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Machine vision-based paddle shadow transfer printing defect identification method

A machine vision, defect recognition technology, applied in character and pattern recognition, optical testing flaws/defects, instruments, etc., can solve the problems of single judgment standard, low product qualification rate, unqualified, etc., to achieve the effect of improving efficiency

Active Publication Date: 2021-07-13
SOUTH CHINA UNIV OF TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

This way of judging the standard is too single, if the implementation is strict, it will lead to some acceptable defects, for example, the deviation within a certain deviation range will be judged as unqualified, resulting in a low product qualification rate; if the matching standard is relaxed, it will be Cause some unacceptable defects even though the features are subtle will be judged as qualified products

Method used

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  • Machine vision-based paddle shadow transfer printing defect identification method
  • Machine vision-based paddle shadow transfer printing defect identification method
  • Machine vision-based paddle shadow transfer printing defect identification method

Examples

Experimental program
Comparison scheme
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Embodiment 1

[0030] Such as figure 1 A method for identifying paddle shadow pad printing defects based on machine vision is shown, comprising the following steps:

[0031] Step 1. Use the dome LED diffuse reflector to illuminate the product, and take pictures of the product with an industrial area array color camera with 5 million pixels to obtain the image of the product's blade to be tested.

[0032] Step 2. Use standard template matching to identify standard qualified products and generalized unqualified products, including the following steps:

[0033] Step 2.1, using the contour line of the product in the standard qualified product image, the contour line of the pad printing graphic and the gray value of the pad printing graphic as the conditions for matching the standard template;

[0034] Step 2.2, performing grayscale and Gaussian filtering preprocessing on the acquired image;

[0035] Step 2.3, using the method of edge extraction to obtain the contour line of the product shape, ...

Embodiment 2

[0056] A method for recognizing paddle shadow pad printing defects based on machine vision, comprising the following steps:

[0057] Step 1. Use the dome LED diffuse reflector to illuminate the product, and take pictures of the product with an industrial area array color camera with 5 million pixels to obtain the image of the product's blade to be tested.

[0058] Step 2. Use standard template matching to identify standard qualified products and generalized unqualified products, specifically including the following steps:

[0059] Step 2.1, using the contour line of the standard qualified product image, the contour line of the paddle shadow pad printing figure and the model number character of the product as the matching conditions;

[0060] Step 2.2, preprocessing the acquired image, that is, using a median filter to remove certain noise interference on the image;

[0061] Step 2.3, using the method of edge extraction to obtain the contour line of the product shape, and usin...

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Abstract

The invention discloses a machine vision-based paddle shadow transfer printing defect identification method. The method comprises the following steps of: acquiring an image of a to-be-detected paddle; matching with a template of a standard qualified product is carried out, the product successfully matched is a qualified product, and the product failed in matching is a generalized unqualified product; training an AI algorithm model by using the classified defect image set to obtain an AI algorithm model classifier, and classifying generalized unqualified products by using the classifier; and changing generalized unqualified products meeting the targeted detection conditions into qualified products. Through the method, different defects are detected differently, the quality inspection process of products is restored more truly, meanwhile, different quality control errors are set for different types of defects, the quality control grade of qualified products can be adjusted, the quality control thought in industrial production is reflected, and machine vision defect detection is flexible.

Description

technical field [0001] The invention relates to the technical field of machine vision defect detection and recognition, in particular to a machine vision-based paddle shadow pad printing defect recognition method. Background technique [0002] During the pad printing process, the paddle shadow on the propeller of the drone will have defects such as pad printing offset, pad printing with more oil, pad printing with less oil, and pad printing color difference. In order to ensure the quality of UAV products, it is necessary to detect and identify these defects. There are currently two methods of manual visual inspection and identification and machine vision automatic identification. The way of artificial vision is greatly affected by the subjective factors of personnel, and it is easy to fatigue after long-term work, which cannot guarantee the quality of inspection well. Machine vision automatic recognition is being adopted by more and more enterprises because of its advantage...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01N21/88G06K9/62G06T7/00
CPCG01N21/8851G06T7/001G01N2021/8887G06T2207/20081G06T2207/20084G06T2207/30144G06F18/241
Inventor 宋建方嵩
Owner SOUTH CHINA UNIV OF TECH
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