Johan Debayle

• Professor in Image Processing and Analysis
• Professor (Full) at Mines Saint-Étienne

Time-series classification (TSC) has been widely utilized across various domains, including brain-computer interfaces (BCI) for emotion recognition through electroencephalogram (EEG) signals. However, traditional methods often struggle to capture the complex emotional patterns present in EEG data. Recent advancements in encoding techniques have pro...

This research work aims to characterize the algal colonization of mortar surfaces using image analysis. The resistance of mortars to the biofouling is studied by means of an accelerated lab-scale test. A suspension of green algae Klebsormidium flaccidum, was performed to periodically sprinkle the mortar surfaces and digital images were acquired tha...

The geometrical modeling of granular objects is a complex challenge that exists in many scientific fields, such as the modeling of granular materials or rocks and coarse aggregates with applications in civil, mechanical, and chemical engineering. In this paper, a model called SPHERE (Stochastic Process for Highly Effective Radial Expansion) is prop...

p>Our study delves into the challenges of emotion recognition through electroencephalogram (EEG) signals in brain-computer interface systems. Recognizing the limitations of existing methods in accurately capturing intricate emotional patterns in EEG data, we propose a novel approach using asymmetric windowing recurrence plots (AWRP). This technique...

p>Our study delves into the challenges of emotion recognition through electroencephalogram (EEG) signals in brain-computer interface systems. Recognizing the limitations of existing methods in accurately capturing intricate emotional patterns in EEG data, we propose a novel approach using asymmetric windowing recurrence plots (AWRP). This technique...

Measuring the morphological properties of complex multiphase systems is a crucial problem in many areas of science and industry and is particularly difficult in dense environments with limited optical access. This paper presents a new approach capable of extracting three-dimensional (3D) information from spherical particle systems based solely on t...

EEG signals are the modality that is widely used to recognize human emotions. However, the limited data on EEG signals remains challenging because of the small recording participants, the need for an expert to interpret EEG signals, and the expensive cost of tools to record EEG signals. This research proposed the data augmentation schemes on the EE...

The main goal of this paper is to propose a method for the 3D morphological characterization of compact aggregates using 2D image analysis. The problem at hand is the 3D morphometric characterization of latex nanoparticle aggregates. The only available information is 2D projection images of these aggregates, one projection per aggregate. In this co...

First International Conference, ICAIDS 2021, Hyderabad, India, December 17–18, 2021, Revised Selected Papers This book constitutes selected papers presented at the First International Conference on Artificial Intelligence and Data Science, ICAIDS 2021, held in Hyderabad, India, in December 2021. The 43 papers presented in this volume were thorou...

The local binary model is a straightforward, dependable, and effective method for extracting relevant local information from images. However, because it only uses sign information in the local region, the local binary pattern (LBP) is ineffective at capturing discriminating characteristics. Furthermore, most LBP variants select a region with one sp...

An original 3D stochastic geometrical model has been developed to simulate the microstructural evolution of porous solid-oxide cell electrodes made of yttria-stabilized zirconia and nickel. The microstructural change induced by Ni agglomeration has been more specifically simulated. The model is based on random sets and algorithms for solving the li...

The main part of recycling processes are carried out in chemical engineering reactors that involve multiphase flows with dense dispersed phase. In a study and modeling approach of these processes, the description and characterization of hydrodynamic phenomena is crucial. A variety of techniques allows us to realize this type of measurement, but the...

An original stochastic model to simulate complex 3D microstructures of SOFC-electrodes with gradient and global heterogeneity has been developed. The synthetic microstructures generated by the model were compared to real microstructures of Ni-YSZ electrodes acquired by tomography. The ability of the model to generate representative microstructures...

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 perim...

A dynamic physically based model has been developed to unravel the relationships between the overall Solid Oxide Cells response and the reaction mechanisms taking place in the electrodes. This tool combines modules at three different length-scales: electrode microstructures, active functional layers, and single repeat unit. It allows computing the...

We introduce a particular localization of the Minkowski functionals to characterize and discriminate different random spatial structures. The aim of this paper is to present a method estimating the typical grain elongation ratio in a homogeneous Boolean model. The use of this method is demonstrated on a range of Boolean models of rectangles featuri...

Local Binary Pattern (LBP) are considered as a classical descriptor for texture analysis, it has mostly been used in pattern recognition and computer vision applications. However, the LBP gets information from a restricted number of local neighbors which is not enough to describe texture information, and the other descriptors that get a large numbe...

The increasing use of 3D models in many areas lead us to think about the impact of the different distortions that can affect the 3D object during the rendering process. These deformations are usually evaluated using geometric metrics, which have not a good correlation with human judgment, while the visual perceptual quality of 3D models is necessar...

