scholarly journals Automatic Contouring from Scattered Data Points

1982 ◽  
Vol 25 (1) ◽  
pp. 7-11 ◽  
Author(s):  
I. P. Schagen
Keyword(s):  
Scattered Data ◽  
Data Points ◽  
Automatic Contouring

AUTOMATIC CONTOURING USING BICUBIC FUNCTIONS

Geophysics ◽  
1972 ◽  
Vol 37 (4) ◽  
pp. 669-674 ◽  
Author(s):  
R. C. Hessing ◽  
Henry K. Lee ◽  
Alan Pierce ◽  
Eldon N. Powers
Keyword(s):  
Spatial Distribution ◽  
Cross Sections ◽  
Digital Computer ◽  
Smooth Surface ◽  
Contour Line ◽  
Contour Maps ◽  
Volume Calculations ◽  
Contour Lines ◽  
Data Points ◽  
Automatic Contouring

A method is described for using a digital computer to construct contour maps automatically. Contour lines produced by this method have correct relations to given discrete data points regardless of the spatial distribution of these points. The computer‐generated maps are comparable to those drawn manually. The region to be contoured is divided into quadrilaterals whose vertices include the data points. After supplying values at each of the remaining vertices by using a surface‐fitting technique, bicubic functions are constructed on each quadrilateral to form a smooth surface through the data points. Points on a contour line are obtained from these surfaces by solving the resulting cubic equations. The bicubic functions may be used for other calculations consistent with the contour maps, such as interpolation of equally spaced values, calculation of cross‐sections, and volume calculations.

Triangulated Surface Construction From Scattered 3-D Points

1992 ◽  
Author(s):  
Sridhar Vajapeyam ◽  
Michael Keefe
Keyword(s):  
Mechanical Design ◽  
Three Dimensional ◽  
Scattered Data ◽  
Three Dimensions ◽  
Triangulated Surface ◽  
Biological Surfaces ◽  
Gabriel Graph ◽  
Mri Scans ◽  
Data Points ◽  
Delaunay Triangles

Abstract A three-dimensional analog to the Gabriel Graph structure is defined and an algorithmic procedure for the construction of a triangulated surface from scattered data points in three dimensions is developed based on the concept on three-dimensional Gabriel Graphs. The algorithm does not require the points to be in the form of a grid or on contours. The closest point 3-D Delaunay triangulation of the points is first constructed and the Delaunay triangles that satisfy the Gabriel Graph criterion are identified. From this set of triangles, extraneous triangles are removed, resulting in a triangulated open surface passing through all the given data points. This surface can then be subjected to smoothing algorithms if necessary and a smooth surface of the desired continuity can be constructed using available interpolation techniques. The algorithm can be used for constructing surfaces from scattered data in mechanical design, geographic terrain modeling and modeling biological surfaces from CT scans and MRI scans.

Fitting scattered data points with ball B-Spline curves using particle swarm optimization

2018 ◽  
Vol 72 ◽  
pp. 1-11 ◽  
Author(s):  
Zhongke Wu ◽  
Xingce Wang ◽  
Yan Fu ◽  
Junchen Shen ◽  
Qianqian Jiang ◽  
...  
Keyword(s):  
Particle Swarm Optimization ◽  
Particle Swarm ◽  
Scattered Data ◽  
Swarm Optimization ◽  
B Spline ◽  
Spline Curves ◽  
Data Points

A Technology to Multi-Resolution Surface Reconstruction

2013 ◽  
Vol 805-806 ◽  
pp. 1933-1936
Author(s):  
Tong Tong Zhu ◽  
Gang Xu ◽  
Ming Cong Ma ◽  
Xing Ye Liu
Keyword(s):  
Surface Reconstruction ◽  
Characteristic Curve ◽  
Scattered Data ◽  
Subdivision Surfaces ◽  
Texture Characteristic ◽  
Reconstruction Process ◽  
Mesh Model ◽  
Data Points ◽  
Image Edge ◽  
Short Time

An approach is presented based on scattered data points subdivision surfaces to achieve multi-resolution surface reconstruction techniques. In the surface reconstruction process, based on gray-scale image edge detection ideological eigenvalues scattered data analysis, these features will generate texture characteristic curve values tessellation, thus forming a multi-resolution mesh model structure; After testing, the technology is not only surface reconstruction short time, while the constructed subdivision surfaces can reflect the characteristics of the original details of the data.

AUTOMATIC CONTOURING OF IRREGULARLY SPACED DATA

Geophysics ◽  
1968 ◽  
Vol 33 (3) ◽  
pp. 424-430 ◽  
Author(s):  
Chester R. Pelto ◽  
Thomas A. Elkins ◽  
H. A. Boyd
Keyword(s):  
Least Squares ◽  
Mathematical Theory ◽  
Mathematical Rule ◽  
Data Points ◽  
Pass Through ◽  
Automatic Contouring ◽  
Polynomial Surface

Machine contouring of irregularly spaced observations can be performed in three basic steps: (1) In large areas with no data points, control values are interpolated by a specified mathematical rule. These values keep the next step “well behaved.” (2) A regional polynomial surface is fitted by least squares to the original and interpolated points. (3) The surface of step (2) is deformed smoothly to pass through the original observations. The final product is similar in appearance to hand‐drawn maps. The complete mathematical theory is developed in an appendix.

Sign in / Sign up

Export Citation Format

Share Document