Dimension-Descending Algorithm for Spherical Delaunay Triangulation

2011 ◽  
Vol 130-134 ◽  
pp. 2915-2919
Author(s):  
Ping Duan ◽  
Jia Tian Li ◽  
Jia Li
Keyword(s):  
Delaunay Triangulation ◽  
Time Complexity ◽  
Image Point ◽  
Spherical Space ◽  
Projected Image ◽  
Plane Image ◽  
Projection Center ◽  
Space Data ◽  
Construction Algorithms ◽  
Main Construction

Spherical Delaunay triangulation (SDT) which is a powerful tool to represent, organize and analyze spherical space data has become a focus of spherical GIS research. Projection stitching algorithm is one of the main construction algorithms of SDT. The basic idea of stitching algorithm is that the sphere is divided into two hemispheres to avoid projected image point coincidence. So, the practicality of projection stitching algorithm is lower because of merging two hemispheres. Aimed at the disadvantage of projection stitching algorithm, this paper puts forward a new algorithm to construct SDT used perspective projection principle. The projection center is placed on sphere to establish one-to-one mapping between spherical space points and plane image points. Experiment shows that the time complexity of our algorithm depends on Delaunay triangulation construction algorithm of the plane.

A Fast 3-D Visualization Methodology Using Characteristic Views of Objects

1998 ◽  
Vol 08 (01) ◽  
pp. 97-114 ◽  
Author(s):  
Soochan Hwang ◽  
Sang-Young Cho ◽  
Taehyung Wang ◽  
Phillip C.-Y. Sheu
Keyword(s):  
Finite Number ◽  
Real Time ◽  
Time Complexity ◽  
Object Oriented ◽  
Equivalence Classes ◽  
Visualization Method ◽  
Tree Algorithm ◽  
Projected Image ◽  
Characteristic Views ◽  
Run Time

This paper describes a 3-D visualization method based on the concept of characteristic views (CVs). The idea of characteristic views was derived based on the observation that the infinite possible views of a 3-D object can be grouped into a finite number of equivalence classes so that within each class all the views are isomorphic in the sense that they have the same line-junction graphs. To visualize the changes of scenes in real time, the BSP tree algorithm is known to be efficient in a static environment in which the viewpoint can be changed easily. However, if a scene consists of many objects and each object consists of many polygons, the time complexity involved in traversing a BSP tree increases rapidly so that the original BSP tree algorithm may not be efficient. The method proposed in this paper is object-oriented in the sense that, for all viewpoints, at the preprocessing stage the ordering for displaying the objects is determined. At run time, the objects are displayed based on a pre-calculated ordering according to the viewpoint. In addition, a CV is used as a basic 2-D projected image of a 3-D object.

scholarly journals OUTPUT SENSITIVE CONSTRUCTION OF THE DELAUNAY TRIANGULATION OF POINTS LYING IN TWO PLANES

1996 ◽  
Vol 06 (01) ◽  
pp. 1-14 ◽  
Author(s):  
JEAN-DANIEL BOISSONNAT ◽  
ANDRÉ CÉRÉZO ◽  
OLIVIER DEVILLERS ◽  
MONIQUE TEILLAUD
Keyword(s):  
Delaunay Triangulation ◽  
Time Complexity ◽  
Dimensional Space ◽  
3 Dimensional

In this paper, we propose an algorithm to compute the Delaunay triangulation of a set [Formula: see text] of n points in 3-dimensional space when the points lie in 2 planes. The algorithm is output-sensitive and optimal with respect to the input and the output sizes. Its time complexity is O(n log n+t), where t is the size of the output, and the extra storage is O(n).

scholarly journals A Boundary Construction Algorithm for a Complex Planar Point Set

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Zhenxiu Liao ◽  
Guodong Shi
Keyword(s):  
Delaunay Triangulation ◽  
State Of The Art ◽  
Rough Boundary ◽  
Boundary Extraction ◽  
Point Density ◽  
Local Areas ◽  
Point Set ◽  
Boundary Construction ◽  
Construction Algorithms ◽  
Concave Envelopes

