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A method and system for detect defects in defective image

A defect detection and image technology, used in image enhancement, image analysis, image data processing, etc., can solve problems such as bad image defect detection methods, and achieve the effect of improving the level of automatic detection, ensuring industrial detection accuracy, and optimizing detection accuracy.

Inactive Publication Date: 2019-03-15
CHENGDU UNION BIG DATA TECH CO LTD
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  • Abstract
  • Description
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Problems solved by technology

[0004] In order to solve the above problems, the present invention proposes a bad image defect detection method and system, which can effectively realize defect position detection and defect category prediction, with high precision and accurate classification, and better detection effect on small targets; it can optimize detection accuracy, reduce missed detection

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  • A method and system for detect defects in defective image
  • A method and system for detect defects in defective image
  • A method and system for detect defects in defective image

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Embodiment Construction

[0045] In order to make the purpose, technical solution and advantages of the present invention clearer, the present invention will be further elaborated below in conjunction with the accompanying drawings.

[0046] In this example, see figure 1 As shown, the present invention proposes a kind of bad image defect detection method, comprises steps:

[0047] S1, upload defect image data and normal image data;

[0048] S2, using a marking tool to mark the defect on the defect image;

[0049] S3, divide the image data into two types of training samples and test samples;

[0050] S4, according to different defect levels, use the neural network of the corresponding calculation level for training, and train the deep learning model;

[0051] S5, performing defect location by template matching method;

[0052] S6, train the test samples through the deep learning model, detect the defect pixel area of ​​the bad image and the specific location of the defect in the image, and predict t...

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Abstract

The invention discloses a defect detection method and a system of a defective image. Through a depth learning method, a depth convolution neural network model is constructed to analyze the deep logical relationship between defect factors in the bad image, the defect relationship between parts and parts, and the defect classification between parts and the whole, thereby realizing defect classification. The invention can effectively realize defect position detection and defect class prediction, has high precision and accurate classification, and has better detection effect on small targets. It can optimize the detection accuracy and reduce the missed detection.

Description

technical field [0001] The invention belongs to the technical field of image defect detection, and in particular relates to a method and system for detecting bad image defects. Background technique [0002] There will be many bad defects in the products produced during the production process, and the detection of product defects can usually be carried out by means of image recognition. However, there are many types of such defects, and the image features of the same defect are diverse, without significant features, and the image performance of some defects is not obvious; the existing feature engineering method to detect image defects is difficult to accurately detect various defects in bad images. [0003] In the traditional image detection method, if the new feature is slightly different from the set feature set, the traditional machine learning cannot accurately detect the defect, resulting in a decrease in the overall accuracy. It is very difficult to realize automatic ...

Claims

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Application Information

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IPC IPC(8): G06T7/00G06T7/73G06K9/62
CPCG06T7/001G06T7/73G06T2207/30108G06T2207/20084G06T2207/20081G06T2207/10004G06F18/2413G06F18/24147
Inventor 不公告发明人
Owner CHENGDU UNION BIG DATA TECH CO LTD
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