The paper concerns a method for assessing similarity of realisations of random sets based on a construction of their morphological skeletons and a consequent covering of the realisations by unions of the so-called maximal discs. Since the realisations are considered to be binary images, the skeletons together with the corresponding discs can be vie...

The paper focuses on a new method for the inference of a parametric random spheroid from the observations of its 2D orthogonal projections. Such a stereological problem is well-known from the literature when the projections come from only one deterministic spheroid. Nevertheless, when the spheroid is random itself, the estimation of its distributio...

Mathematical Morphology (MM) is a tool that can be applied to many digital image processing tasks that include the reduction of impulsive or salt and pepper noise in grayscale images. The morphological filters used for this task are filters resulting from two basic operators: erosion and dilation. However, when the level of contamination of the ima...

The prediction of dry friction requires a quantification of the rheology of the tribological interface (third body). Until now this rheology has been characterized qualitatively by a broad description of its morphology (from powdery granular media to ductile continuous media) at the contact scale. The present work proposes to enrich this characteri...

Purpose: Utilization of computer-aided diagnosis (CAD) on radiological ultrasound (US) imaging has increased tremendously. The prominent CAD applications are found in breast and thyroid cancer investigation. To make appropriate clinical recommendations, it is important to accurately segment the cancerous object called a lesion. Segmentation is a cr...

This paper presents a simple and novel descriptor named Homogeneous Local Binary Pattern (HLBP) for texture analysis. The purpose of this description is to improve the Local Binary Pattern (LBP) approach basing on the impact of criterion homogeneous region using General Adaptive Neighborhood (GAN) principle. HLBP method is generated by using the cr...

A novel particle-based model is proposed to generate synthetic yet representative 3D microstructures of typical SOC electrodes. The model steps can be related to the real electrode manufacturing routes, classically via powders processing, making it a practical tool for electrodes design optimization. The representativeness of the synthetic microstr...

Ultrasound is widely utilized in radiological screening to achieve early cancer investigations. Alongside this utilization, the need of object detection and segmentation techniques highly increases as crucial procedure of computer aided diagnosis tool. In addition, the industrial revolution 4.0 also demands automation and digitization in every tech...

Time-Series Classification (TSC) has attracted a lot of attention in pattern recognition, because wide range of applications from different domains such as finance and health informatics deal with time-series signals. Bag of Features (BoF) model has achieved a great success in TSC task by summarizing signals according to the frequencies of "feature...

The reaction mechanism and the impact of microstructure on performances for a porous LSCF‐CGO composite used as O2 electrode in SOCs have been investigated. For this purpose, an integrated approach coupling (i) electrochemical testing, (ii) advanced 3D characterizations, and (iii) modeling was proposed. In this frame, a symmetrical cell was tested...

The mechanical and use properties of metal alloys depend on several factors, including the amount and the geometry of impurities (inclusions). In this context, image analysis enables these inclusions to be studied from digital images acquired by various systems such as optical/electron microscopy or X-ray tomography. This paper therefore aims to pr...

Go to iptutorials.science to download the complete codes in python or use the QR codes inside to access each tutorial correction.

In this paper a new approach to geometrically model and characterize 2D silhouette images of two-phase flows is proposed. The method consists of a 3D modeling of the particles population based on some morphological and interaction assumptions. It includes the following steps. First, the main analytical properties of the proposed model – which is an...

Time-Series Classification (TSC) has attracted a lot of attention in pattern recognition, because wide range of applications from different domains such as finance and health informatics deal with time-series signals. Bag of Features (BoF) model has achieved a great success in TSC task by summarizing signals according to the frequencies of "feature...

An original 3D stochastic model, based on the truncated plurigaussian random fields, has been adapted to simulate the complex microstructure of SOC electrodes. The representativeness of the virtual microstructures has been checked on several synchrotron X-ray and FIB-SEM tomographic reconstructions obtained on typical LSCF, LSC and Ni-YSZ electrode...

Image analysis is a widespread and performant tool for the characterization of particulate systems in chemical engineering. However, for bubbly flows, due to the wide range of particles size, shape and the appearance of large clusters resulting from particles projections overlapping at high hold-up, automatic particle detection remains a challenge....

Convolutional Neural Networks (CNN) has achieved a great success in image recognition task by automatically learning a hierarchical feature representation from raw data. While the majority of Time-Series Classification (TSC) literature is focused on 1D signals, this paper uses Recurrence Plots (RP) to transform time-series into 2D texture images an...

