Image processing method for detecting similar round by using improved hough transformation

Abstract

The invention provides an image processing method for detecting a similar round by using improved hough transformation. The method comprises the following seven steps of: preprocessing an image, extracting an edge and filtering out noises, weighing along a gradient direction and projecting the hough transformation, performing low-pass smooth filtering on a projection space, contracting and binaryzing, positioning a circle center and estimating a radius. Compared with the conventional method for detecting the round by using the hough transformation, the method has the advantages that: on the one hand, the requirement of an algorithm on a memory is reduced and the algorithm efficiency is improved; on the other hand, the performance of the algorithm for detecting irregular similar round objects is improved; meanwhile, the detection precision of the algorithm under the condition of a larger variation region of the round radius is enhanced.

Description

technical field [0001] The invention relates to an image processing method for circle-like detection by using the improved Hough transform, which is used for image processing, computer vision and industrial automation inspection. It belongs to the technical field of computer information image processing. Background technique [0002] Fast and accurate detection of circular and quasi-circular objects has broad application prospects in the fields of computer vision and pattern recognition. For example, industrial inspection lines, biomedical monitoring equipment, and automated assembly lines all involve the application of computer vision technology for circular and quasi-circular detection. For a long time, Hough transform has been a practical and effective method for detecting straight lines / circles / ellipses, but for detecting circles, Hough transform also has several major disadvantages: 1. It takes up a lot of memory; 2. Unable to detect irregular round objects (such as b...

AI Technical Summary

Problems solved by technology

For a long time, Hough transform has been a practical and effective method for detecting straight lines / circles / ellipses, but for detecting circles, Hough transform also has several major disadvantages: 1. It takes up a lot of memory; 2. Unable to detect irregular round objects (such as bubbles, cells, etc.); 3. Poor anti-interference performance;

Although the random Hough transform reduces the complexity and memory requirements of the algorithm, it also has several shortcomings: 1. The detection performance is not good when dealing with multiple circles or ellipses on the same image; 2. Unable to detect irregular round objects (such as bubbles, cells); 3. With the increase of image noise, the performance of the algorithm is greatly reduced

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