-Forero (2016): A Bayesian Approach to Linear Unmixing in the Presence of Highly Mixed Spectra. Advanced Concepts for Intelligent Vision Systems: 17th International Conference, ACIVS 2016, Leecy (Italy) Lecture Notes in COmputer Science(0016 2016) 263—274.
In this article, we present a Bayesian algorithm for endmember extraction and abundance estimation in situations where prior information is available for the abundances. The algorithm is considered within the framework of the linear mixing model. The novelty of this work lies in the introduction of bound parameters which allow us to introduce prior information on the abundances. The estimation of these bound parameters is performed using a simulated annealing algorithm. The algorithm is illustrated by simulations conducted on synthetic AVIRIS spectra and on the SAMSON dataset.

A. Belhedi, B. Marcotegui (2016): Adaptive scene-text binarization on images captured by smartphones. Image Processing, IET 10(7).
We address, in this paper, a new adaptive binarization method on images captured by smartphones. This work is part of an application for visually impaired people assistance, that aims at making text information accessible to people who cannot read it. The main advantage of the proposed method is that the windows underlying the local thresh-olding process are automatically adapted to the image content. This avoids the problematic parameter setting of local thresholding approaches, difficult to adapt to a heterogeneous database. The adaptive windows are extracted based on ultimate opening (a...

A. Serna, B. Marcotegui, J. Hernández (2016): Segmentation of Façades from Urban 3D Point Clouds using Geometrical and Morphological Attribute-based Operators. ISPRS International Journal of Geo-Information 5(1).
3D building segmentation is an important research issue in the remote sensing community with relevant applications to urban modeling, cloud-to-cloud and cloud-to-model registration, 3D cartography, virtual reality, cultural heritage documentation, among others. In this paper, we propose automatic, parametric and robust approaches to segment façades from 3D point clouds. Processing is carried out using elevation images and 3D decomposition, and the final result can be reprojected onto the 3D point cloud for visualization or evaluation purposes. Our methods are based on geometrical and...

J.X. Zhao, C. Thierry, E. Decencière, D. Jeulin, D. Cárdenas-Peña, L. Silva (2016): Direct multiphase mesh generation from 3D images using anisotropic mesh adaptation and a redistancing equation. Computer Methods in Applied Mechanics and Engineering 309 288–306.
In this paper, a new methodology to build automatically 3D adapted meshes, ready for numerical simulations and directly from images, is proposed. It is based on the Immersed Image Method, which interpolates the image information on an initial mesh and combines it with parallel automatic anisotropic mesh adaptation with a control of the number of mesh nodes. Simultaneously, a smooth redistancing technique, based on the resolution of a Hamilton–Jacobi equation, is developed to produce phase functions for the objects to be detected in the image. The proposed methodology is applied on mesh...

A. Fehri, S. Velasco-Forero, F. Meyer (2016): Automatic Selection of Stochastic Watershed Hierarchies. European Conference of Signal Processing (EUSIPCO), Budapest (Hungary).
The segmentation, seen as the association of a partition with an image, is a difficult task. It can be decomposed in two steps: at first, a family of contours associated with a series of nested partitions (or hierarchy) is created and organized, then pertinent contours are extracted. A coarser partition is obtained by merging adjacent regions of a finer partition. The strength of a contour is then measured by the level of the hierarchy for which its two adjacent regions merge. We present an automatic segmentation strategy using a wide range of stochastic watershed hierarchies. For a given set...

E. Chevallier, F. Barbaresco, J. Angulo (2016): Kernel density estimation on the Siegel space applied to radar processing.
Main techniques of probability density estimation on Riemannian manifolds are reviewed in the case of the Siegel space. For computational reasons we chose to focus on the kernel density estimation. The main result of the paper is the expression of Pelletier's kernel density estimator. The method is applied to density estimation of reflection coefficients from radar observations.

