An Efficient Convex Hull Algorithm for Planar Point Set Based on Recursive Method

2012 ◽  
Vol 38 (8) ◽  
pp. 1375 ◽  
Author(s):  
Bin LIU ◽  
Tao WANG
2013 ◽  
Vol 706-708 ◽  
pp. 1852-1855
Author(s):  
Hong Fei Jiang

In this paper ,a new algorithm is proposed for improving speed of calculating convex hull of planar point set .The algorithm creates a square mesh to manage points ,when eliminating points which are obviously in convex hull ,selecting or eliminating of points can be converted to that of grid , work of calculation depends on points near edges of convex hull and density of grid but not the number of points ;at the meantime ,remainder points are sorted roughly .When calculating convex hull of remainder points ,a method is presented which can take advantage of order of remainder points ,it calculates boundaries of convex hull segment by segment ,then ,combines the boundaries to form convex hull.


2014 ◽  
Vol 39 (11) ◽  
pp. 7785-7793 ◽  
Author(s):  
Changyuan Xing ◽  
Zhongyang Xiong ◽  
Yufang Zhang ◽  
Xuegang Wu ◽  
Jingpei Dan ◽  
...  

Author(s):  
XUE GANG WU ◽  
BIN FANG ◽  
YUAN YAN TANG ◽  
PATRICK SHEN-PEI WANG

The number of inner points excluded in an initial convex hull (ICH) is vital to the efficiency getting the convex hull (CH) in a planar point set. The maximum inscribed circle method proposed recently is effective to remove inner points in ICH. However, limited by density distribution of a planar point set, it does not always work well. Although the affine transformation method can be used, it is still hard to have a better performance. Furthermore, the algorithm mentioned above fails to deal with the exceptional distribution: the gravity centroid (GC) of a planar point set is outside or on the edge formed by the extreme points in ICH. This paper considers how to remove more inner points in ICH when GC is inside of ICH and completely process the case which mentioned above. Further, we presented a complete algorithm architecture: (1) using the ellipse and elasticity ellipse methods (EM and EEM) to remove more inner points in ICH and process the cases: GC is inside or outside of ICH. (2) Using the traditional methods to process the situation: the initial centroid is on the edge in ICH. It is adaptive to more data sets than other algorithms. The experiments under seven distributions show that the proposed method performs better than other traditional algorithms in saving time and space.


2007 ◽  
Vol 8 (8) ◽  
pp. 1210-1217 ◽  
Author(s):  
Guang-hui Liu ◽  
Chuan-bo Chen
Keyword(s):  

2014 ◽  
Vol 571-572 ◽  
pp. 721-724
Author(s):  
Xiu Xun Huang ◽  
Ji Ting Zhou ◽  
Chen Ling ◽  
Wen Jun Zhang

A novel three-dimensional (3D) convex hull method is proposed, which is called dimensionality reduction convex hull method (DRCH).Through having 3d point set map to 2d plane, most initial 3D points in the convex hull are removed. Then, the remaining points are to generate 3D convex hull using any convex hull algorithm. The experiment demonstrates 3D DRCH is faster than general 3D convex hull algorithms. Its time complexity is O(r log r), where r is the number of points not in the hull. And DRCH can be generalized to higher-dimensional problems.


2013 ◽  
Vol 17 (1) ◽  
pp. 29-35 ◽  
Author(s):  
Byeong-Ju Park ◽  
Jae-Heung Lee

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