0000000000003352
AUTHOR
Yvon Voisin
Contribution to a marker-free system for human motion analysis
This paper presents a novel approach to human gait analysis using a marker-free system. The devised acquisition system is composed of three synchronized and calibrated charge coupled device cameras. The aim of this work is to recognize in gray level image sequences the leg of a walking human and to reconstruct it in the three-dimensional space. An articulated threedimensional (3D) model of the human body, based on the use of tapered superquadric curves, is first introduced. A motion-based segmentation, using morphological operators, is then applied to the image sequences in order to extract the boundaries of the leg in motion. A reconstruction process, based on the use of a least median of …
Design of a customized pattern for improving color constancy across camera and illumination changes
International audience; This paper adresses the problem of color constancy on a large image database acquired with varying digital cameras and lighting conditions. Automatic white balance control proposed by an available commercial camera is not sufficient to provide reproducible color classification. A device-independent color representation may be obtained by applying a chromatic adaptation transform, from a calibrated color checker pattern included in the field of view. Instead of using the standard Macbeth color checker, we suggest to select judicious colors to design a customized pattern from contextual information. A comparative study demonstrates that this approach insures a stronger…
Spatially variant dimensionality reduction for the visualization of multi/hyperspectral images
International audience; In this paper, we introduce a new approach for color visu- alization of multi/hyperspectral images. Unlike traditional methods, we propose to operate a local analysis instead of considering that all the pixels are part of the same population. It takes a segmentation map as an input and then achieves a dimensionality reduction adaptively inside each class of pixels. Moreover, in order to avoid unappealing discon- tinuities between regions, we propose to make use of a set of distance transform maps to weigh the mapping applied to each pixel with regard to its relative location with classes' centroids. Results on two hyperspec- tral datasets illustrate the efficiency of…
Three-dimensional level-curve scanning based on intersection of laser lines
A dimensional measurement system that also tracks object movements is presented here. The method directly yields the level curves of an object. It is an extension of collimation methods, coupled with the use of structured lighting with features formed from several luminous planes intersecting in a single line. This line defines a set of points of the space at a fixed distance Z 0 from the measuring head. The locus of the points of the object where the lighting is reduced to a single line is the level curve sought. The introduction of an asymmetry into the lighting structure permits one to determine the direction as well as an approximate value of the value of the distance to the level curve…
Visual servo control using orthinormal polynomial
This paper describes an application of the visual servoing approach to vision-based control in robotics. The basic idea addresses the use of a vision sensor in the feedback loop within the controlled vision framework. It consists in tracking of arbitrary 3-D objects travelling at unknown velocities in a 2-D space (depth is given as known). Once the necessary modeling stage is performed, the framework becomes one of automatic control, and naturally stability, performance and robustness questions arise. Here, we consider to track line segments corresponding to the edges extracted from the image being analyzed. Two representations for a line segment are presented and discussed, and an appropri…
Needle-shape quality control by shadowgraphic image processing
International audience; We propose a needle-shape quality-control method. To this end, we have devised a new acquisition system that combines a camera and a backlight. Needle measurements are carried out at a micrometric scale using shadowgraphic image processing. Our method not only distinguishes good needles from bad ones, but also allows classifying flawed needles into various categories of defects. This classification is important because some categories of defects can affect the entire production, whereas others do not. The results of our needle-shape quality-control method are validated using real samples directly off the manufacturing line. Needles are correctly classified at >97%, a…
Sélection de bandes pour la visualisation d'images spectrales : une approche basée sur l'étude de saillance
National audience; De nos jours, la plupart des technologies d'affichage numériques sont basées sur le paradigme qu'une combinaison de trois couleurs primaires spécifiques est suffisante pour la reproduction d'une couleur quelconque pour l'oeil humain. Par ailleurs, les dispositifs d'affichage multispectraux ne sont pas encore monnaie courante sur le marché du multimédia. Ainsi, lorsqu'il s'agit de visualiser une image spectrale en couleur, sur un écran traditionnel, seuls trois bandes peuvent être utilisées simultanément, ce qui implique une réduction de dimensionnalité. Cette étape doit permettre la préservation d'un maximum de contenu informatif tout en préservant contrastes et couleurs …
Automatic object detection in point clouds based on knowledge guided algorithms
The modeling of real-world scenarios through capturing 3D digital data has been proven applicable in a variety of industrial applications, ranging from security, to robotics and to fields in the medical sciences. These different scenarios, along with variable conditions, present a challenge in discovering flexible appropriate solutions. In this paper, we present a novel approach based on a human cognition model to guide processing. Our method turns traditional data-driven processing into a new strategy based on a semantic knowledge system. Robust and adaptive methods for object extraction and identification are modeled in a knowledge domain, which has been created by purely numerical strate…
A Variational Approach for Denoising Hyperspectral Images Corrupted by Poisson Distributed Noise
Poisson distributed noise, such as photon noise is an important noise source in multi- and hyperspectral images. We propose a variational based denoising approach, that accounts the vectorial structure of a spectral image cube, as well as the poisson distributed noise. For this aim, we extend an approach for monochromatic images, by a regularisation term, that is spectrally and spatially adaptive and preserves edges. In order to take the high computational complexity into account, we derive a Split Bregman optimisation for the proposed model. The results show the advantages of the proposed approach compared to a marginal approach on synthetic and real data.
