Rapid ellipse detection method based on contour curve segmentation arc merging and combination

Abstract

The invention discloses a rapid ellipse detection method based on contour curve segmentation arc merging and combination. The method comprises steps that A, edge contour curves of single pixel width of an image are extracted, and broken line approximation contours are acquired; B, multiple types of constrained conditions are utilized to carry out condition segmentation of the broken line approximation contours; C, neighborhood merging of contour arc segment curves after segmentation is carried out, and adjacent same-type arc segments are merged; D, for L candidate ellipse arc segments after neighborhood merging, non-adjacent same-type arc segments are combined; E, pixel points on each candidate arc segment on L+H ellipse candidate arc segments are utilized to carry out ellipse fitting, authenticity verification is carried out for ellipses after fitting, and FALSE ellipses are eliminated; F, for the real ellipses, the repeated ellipses are eliminated through utilizing distances of the ellipses in a five-dimensional parameter space. Through the method, ellipse detection is carried out, relatively high reliability and robustness are realized, rapid ellipse detection can be realized, and difficulty in extracting ellipse characteristics from images is reduced.

Description

technical field [0001] The invention relates to computer vision recognition technology, in particular to an ellipse rapid detection method based on contour curve segmentation arc merging and combination. Background technique [0002] The perspective projection of a circle is generally an ellipse. Ellipse detection is a classic problem in machine vision and computer vision techniques. The results of ellipse detection can be widely used in various fields of computer vision, including cell detection and counting, face detection, traffic sign detection, 3D pose measurement, camera viewpoint estimation and other scenarios. [0003] Traditional ellipse detection methods can be divided into two categories: one is the ellipse detection method based on Hough generalized transform; the other is the detection method based on edge detection and ellipse fitting. in: [0004] The generalized Hough transform is based on the multi-dimensional parameter space voting decision, which has th...

AI Technical Summary

Problems solved by technology

[0006] However, the traditional ellipse detection method based on edge detection and ellipse fitting has the following problems because it is difficult to determine whether the fitting point is located on the target feature image: (1) When dividing the contour edge into segmented edges belonging to the same ellipse contour The time efficiency is low; (2) when looking for the edge set that may belong to the same ellipse, the combination ratio of the false ellipse; (3) the calculation of the false ellipse is large

Therefore, the detection results of the traditional ellipse detection method based on edge detection and ellipse fitting are greatly affected by noise, the false detection rate is high, and the amount of calculation is large. It is still difficult to achieve real fast detection.

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