Camera calibration method based on projected Gaussian grid pattern

Abstract

A camera calibration method based on a projected Gaussian grid pattern, which is disclosed by the invention, belongs to the field of image processing and computer visual inspection, in particular to an on-site calibration method for the intrinsic and exterior parameters of cameras in a large forging dimension measurement system. By utilizing the characteristic of the Gaussian distribution of the widthwise grey scales of transverse and vertical light bars in the Gaussian grid pattern and fitting a Gaussian curve, the camera calibration method can accurately obtain the image coordinates of the points on the central lines of the light bars, so that a central line equation of the transverse and vertical light bars is fit out, the intersection points of the central lines of the transverse and vertical light bars are feature points for calibration, and according to the image coordinates of the feature points for calibration provided in the shot image of the Gaussian grid pattern, the intrinsic and exterior parameters of the cameras are acquired step by step. The camera calibration method has high real-timeness, robustness and high calibration precision, high-precision camera parameters can be obtained by step-by-step calibration, the problem of coupling in the simultaneous solution of all the camera parameters is avoided, and the camera calibration method is applicable to the on-line calibration of cameras on the forging site.

Description

technical field [0001] The invention belongs to the field of image processing and computer vision detection, in particular to a method for on-site calibration of internal and external parameters of a camera in a size measurement system for large forgings. Background technique [0002] One of the basic tasks of computer vision processing is to recover the 3D geometric information of objects from 2D image information. To achieve the task of using image points to obtain the corresponding surface points of space objects, it is necessary to determine the camera imaging geometric model, and the parameters of the geometric model are called camera parameters. The camera parameters are divided into internal and external parameters. The internal parameters are parameters related to the geometric and optical characteristics of the camera itself, and the external parameters are the three-dimensional position and direction of the camera relative to a certain world coordinate system. The...

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Problems solved by technology

[0005] The technical problem to be solved by the present invention is to overcome the deficiencies of the prior art. For the forging site, the traditional calibration method has low precision, non-real-time, and even cannot be applied, and the self-calibration method has problems such as low precision and insufficient robustness. , invented a large-field-of-view camera calibration method based on projected Gaussian grid patterns, using the characteristics of the Gaussian distribution of the horizontal and vertical light bars in the width direction of the Gaussian grid pattern, and by fitting Gaussian curves, high-precision Accurately obtain the image coordinates of the points on the centerline of the light strip, and then fit the centerline equation of the horizontal and vertical light strips. The intersection of the centerlines of the horizontal and vertical light strips is the calibration feature point. According to the Gaussian grid pattern obtained by shooting The image coordinates of the calibration feature points provided in the image, and the internal and external parameters of the camera are obtained step by step

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