Displaying similar documents to “Denoising Manifolds for Dimension”

Adaptive Document Image Binarization with Application in Processing Astronomical Logbooks

Laskov, Lasko (2012)

Serdica Journal of Computing

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ACM Computing Classification System (1998): I.7, I.7.5. Recently, the digitalization of the astronomical scientific heritage has been considered an important task that can facilitate much researches in astronomy. The creation of digital libraries and databases of astronomical photographic plates brings up the problem of digitalization astronomical logbooks, since the data contained in them is crucial for the usage of the plates. An optical character recognition (OCR) system...

Local detection of defects from image sequences

Ewaryst Rafajłowicz, Marek Wnuk, Wojciech Rafajłowicz (2008)

International Journal of Applied Mathematics and Computer Science

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Our aim is to discuss three approaches to the detection of defects in continuous production processes, which are based on local methods of processing image sequences. These approaches are motivated by and applicable to images of hot metals or other surfaces, which are uniform at a macroscopic level, when defects are not present. The first of them is based on the estimation of fractal dimensions of image cross-sections. The second and third approaches are compositions of known techniques,...

Integrated region-based segmentation using color components and texture features with prior shape knowledge

Mehryar Emambakhsh, Hossein Ebrahimnezhad, Mohammad Hossein Sedaaghi (2010)

International Journal of Applied Mathematics and Computer Science

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Segmentation is the art of partitioning an image into different regions where each one has some degree of uniformity in its feature space. A number of methods have been proposed and blind segmentation is one of them. It uses intrinsic image features, such as pixel intensity, color components and texture. However, some virtues, like poor contrast, noise and occlusion, can weaken the procedure. To overcome them, prior knowledge of the object of interest has to be incorporated in a top-down...

Simultaneous Localization And Mapping: A feature-based probabilistic approach

Piotr Skrzypczyński (2009)

International Journal of Applied Mathematics and Computer Science

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This article provides an introduction to Simultaneous Localization And Mapping (SLAM), with the focus on probabilistic SLAM utilizing a feature-based description of the environment. A probabilistic formulation of the SLAM problem is introduced, and a solution based on the Extended Kalman Filter (EKF-SLAM) is shown. Important issues of convergence, consistency, observability, data association and scaling in EKF-SLAM are discussed from both theoretical and practical points of view. Major...

Segmentation of MRI data by means of nonlinear diffusion

Radomír Chabiniok, Radek Máca, Michal Beneš, Jaroslav Tintěra (2013)

Kybernetika

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The article focuses on the application of the segmentation algorithm based on the numerical solution of the Allen-Cahn non-linear diffusion partial differential equation. This equation is related to the motion of curves by mean curvature. It exhibits several suitable mathematical properties including stable solution profile. This allows the user to follow accurately the position of the segmentation curve by bringing it quickly to the vicinity of the segmented object and by approaching...

Accent Recognition for Noisy Audio Signals

Ma, Zichen, Fokoue, Ernest (2014)

Serdica Journal of Computing

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It is well established that accent recognition can be as accurate as up to 95% when the signals are noise-free, using feature extraction techniques such as mel-frequency cepstral coefficients and binary classifiers such as discriminant analysis, support vector machine and k-nearest neighbors. In this paper, we demonstrate that the predictive performance can be reduced by as much as 15% when the signals are noisy. Specifically, in this paper we perturb the signals with different levels...

Quad-tree Based Finite Volume Method for Diffusion Equations with Application to SAR Imaged Filtering

Zuzana Krivá, Juraj PAPČO, Jakub VANKO (2015)

Acta Universitatis Palackianae Olomucensis. Facultas Rerum Naturalium. Mathematica

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In this paper we present a method to remove the noise by applying the Perona Malik algorithm working on an irregular computational grid. This grid is obtained with a quad-tree technique and is adapted to the image intensities—pixels with similar intensities can form large elements. We apply this algorithm to remove the speckle noise present in SAR images, i.e., images obtained by radars with a synthetic aperture enabling to increase their resolution in an electronic way. The presence...