Ellipse detection method based on chord tangent distance

Abstract

The invention discloses an ellipse detection method based on chord tangent distance. The method comprises the following steps: 1, image edge pixel chain extraction: converting an input image into an LAB color space, extracting an image edge on an L color channel, performing connected component marking and edge tracking operations, and obtaining an edge pixel chain from each connected component; 2,ellipse fitting: under a least square fitting framework, establishing an objective function by using a chord tangent distance as a fitting error metric, and iteratively solving ellipse parameters byusing a Gauss-Newton method. Due to the fact that the chord tangent distance is adopted, a simple closed-form solution is provided for calculating the corresponding point of one point on the given ellipse. The iterative solution does not need to be carried out like most of existing geometric distance fitting methods. The calculated amount is greatly reduced. Meanwhile, errors occurring in calculation are reduced, and the practicability of the method is improved.

Description

technical field [0001] The invention belongs to the technical fields of image processing and computer vision, and in particular relates to an ellipse detection method based on chord tangent distance. Background technique [0002] Detecting elliptical structures from images is a basic problem in the field of image analysis and computer vision. Many visual objects or structures in images can be reasonably approximated as ellipses, so that they can be expressed and described with a few parameters, which can be used for subsequent images. analysis or computer vision tasks. Therefore, ellipse detection technology has a wide range of applications in target recognition, 3D structure inference, machine vision and industrial automation, medical image analysis and other fields. [0003] In practical applications, various interference factors will bring challenges to ellipse detection and affect its performance. For example, a given point can only cover part of the ellipse arc segment...

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Problems solved by technology

[0003] In practical applications, various interference factors will bring challenges to ellipse detection and affect its performance, for example, a given point can only cover part of the ellipse arc segment, slender ellipse, noise and outlier points, etc.

Early ellipse detection methods voted on all possible ellipse parameters to determine the final ellipse parameters. This type of method has good robustness to interference factors such as a given point covering only part of the arc segment, noise and outliers. However, this method is too sensitive to the discretization of the parameter space; another type of ellipse detection method is based on least squares fitting, using a certain fitting error measure to establish an objective function about the ellipse parameters, and then using the optimization algorithm to solve the ellipse parameters, but the key to this type of method is how to measure the fitting error, the interpretability is poor, and the fitting results usually tend to be smaller or slender ellipses, the limitations of use are relatively large; in order to overcome the algebraic distance fitting However, there are also methods using geometric distance fitting, but the computational complexity is very high, which greatly limits their application in practical problems

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