CN112763496A - Mobile phone battery surface defect detection device and detection method thereof - Google Patents
Mobile phone battery surface defect detection device and detection method thereof Download PDFInfo
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- CN112763496A CN112763496A CN202011549567.6A CN202011549567A CN112763496A CN 112763496 A CN112763496 A CN 112763496A CN 202011549567 A CN202011549567 A CN 202011549567A CN 112763496 A CN112763496 A CN 112763496A
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- 238000001514 detection method Methods 0.000 title claims abstract description 41
- 238000007781 pre-processing Methods 0.000 claims abstract description 11
- 230000001131 transforming Effects 0.000 claims abstract description 7
- 238000005259 measurement Methods 0.000 claims abstract description 6
- 238000000034 method Methods 0.000 claims description 11
- 238000003860 storage Methods 0.000 claims description 6
- 238000003708 edge detection Methods 0.000 claims description 4
- 238000004458 analytical method Methods 0.000 claims description 3
- 238000004364 calculation method Methods 0.000 claims description 3
- 238000000605 extraction Methods 0.000 claims description 3
- 238000005286 illumination Methods 0.000 claims description 3
- 239000011159 matrix material Substances 0.000 claims description 3
- 238000004519 manufacturing process Methods 0.000 abstract description 3
- 230000002349 favourable Effects 0.000 abstract description 2
- 238000009776 industrial production Methods 0.000 abstract description 2
- 238000004891 communication Methods 0.000 description 2
- 241000519995 Stachys sylvatica Species 0.000 description 1
- 230000000875 corresponding Effects 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000007689 inspection Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000006011 modification reaction Methods 0.000 description 1
Classifications
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/84—Systems specially adapted for particular applications
- G01N21/88—Investigating the presence of flaws or contamination
- G01N21/8851—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration
- G06T5/001—Image restoration
- G06T5/002—Denoising; Smoothing
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0004—Industrial image inspection
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/13—Edge detection
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/194—Segmentation; Edge detection involving foreground-background segmentation
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/84—Systems specially adapted for particular applications
- G01N21/88—Investigating the presence of flaws or contamination
- G01N21/8851—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges
- G01N2021/8887—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges based on image processing techniques
Abstract
The invention discloses a device and a method for detecting surface defects of a mobile phone battery, wherein the device comprises: the machine vision measurement system is used for carrying out image acquisition and preprocessing on the mobile phone battery so as to obtain an image to be detected; and the surface defect detection module is used for aligning the image to be detected and the standard image in an affine transformation mode and detecting the surface defects of the mobile phone battery. The machine vision is used for observing fatigue cracks instead of human eyes, so that the problems that the manual detection of the mobile phone battery requires the energy of an operator, the labor cost is high, the efficiency is low and the like are solved; the efficiency of industrial production is improved by a wide margin, simultaneously reduces operator's the use degree of difficulty effectively, is favorable to the equipment manufacturing of high accuracy to the automatic development.
Description
Technical Field
The invention relates to the technical field of surface defect detection of mobile phone batteries, in particular to a device and a method for detecting surface defects of mobile phone batteries.
Background
In the process of automatically producing the mobile phone batteries in the modern industry, the requirements on the mobile phone batteries are increased, each battery has corresponding characters and patterns, the date of delivery, manufacturers, attention points and the like of the mobile phone are shown, and therefore more time is needed to judge whether the patterns and characters printed on the surfaces of the batteries meet the specified standards.
The detection work of the surface defects of the mobile phone battery belongs to the work with high repeatability and intelligence, and needs higher stability and reliability. At present, the detection work of the surface defects of the mobile phone battery is mainly completed by naked eyes of people. However, in the actual detection process, people cannot continuously and stably detect the object with naked eyes, so that the detection stability and reliability are poor, and the labor cost is high.
Disclosure of Invention
The invention provides a device and a method for detecting surface defects of a mobile phone battery, which can detect the surface of the mobile phone battery in real time in the production process based on a machine vision technology, and aims to solve the problems of detecting defects such as scratches, missing prints, white spots and the like on the surface of the mobile phone battery.
The technical scheme adopted by the invention for solving the technical problems is as follows:
a surface defect detection device for a mobile phone battery comprises:
the machine vision measurement system is used for acquiring and processing images of the mobile phone battery so as to obtain an image to be detected; and
the surface defect detection module is used for aligning the image to be detected and the standard image in an affine transformation mode and detecting the surface defects of the mobile phone battery;
wherein the machine vision measurement system comprises:
the mobile phone battery detection device comprises an image acquisition device, a detection device and a control device, wherein the image acquisition device is used for acquiring images of a mobile phone battery to be detected;
the light source comprises a foreground light source and a background light source, the foreground light source can enable the illumination of the mobile phone battery to be uniform, and the background light source can improve the contrast ratio of the mobile phone battery and the background;
a data processor for pre-processing the acquired image;
the image storage device is used for storing images and is in communication connection with the data processor; and
and the detection platform is used for supporting and positioning the mobile phone battery to be detected.
