High-precision visual measurement method, device and system based on bionic algorithm

A visual measurement and high-precision technology, which is applied in the field of high-precision visual measurement based on bionic algorithms, can solve the problems of single-shot imaging field of view imaging accuracy constraints, and achieve the effect of improving efficiency and expanding the field of view

Active Publication Date: 2019-06-04
EAST CHINA JIAOTONG UNIVERSITY
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  • Abstract
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Problems solved by technology

[0007] The purpose of the present invention is to provide a bionic algorithm-based high-precision visual measurement method, device and system to solve the techni

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  • High-precision visual measurement method, device and system based on bionic algorithm
  • High-precision visual measurement method, device and system based on bionic algorithm
  • High-precision visual measurement method, device and system based on bionic algorithm

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Embodiment 1

[0075] see figure 1 As shown, the bionic algorithm-based high-precision visual measurement method provided by the present invention mainly includes steps:

[0076] Step S110, establishing a mapping relationship between the image pixel size and the actual spatial geometric size of the object to be measured.

[0077] This step is to establish the corresponding relationship between the coordinates of the pixel points in the image coordinate system and the coordinates of the target feature points of the measured object (such as a precision axis equiaxed set) in the world coordinate system. As a possible implementation manner, a reference image may be obtained in advance, and the correspondence relationship between the pixel size in the image and the actual spatial geometric size of the object to be measured can be established through the reference image.

[0078] Step S111, acquiring a plurality of first low-resolution images of the object to be measured.

[0079] Step S112, per...

Embodiment 2

[0087] Embodiment 2 of the present invention provides a preferred embodiment of a bionic algorithm-based high-precision visual measurement method.

[0088] In this embodiment, the method includes the steps of:

[0089] Step S211, acquiring a reference image, and establishing a mapping relationship between the pixel size in the reference image and the actual spatial geometric size of the object to be measured.

[0090] The reference image is a pre-acquired standard image, which is used to establish the correspondence between the pixel size of the image and the actual size of the object to be measured.

[0091] Preferably, before performing the measurement, it is also necessary to adjust the measurement accuracy of the imaging system from the perspective of hardware equipment. In the embodiment of the present invention, when the object plane moves along the optical axis of the system, a mathematical model is established to calculate the deflection angle between the optical axis...

Embodiment 3

[0212] The embodiment of the present invention also provides a high-precision visual measuring device based on a bionic algorithm. The unit includes:

[0213] The mapping module is used to obtain a reference image, and establish a mapping relationship between the pixel size in the reference image and the actual spatial geometric size of the object to be measured.

[0214] The image acquisition module is used to acquire multiple low-resolution images of the object to be measured.

[0215] The reconstruction module is used to perform super-resolution reconstruction based on the residual network on multiple low-resolution images to obtain the first super-resolution image.

[0216] The rough edge detection module is used for extracting edge points through an improved Canny edge detection operator for the first super-resolution image; and extracting corner points through Hilbert transform.

[0217] The fruit fly detection module is used to use edge points and corner points as heuri...

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Abstract

The invention provides a high-precision visual measurement method, device and system based on a bionic algorithm. The method comprises the following steps: establishing a mapping relation between a pixel size and an actual spatial geometric size of a to-be-measured object; Obtaining low-resolution images of the plurality of to-be-measured objects; Carrying out super-resolution reconstruction through a super-resolution algorithm based on a residual network; For the reconstructed image, extracting edge points by using a Canny edge detection operator, extracting corner points by using Hilbert transform, and carrying out edge tracking by using the edge points and the corner points as heuristic information through a fruit fly algorithm; And finally, obtaining a single-pixel edge by utilizing arelated mechanism, and calculating the spatial geometric dimension of the to-be-measured object. The device comprises a mapping module, an image acquisition module, a reconstruction module, an edge coarse detection module, a fruit fly detection module and a calculation module. The system comprises an objective table, a CCD camera, a two-dimensional workbench and the like. According to the invention, the field of view of single imaging is effectively expanded, the measurement cost is reduced, and the detection efficiency is improved.

Description

technical field [0001] The invention relates to the technical field of high-precision visual measurement based on bionic algorithms, in particular to a high-precision visual measurement method, device and system based on bionic algorithms. Background technique [0002] Shaft sleeve parts are basic components in the field of industrial production and are very common in various mechanical equipment. In the process of manufacturing and assembly, various defects, such as scratches and pits, inevitably appear on the outer surface of parts. These defects seem to be insignificant, but they may have adverse effects on their performance, so they need to be strictly tested during the production and assembly of parts. Traditional part defect detection usually uses manual methods to detect part defects, which is not only slow, but also cannot effectively guarantee the reliability of product defect detection, and cannot meet the urgent needs of enterprises for improving product quality....

Claims

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Application Information

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IPC IPC(8): G06T3/40G06T7/13G06N3/00G06N3/04G06N3/08G01N21/88G01B11/30G01B11/00
CPCY02P90/30
Inventor 谢昕王伟如胡锋平江勋绎王斌万天成
Owner EAST CHINA JIAOTONG UNIVERSITY
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