Grid feature point extraction method based on fast line extraction

Abstract

The invention discloses a grid feature point extraction method based on fast line extraction, and the method is used for extracting coordinates of a feature point in a grid image quickly and accurately. The execution steps are as follows: firstly carrying out the binary processing of an image, enabling an initial color image to be converted into a grey-scale map, and reducing a calculation quantity; secondly sequentially carrying out the erosion and dilation conversion and Gaussian filtering of the image, and eliminating interference and noises; carrying out the edge detection of a preprocessed image through employing a Canny edge detector, obtaining a grid contour, then carrying out fast line extraction through employing improved Hough conversion, and obtaining a line set; enabling the line set to be divided into two classes according to the slope of a line, and reducing the number of times of intersection point solving operation; enabling lines which are perpendicular to each other to be combined together so as to obtain the coordinates of intersection points, and obtaining a feature point set; setting a threshold value for the aggregation of the extracted feature points, eliminating interference, and finally obtaining a precise feature point set. The method is higher in speed and precision of feature point extraction, can eliminate the interference, and is better in fault tolerance performance.

Description

technical field [0001] The present invention proposes a feature point extraction method in a grid image based on fast line extraction, specifically relates to fast line extraction in an image, classification of lines, and aggregation of feature points, which can realize accurate and fast feature points in a grid extract. Background technique [0002] Image feature point extraction is of great significance in image processing and machine vision. It has broad application prospects in the fields of automatic detection, biomedicine, and industrial manufacturing, and has also received more and more attention. As a common regular graph, checkerboard grid is widely used in camera calibration and visual localization of mobile robots. The commonly used checkerboard feature point detection method is based on the classic Harris corner detection algorithm. Although it has strong robustness, the algorithm cannot automatically adapt to the scale transformation of the image, and the corne...

AI Technical Summary

Problems solved by technology

The commonly used checkerboard feature point detection method is based on the classic Harris corner detection algorithm. Although it has strong robustness, the algorithm cannot automatically adapt to the scale transformation of the image, and the corner points extracted by this algorithm are pixels. Level, the time performance is not good enough, for images with relatively regular and regular feature points such as chessboards and grids, using the Harris algorithm will have a significant waste of time

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