Precise positioning method for circular object with thickness interference

Abstract

The invention belongs to the technical field of machine vision image processing, and particularly relates to a precise positioning method for a circular object with thickness interference. According to the invention, a thickness noise removing method based on the edge density is used to eliminate the interference of thickness noise to the circular object; the noise center position relation is used to solve a rotation mirror problem, and the rotation direction of the object is calculated; and the size of the rotation angle of the object is calculated through a center offset algorithm for an object with a prominent column in the middle. The method comprises the concrete steps that the edge contour after removing noise from thickness is extracted based on the edge point density; rotation mirror processing is carried out based on the thickness noise center; and accurate target positioning is carried out based on the center point offset. The method provided by the invention is particularly applicable to rapid and accurate detection and positioning of the circular object with thickness interference in an industrial environment, and has the advantages of high positioning accuracy, efficient processing rate and great anti-noise ability.

Description

technical field [0001] The invention belongs to the technical field of machine vision image processing, and in particular relates to a method for precise detection and positioning of a circular object in an industrial scene. Background technique [0002] Image processing technology is usually the core part of a vision system, and the edge point extraction and ellipse detection involved in the present invention are one of the most important research methods in the field of image processing. [0003] When people observe an object, the perceived edge is usually a place where the color has obvious changes, and the mathematical representation of this change in the image is the edge detection operator. The commonly used operators include Roberts operator, Sobel operator, Prewitt operator, Laplacian operator, and Canny operator. Although these traditional algorithms based on edge detection operators can extract edge pixels, many noise points will be mistaken for edges at the same ...

AI Technical Summary

Problems solved by technology

But since y=cos -1 (x) The function curve is relatively steep near x=1, when or When it is close to 1, even if the detected c and d errors are small, the error of the calculated rotation angle will be large

Images