[1]黄亚伟,陈 悦,黄晓华.基于遗传算法的二维最大类间方差法的优化[J].机械与电子,2018,(04):20-23.
　HUANG Yawei,CHEN Yue,HUANG Xiaohua.Optimization of Two-Dimensional Otsu Method Based on Genetic Algorithm[J].Machinery & Electronics,2018,(04):20-23.
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基于遗传算法的二维最大类间方差法的优化
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《机械与电子》[ISSN:1001-2257/CN:52-1052/TH]

卷:
期数:
2018年04期
页码:
20-23
栏目:
设计与研究
出版日期:
2018-04-24

文章信息/Info

Title:
Optimization of Two-Dimensional Otsu Method Based on Genetic Algorithm
文章编号:
1001-2257(2018)04-0020-04
作者:
黄亚伟; 陈 悦; 黄晓华
(南京理工大学机械工程学院,江苏 南京 210094)
Author(s):
HUANG Yawei; CHEN Yue; HUANG Xiaohua
(School of Mechanical Engineering, Nanjing University of Science & Technology, Nanjing 210094, China)
关键词:
图像分割;  自适应;  遗传算法;  二维最大类间方差法
Keywords:
image segmentation;  self-adaption;  genetic algorithm;  two-dimensional Otsu Method
分类号:
TP751.1
文献标志码:
A
摘要:
针对经典的二维最大类间方差法存在时效性差的问题,提出一种快速实现方法。通过对原有的二维灰度直方图计算其边缘概率分布,将作为判别标准的离散度矩阵分解为2个一维类间方差之和,在保证原有鲁棒性的同时降低了算法的时间和空间复杂度。同时,与遗传算法相结合,加快寻优过程,且遗传过程中可以自动调节遗传控制参数,避免早熟。实验证明其运算速度提升约50%。
Abstract:
A fast implementation method is proposed to solve the problem of poor timeliness of the classical two-dimensional Otsu method. The edge probability distribution of the original two-dimensional gray histogram was calculated, and the discrete matrix was decomposed into the sum of two one-dimensional interclass variance, which ensured the original robustness while reducing the time and space complexity of the algorithm. Besides, the genetic algorithm was used to accelerate the optimization process and the genetic control parameters could be automatically adjusted in the genetic process to avoid premature. The experimental results show that the speed of calculation increases by 50%.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期:2017-11-25
作者简介:黄亚伟(1993-),男,江苏宜兴人,硕士研究生,研究方向为机械制造及自动化; 陈 悦(1989-),女,四川成都人,研究员实习员,研究方向为高等教育; 黄晓华(1969-),男,江苏南通人,副教授,硕士研究生导师,研究方向为机电一体化。
更新日期/Last Update: 2018-04-24