Detection of rupture lines for active scanning
Corner and junction detection is an important preprocessing step in image registration, data fusion, object recognition, and many other tasks. This work deals with corner and junction detection of characteristic features of the structure resulting from cross-pattern projection. The ultimate aim is to adapt the positions and orientation of the cross-pattern projections to what has been observed. The use of this projected light pattern in the framework of active vision allows us to identify certain points of interest on 3-D objects, to directly acquire a synthesis, which thus permits simplified detection, measurement, recognition, or tracking. We present detection methods for corners and junc…
Saliency-Based Band Selection For Spectral Image Visu- alization
International audience; In this paper, we introduce a new band selection ap- proach for the color visualization of spectral images. Un- like traditional methods, we propose to make a selection out of a comparison of the saliency maps of the individual spectral channels. This allows to assess how different they are in terms of prominent features. A comparison metric based on Shannon's information theory at the second and third order is presented and results are subjectively and ob- jectively compared to other dimensionality reduction tech- niques on three datasets, demonstrating the efficiency of the proposed approach.
A Neural Network-Based Algorithm for 3D Multispectral Scanning Applied to Multimedia
We describe a new stereoscopic system based on a multispectral camera and an LCD-Projector. The novel concept we want to show consists in the use of multispectral information for 3D-scenes reconstruction. Each 3D point is linked to a curve representing the spectral reflectance. This latter is a physical representation of the matter and presents the advantage over color information, which is perceptual, that it is independent from both illuminant and observer. We first present an easy methodology to geometrically and spectrally calibrate such a system. We then describe an algorithm for recovering 3D coordinates based on triangulation and an algorithm for reflectance curves reconstruction bas…
Salient Pixels and Dimensionality Reduction for Display of Multi/Hyperspectral Images
International audience; Dimensionality Reduction (DR) of spectral images is a common approach to different purposes such as visualization, noise removal or compression. Most methods such as PCA or band selection use either the entire population of pixels or a uniformly sampled subset in order to compute a projection matrix. By doing so, spatial information is not accurately handled and all the objects contained in the scene are given the same emphasis. Nonetheless, it is possible to focus the DR on the separation of specific Objects of Interest (OoI), simply by neglecting all the others. In PCA for instance, instead of using the variance of the scene in each spectral channel, we show that i…
Statistical analysis of engraving traces on a 3D digital model of prehistoric stone stelae
International audience; Studying cultural heritage artefacts, using 3D digital models, is gaining interest. It not only allows applications in documentation and visualisation, but also permits further contact-less examination. In this paper, we are presenting a statistical analysis of stone engravings based on features that were semi-automatically extracted from 3D acquisition data. Our objects of study are two Neolithic stone stelae and a faithful replica that was created in the course of an archaeological study. We use common statistical methods and investigate the populations of depth and diameter of the engraving traces, as well as their correlation. We observe that the erosion of the t…
A Constrained Band Selection Method Based on Information Measures for Spectral Image Color Visualization
International audience; We present a new method for the visualization of spectral images, based on a selection of three relevant spectral channels to build a Red-Green-Blue composite. Band selection is achieved by means of information measures at the first, second and third orders. Irrelevant channels are preliminarily removed by means of a center-surround entropy comparison. A visualization-oriented spectrum segmentation based on the use of color matching functions allows for computational ease and adjustment of the natural rendering. Results from the proposed method are presented and objectively compared to four other dimensionality reduction techniques in terms of naturalness and informa…
Representation and estimation of spectral reflectances using projection on PCA and wavelet bases
In this article, we deal with the problem of spectral reflectance function representation and estimation in the context of multispectral imaging. Because the reconstruction of such functions is an inverse problem, slight variations in input data completely skew the expected results. Therefore, stabilizing the reconstruction process is necessary. To do this, we propose to use wavelets as basis functions, and we compare those with Fourier and PCA bases. We present the idea and compare these three methods, which belong to the class of linear models. The PCA method is training-set dependent and confirms its robustness when applied to reflectance estimation of the training sets. Fourier and wave…
An Efficient Method for the Visualization of Spectral Images Based on a Perception-Oriented Spectrum Segmentation
We propose a new method for the visualization of spectral images. It involves a perception-based spectrum segmentation using an adaptable thresholding of the stretched CIE standard observer colormatching functions. This allows for an underlying removal of irrelevant channels, and, consequently, an alleviation of the computational burden of further processings. Principal Components Analysis is then used in each of the three segments to extract the Red, Green and Blue primaries for final visualization. A comparison framework using two different datasets shows the efficiency of the proposed method.
