Search results for "computer vision"
showing 10 items of 2353 documents
Distance-based functions for image comparison
1999
The interest in digital image comparison is steadily growing in the computer vision community. The definition of a suitable comparison measure for non-binary images is relevant in many image processing applications. Visual tasks like segmentation and classification require the evaluation of equivalence classes. Measures of similarity are also used to evaluate lossy compression algorithms and to define pictorial indices in image content based retrieval methods. In this paper we develop a distance-based approach to image similarity evaluation and we present several image distances which are based on low level features. The sensitivity and eAectiveness are tested on real data. ” 1999 Published…
Block Based Deconvolution Algorithm Using Spline Wavelet Packets
2010
This paper presents robust algorithms to deconvolve discrete noised signals and images. The idea behind the algorithms is to solve the convolution equation separately in different frequency bands. This is achieved by using spline wavelet packets. The solutions are derived as linear combinations of the wavelet packets that minimize some parameterized quadratic functionals. Parameters choice, which is performed automatically, determines the trade-off between the solution regularity and the initial data approximation. This technique, which id called Spline Harmonic Analysis, provides a unified computational scheme for the design of orthonormal spline wavelet packets, fast implementation of the…
Weighted distance-based trees for ranking data
2017
Within the framework of preference rankings, the interest can lie in finding which predictors and which interactions are able to explain the observed preference structures, because preference decisions will usually depend on the characteristics of both the judges and the objects being judged. This work proposes the use of a univariate decision tree for ranking data based on the weighted distances for complete and incomplete rankings, and considers the area under the ROC curve both for pruning and model assessment. Two real and well-known datasets, the SUSHI preference data and the University ranking data, are used to display the performance of the methodology.
On 1-Laplacian Elliptic Equations Modeling Magnetic Resonance Image Rician Denoising
2015
Modeling magnitude Magnetic Resonance Images (MRI) rician denoising in a Bayesian or generalized Tikhonov framework using Total Variation (TV) leads naturally to the consideration of nonlinear elliptic equations. These involve the so called $1$-Laplacian operator and special care is needed to properly formulate the problem. The rician statistics of the data are introduced through a singular equation with a reaction term defined in terms of modified first order Bessel functions. An existence theory is provided here together with other qualitative properties of the solutions. Remarkably, each positive global minimum of the associated functional is one of such solutions. Moreover, we directly …
Decomposable multiphase entropic descriptor
2013
To quantify degree of spatial inhomogeneity for multiphase materials we adapt the entropic descriptor (ED) of a pillar model developed to greyscale images. To uncover the contribution of each phase we introduce the suitable 'phase splitting' of the adapted descriptor. As a result, each of the phase descriptors (PDs) describes the spatial inhomogeneity attributed to each phase-component. Obviously, their sum equals to the value of the overall spatial inhomogeneity. We apply this approach to three-phase synthetic patterns. The black and grey components are aggregated or clustered while the white phase is the background one. The examples show how the valuable microstuctural information related…
Estimation of orientation characteristic of fibrous material
2001
A new statistical method for estimating the orientation distribution of fibres in a fibre process is suggested where the process is observed in the form of a degraded digital greyscale image. The method is based on line transect sampling of the image in a few fixed directions. A well-known method based on stereology is available if the intersections between the transects and fibres can be counted. We extend this to the case where, instead of the intersection points, only scaled variograms of grey levels along the transects are observed. The nonlinear estimation equations for a parametric orientation distribution as well as a numerical algorithm are given. The method is illustrated by a real…
Resuming Shapes with Applications
2004
Many image processing tasks need some kind of average of different shapes. Frequently, different shapes obtained from several images have to be summarized. If these shapes can be considered as different realizations of a given random compact set, then the natural summaries are the different mean sets proposed in the literature. In this paper, new mean sets are defined by using the basic transformations of Mathematical Morphology (dilation, erosion, opening and closing). These new definitions can be considered, under some additional assumptions, as particular cases of the distance average of Baddeley and Molchanov. The use of the former and new mean sets as summary descriptors of shapes is i…
Steady-state and tracking analysis of a robust adaptive filter with low computational cost
2007
This paper analyses a new adaptive algorithm that is robust to impulse noise and has a low computational load [E. Soria, J.D. Martin, A.J. Serrano, J. Calpe, and J. Chambers, A new robust adaptive algorithm with low computacional cost, Electron. Lett. 42 (1) (2006) 60-62]. The algorithm is based on two premises: the use of the cost function often used in independent component analysis and a fuzzy modelling of the hyperbolic tangent function. The steady-state error and tracking capability of the algorithm are analysed using conservation methods [A. Sayed, Fundamentals of Adaptive Filtering, Wiley, New York, 2003], thus verifying the correspondence between theory and experimental results.
A new method for linear affine self-calibration of stationary zooming stereo cameras
2012
This paper presents a simple, yet effective, method to recover the affine structure of a scene from a (stereo) pair of stationary zooming cameras. The proposed method solely relies on point correspondences across images and no knowledge about the scene whatsoever is required. Our method exploits implicit properties of the projective camera matrices of zooming cameras and allows to estimate the affine structure of a scene by solving a linear system of equations. The 3D reconstruction results obtained by using our method, on both real and simulated data, have remarkably validated its feasibility.
3-D shape reconstruction in an active stereo vision system using genetic algorithms
2003
Abstract The recovery of 3-D shape information (depth) using stereo vision analysis is one of the major areas in computer vision and has given rise to a great deal of literature in the recent past. The widely known stereo vision methods are the passive stereo vision approaches that use two cameras. Obtaining 3-D information involves the identification of the corresponding 2-D points between left and right images. Most existing methods tackle this matching task from singular points, i.e. finding points in both image planes with more or less the same neighborhood characteristics. One key problem we have to solve is that we are on the first instance unable to know a priori whether a point in t…