Robot camera calibration method based on edge scale adaptive defocusing fuzzy estimation

Abstract

The invention discloses a robot camera calibration method based on edge scale adaptive defocusing fuzzy estimation, which comprises the following steps: firstly, acquiring a checkerboard picture by using a camera to be calibrated, and carrying out Canny edge detection and corner detection on the acquired checkerboard picture; secondly, constructing an edge graph with a consistent scale according to a Canny edge detection value; then, setting a local scale value of edge detection while setting blurring values of two-time re-blurring images; carrying out gaussian blur on the checkerboard image again, and solving the gradient ratio of the two re-blurred images; then, calculating the defocusing fuzzy quantity of each corner point of the checkerboard original picture; drawing a circle by taking the detected angular point as a circle center and the defocusing fuzzy quantity as a radius, and setting a weight of a camera calibration energy equation; and finally, according to the optimized camera calibration energy equation, performing iteration on the energy equation in the obtained circle range until convergence, and outputting an optimal camera calibration parameter, so that the camera calibration precision can be greatly improved.

Description

technical field [0001] The present invention mainly relates to the technical field of visual perception, in particular to a robot camera calibration method based on edge scale adaptive defocus blur estimation. Background technique [0002] The camera calibration technology plays a vital role in the visual perception of the mobile car, the end vision of the robotic arm, and even the visual perception process of the lunar rover and the Mars rover. The camera calibration process is related to the acquisition of camera parameters, which directly affects the stereo matching in stereo vision. Accuracy, and the accuracy of three-dimensional reconstruction of the environment, so the camera calibration process also plays a key role in improving the accuracy of the stereo vision-based visual navigation of the mobile car, directly affecting whether the visual perception task can be completed. [0003] In the process of high-precision camera calibration, the high-precision extraction of...

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Problems solved by technology

In the article "Edge-Based Defocus Blur Estimation With Adaptive Scale Selection", AliKaraali et al. used to obtain the edge map of the image, and then re-blur the original image twice to construct an edge map with the same scale and perform scale adaptive selection. The method of obtaining the initial blur estimation of the edge position, but its purpose is to obtain the full defocus blur map of the whole picture, and it is not applied to the camera calibration process to improve the accuracy of camera calibration

In "Camera Weighted Calibration Method for Defocus Blur Estimation", Wang Lei et al. applied the defocus blur process to the camera calibration process, and introduced weights into the camera calibration energy function to improve the accuracy of camera calibration, but The method of obtaining the defocus blur amount is to obtain the one-dimensional blur amount in the horizontal and numerical directions first, and then integrate it into a two-dimensional blur amount, which has poor precision and low robustness, and the weight introduced by it is simply based on The effect of controlling the sharpness of points to increase clear points or reduce blurred points in the camera calibration process does not fully play the role of blur amount

In the article "Robust Camera Calibration by Optimal Localization of Spatial Control Points", Jianyang Liu et al. used the correction distance of lens distortion and perspective distortion of the camera, and the blur amount of defocus blur as the radius to make circles respectively, and the range obtained by taking the union was used as To return to the precise control point, but the acquisition accuracy of the defocus blur is low, and the defocus blur cannot be used alone. In the process of minimizing the camera calibration energy function, there is no appropriate weighting of the camera calibration energy function. The introduction of the value, the convergence speed is too low

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