J.C. Bricola, M. Bilodeau, S. Beucher (2016): Morphological processing of stereoscopic image superimpositions for disparity map estimation.
This paper deals with the problem of depth map computation from a pair of rectified stereo images and presents a novel solution based on the morphological processing of disparity space volumes. The reader is guided through the four steps composing the proposed method: the segmentation of stereo images, the diffusion of superimposition costs controlled by the segmentation, the resulting generation of a sparse disparity map which finally drives the estimation of the dense disparity map. An objective evaluation of the algorithm's features and qualities is provided and is accompanied by the...

V. Bortolussi, F. Borit, A. Chesnaud, M. Jeandin, M. Faessel, B. Figliuzzi, F. Willot, K. Roche, G. Surdon (2016): Cold spray of metal-polymer composite coatings onto carbon fiber-reinforced polymer (CFRP). ITSC 2016, Shanghai (China) 7 p..
The growing use of Polymer-Matrix Composite (PMC) materials within transport industry raises new security concerns, especially those due to lightning. To protect these electrically insulating materials, conductive coatings can be applied. Due to the high level of required properties, cold spray is believed to be an effective way to achieve these coatings. Recent studies showed that obstacles remained to be overcome when cold spraying metallic particles onto Carbon Fiber-Reinforced Polymer (CFRP). These are rather due to a poor adhesion of metallic particles onto carbon fibers, which prevents...

A. Giachetti, F. Fornasa, F. Parezzan, A. Saletti, L. Zambaldo, L. Zanini, F. Achilles, A.E. Ichim, F. Tombari, N. Navab, S. Velasco-Forero (2016): Shrec'16 Track: Retrieval of Human Subjects from Depth Sensor Data. Eurographics Workshop on 3D Object Retrieval, Lisbon (Portugal) 1—6.
In this paper we report the results of the SHREC 2016 contest on "Retrieval of human subjects from depth sensor data". The proposed task was created in order to verify the possibility of retrieving models of query human subjects from single shots of depth sensors, using shape information only. Depth acquisition of different subjects were realized under different illumination conditions, using different clothes and in three different poses. The resulting point clouds of the partial body shape acquisitions were segmented and coupled with the skeleton provided by the OpenNI software and provided...

B.R. Kiran, B. Stanciulescu, J. Angulo (2016): Unsupervised clustering of hyperspectral images of brain tissues by hierarchical non-negative matrix factorization. BIOIMAGING 2016, Rome (Italy) 2(77-84) 8.
Hyperspectral images of high spatial and spectral resolutions are employed to perform the challenging task of brain tissue characterization and subsequent segmentation for visualization of in-vivo images. Each pixel is a high-dimensional spectrum. Working on the hypothesis of pure-pixels on account of high spectral resolution, we perform unsupervised clustering by hierarchical non-negative matrix factorization to identify the pure-pixel spectral signatures of blood, brain tissues, tumor and other materials. This subspace clustering was further used to train a random forest for subsequent...

V. Machairas, T. Baldeweck, T. Walter, E. Decencière (2016): NEW GENERAL FEATURES BASED ON SUPERPIXELS FOR IMAGE SEGMENTATION LEARNING. International Symposium on Biomedical Imaging, Prague (Czech Republic).
Segmenting an image is usually one of the major and most challenging steps in the pipeline of biomedical image analysis. One classical and promising approach is to consider seg-mentation as a classification task, where the aim is to assign to each pixel the label of the objects it belongs to. Pixels are therefore described by a vector of features, where each feature is calculated on the pixel itself or, more frequently, on a sliding window centered on the pixel. In this work, we propose to replace the sliding window by superpixels, i.e. regions which adapt to the image content. We call the...

T. Chabardes, P. Dokládal, M. Faessel, M. Bilodeau (2016): A parallel, O(n), algorithm for unbiased, thin watershed. IEEE International Conference on Image Processing, Phoenix (United States).
The watershed transform is a powerful tool for morphological segmentation. Most common implementations of this method involve a strict hierarchy on gray tones in processing the pixels composing an image. Those dependencies complexify the efficient use of modern computational architectures. This paper aims at answering this problem by introducing a new way of simulating the waterflood that preserves the locality of data to be processed. We propose a region growth algorithm based on arrowing graphs that is strictly linear despite the valuation domain of input images. Simultaneous and disorderly...

