摘要
为提高金属工件在线检测的精度和速度,提出了一种提取金属工件形状特征的方法。首先,提出一种基于除法运算和颜色模型转换相结合的方法来实现高光消除;其次,运用免疫遗传算法完成工件形状特征的提取。实验结果表明:该算法能够有效抑制噪声,并可以快速准确地提取金属工件的形状特征,满足工件在线实时检测的要求。
In order to improve the accuracy and speed of metal workpiece detection online,a method for extracting shape features of metal workpieces was proposed.Firstly,a method based on division operation and color model transformation was proposed to achieve high-light elimination,and then immune genetic algorithm was used to extract the shape features of the workpiece.The experimental results show that the proposed algorithm can suppress noise effectively,and extract the shape features of metal workpieces quickly and accurately,which meets the requirements of real-time detection of workpieces online.
作者
巩晓丹
杨慕升
姜立志
Gong Xiaodan;Yang Musheng;Jiang Lizhi(Shandong University of Technology,Zibo 255000,Shandong,China)
出处
《现代制造工程》
CSCD
北大核心
2020年第3期121-124,共4页
Modern Manufacturing Engineering
基金
山东省自然科学基金项目(ZR2016EEM20)。
关键词
形状特征提取
高光消除方法
免疫遗传算法
金属工件
shape feature extraction
high-light elimination method
immune genetic algorithm
metal workpiece
