Zhang He, Wang Li, Liu Wenya, Cui Jiwen, Tan Jiubin
Center of Ultra-Precision Optoelectronic Instrument, Harbin Institute of Technology, Harbin 150080, China.
Key Lab of Ultra-Precision Intelligent Instrumentation, Harbin Institute of Technology, Ministry of Industry and Information Technology, Harbin 150080, China.
Sensors (Basel). 2023 Jul 15;23(14):6433. doi: 10.3390/s23146433.
Ellipse detection has a very wide range of applications in the field of object detection, especially in the geometric size detection of inclined microporous parts. However, due to the processing methods applied to the parts, there are certain defects in the features. The existing ellipse detection methods do not meet the needs of rapid detection due to the problems of false detection and time consumption. This article proposes a method of quickly obtaining defective ellipse parameters based on vision. It mainly uses the approximation principle of circles to repair defective circles, then combines this with morphological processing to obtain effective edge points, and finally uses the least squares method to obtain elliptical parameters. By simulating the computer-generated images, the results demonstrate that the center fitting error of the simulated defect ellipses with major and minor axes of 600 and 400 pixels is less than 1 pixel, the major and minor axis fitting error is less than 3 pixels, and the tilt angle fitting error is less than 0.1°. Further, experimental verification was conducted on the engine injection hole. The measurement results show that the surface size deviation was less than 0.01 mm and the angle error was less than 0.15°, which means the parameters of defective ellipses can obtained quickly and effectively. It is thus suitable for engineering applications, and can provide visual guidance for the precise measurement of fiber probes.
椭圆检测在目标检测领域有着非常广泛的应用，尤其在倾斜微孔零件的几何尺寸检测方面。然而，由于应用于零件的加工方法，其特征存在一定缺陷。现有的椭圆检测方法由于存在误检和耗时等问题，无法满足快速检测的需求。本文提出一种基于视觉快速获取缺陷椭圆参数的方法。它主要利用圆的近似原理修复缺陷圆，然后结合形态学处理得到有效的边缘点，最后使用最小二乘法获取椭圆参数。通过对计算机生成图像的模拟，结果表明，对于长轴和短轴分别为600像素和400像素的模拟缺陷椭圆，其中心拟合误差小于1像素，长轴和短轴拟合误差小于3像素，倾斜角拟合误差小于0.1°。此外，对发动机喷油孔进行了实验验证。测量结果表明，表面尺寸偏差小于0.01mm，角度误差小于0.15°，这意味着可以快速有效地获取缺陷椭圆的参数。因此，它适用于工程应用，并可为光纤探头的精确测量提供视觉指导。