Subpixel determination of imperfect circles characteristics
This article deals with the problem of the determination of characteristics of imperfect circular objects in discrete images, namely the radius and center coordinates. To limit distortion, a multi-level method based on active contours was developed. Its originality is to furnish a set of geometric envelopes in one pass, with a correspondence between grayscale and a regularity scale. The adequacy of this approach was tested with several methods, among them is the Radon-based method. More particularly, this study indicates the relevance of the use of active contours combined with a Radon transform-based method which was improved using a fitting considering the discrete implementation of the R…
Segmentation et métrologie des sinus de Valsalva à partir de ciné-IRM
Automatic segmentation of Valsalva sinuses from cine-MRI
Calibration of a three-dimensional reconstruction system using a structured light source
We present a method for calibrating a range finder system composed of a camera and a structured light source. The system is used to reconstruct the three-dimensional (3-D) surface of an object. This is achieved by projecting a pattern, represented by a set of regularly spaced spots, on the surface of the object using the structured light source. An image of the illuminated object is next taken and by analyzing the distortion of the projected pattern, the 3-D surface of the object can be reconstructed. This reconstruction operation can be envisaged only if the system is calibrated. Instead of using a classical calibration method, which is based on the determination of the matrices that chara…
Extraction et analyse automatiques des sinus de Valsalva à partir de séquences IRM
MRI appears to be particularly attractive for the study of the Sinuses of Valsalva (SV), however there is no global consensus on their suitable measurements. In this paper, we propose a new method to automatically evaluate the SV from cine-MRI in a cross-sectional orientation. It consists in the extraction of the shape, the detection of relevant points (commissures, cusps and the centre of the SV), the measure of associated distances and in a classification of the SV as bicuspid or tricuspid. Our method was tested on 23 patient examinations and radii calculations were compared with manual processing. The classification of the valve as tricuspid or bicuspid was correct for all the cases. Mor…
An evaluation framework and a benchmark for multi/hyperspectral image compression
International audience; This paper benchmarks three multi/hyperspectral image compression approaches: the classic Multi-2D compression approach and two different implementations of 3D approach (Full 3D and Hybrid). All approaches are combined with a spectral PCA decorrelation stage to optimize performance. These three compression approaches are compared within a larger comparison framework than the conventionally used PSNR, which includes eight metrics divided into three families. The comparison is carried out with regard to variations in bitrates, spatial, and spectral dimensions variations of images. The time and memory consumption difference between the three approaches is also discussed…
Improving color correction across camera and illumination changes by contextual sample selection
International audience; In many tasks of machine vision applications, it is important that recorded colors remain constant, in the real world scene, even under changes of the illuminants and the cameras. Contrary to the human vision system, a machine vision system exhibits inadequate adaptability to the variation of lighting conditions. Automatic white bal- ance control available in commercial cameras is not sufficient to pro- vide reproducible color classification. We address this problem of color constancy on a large image database acquired with varying digi- tal cameras and lighting conditions. A device-independent color repre- sentation may be obtained by applying a chromatic adaptation…
Saliency in spectral images
International audience; Even though the study of saliency for color images has been thoroughly investigated in the past, very little attention has been given to datasets that cannot be displayed on traditional computer screens such as spectral images. Nevertheless, more than a means to predict human gaze, the study of saliency primarily allows for measuring infor- mative content. Thus, we propose a novel approach for the computation of saliency maps for spectral images. Based on the Itti model, it in- volves the extraction of both spatial and spectral features, suitable for high dimensionality images. As an application, we present a comparison framework to evaluate how dimensionality reduct…
A class-separability-based method for multi/hyperspectral image color visualization
In this paper, a new color visualization technique for multi- and hyperspectral images is proposed. This method is based on a maximization of the perceptual distance between the scene endmembers as well as natural constancy of the resulting images. The stretched CMF principle is used to transform reflectance into values in the CIE L*a*b* colorspace combined with an a priori known segmentation map for separability enhancement between classes. Boundaries are set in the a*b* subspace to balance the natural palette of colors in order to ease interpretation by a human expert. Convincing results on two different images are shown.
