In this work, we propose a surface fitting strategy based on a two-step model to remove noise from digital images. In the first step, we minimize the total variation energy functional of an image by using the projection gradient method in order to obtain the dual variable as the smoothed normal vector. In the second step, we try to find a surface as the recovered image to fit the smoothed norma...

In this work one year hourly solar radiation data are analyzed and modeled. Using a 2-D surface fitting approach, a novel model is developed for the general behavior of the solar radiation. The mathematical formulation of the 2-D surface model is obtained. The accuracy of the analytical surface model is tested and compared with another surface model obtained from a feed-forward Neural Network(N...

sented, where cost is defined to be the product of time and the number of processors used [19]. Using a newly proposed computational model called the mesh-of-unshuffle network, Chung and Lin [7] presented an O(log m log n)-time parallel algorithm using O(mn/(log m log n)) processors. On a hypercube network, a similar result was presented by Lin and Chung [20]. Using the pipelining strategy [11]...

Non-uniform rational B-spline (NURBS) surface fitting from data points is wildly used in the fields of computer aided design (CAD), medical imaging, cultural relic representation and object-shape detection. Usually, the measured data acquired from coordinate measuring systems is neither gridded nor completely scattered. The distribution of this kind of data is scattered in physical space, but t...

This paper presents scalable parallel algorithms for high dimensional surface fitting and predictive modelling which are used in data mining applications. These algorithms are based on techniques like finite elements, thin plate splines, wavelets and additive models. They all consist of two steps: First, data is read from secondary storage and a linear system is assembled. Secondly, the linear ...

This article presents a new and direct approach for fitting a subdivision surface from an irregular and dense triangle mesh of arbitrary topological type. All feature edges and feature vertices of the original mesh model are first identified. A topologyand feature-preserving mesh simplification algorithm is developed to further simplify the dense triangle mesh into a coarse mesh. A subdivision ...

Examination of sealants recovered at their moment of failure offers clues to factors which played a role in failure. The fitting surfaces of 10 failed sealants recovered immech’ately after placement, and 14 winch had failed after several months in the mouth were examined by scanning electron microscopy. Large areas of the fitting surfaces were smooth, with only localized regions showing evidenc...

We describe a method based on the Hough transform to compute a set of parameters that completely describe line segments. By complete, we mean the description includes the endpoints of each segment as well as the number of points along the segment, and, assuming a noise model N, the parameter(s) of N. The method involves fitting a surface locally to the Hough array, where the variables of the fi...

Because the application of surface fitting algorithms exerts a considerable fuzzy influence on the mathematical features of kinetic energy distribution, their relation mechanism in different external conditional parameters must be quantitatively analyzed. Through determining the kinetic energy value of each selected representative position coordinate point by calculating kinetic energy paramete...

This paper shows a new approach for non-linear least squares fitting with NURBS as curves and surfaces to measured data by the Gauss-Newton method. A Trust Region algorithm is used to reach global convergence as well as variable substitution and simple bounds. Key–Words: Non-linear least squares, NURBS, curve and surface fitting, reverse engineering, optimisation, GaussNewton