OU Yang, LUO Jianqiao, Xiong Ying, et al. Rivet size detection based on adaptive threshold Zernike moment[J]. 2020, (3): 139-142+152. DOI: 10.13873/J.1000-9787(2020)03-0139-04.
基于自适应阈值Zernike矩的铆钉尺寸检测
摘要
针对铆钉尺寸检测精度低的问题
提出一种改进Zernike矩算法检测铆钉亚像素边缘
采用自适应方法取代固定阶跃阈值
从而实现高精度铆钉尺寸测量。首先
为检测铆钉直径、长度等尺寸
构造6个感兴趣区域并采用Canny算子提取粗定位边缘。然后
根据感兴趣区域内铆钉和背景之间的差异
自适应确定Zernike矩的阶跃阈值
从粗定位边缘中提取亚像素边缘点。最后
引入铆钉结构信息定义直线簇
对提取的亚像素边缘点进行拟合
根据直线簇方程计算得到铆钉尺寸。实验表明:相比其它亚像素方法
改进算法精度更高
铆钉长度和角度的检测精度分别达到0. 01 mm和0. 1°。
Abstract
Aiming at the problem of low precision of rivet size detection
an improved Zernike moment algorithm is proposed to detect the sub-pixel edge of rivet self-adpptive method is used to replace threshold of fixed step. First
in order to detect the diameter and length of the rivet
six regions of interest( ROI) are constructed and the coarse positioning edge is extracted by the Canny operator. Then
the step threshold of the Zernike moment is adaptively determined according to the difference between the rivet and the background in the ROI
and the sub-pixel edge point is extracted from the coarse positioning edge. Finally
the rivet structure information is introduced to define straight linear cluster
the extracted sub-pixel edge points are fitted
and the rivet size is calculated according to the straight linear cluster equation. Experiments show that the improved algorithm has higher precision than other subpixel methods
and the detection precision of rivet length and angle reaches 0. 01 mm and 0. 1°