In this paper we propose a simple but efficient methodology for text detection in video frames. The method is based on the gradient information and edge map selection. In the proposed method we first find the gradient of the image and then enhance the gradient information. We later binarized the enhanced gradient image and select the edges by taking the intersection of the edge map with the bin...

Nonnegative Matrix Factorization (NMF) solves the following problem: find nonnegative matrices A ∈ RM×R + and X ∈ RR×T + such that Y ∼= AX, given only Y ∈ RM×T and the assigned index R. This method has found a wide spectrum of applications in signal and image processing, such as blind source separation, spectra recovering, pattern recognition, segmentation or clustering. Such a factorization is...

We provide a unified optimization view of iterative Hessian sketch (IHS) and iterative dual random projection (IDRP). We establish a primal-dual connection between the Hessian sketch and dual random projection, and show that their iterative extensions are optimization processes with preconditioning. We develop accelerated versions of IHS and IDRP based on this insight together with conjugate gr...

Although many methods exist for intensity modulated radiotherapy (IMRT) fluence map optimization for crisp data, based on clinical practice, some of the involved parameters are fuzzy. In this paper, the best fluence maps for an IMRT procedure were identifed as a solution of an optimization problem with a quadratic objective function, where the prescribed target dose vector was fuzzy. First, a d...

We introduce a flexible optimization framework for nuclear norm minimization of matrices with linear structure, including Hankel, Toeplitz and moment structures, and catalog applications from diverse fields under this framework. We discuss various first-order methods for solving the resulting optimization problem, including alternating direction methods of multipliers, proximal point algorithms...

An orthogonal subspace minimization method is developed for finding multiple (eigen) solutions to the defocusing nonlinear Schrödinger equation with symmetry. Since such solutions are unstable, gradient search algorithms are very sensitive to numerical errors, will easily break symmetry, and will lead to unwanted solutions. Instead of enforcing a symmetry by the Haar projection, the authors use...

This paper describes an active-set algorithm for nonlinear programming that solves a parametric linear programming subproblem at each iteration to generate an estimate of the active set. A step is then computed by solving an equality constrained quadratic program based on this active-set estimate. This approach respresents an extension of the standard sequential linear-quadratic programming (SL...