Industrial product defect intelligent detection method and device and computer storage medium thereof

A technology of intelligent detection and industrial products, which is applied in computing, image data processing, instruments, etc., can solve the problems of inability to obtain accurate characteristic parameters of targets, inability to meet customers' precise and high-speed detection requirements, and inability of accuracy rate to stably reach recognition rate, etc.

Pending Publication Date: 2021-08-10
维库(厦门)信息技术有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] There are two types of detection methods in the existing technology, one is pure deep learning target detection and target segmentation, this method cannot obtain the precise characteristic parameters of the target, that is, it cannot meet the customer's precise and high-speed detection requirements; the other is It is a traditional machine learning method for detection, which requires an expert mode to adjust parameters, and the accuracy rate cannot stably reach a recognition rate of more than 99%.

Method used

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  • Industrial product defect intelligent detection method and device and computer storage medium thereof
  • Industrial product defect intelligent detection method and device and computer storage medium thereof
  • Industrial product defect intelligent detection method and device and computer storage medium thereof

Examples

Experimental program
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Embodiment 1

[0028] This embodiment provides an intelligent detection method for industrial product defects based on the combination of traditional machine learning and deep learning. The camera head obtains), and the image data is transmitted to the memory of the PC terminal, and the PC terminal processor of this embodiment processes the image data in the memory for the X86 processor; then, the X86 processor (the processor includes but is not limited to CPU, GPU, FPGA , ASIC processor) to process the image data, such as figure 1 As shown, it specifically includes the following steps:

[0029] Step 1: Scale the image data using a bilinear interpolation scaling algorithm to obtain the scaled image data;

[0030] Step 2: Normalize the scaled image data. The normalization algorithm includes: first calculate the mean and variance of the image data, and then subtract the mean from each data and divide by the variance;

[0031] Step 3: Use a segmentation model (for example, a UNet++ model) to ...

Embodiment 2

[0039] The invention provides an intelligent detection device for industrial product defects based on the combination of traditional machine learning and deep learning, such as figure 2 shown, including:

[0040] The image scaling module is used to scale the image data using a bilinear interpolation scaling algorithm to obtain the scaled image data;

[0041] A normalization module is used to normalize the scaled image data. The normalization algorithm includes: first calculating the mean and variance of the image data, and then subtracting the mean from each data and dividing by the variance;

[0042] Coarse detection module, for using segmentation model (for example, can be UNet++ model) to carry out first rough detection to the image data after normalization, obtains target position ROI rectangular frame;

[0043] The fine inference detection module is used to cut out the image data of the ROI rectangular frame and use the segmentation model (UNet++ model) to carry out fin...

Embodiment 3

[0050] The present invention provides a computer-readable storage medium, such as image 3 As shown, a computer program is stored thereon, and when the program is executed by a processor, the method described in the first embodiment is realized.

[0051]Those skilled in the art should understand that the embodiments of the present invention may be provided as methods, apparatuses, or computer program products. Accordingly, the present invention can take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) having computer-usable program code embodied therein.

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Abstract

The invention discloses an industrial product defect intelligent detection method and device and a computer storage medium thereof, and the method comprises the steps: zooming image data by a bilinear interpolation zooming algorithm, and obtaining the zoomed image data; normalizing the zoomed image data; performing first coarse detection on the normalized image data by a segmentation model to obtain a target position ROI rectangular frame; cutting out image data of the ROI rectangular frame, and performing fine reasoning detection by using a segmentation model to obtain segmented target image data; performing a contour extraction algorithm on the segmented target image data to obtain a coordinate sequence of all target contours; and according to the multi-target contour coordinate sequence, counting and analyzing target data in the contour in the image data to obtain target characteristic parameters, and according to the multi-target contour coordinate sequence, carrying out contour characteristic parameter calculation so as to carry out defect identification on the product image. The invention has the characteristics of being suitable for low-cost, large-scale, high-accuracy and high-efficiency detection.

Description

【Technical field】 [0001] The invention belongs to the technical field of industrial product detection, and specifically refers to an industrial product defect intelligent detection method, device and computer storage medium thereof. 【Background technique】 [0002] The machine vision system in the field of industrial product defect detection is mainly divided into two parts: the image acquisition unit composed of traditional cameras, lenses, light sources, camera fixing and motion mechanisms, and the machine vision detection system composed of PC hosts and image acquisition cards and other image processing units. . This kind of machine vision has high extensibility and plasticity, and it can develop customized hardware and customized software for different product defects. [0003] There are two types of detection methods in the existing technology, one is pure deep learning target detection and target segmentation, this method cannot obtain the precise characteristic parame...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T3/40G06T7/00G06T7/13G06T7/62
CPCG06T3/4023G06T7/0004G06T2207/20104G06T7/13G06T7/62
Inventor 黄旭东林宇
Owner 维库(厦门)信息技术有限公司
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