基于遗传算法的三角网格折叠简化

段黎明; 杨尚朋; 张霞; 任华桥; 沈宽

doi:10.3788/OPE.20182606.1489

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基于遗传算法的三角网格折叠简化

信息科学 | 更新时间：2020-07-05

- 基于遗传算法的三角网格折叠简化
- Collapsing simplification of triangular mesh based on genetic algorithm
- 光学精密工程 2018年26卷第6期页码：1489-1496
- 作者机构：
  
  1.重庆大学光电技术及系统教育部重点实验室ICT研究中心, 重庆 400044
  2.重庆大学机械工程学院, 重庆 400044
  3.中国科学院重庆绿色智能技术研究院, 重庆 400044
- 作者简介：
  
  [ "段黎明(1964-), 男, 四川营山人, 教授, 博士生导师。1985年于成都科技大学获得学士学位, 1988年、1998年于重庆大学分别获得硕士、博士学位, 主要从事工业CT技术及应用, 基于工业CT的逆向设计, 网格重建与处理等研究。E-mail:duanliming163@163.com" ]
  [ "杨尚朋(1990-), 男, 山东滕州人, 硕士研究生。2013年于山东理工大学取得学士学位, 主要研究方向为三角网格处理, 基于工业CT的逆向工程。E-mail:yangshangpeng163@163.com" ]
- 基金信息：
  
  重庆市自然科学基金资助项目(CSTC2016jcyjA0353);国家重大科学仪器设备开发专项(2013YQ030629)
- DOI：10.3788/OPE.20182606.1489
  中图分类号： TP751.1
- 收稿日期：2017-09-01，
  
  录用日期：2017-10-30，
  
  纸质出版日期：2018-06-25
- 稿件说明：
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段黎明, 杨尚朋, 张霞, 等. 基于遗传算法的三角网格折叠简化[J]. 光学精密工程, 2018,26(6):1489-1496.

Li-ming DUAN, Shang-peng YANG, Xia ZHANG, et al. Collapsing simplification of triangular mesh based on genetic algorithm[J]. Optics and precision engineering, 2018, 26(6): 1489-1496.
段黎明, 杨尚朋, 张霞, 等. 基于遗传算法的三角网格折叠简化[J]. 光学精密工程, 2018,26(6):1489-1496. DOI： 10.3788/OPE.20182606.1489.

Li-ming DUAN, Shang-peng YANG, Xia ZHANG, et al. Collapsing simplification of triangular mesh based on genetic algorithm[J]. Optics and precision engineering, 2018, 26(6): 1489-1496. DOI： 10.3788/OPE.20182606.1489.

摘要

针对处理大数据量的三角网格模型会给计算机带来较大压力的问题，本文提出了一种基于遗传算法的三角形折叠简化方法。先求取三角形重心，用重心的三个坐标值与初始化的三个步长进行计算，得到新点坐标，重复多次得到顶点种群，利用遗传算法求取适应度值最小点，修正后得到最优折叠点，最后依照简化误差对三角形排序并根据输入的简化比进行折叠简化。本文方法的适应度函数采用简化误差和三角形规范化系数之商。采用本文方法对花朵和瓶子的三角网格模型进行简化，体积变化率分别为0.010 6%和0.2%，规范化系数分别提高了11.0%和4.56%，优于其他方法。实验结果表明本文方法在有效简化模型的同时，既能保形又能提升三角形的质量。

Abstract

To solve the problem that the triangular mesh model which deals with large amount of data will bring great pressure to the computer

a triangle collapsing simplification method based on genetic algorithm was proposed in this paper. In this method

the gravity of the triangles was first derived

the new coordinates were calculated by using the three coordinates of the gravity and the three initialized step lengths

the vertex population was obtained through repeating the above operation several times

the minimum point of fitness value was calculated by using genetic algorithm

the optimal collapsing point was obtained after appropriate amendment

and finally

the sequence of the triangles and collapsing simplification were made according to the simplified error and the proportion of input simplification

respectively. The fitness function adopted in this paper was the quotient of the simplified error and the triangle normalization coefficient. The proposed method was used to achieve the simplification of the triangular mesh model of the flower and the vase

whose volume change rates were 0.0106% and 0.2%

respectively. Besides

their normalized coefficients increased by 11.0% and 4.56%

respectively

which were better than the other methods. The experimental results show that the method proposed can not only simplify the model effectively but also remain its shape as well as improve the quality of the triangular.

关键词

Keywords

references

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