A geometric dissimilarity criterion between Jordan spatial mosaics. Theoretical aspects and application to segmentation evaluation

International audienceAn image segmentation process often results in a special spatial set, called a mosaic, as the subdivision of a domain S within the n-dimensional Euclidean space. In this paper, S will be a compact domain and the study will be focused on finite Jordan mosaics, that is to say mosaics with a finite number of regions and where the boundary of each region is a Jordan hypersurface. The first part of this paper addresses the problem of comparing a Jordan mosaic to a given reference Jordan mosaic and introduces the (Epsilon) dissimilarity criterion. The second part will show that the (Epsilon) dissimilarity criterion can be used to perform the evaluation of image segmentation processes. It will be compared to classical criterions in regard to several geometric transformations. The pros and cons of these criterions are presented and discussed, showing that the dissimilarity criterion outperforms the other ones

Surface Topography and Texture Restoration from Sectional Optical Imaging by Focus Analysis

International audienceThis chapter focused on image restoration of both topographical and textural information of an observed surface from a registered image sequence acquired by optical sectioning through the common concepts of Shape-From-Focus (SFF) and Extended Depth-of-Field (EDF). More particularly, the essential step of these complementary processes of restoration: the focus measurement, is examined. After a brief specialized review, we introduced novel evolved focus measurements that push the limits of state-of-the-art ones in terms of sensitivity and robustness, in order to cope with various frequently encountered acquisition issues

Quantitative evaluation of image registration techniques in the case of retinal images

International audienceIn human retina observation (with non mydriatic optical microscopes), an image registration process is often employed to enlarge the field of view. Analyzing all the images takes a lot of time. Numerous techniques have been proposed to perform the registration process. Its good evaluation is a difficult question that is then raising. This article presents the use of two quantitative criterions to evaluate and compare some classical feature-based image registration techniques. The images are first segmented and the resulting binary images are then registered. The good quality of the registration process is evaluated with a normalized criterion based on the ϵ dissimilarity criterion, and the figure of merit criterion (fom), for 25 pairs of images with a manual selection of control points. These criterions are normalized by the results of the affine method (considered as the most simple method). Then, for each pair, the influence of the number of points used to perform the registration is evaluated

Automatic quantitative evaluation of image registration techniques with the "epsilon" dissimilarity criterion in the case of retinal images.

International audienceIn human retina observation (with non mydriatic optical microscopes), a registration process is often employed to enlarge the field of view. For the ophthalmologist, this is a way to spare time browsing all the images. A lot of techniques have been proposed to perform this registration process, and indeed, its good evaluation is a question that can be raised. This article presents the use of the "epsilon" dissimilarity criterion to evaluate and compare some classical featurebased image registration techniques. The problem of retina images registration is employed as an example, but it could also be used in other applications. The images are first segmented and these segmentations are registered. The good quality of this registration is evaluated with the "epsilon" dissimilarity criterion for 25 pairs of images with a manual selection of control points. This study can be useful in order to choose the type of registration method and to evaluate the results of a new one

Characterization of the corneal endothelial mosaic and comparison with simulated tessellations modeled withGaussian random fields

International audienceIn this article, manually segmented corneal endothelial mosaic will be characterized with spatial statistical functionsand criteria issued from granulometry and morphometry. A novel approach to simulate spatial tessellationswith Gaussian random fields with Gaussian and Bessel covariance functions, watershed and h-maxima is reported.Finally, these random spatial tessellations will be characterized and compared to corneal mosaics

A feature-based dense local registration of pairs of retinal images.

International audienceA method for spatial registering pairs of digital images of the retina is presented, using intrinsic feature points (landmarks) and dense local transformation. First, landmarks, i.e. blood vessel bifurcations, are extracted from both retinal images using filtering followed by thinning and branch point analysis. Correspondances are found by topological and structural comparisons between both retinal networks. From this set of matching points, a displacement field is computed and, finally, one of the two images is transformed. Due to complex retinal registration problem, the presented transformation is dense, local and adaptive. Experimental results established the effectiveness and the interest of the dense registration method

Roughness variability estimation of microscopic surfaces during engineering wear process-Application to total hip implant

International audienceThis paper proposes a new method to estimate the roughness changes from topographic features of microscopic surfaces during an engineering wear process. We demonstrate that the evolution of the significant upcrossings of surface topography is the most efficient way to estimate the roughness changes associated with the small-scale changes during the time of wear process. The motivation of this work comes from the fact that the surface roughness is, largely, interpolated with many important mechanical and physical phenomena, such as friction, and wear behaviour during the mechanical contact between joined and sliding surfaces. A special application is investigated on UHMWPE (Ultra High Molecular Weight Polythene) components involved in total hip implants. The aim is to understand the in-vitro wear mechanism of the UHMWPE surface by estimating its roughness evolution

Color Correction in the Framework of Color Logarithmic Image Processing

International audienceThe Logarithmic Image Processing (LIP) approach is a mathematical framework developed for the representation and processing of images valued in a bounded intensity range. The LIP theory is physically and psychophysically well justified since it is consistent with several laws of human brightness perception and with the multiplicative image formation model. In this paper, the so-called Color Logarithmic Image Processing (CoLIP) framework is introduced. This novel framework expands the LIP theory to color images in the context of the human color visual perception. Color images are represented by their color tone functions that can be combined by means of basic operations, addition, scalar multiplication and subtraction, opening new pathways for color image processing. In order to highlight the CoLIP relevance with color constancy, a color correction method based on the subtraction is proposed and tested on CoLIP approach and Logarithmic hUe eXtension (LUX) approach, also based on the LIP theory, on differently illuminated images: underwater images with a blue illuminant, and indoor images with yellow illuminant

VISUAL PERCEPTION BASED AUTOMATIC RECOGNITION OF CELL MOSAICS IN HUMAN CORNEAL ENDOTHELIUMMICROSCOPY IMAGES

The human corneal endothelium can be observed with two types of microscopes: classical optical microscope for ex-vivo imaging, and specular optical microscope for in-vivo imaging. The quality of the cornea is correlated to the endothelial cell density and morphometry. Automatic methods to analyze the human corneal endothelium images are still not totally efficient. Image analysis methods that focus only on cell contours do not give good results in presence of noise and of bad conditions of acquisition. More elaborated methods introduce regional informations in order to performthe cell contours completion, thus implementing the duality contour-region. Their good performance can be explained by their connections with several basic principles of human visual perception (Gestalt Theory and Marr's computational theory)

Binarization of the gray scale images of droplets during dropwise condensation on textured surfaces

Session: Image Analysis IIInternational audienceIn this research two methods for recognizing water droplets that are formed during dropwise condensation on the flat and pillared substrates are presented. The aim of these methods is to binarize the gray scale images of the droplets taken by a CCD camera in order to extract the information related to the droplets size and density