Full-automatic camera parameter calibration method based on colored calibration board

Abstract

The invention provides a full-automatic camera parameter calibration method based on a colored calibration board. The method includes the following steps that firstly, the colored chess calibration board is drawn, wherein four neighborhoods of each corner are a combination of different colors; secondly, the movement of the colored chess calibration board is controlled by a mechanical arm to set presetting bits and capture calibration images; thirdly, corner detection is carried out according to the calibrated images obtained in the second step; fourthly, fake corners are removed according to whether 'color codes' of the corners are in a 'color code' library of the calibration board or not; fifthly, all parameters for camera calibration are obtained based on space coordinates of the true corners obtained in the fourth step and pixel coordinates of the true corners in the calibration image; sixthly, the camera parameters are acquired to complete camera calibration.

Description

technical field [0001] The invention relates to a fully automatic camera parameter calibration method based on a color calibration board, which belongs to the field of computer vision. Background technique [0002] One of the basic tasks of computer vision is to calculate the geometric information of objects in three-dimensional space from the image information obtained by the camera, and then reconstruct or recognize objects, and further recognize the real world. Among them, camera calibration is the necessary way to complete the task, especially in the field of image-based modeling, camera calibration is a particularly important link. The calibration accuracy will directly affect the final accuracy of subsequent computer vision operations. [0003] At present, there are mainly two camera calibration methods, one is the self-calibration method, and the other is the active calibration method. The self-calibration method does not need other reference objects and external eq...

AI Technical Summary

Problems solved by technology

[0006] However, in practical applications, there are still some shortcomings in the mainstream camera calibration algorithm based on reference objects

It mainly includes the following points: a. It is usually necessary to manually take several images of the calibration board, and manual participation is required, and the accuracy is not high; b. There are usually large errors in the corner detection results; c The calibration of the zoom lens requires a lot of repetitive work, manual adjustment of the chessboard and focal length, etc.

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