Mobile phone screen backlight foreign matter defect diagnosis method and device based on machine vision

A machine vision and defect diagnosis technology, applied in the field of defect diagnosis, can solve problems such as the inability to meet mobile phone screens, manual inspection time-consuming and labor-intensive, etc., and achieve the effects of low cost, high factory cost, and high detection accuracy.

Pending Publication Date: 2019-11-12
NORTHEASTERN UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

For mobile phone screen defect detection, manual detection is time-consuming and labor-intensive. Most automatic detection algorithms based on machine vision can only detect several types of screens, which can no longer meet the requirements of mobile phone screen manufacturers.

Method used

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  • Mobile phone screen backlight foreign matter defect diagnosis method and device based on machine vision
  • Mobile phone screen backlight foreign matter defect diagnosis method and device based on machine vision
  • Mobile phone screen backlight foreign matter defect diagnosis method and device based on machine vision

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Experimental program
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Effect test

Embodiment approach

[0102] As a preferred implementation manner, the step S3 also includes the following steps:

[0103] Step S31: After the screen of the mobile phone is turned off, when the side light is turned on, the surrounding environment of the captured image and the boundary between the screen of the mobile phone are not obvious, but because the relative position of the screen of the mobile phone to the CCD camera does not change before and after the screen is turned on and off , at this time, the coordinates of the screen area of ​​the mobile phone in the side light image obtained by shooting should be the same as the coordinates described in step S1, according to this coordinate (y+3: y+h-3, x+3: x+w-3 ) to crop the image to obtain the mobile phone screen area Q' in the side light image.

[0104] Step S32: Dust can be shown in the side light image because it can be captured by a CCD industrial camera due to its diffuse reflection under the irradiation of side light. Although the gray v...

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Abstract

The invention provides a mobile phone screen backlight foreign matter defect diagnosis method based on machine vision, and the method comprises the following steps: lightening a screen through a PLC (Programmable Logic Controller) to enable the mobile phone screen to be in a white ground color, collecting an image through a CCD (Charge Coupled Device) industrial camera, extracting an area of the mobile phone screen in the image, and obtaining a mobile phone screen image P; turning off the screen of the mobile phone, starting a dust sidelight device, and acquiring an image through a CCD industrial camera to obtain a sidelight image Q; carrying out preprocessing and threshold segmentation on the mobile phone screen image P to obtain a backlight foreign matter candidate region; positioning dust in combination with the sidelight graph Q, and eliminating dust interference in the candidate area; extracting a local sub-graph of a backlight foreign matter candidate region without dust interference, and eliminating the interference of scratches and dirty spots through secondary threshold segmentation; and finally, positioning the backlight foreign matter area of the mobile phone screen. Inthe aspect of interference removal of dust factors, the dust sidelight device is designed, dust interference is accurately eliminated, and the detection accuracy is improved.

Description

technical field [0001] The present invention relates to the technical field of defect diagnosis, in particular to a machine vision-based method and device for diagnosing foreign matter defects in the backlight of a mobile phone screen. Background technique [0002] Today, with the rapid development of industrial production, mobile phones of various sizes and models are flooding all over the world, and the speed of product replacement is also jaw-dropping. For mobile phone screen defect detection, manual detection is time-consuming and labor-intensive. Most automatic detection algorithms based on machine vision can only detect several types of screens, which can no longer meet the requirements of mobile phone screen manufacturers. For mobile phone screen manufacturers, it is imperative to find a set of efficient, accurate, and general-purpose automated testing equipment to replace manual testing. Machine vision (also known as computer vision) technology has been accumulated ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04M1/24H04N5/225G06T7/136G06T7/11G06T7/00G06T5/30G06T5/00
CPCH04M1/24G06T7/11G06T7/0002G06T7/136G06T5/002G06T5/30H04N23/54
Inventor 张衍超张瑜侯竞夫宫俊
Owner NORTHEASTERN UNIV
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