Adaptive Point Location with almost No Preprocessing in Delaunay Triangulations

2012 ◽  
Author(s):  
Binhai Zhu
Keyword(s):  
Point Location ◽  
Delaunay Triangulations

A Note on Point Location in Delaunay Triangulations of Random Points

Algorithmica ◽  
1998 ◽  
Vol 22 (4) ◽  
pp. 477-482 ◽  
Author(s):  
L. Devroye ◽  
E. P. Mücke ◽  
Binhai Zhu
Keyword(s):  
Point Location ◽  
Delaunay Triangulations

Building an Optimal Point-Location Structure in $$O( sort (n))$$ O ( s o r t ( n ) ) I/Os

Algorithmica ◽  
2018 ◽  
Vol 81 (5) ◽  
pp. 1921-1937
Author(s):  
Xiaocheng Hu ◽  
Cheng Sheng ◽  
Yufei Tao
Keyword(s):  
Point Location ◽  
Optimal Point

scholarly journals Automatic measurement of traditional Chinese costume from its silhouette through Fuzzy c-means clustering method

2020 ◽  
Vol 15 ◽  
pp. 155892502097832
Author(s):  
Jiaqin Zhang ◽  
Jingan Wang ◽  
Le Xing ◽  
Hui’e Liang
Keyword(s):  
Industrial Application ◽  
Clustering Algorithm ◽  
Color Space ◽  
Automatic Measurement ◽  
Feature Point ◽  
Feature Points ◽  
Point Location ◽  
Fuzzy C Means ◽  
Fuzzy C Means Clustering ◽  
Environmental Robustness

As the precious cultural heritage of the Chinese nation, traditional costumes are in urgent need of scientific research and protection. In particular, there are scanty studies on costume silhouettes, due to the reasons of the need for cultural relic protection, and the strong subjectivity of manual measurement, which limit the accuracy of quantitative research. This paper presents an automatic measurement method for traditional Chinese costume dimensions based on fuzzy C-means clustering and silhouette feature point location. The method is consisted of six steps: (1) costume image acquisition; (2) costume image preprocessing; (3) color space transformation; (4) object clustering segmentation; (5) costume silhouette feature point location; and (6) costume measurement. First, the relative total variation model was used to obtain the environmental robustness and costume color adaptability. Second, the FCM clustering algorithm was used to implement image segmentation to extract the outer silhouette of the costume. Finally, automatic measurement of costume silhouette was achieved by locating its feature points. The experimental results demonstrated that the proposed method could effectively segment the outer silhouette of a costume image and locate the feature points of the silhouette. The measurement accuracy could meet the requirements of industrial application, thus providing the dual value of costume culture research and industrial application.

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