Geometric transformations such as scaling or rotation are common tools employed by forgery creators. These procedures are typically based on a resampling and interpolation step. The interpolation process brings specific periodic properties into the image. In this paper, we show how to detect these properties. Our aim is to detect all possible geometric transformations in the image being investigated. Furthermore, as the proposed method, as well as other existing detectors, is sensitive to noise, we also briefly show a simple method capable of detecting image noise inconsistencies. Noise is a common tool used to conceal the traces of tampering.

A network of multi modal sensors with distributed and embedded computations is con-sidered for a video surveillance and monitoring application. Practical factors limiting the video surveillance of large areas are highlighted. A network of line-of-sight sensors and mobile-agents based computations are proposed to increase the e ectiveness. CMOS digi-tal cameras in which both sampling and quantization occur on the sensor focal plane are more suitable for this application. These cameras operate at very high video frame rates and are easily synchronized to acquire images synaptically across the entire network. Also, they feature highly localized short term memories and include some SIMD parallel computa-tions as an integral part of the image acquisition. This new framework enables distributed computation for piecewise stereovision across the camera network, enhanced spatio-temporal fusion, and super resolution imaging of steadily moving subjects. A top level description of the monitor, locate and track model of a surveillance and monitoring task is presented. A qualitative assessment of several key elements of the mobile agents based computation for tracking persistent tokens moving across the entire area is outlined. The idea is to have as

Abstract—This paper establishes a new coherent framework to extend the class of unitary warping operators to the case of discrete–time sequences. Providing some a priori considerations on signals, we show that the class of discrete–time warping operators finds a natural description in linear shift– invariant spaces. On such spaces, any discrete–time warping operator can be seen as a non–uniform weighted resampling of the original signal. Then, gathering different results from the non–uniform sampling theory, we propose an efficient iterative algorithm to compute the inverse discrete–time warping operator and we give the conditions under which the warped sequence can be inverted. Numerical examples show that the inversion error is of the order of the numerical round–off limitations after few iterations. Index Terms—Time–frequency, Unitary equivalence, Implementation of time–warping operators, Non–stationary filtering. I.

This paper explores numerical solutions of optimal control problems using B--Spline curves. It is aimed to give a general framework on how to use B--Splines to formulate optimal control problems and to solve them numerically using Nonlinear Trajectory Generation software package. E#ects of the selection of the B--Spline parameters, such as, number of intervals, smoothness, piecewise polynomial orders, number of berak points, on the solution of an optimal control problem are investigated. Formulation of optimal control problems involving complex arbitrary shape obstacles and tabular data using B--Splines and tensor product B--Spline curves are also studied. Illustrative examples of these issues are presented.

In this paper, we propose a new interpolatory subdivision scheme for generating nice-looking curvature-continuous curves of round shapes. The scheme is based on a diffusion of normals. Given a subdivided polyline, the new polyline vertices inserted at the the splitting step are updated in order to fit diffused (averaged with appropriate weights) normals. Although the resulting interpolatory subdivision scheme is non-stationary, nonlinear, and nonuniform from the traditional point of view, the scheme is easy to implement because the same simple geometric procedure for generating new vertices is used at each subdivision step. According to our experiments, the scheme is robust and demonstrate very good convergence properties.

Abstract—Except some extremely special cases, signal resampling was generally considered to be irreversible because of strong attenuation of high frequencies after interpolation. In this paper, we prove that signal resampling based on polynomial interpolation can be reversible even for integer signals, i.e., the original signal can be reconstructed losslessly from the resampled data. By using matrix factorization, we also propose a reversible method for uniform shifted resampling and uniform scaled and shifted resampling. The new factorization yields three elementary integer-reversible matrices. The method is actually a new way to compute linear transforms and a lossless integer implementation of linear transforms with the factor matrices. It can be applied to integer signals by in-place integer-reversible computation, which needs no auxiliary memory to keep the original sample data for the transformation during the process or for “undo ” recovery after the process. Some examples of low-order resampling solutions are also presented in this paper and our experiments show that the resampling error relative to the original signal is comparable to that of the traditional irreversible resampling. Index Terms—Factorial polynomials, integer-to-integer transforms, PLUS factorization of matrices, resampling, Stirling

This paper provides a new variational paradigm to measure the smoothness of unit vector fields on spatial domains, leading to new methods for smoothing and interpolating such datasets. Our point of view is to consider unit vector fields as linear forms acting on reproducing kernel Hilbert spaces of vector fields or tensors and work with the dual norm, leading to new variational problems and algorithms. We prove, in particular, that these variational problems are well-posed, in the sense that optimal solutions exist in the space of unit vector fields. Experimental results are based on synthetic data and diffusion tensor–magnetic resonance imaging datasets.

Based on the results of [8], [9] and [12], in this paper we present a calculus algorithm for the study of the compressible fluid’s stationary movement through profile grids, on an axial–symmetric flow–surface, in variable thickness of stratum. We show the applicability of the boundary element methods (BEM) with real values, and the possibility of solving the integral equation of the velocity potential by using the successive approximation method w.r.t. the parameters ρ (fluid’s density) and h (thickness variation of fluid stratum), and using the Lagrangian interpolation formula through five points for the calculation of the derivatives of the velocity potential.

Abstract. Estimating the disparity field between two stereo images is a common task in computer vision, e.g., to determine a dense depth map. Variational methods currently are among the most accurate techniques for dense disparity map reconstruction. In this paper a multi-level adaptive technique is combined with a multigrid approach that allows the variational method to achieve real-time performance (on a CPU). The multi-level adaptive technique refines the grid only at peculiarities in the solution. Thereby it reduces the computational effort and ensures that the reconstruction quality is kept almost the same. Further, we introduce a technique that adapts the regularizer, used in the variational approach, dependend on the the current state of the optimization. This improves the reconstruction quality. Our real-time approach is evaluated on standard datasets and it is shown to perform better than other real-time disparity estimation approaches. 1

Abstract – Discrete Wavelet Transform (DWT) foveated compression can be used in real-time video processing frameworks for reducing the communication overhead. Such algorithms lead into high rate compression results due to the fact that the information loss is isolated outside a region of interest (ROI). The fovea compression can also be applied to other classic transforms such as the commonly used discrete cosine transform (DCT). An analysis has then been performed showing different error and compression rates for the DWT-based and the DCT-based foveated compression algorithms. Simulation results show that with foveated compression high ratio of compression can be achieved while keeping high quality over the designed ROI.