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Sub-pixel edge point detection method based on Gaussian model convolution

A sub-pixel edge and Gaussian model technology, applied in the field of image processing, can solve the problems of large edge point coordinate errors, low detection accuracy, and difficulty in obtaining the real edge of the image, and achieve the effect of improving detection accuracy and algorithm robustness

Active Publication Date: 2021-10-01
成都新西旺自动化科技有限公司
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Problems solved by technology

This detection method is greatly affected by the shooting environment, it is difficult to obtain the real edge of the image, and the detection accuracy is relatively low, and the stability is poor. The error of edge point coordinates is larger

Method used

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  • Sub-pixel edge point detection method based on Gaussian model convolution
  • Sub-pixel edge point detection method based on Gaussian model convolution
  • Sub-pixel edge point detection method based on Gaussian model convolution

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Embodiment

[0071] A sub-pixel edge point detection method based on Gaussian model convolution, such as figure 1 shown, including the following steps:

[0072] S1: Obtain the sub-pixel points of the area to be detected;

[0073] First, the image of the product to be tested is collected by the camera, and then a point is randomly selected at the edge of the image to be tested as the center point of the rotating rectangle and the regular rectangle, which is denoted as , and then set the width, height and angle of the rotating rectangle and the regular rectangle according to the position of the center point on the edge of the image to be tested; specifically, when the center point is set on the horizontal edge of the image, the set width value should be smaller than the height value; when the center When the point is set on the vertical edge of the image, the set width value should be greater than the height value.

[0074] The positive rectangle mentioned in this embodiment is a rectangl...

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Abstract

The invention discloses a sub-pixel edge point detection method based on Gaussian model convolution. The method comprises the following steps: obtaining sub-pixel points of a to-be-detected area; obtaining a gray value of the sub-pixel point; obtaining a gray average value of the sub-pixel points in each row or each column in the detection area in a direction perpendicular to the search direction; performing convolution acquisition on the gray average value by using a Gaussian convolution kernel model to obtain an edge strength value; obtaining an optimal edge point according to an edge type and the edge strength value; and fitting a parabola according to the optimal edge point, wherein the intersection point of the symmetry axis of the parabola and the center line of the rotating rectangle is the optimal sub-pixel edge point. The invention aims to provide the sub-pixel edge point detection method based on Gaussian model convolution, edge point detection can be carried out on the edge image with any intensity by setting the convolution kernel width, and the detection precision and algorithm robustness of the sub-pixel edge points are effectively improved.

Description

technical field [0001] The invention relates to the technical field of image processing, in particular to a sub-pixel edge point detection method based on Gaussian model convolution. Background technique [0002] With the development of artificial intelligence technology, the speed of upgrading of electronic products such as mobile phones is accelerating, and the assembly requirements for electronic product components are getting higher and higher. The edge of the product image is the main part of the image feature, and the accuracy of edge point detection has a crucial impact on the assembly accuracy of the product. [0003] The commonly used method for edge point detection is visual detection, that is, the use of image processing algorithms to extract image edge points, and use this as a basis for subsequent straight line fitting or other operations. But most of the current algorithms only stop at the detection of the edge point of the whole pixel. The conventional method...

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Application Information

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IPC IPC(8): G06T7/13G06T7/68
CPCG06T7/13G06T7/68
Inventor 冯西王盼刘中张勇
Owner 成都新西旺自动化科技有限公司
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