Optical methods for investigating multiphase flows are reviewed and discussed in the scope of the development of apparatus convenient for nuclear fuel reprocessing. Indeed, the various processes implemented (e.g. leaching, solvent extraction, filtration, crystallization, etc.) involve either liquid/gas, liquid/liquid and/or liquid/solid flows. Besi...

Optical methods for investigating multiphase flows are reviewed and discussed in the scope of the development of apparatus convenient for nuclear fuel reprocessing. Indeed, the various processes implemented (e.g. leaching, solvent extraction, filtration, crystallization, etc.) involve either liquid/gas, liquid/liquid and/or liquid/solid flows. Besi...

In this paper, the 2-D random closed sets (RACS) are studied by means of the Feret diameter, also known as the caliper diameter. More specifically, it is shown that a 2-D symmetric convex RACS can be approximated as precisely as we want by some random zonotopes (polytopes formed by the Minkowski sum of line segments) in terms of the Hausdorff dista...

In this paper, the 2-D random closed sets (RACS) are studied by means of the Feret diameter, also known as the caliper diameter. More specifically, it is shown that a 2-D symmetric convex RACS can be approximated as precisely as we want by some random zonotopes (polytopes formed by the Minkowski sum of line segments) in terms of the Hausdorff dista...

Road information plays an important role in many civilian and military applications. Road centerlines extraction from high-resolution remote sensing images can be used to update a transportation database. However, it is difficult to extract a complete road network from high-resolution images, especially when the color of road is close to that of ba...

This paper aims to propose a new feature and intensity-based image registration method. The proposed approach is based on the block matching algorithm : a displacement field is locally computed by matching spatially-invariant intensity sub-blocks of the images before performing an optimization algorithm from this vector field to estimate the transf...

In this paper, different texture descriptors are proposed for the automatic classification of skin lesions from dermoscopic images. They are based on color texture analysis obtained from (1) color mathematical morphology (MM) and Kohonen Self-Organizing Maps (SOM) or (2) Local Binary Patterns (LBPs), computed with the use of local adaptive neighbor...

This paper introduces a method for characterizing and classifying skin lesions in dermoscopic color images with the goal of detecting which ones are melanoma (cancerous lesions). The images are described by means of the Local Binary Patterns (LBPs) computed on geometrical feature maps of each color component of the image. These maps are extracted f...

The color logarithmic image processing (CoLIP) is a mathematical framework for the representation and processing of color images. It is psychophysically well justified since it is consistent with several human visual perception laws and characteristics. It is mathematically and computationally relevant since it allows to consider color images as ve...

In this paper an automatic classification method of skin lesions from dermoscopic images is proposed. This method is based on color texture analysis based both on color mathematical morphology and Kohonen Self-Organizing Maps (SOM), and it does not need any previous segmentation process. More concretely, mathematical morphology is used to compute a...

The CoLIP framework defines a vectorial space for color images. It is in accordance with the theories of visual perception (Weber, Fechner) as well as Hering’s trichromacy theory. It is mathematically well defined and computationally usable. This article recalls the fundamentals of the LIP framework for graytone images, and introduces the elementar...

The presented work is motivated by a pharmaceutical issue. Indeed, the production of drugs involves a crystallization process in solution depending on several parameters and their quality is closely linked to its geometrical characteristics (size, shape, quantity ...). Therefore, it is necessary to control the distribution of the “crystal geometry”...

In this paper we propose a method to characterize and estimate the variations of a random convex set Ξ0 in terms of shape, size and direction. The mean n-variogram γ (n) Ξ 0 : (u1 · · · un) → E[ν d (Ξ0 ∩(Ξ0 −u1) · · ·∩ (Ξ0 − un))] of a random convex set Ξ0 on R d reveals information on the nth order structure of Ξ0. Especially we will show that con...

This chapter is focused on spatially adaptive image processing for color images in the context of the General Adaptive Neighborhood Image Processing (GANIP) approach. The GANIP was first defined for gray-tone images and is here extended to color images. A set of local adaptive neighborhoods is defined for each image point, depending on the color in...

The quantitative evaluation of image segmentation is an important and difficult task that is required for making a decision on the choice of a segmentation method and for the optimal tuning of its parameter values. To perform this quantitative evaluation, dissimilarity criteria are relevant with respect to the human visual perception, contrary to m...

In this paper spatially adaptive Mathematical Morphology (MM) is studied for color images. More precisely, the General Adaptive Neighborhood Image Processing (GANIP) approach is generalized to color images. The basic principle is to define a set of locally Color Adaptive Neighborhoods (CAN), one for each point of the image, and to use them as adapt...