A sensor-data-based denoising framework for hyperspectral images
Many denoising approaches extend image processing to a hyperspectral cube structure, but do not take into account a sensor model nor the format of the recording. We propose a denoising framework for hyperspectral images that uses sensor data to convert an acquisition to a representation facilitating the noise-estimation, namely the photon-corrected image. This photon corrected image format accounts for the most common noise contributions and is spatially proportional to spectral radiance values. The subsequent denoising is based on an extended variational denoising model, which is suited for a Poisson distributed noise. A spatially and spectrally adaptive total variation regularisation term…
Image Segmentation and Object Extraction for Automatic Diatoms Classification
The diatoms are unicellular algae of great interest in paleontology, aquatic ecology, and forensic medicine, among others. Currently, there are more than 100 000 known species distributed in aquatic ecosystems. For that reason, there is a big interest in the automatic classification of diatom images, however, the preliminary process applied to isolate the diatom from the background is a complex task. In this paper, we propose a segmentation method and an object-extraction procedure to extract the diatom from the background. First, we binarize the image by searching the optimal threshold in the histogram based on its cumulative distribution function. Then we eliminate, under some spatial cri…
A Model to Characterize the D-T Layer of ICF Targets by Backlit Optical Shadowgraphy
A numerical model is presented in order to modelize the bright ring that appears in backlit optical shadowgraphy on a transparent hollow sphere with a solid deuterium-tritium layer inside. This novel model is based on computational calculations applied to the problem of the targets used in inertial confinement fusion. The model takes into account the influences of the optical imaging system (numerical aperture, source divergence, camera resolution, etc.) and the effect of the capsule itself, diameter, thickness, and refractive index, and allows one to analyze the inner surface of a capsule in terms of thickness and roughness.
Preprocessing of region of interest localization based on local surface curvature analysis for three-dimensional reconstruction with multiresolution
We present an approach to integrate a preprocessing step of the region of interest ROI localization into 3-D scanners laser or ste- reoscopic. The definite objective is to make the 3-D scanner intelligent enough to localize rapidly in the scene, during the preprocessing phase, the regions with high surface curvature, so that precise scanning will be done only in these regions instead of in the whole scene. In this way, the scanning time can be largely reduced, and the results contain only per- tinent data. To test its feasibility and efficiency, we simulated the prepro- cessing process under an active stereoscopic system composed of two cameras and a video projector. The ROI localization is…
Computation of the area in the discrete plane: Green’s theorem revisited
International audience; The detection of the contour of a binary object is a common problem; however, the area of a region, and its moments, can be a significant parameter. In several metrology applications, the area of planar objects must be measured. The area is obtained by counting the pixels inside the contour or using a discrete version of Green's formula. Unfortunately, we obtain the area enclosed by the polygonal line passing through the centers of the pixels along the contour. We present a modified version of Green's theorem in the discrete plane, which allows for the computation of the exact area of a two-dimensional region in the class of polyominoes. Penalties are introduced and …
A Comparative Study and an Evaluation Framework of Multi/Hyperspectral Image Compression
In this paper, we investigate different approaches for multi/hyperspectral image compression. In particular, we compare the classic multi-2D compression approach and two different implementations of 3D approach (full 3D and hybrid) with regards to variations in spatial and spectral dimensions. All approaches are combined with a weighted Principal Component Analysis (PCA) decorrelation stage to optimize performance. For consistent evaluation, we propose a larger comparison framework than the conventionally used PSNR, including eight metrics divided into three families. The results show the weaknesses and strengths of each approach.
Comparative study of multi-2D, Full 3D and hybrid strategies for multi/hyperspectral image compression
In this paper, we investigate appropriate strategies for multi/hyperspectral image compression. In particular, we compare the classic multi-2D compression strategy and two different implementations of 3D strategies (Full 3D and hybrid). All strategies are combined with a PCA decorrelation stage to optimize performance. For multi-2D and hybrid strategies, we propose a weighted version of PCA. Finally, for consistent evaluation, we propose a larger comparison framework than the conventionally used PSNR. The results are significant and show the weaknesses and strengths of each strategy.
An adaptive-PCA algorithm for reflectance estimation from color images
This paper deals with the problem of spectral reflectance estimation from color camera outputs. Because the reconstruction of such functions is an inverse problem, stabilizing the reconstruction process is highly desirable. One way to do this is to decompose reflectance function on a basis functions like PCA. The present work proposes an algorithm making PCA adaptive in reflectance estimation from a color camera output. We propose to adapt the PCA basis derivation by selecting, for each sample, the more relevant elements from the training set elements. The adaptivity criterion is achieved by a likelihood measurement. Finally, the spectral reflectance estimation results are evaluated with th…