It is difficult to extract the boundary of complex planar points with nonuniform distribution of point density, concave envelopes, and holes. To solve this problem, an algorithm is proposed in this paper. Based on Delaunay triangulation, the maximum boundary angle threshold is introduced as the parameter in the extraction of the rough boundary. Then, the point looseness threshold is introduced, and the fine boundary extraction is conducted for the local areas such as concave envelopes and holes. Finally, the complete boundary result of the whole point set is obtained. The effectiveness of the proposed algorithm is verified by experiments on the simulated point set and practical measured point set. The experimental results indicate that it has wider applicability and more effectiveness in engineering applications than the state-of-the-art boundary construction algorithms based on Delaunay triangulation.

Analysis of STEM micrographs of thick objects

1978 ◽  
Vol 36 (2) ◽  
pp. 106-107
Author(s):  
S. Golladay
Keyword(s):  
Inelastic Scattering ◽  
Multiple Scattering ◽  
Mass Distribution ◽  
Cross Sections ◽  
Phase Contrast ◽  
Image Point ◽  
Contrast Effects ◽  
Total Cross Sections ◽  
Elastic And Inelastic Scattering

The theory of multiple scattering has been worked out by Groves and comparisons have been made between predicted and observed signals for thick specimens observed in a STEM under conditions where phase contrast effects are unimportant. Independent measurements of the collection efficiencies of the two STEM detectors, calculations of the ratio σe/σi = R, where σe, σi are the total cross sections for elastic and inelastic scattering respectively, and a model of the unknown mass distribution are needed for these comparisons. In this paper an extension of this work will be described which allows the determination of the required efficiencies, R, and the unknown mass distribution from the data without additional measurements or models. Essential to the analysis is the fact that in a STEM two or more signal measurements can be made simultaneously at each image point.

New polarized-light microscope for fast and orientation independent measurement of birefringent fine structure

1993 ◽  
Vol 51 ◽  
pp. 82-83
Author(s):  
Rudolf Oldenbourg
Keyword(s):  
Light Microscope ◽  
Polarized Light ◽  
Video Camera ◽  
Limited Range ◽  
Image Point ◽  
Computer Assisted ◽  
Optical Modulators ◽  
Anisotropic Structures ◽  
Long Time ◽  
Computer Assisted Image

The polarized light microscope has the unique potential to measure submicroscopic molecular arrangements dynamically and non-destructively in living cells and other specimens. With the traditional pol-scope, however, single images display only those anisotropic structures that have a limited range of orientations with respect to the polarization axes of the microscope. Furthermore, rapid measurements are restricted to a single image point or single area that exhibits uniform birefringence or other form of optical anisotropy, while measurements comparing several image points take an inordinately long time.We are developing a new kind of polarized light microscope which combines speed and high resolution in its measurement of the specimen anisotropy, irrespective of its orientation. The design of the new pol-scope is based on the traditional polarized light microscope with two essential modifications: circular polarizers replace linear polarizers and two electro-optical modulators replace the traditional compensator. A video camera and computer assisted image analysis provide measurements of specimen anisotropy in rapid succession for all points of the image comprising the field of view.

Recognition of Birds in Blurred and Illumination Images by Local Features

2017 ◽  
Vol 7 (7) ◽  
pp. 243
Author(s):  
Suresha .M ◽  
. Sandeep
Keyword(s):  
Computer Vision ◽  
Time Complexity ◽  
Feature Detection ◽  
Feature Matching ◽  
Fast Algorithms ◽  
Local Features ◽  
Experimental Demonstration ◽  
Harris Corner ◽  
Blurred Image ◽  
Blurred Images

Local features are of great importance in computer vision. It performs feature detection and feature matching are two important tasks. In this paper concentrates on the problem of recognition of birds using local features. Investigation summarizes the local features SURF, FAST and HARRIS against blurred and illumination images. FAST and Harris corner algorithm have given less accuracy for blurred images. The SURF algorithm gives best result for blurred image because its identify strongest local features and time complexity is less and experimental demonstration shows that SURF algorithm is robust for blurred images and the FAST algorithms is suitable for images with illumination.

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