Search results for "Curvelet"
showing 10 items of 12 documents
Approximation of piecewise smooth functions and images by edge-adapted (ENO-EA) nonlinear multiresolution techniques
2008
Abstract This paper introduces and analyzes new approximation procedures for bivariate functions. These procedures are based on an edge-adapted nonlinear reconstruction technique which is an intrinsically two-dimensional extension of the essentially non-oscillatory and subcell resolution techniques introduced in the one-dimensional setting by Harten and Osher. Edge-adapted reconstructions are tailored to piecewise smooth functions with geometrically smooth edge discontinuities, and are therefore attractive for applications such as image compression and shock computations. The local approximation order is investigated both in L p and in the Hausdorff distance between graphs. In particular, i…
Sparse Image Representation by Directionlets
2010
Despite the success of the standard wavelet transform (WT) in image processing in recent years, the efficiency and sparsity of its representation are limited by the spatial symmetry and separability of its basis functions built in the horizontal and vertical directions. One-dimensional discontinuities in images (edges or contours), which are important elements in visual perception, intersect too many wavelet basis functions and lead to a non-sparse representation. To capture efficiently these elongated structures characterized by geometrical regularity along different directions (not only the horizontal and vertical), a more complex multidirectional (M-DIR) and asymmetric transform is requi…
Designing a framework for assisting depression severity assessment from facial image analysis
2015
Depression is one of the most common mental disorders affecting millions of people worldwide. Developing adjunct tools aiding depression assessment is expected to impact overall health outcomes and treatment cost reduction. To this end, platforms designed for automatic and non-invasive depression assessment could help in detecting signs of the disease on a regular basis, without requiring the physical presence of a mental health professional. Despite the different approaches that can be found in the literature, both in terms of methods and algorithms, a fully satisfactory system for the automatic assessment of depression severity has not been presented as yet. This paper describes a propose…
Video-Based Depression Detection Using Local Curvelet Binary Patterns in Pairwise Orthogonal Planes
2016
International audience; Depression is an increasingly prevalent mood disorder. This is the reason why the field of computer-based depression assessment has been gaining the attention of the research community during the past couple of years. The present work proposes two algorithms for depression detection, one Frame-based and the second Video-based, both employing Curvelet transform and Local Binary Patterns. The main advantage of these methods is that they have significantly lower computational requirements, as the extracted features are of very low dimensionality. This is achieved by modifying the previously proposed algorithm which considers Three-Orthogonal-Planes, to only Pairwise-Ort…
"Towards a "fingerprint" of paper network; separating forgeries from genuine by the properties of fibre structure"
2014
A novel method is introduced for distinguishing counterfeit banknotes from genuine samples. The method is based on analyzing differences in the networks of paper fibers. The main tool is a curvelet-based algorithm for measuring the distribution of overall fiber orientation and quantifying its anisotropy. The use of a couple or more appropriate parameters makes it possible to distinguish forgeries from genuine samples as concentrated point clouds in a two- or three-dimensional parameter space. Furthermore, the techniques of making watermarks is investigated by comparing genuine and counterfeit €50 banknotes. In addition, the so-called wire markings are shown to differ significantly from each…
Using the fibre structure of paper to determine authenticity of the documents: analysis of transmitted light images of stamps and banknotes.
2014
A novel method is presented for distinguishing postal stamp forgeries and counterfeit banknotes from genuine samples. The method is based on analyzing differences in paper fibre networks. The main tool is a curvelet-based algorithm for measuring overall fibre orientation distribution and quantifying anisotropy. Using a couple of more appropriate parameters makes it possible to distinguish forgeries from genuine originals as concentrated point clouds in two- or three-dimensional parameter space.
Towards a "fingerprint" of paper network; separating forgeries from genuine by the properties of fibre structure
2014
A novel method is introduced for distinguishing counterfeit banknotes from genuine samples. The method is based on analyzing differences in the networks of paper fibers. The main tool is a curvelet-based algorithm for measuring the distribution of overall fiber orientation and quantifying its anisotropy. The use of a couple or more appropriate parameters makes it possible to distinguish forgeries from genuine samples as concentrated point clouds in a two- or three-dimensional parameter space. Furthermore, the techniques of making watermarks is investigated by comparing genuine and counterfeit e50 banknotes. In addition, the so-called wire markings are shown to differ significantly from each…
Curvelet-based method for orientation estimation of particles from optical images
2014
A method based on the curvelet transform is introduced to estimate the orientation distribution from two-dimensional images of small anisotropic particles. Orientation of fibers in paper is considered as a particular application of the method. Theoretical aspects of the suitability of this method are discussed and its efficiency is demonstrated with simulated and real images of fibrous systems. Comparison is made with two traditionally used methods of orientation analysis, and the new curvelet-based method is shown to perform better than these tradi- tional methods. peerReviewed
Directionlets: Anisotropic Multidirectional representation with separable filtering
2006
In spite of the success of the standard wavelet transform (WT) in image processing in recent years, the efficiency of its representation is limited by the spatial isotropy of its basis functions built in the horizontal and vertical directions. One-dimensional (1-D) discontinuities in images (edges and contours) that are very important elements in visual perception, intersect too many wavelet basis functions and lead to a nonsparse representation. To efficiently capture these anisotropic geometrical structures characterized by many more than the horizontal and vertical directions, a more complex multidirectional (M-DIR) and anisotropic transform is required. We present a new lattice-based pe…
Curvelet-based method for orientation estimation of particles
2013
A method based on the curvelet transform is introduced for estimating from two-dimensional images the orientation distribution of small anisotropic particles. Orientation of fibers in paper is considered as a particular application of the method. Theoretical aspects of the suitability of this method are discussed and its efficiency is demonstrated with simulated and real images of fibrous systems. Comparison is made with two traditionally used methods of orientation analysis, and the new curvelet-based method is shown to perform clearly better than these traditional methods.