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

Cyclin B–Cdk1 activates its own pump to get into the nucleus

The transition to mitosis requires extensive nuclear and cytoplasmic rearrangements that must be spatially and temporally coordinated. In this issue, Gavet and Pines (2010a. J. Cell Biol. doi:10.1083/jcb.200909144) report on a simple yet elegant mechanism as to how this is achieved. By monitoring the activity of cyclin B–Cdk1 in real time, the authors show that concomitant with its activation in the cytoplasm, the kinase complex is rapidly imported into the nucleus by modifying the activity of the nucleocytoplasmic transport machinery. Thus, cyclin B–Cdk1 activates its own pump to get into the nucleus

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

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