Checkerboard corner detection method based on neural network and application thereof

Abstract

The invention belongs to the technical field of image processing, and particularly discloses a checkerboard corner detection method based on a neural network and application of the checkerboard cornerdetection method. The method comprises the following steps: acquiring a multi-angle image of a checkerboard to be detected, and preprocessing the multi-angle image to obtain a grayscale image; basedon a neural network, carrying out angular point detection on the gray level image so as to determine candidate angular points; removing the candidate angular points which do not meet the geometric standard of the checkerboard to determine the angular points to be detected; determining sub-pixel positions of the checkerboard corner points to be detected according to the obtained corner points to bedetected; and performing region screening on the obtained to-be-detected corner points, determining an index matrix of each to-be-detected corner point, and further obtaining a plurality of checkerboard corner point sequences which are not crossed with one another, thereby finishing corner point detection of the to-be-detected checkerboard. The method has high detection robustness for interference such as illumination shielding and noise offset, has high positioning stability for image bending and distortion caused by uneven lenses or wide-angle camera shooting, and can complete detection formultiple chessboards at the same time.

Description

technical field [0001] The invention belongs to the technical field of image processing, and more specifically relates to a checkerboard corner detection method based on a neural network and its application. Background technique [0002] Camera calibration has a wide range of applications in the fields of object tracking, image fusion, 3D reconstruction, and robot navigation. In these fields, the camera completes the precise three-dimensional modeling of the target scene by acquiring multiple two-dimensional plane images of the target scene. The completion of 3D modeling needs to know the physical (internal) parameters and geometric (external) parameters of the camera in advance, and these specific parameters are generally determined through camera calibration. Camera calibration detects the two-dimensional position coordinates of the feature points on the calibration template of known size, and then corresponds the three-dimensional space positions of these feature points ...

AI Technical Summary

Problems solved by technology

However, this score is only used in corner detection and is not used in the subsequent checkerboard generation stage, so the utilization rate is also low

In addition, most of the above corner detection schemes are only suitable for single checkerboard detection, and the detection effect for an image containing multiple checkerboards is often not good.

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