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Mobile phone screen detection method

A mobile phone screen and detection method technology, applied in image data processing, instruments, calculations, etc., can solve problems such as scratches, failure to meet industrial production requirements, and detection difficulties, and achieve the effects of eliminating noise, high detection efficiency and accuracy Effect

Active Publication Date: 2019-08-09
SHANGHAI APPLIED TECHNOLOGIES COLLEGE
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  • Abstract
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AI Technical Summary

Problems solved by technology

After a series of processing, mobile phone screen glass will inevitably have defects, mainly including scratches, surface light transmission, ink falling in the character area, chipping and other defects. Due to the complex types of defects and the printed part of the surface, the detection of defects becomes more difficult
At present, domestic defect detection methods for LCD screens can only detect individual defects, which cannot meet the requirements of industrial production

Method used

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Embodiment Construction

[0043] In order to make the above objects, features and advantages of the present invention more comprehensible, the present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0044] Such as figure 1 As shown, the present invention provides a mobile phone screen detection method, including:

[0045] Step 1: Obtain a clear pixel image of the mobile phone screen;

[0046] Step 2: Use the PatMax algorithm to perform model training on the pixel image obtained in step 2 to obtain a model with pose information;

[0047] Step 3: receiving the pose information in the model, establishing a coordinate system based on the model, and outputting an image from the model on the coordinate system, the coordinate system is used to provide coordinate positions for subsequent identification;

[0048] Step 4: performing affine transformation on the image output from the model in step 3 to generate a rectangular output im...

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Abstract

The invention provides a mobile phone screen detection method. The method comprises the following steps of firstly, carrying out image positioning on an obtained mobile phone screen image by using a template positioning technology of a PatMax algorithm, correcting the mobile phone screen image by using an image correction technology based on affine transformation, and carrying out image filteringby using 3 * 3 median filtering to eliminate the noise influence and protect the edge information of a test image, and then training a template image, subtracting the template image from the test image to obtain a difference image, and finally detecting and positioning the defect features in the image by utilizing a Blob analysis method. The method provided by the invention can effectively identify various defects of the mobile phone screen, and has the higher detection efficiency and precision.

Description

technical field [0001] The invention relates to a mobile phone screen detection method. Background technique [0002] Smartphones are currently the best-selling mobile terminal equipment, and their market competition is becoming increasingly fierce. It is of great significance to inspect the appearance of the mobile phone screen before leaving the factory. At present, manual visual inspection is the most commonly used method for detecting defects on mobile phone screens. However, manual inspection is very time-consuming, and different people or even the same person have different inspection results under different conditions, and defects are easily missed or wrongly detected. [0003] Compared with manual visual inspection, machine vision adopts non-contact detection method, which not only has the characteristics of high efficiency, strong stability, and high automation, but also can achieve high resolution accuracy, is safe and reliable, and has been widely used in defect d...

Claims

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Application Information

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IPC IPC(8): G06T7/00G06T5/00G06T7/136
CPCG06T7/001G06T7/136G06T2207/20032G06T2207/30121G06T5/70
Inventor 张建国李颖候慧敏齐家坤季甜甜刘隽
Owner SHANGHAI APPLIED TECHNOLOGIES COLLEGE
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