Analysis of Noisy Digital Contours with Adaptive Tangential Cover

International audienceThe notion of tangential cover, based on maximal segments, is a well-known tool to study the geometrical characteristics of a discrete curve. However, it is not robust to noise, while extracted contours from digital images typically contain noise and this makes the geometric analysis tasks on such contours difficult. To tackle this issue, we investigate in this paper a discrete structure, named Adaptive Tangential Cover (ATC), which is based on the notion of tangential cover and on a local noise estimator. More specifically, the ATC is composed of maximal segments with different widths deduced from the local noise values estimated at each point of the contour. Furthermore, a parameter-free algorithm is also presented to compute ATC. This study leads to the proposal of several applications of ATC on noisy digital contours: dominant point detection, contour length estimator, tangent/normal estimator, detection of convex and concave parts. An extension of ATC to 3D curves is also proposed in this paper. The experimental results demonstrate the efficiency of this new notion

Adaptive Tangential Cover for Noisy Digital Contours

International audienceThe notion of tangential cover, based on maximal segments, is a well-known tool to study the geometrical characteristics of a discrete curve. However, it is not adapted to noisy digital contours. In this paper, we propose a new notion, named Adaptive Tangential Cover, to study noisy digital contours. It relies on the meaningful thickness, calculated at each point of the contour, which permits to locally estimate the noise level. The Adaptive Tangential Cover is then composed of maximal blurred segments with appropriate widths, deduced from the noise level estimation. We present a parameter-free algorithm for computing the Adaptive Tangential Cover. Moreover an application to dominant point detection is proposed. The experimental results demonstrate the efficiency of this new notion

A discrete approach for decomposing noisy digital contours into arcs and segments

International audienceIn the paper, we present a method for decomposing a discrete noisy curve into arcs and segments which are the frequent primitives in digital images. This method is based on two tools: dominant point detection using adaptive tangential cover and tangent space representation of the polygon issued from detected dominant points. The experiments demonstrate the robustness of the method w.r.t. noise

An algorithm to decompose noisy digital contours

International audienceFrom the previous digital contour decomposition algorithm, this paper focuses on the implementation and on the reproduction of the method linking to an online demonstration. This paper also gives improvement of the previous method with details on the intern parameter choice and shows how to use the C++ source code in other context

The 400d Galaxy Cluster Survey Weak Lensing Programme: I: MMT/Megacam Analysis of CL0030+2618 at z=0.50

The mass function of galaxy clusters at high redshifts is a particularly useful probe to learn about the history of structure formation and constrain cosmological parameters. We aim at deriving reliable masses for a high-redshift, high-luminosity sample of clusters of galaxies selected from the 400d survey of X-ray selected clusters. Here, we will focus on a particular object, CL0030+2618 at z=0.50 Using deep imaging in three passbands with the MEGACAM instrument at MMT, we show that MEGACAM is well-suited for measuring gravitational shear. We detect the weak lensing signal of CL0030+2618 at 5.8 sigma significance, using the aperture mass technique. Furthermore, we find significant tangential alignment of galaxies out to ~10 arcmin or >2r_200 distance from the cluster centre. The weak lensing centre of CL0030+2618 agrees with several X-ray measurements and the position of the brightest cluster galaxy. Finally, we infer a weak lensing virial mass of M_200=7.5 10^{14} M_sun for CL0030+2618. Despite complications by a tentative foreground galaxy group in the line of sight, the X-ray and weak lensing estimates for CL0030+2618 are in remarkable agreement. This study paves the way for the largest weak lensing survey of high-redshift galaxy clusters to date.Comment: 32 pages, 24 figures, submitted to Astronomy & Astrophysics; fixed some LaTeX issues, now 30 pages v3: Improved version accepted by Astronomy & Astrophysic

A Statistical-Topological Feature Combination for Recognition of Isolated Hand Gestures from Kinect Based Depth Images

International audienceReliable hand gesture recognition is an important problem for automatic sign language recognition for the people with hearing and speech disabilities. In this paper, we create a new benchmark database of multi-oriented, isolated ASL numeric images using recently launched Kinect V2. Further, we design an effective statistical-topological feature combinations for recognition of the hand gestures using the available V1 sensor dataset and also over the new V2 dataset. For V1, our best accuracy is 98.4% which is comparable with the best one reported so far and for V2 we achieve an accuracy of 92.2% which is first of its kind

Curvature Estimation along Noisy Digital Contours by Approximate Global Optimization

International audienceIn this paper we introduce a new curvature estimator along digital contours, that we called Global Min-Curvature estimator (GMC). As opposed to previous curvature estimators, it considers all the possible shapes that are digitized as this contour, and selects the most probable one with a global optimization approach. The GMC estimator exploits the geometric properties of digital contours by using local bounds on tangent directions defined by the maximal digital straight segments. The estimator is then adapted to noisy contours by replacing maximal segments with maximal blurred digital straight segments. Experiments on perfect and damaged digital contours are performed and in both cases, comparisons with other existing methods are presented

Galaxy alignments: Observations and impact on cosmology

Galaxy shapes are not randomly oriented, rather they are statistically aligned in a way that can depend on formation environment, history and galaxy type. Studying the alignment of galaxies can therefore deliver important information about the physics of galaxy formation and evolution as well as the growth of structure in the Universe. In this review paper we summarise key measurements of galaxy alignments, divided by galaxy type, scale and environment. We also cover the statistics and formalism necessary to understand the observations in the literature. With the emergence of weak gravitational lensing as a precision probe of cosmology, galaxy alignments have taken on an added importance because they can mimic cosmic shear, the effect of gravitational lensing by large-scale structure on observed galaxy shapes. This makes galaxy alignments, commonly referred to as intrinsic alignments, an important systematic effect in weak lensing studies. We quantify the impact of intrinsic alignments on cosmic shear surveys and finish by reviewing practical mitigation techniques which attempt to remove contamination by intrinsic alignments.Comment: 52 pages excl. references, 16 figures; minor changes to match version published in Space Science Reviews; part of a topical volume on galaxy alignments, with companion papers arXiv:1504.05456 and arXiv:1504.0554