Checkerboard angular point automatic detection method under fish-eye lens

Abstract

A checkerboard angular point automatic detection method under a fish-eye lens comprises the steps of selecting a particular region of a checkerboard and shielding useless information to reduce angular point detection time and raise detection precision; carrying out Harris angular point detection on the particular region; adding an angular point manual extraction step in an algorithm and manually adding the hidden angular point information; adding angular point combining operation according to the total number of checkerboard angular points and angular point separation situations; as for the checkerboard which is small in checkerboard rotating angle, slight in distortion and few in angular corner, sorting the angular points in a binomial fitting manner; and as for the checkerboard distorted under the fish-eye lens, calculating the sequence of the checkerboard angular points by using a modified convex hull algorithm. Simulation software is utilized to automatically detect coordinates of the checkerboard angular points, and under the condition of ensuring detection reliability of the angular points, the detection speed and precision of the angular points are greatly raised, and the complexity of manually extracting the checkerboard angular points is removed.

Description

technical field [0001] The invention relates to the field of machine vision, in particular to an automatic detection method for checkerboard corners under a fisheye lens. Background technique [0002] As the first condition of visual measurement, camera calibration aims to establish the transformation relationship between the image coordinate system and the space coordinate system. Camera calibration generally includes two steps: detection of image feature points and solution of camera parameters. As a typical calibration image, the checkerboard image has been widely used in camera calibration, and its corner detection has become one of the hot issues in computer vision. For the checkerboard image, the task of image feature point detection is not only to extract the image coordinates of each corner point in the checkerboard image, but also to establish a one-to-one correspondence between each image corner point and the spatial corner point. [0003] At present, the researc...

AI Technical Summary

Problems solved by technology

However, these toolboxes do not make assumptions about the shape of the lens, and the detection effect of fisheye lens images with serious distortion is not ideal.

[0005] To sum up, the traditional checkerboard corner detection method cannot directly detect the corners of the severely distorted checkerboard image under the fisheye lens.

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