B. Figliuzzi, D. Jeulin, M. Faessel, F. Willot, M. Koishi, N. Kowatari (2016): Modelling the microstructure and the viscoelastic behaviour of carbon black filled rubber materials from 3D simulations. Technische Mechanik 32(1-2) 22—46.
Volume fraction and spatial repartition of fillers impact the physical properties of rubber. Extended percolating networks of nano-sized fillers significantly modify the macroscopic mechanical properties of rubbers. Random models that describe the multiscale microstructure of rubber and efficient Fourier-based numerical algorithms are combined to predict the material’s mechanical properties. From TEM image analysis, various types of multiscale models were proposed and validated, accounting for the non-homogeneous distribution of fillers: in the present work, aggregates are located outside...

B. Abdallah, F. Willot, D. Jeulin (2016): Morphological modeling of three-phase microstructures of anode layers using SEM images. Journal of Microscopy 263(1) 51—63.
A general method is proposed to model 3D microstructures representative of three-phase anode layers used in fuel cells. The models are based on SEM images of cells with varying morphologies. The materials are first characterized using three morphological measurements: (cross-)covariances, granulometry and linear erosion. They are measured on segmented SEM images, for each of the three phases. Second, a generic model for three-phase materials is proposed. The model is based on two independent underlying random sets which are otherwise arbitrary. The validity of this model is verified using the...

J. Angulo (2016): Generalised morphological image diffusion. Nonlinear Analysis: Theory, Methods & Applications 134.
Relationships between linear and morphological scale-spaces have been considered by various previous works. The aim of this paper is to study how to generalise the diffusion-based approaches in order to introduce nonlinear filters whose effects mimic the asymmetric behaviour of morphological dilation and erosion, as well as other evolved morphological filters. A methodology based on the counter-harmonic mean is adopted here. Details of numerical implementation are discussed and results are provided to illustrate the various studied cases: isotropic, nonlinear and coherence-enhancing...

G. Franchi, J. Angulo (2016): Morphological Principal Component Analysis for Hyperspectral Image Analysis.
This paper deals with a problem of dimensionality reduction for hyperspectral images using the principal component analysis. Hyper-spectral image reduction is improved by adding structural/spatial information to the spectral information, by means of mathematical morphology tools. Then it can be useful in supervised classification for instance. The key element of the approach is the computation of a covariance matrix which integrates simultaneously both spatial and spectral information. Thanks to these new covariance matrices, new features can be extracted. To prove the efficiency of these new...

N. Lermé, P. Dokládal (2016): Geometry Analysis of Superconducting Cables For The Optimization of Global Performances. ICPRAM, Rome (Italy).
Superconducting cables have now become a mature technology for energy transport, high-field magnets (MRI, LHC) and fusion applications (ToreSupra, and eventually ITER and DEMO). The superconductors are extremely brittle and suffer from electrical damages brought by mechanical strain induced by electromagnetic field that they generate. An optimal wiring architecture, obtained by simulation, can limit these damages. However, the simulation is a complex process and needs validation. This validation is performed on real 3D samples by the means of image processing. Within this objective, this...

J. Escoda, F. Willot, D. Jeulin, J. Sanahuja, C. Toulemonde (2016): Influence of the multiscale distribution of particles on elastic properties of concrete. International Journal of Engineering Science 98 60—71.
The mechanical role of the shape of the aggregates, and their spatial distribution in concrete materials is examined. The effect on the macroscopic mechanical response as well as on the local stress fields are investigated by numerical means, making use of a recently developed Poisson-polyhedra model in which the aggregates have polyhedral shapes. Comparison is made with previous microstructure models of spheres. Full-field computations are carried out on large volume size using Fourier methods. The field maps are used to determine zones of highest stress. Furthermore, the scale separation...


List of all publications from the CMM, recorded on the HAL depository under the tag ENSMP_CMM.

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