This paper introduces a new descriptor for characterizing and classifying the pixels of texture images by means of General Adaptive Neighborhoods (GANs). The GAN of a pixel is a spatial region surrounding it and fitting its local image structure. The features describing each pixel are then regionbased and intensity-based measurements of its corresp...

Road information has a fundamental role in modern society. Road extraction from optical satellite images is an economic and efficient way to obtain and update a transportation database. This paper presents an integrated method to extract urban main-road centerlines from satellite optical images. The proposed method has four main steps. First, gener...

Shape diagrams are integral geometric representations in the Euclidean plane introduced to study 2D connected compact sets. Such a set is represented by a point within a shape diagram whose coordinates are morphometrical functionals defined as normalized ratios of geometrical functionals. In addition, the General Adaptive Neighborhoods (GANs) are s...

Compression therapy is used in the management and the treatment of various forms of venous insufficiency ranging from the relief of heavy and achy legs to the treatment of more severe forms such as acute venous ulceration. However, the pressure needed to achieve clinical benefit is a matter of debate. The purpose of this study was to examine the tr...

The aim of this paper is to present a new projective stereological method that enables to estimate the size and the shape of a three-dimensional convex object from measurements only made on its two-dimensional projections. To do so, some geometrical and morphometrical measurements on the projected shadows of the three-dimensional convex object are...

In this paper, spatially and intensity adaptive morphology is introduced and studied in the context of the General Adaptive Neighborhood Image Processing (GANIP) approach. The combination of GAN (General Adaptive Neighborhood)-based filtering and semi-flat morphology is particularly efficient in the sense that the filtering is adaptive to the image...

Several imaging acquisition systems (confocal microscopy, computer tomography, positron emission tomography, magnetic resonance imaging.. ) provide 3D images allowing to investigate the microstructure of a large variety of materials (metallic alloys, biological cells and tissues, porous media.. ). Nevertheless, in order to generate effective numeri...

The aim of this article is to present a new projective stereological method which enables to estimate the size and the shape of a three-dimensional (3-D) convex geometrical object from measurements only made on some of its two-dimensional (2-D) projections. In order to do so, some geometrical and morphometrical measurements on the projected shadows...

This paper aims to introduce and study two novel metrics on gray tone images. These metrics are based on the General Adaptive Neighborhood Image Processing (GANIP) framework that enables to represent an image by spatial neighborhoods, named General Adaptive Neighborhoods (GAN) that fit to their local context. These metrics are generalized in the se...

This paper deals with the problem of shape reconstruction from an unorganized and not necessarily uniformly distributed point cloud with outliers. A shape reconstruction method based on a Delaunay filtration called LDA-α-shapes has been introduced in 2010 [1]. This method may be used to reconstruct 2-D or 3-D shapes from a non necessary uniformly d...

The light scattering cross-section of a certain class of aggregates is calculated by GMM theory. The aggregates are submicronic and are allowed to have various shapes. They consist of N spherical particles. The material is non-absorbing and optically hard. 1792 aggregates with N>13N>13 have been studied. The varied parameters are the shape and the...

Compression therapy is used in the management and the treatment of various forms of venous insufficiency ranging from the relief of heavy and achy legs to the treatment of more severe forms such as acute venous ulceration. However , the pressure needed to achieve clinical benefit is a matter of debate. The purpose of this study was to examine the t...

Quantification of the overlapping particles in crystallization processes is very important for the quality control of chemical products or drugs. We present a method of segmentation of polygonal-shaped (i.e., rectangles, regular/irregular prisms) and overlapping particles from in situ images during a crystallization process for measuring their size...

The image-processing techniques using spatially invariant transformations, with fixed operational windows, provide efficient and compact computing structures with the conventional separation between data and operations. To efficiently handle and process intensity images, it is necessary to represent image mappings, in a mathematically rigorous and...

Résumé La cristallisation discontinue d'oxalate d'ammonium (OA) a été étudiée en vue de la mise au point d'un modèle dynamique du procédé en solvant pur ou contaminé par des impuretés dissoutes. La concentration en soluté a été mesurée par spectroscopie ATR FTIR in situ, tandis que la phase solide dispersée était suivie par une sonde vidéo CCD imme...

This paper introduces pretopological image filtering in the context of the General Adaptive Neighborhood Image Processing (GANIP) approach. Pretopological filters act on gray level image while satisfying some topological properties. The GANIP approach enables to get an image representation and mathematical structure for adaptive image processing a...

A geometric-based method is proposed to recognize the overlapping particles of different polygonal shapes such as rectangular, regular and/or irregular prismatic particles in a gray tone image. The first step consists in extracting the salient corners, identified by their locations and orientations, of the overlapping particles. Although there are...