Preferably, the image acquisition device is a camera or an image sensor.
Preferably, the data processor is a computer capable of processing images, the computer comprising a hardware system and a software system.
Preferably, the light source is a parallel light source, and the image storage device is a magnetic disk or a flash memory.
Preferably, the preprocessing includes image denoising and edge detection.
The method for detecting the surface defects of the mobile phone battery comprises the following steps:
firstly, a machine vision measuring system is adopted to collect and process images of a mobile phone battery to be detected, namely, the mobile phone battery is fixed on a detection platform, and the positions of an image collecting device and a light source relative to the mobile phone battery are adjusted to collect the images of the mobile phone battery; then, preprocessing the acquired image, namely, denoising the image and detecting the edge to obtain an image to be detected;
and step two, aligning the image to be detected and the standard image by adopting a surface defect detection module, and detecting the surface defects of the mobile phone battery.
Preferably, the specific detection process in the step two is as follows: in a surface defect detection module, ROI extraction is carried out at a place where characteristic information of an image to be detected is obvious, an affine transformation matrix is obtained through registration information of the ROI, then the whole image to be detected is transformed, the adopted ROI is not changed, then the image to be detected and a standard image are aligned, gray difference is carried out on the image to be detected and the initially defined standard image after the image is aligned, and binarization is carried out on the image after difference to carry out defect detection on the image.
Preferably, the defect detecting process further includes: and (3) performing mathematical form exit on the image to be detected, analyzing the defects by adopting Blob, performing related calculation on the connected components after the image to be detected is divided into a target image and a background image, performing connectivity analysis, and finally judging the defects.
Compared with the prior art, the invention has the beneficial effects that: the machine vision is used for observing fatigue cracks instead of human eyes, so that the problems that the traditional mobile phone battery highly requires the energy of an operator, has high labor cost, low efficiency and the like in the aspect of manual detection are effectively solved. The efficiency of industrial production is improved by a wide margin, simultaneously reduces operator's the use degree of difficulty effectively, is favorable to the equipment manufacturing of high accuracy to the automatic development. Drawings
Fig. 1 is a position layout of a machine vision measuring system.
Fig. 2 is a flow chart of machine vision inspection.
Detailed Description
The present invention is further described in detail below with reference to the attached drawings so that those skilled in the art can implement the invention by referring to the description text.
Referring to fig. 1 and 2, a surface defect detecting apparatus for a mobile phone battery includes:
the machine vision measurement system is used for carrying out image acquisition and preprocessing on the mobile phone battery so as to obtain an image to be detected; and
and the surface defect detection module is used for aligning the image to be detected and the standard image in an affine transformation mode and detecting the surface defects of the mobile phone battery.
As an embodiment of the present invention, the machine vision measuring system includes:
the mobile phone battery detection device comprises an image acquisition device, a detection device and a control device, wherein the image acquisition device is used for acquiring images of a mobile phone battery to be detected;
the light source comprises a foreground light source and a background light source, the foreground light source can enable the illumination of the mobile phone battery to be uniform, and the background light source can improve the contrast ratio of the mobile phone battery and the background;
a data processor for pre-processing the acquired image;
the image storage device is used for storing images and is in communication connection with the data processor; and
the detection platform is used for supporting and positioning the mobile phone battery to be detected;
as an embodiment of the present invention, the image acquisition device is a camera or an image sensor.
As an embodiment of the present invention, the data processor is a computer capable of processing an image, and the computer includes a hardware system and a software system.
Further, the light source is a parallel light source, and the image storage device is a magnetic disk or a flash memory.
Further, the preprocessing comprises image denoising and edge detection.
As an embodiment of the present invention, the present invention further provides a method for detecting surface defects of a mobile phone battery, including the following steps:
firstly, a machine vision measuring system is adopted to collect and process images of a mobile phone battery to be detected, namely, the mobile phone battery is fixed on a detection platform, the position of an image collecting device and a light source relative to the mobile phone battery is adjusted, the mobile phone battery is collected, and then the collected images are preprocessed, namely, image denoising and edge detection are carried out, so that an image to be detected is obtained;
and step two, aligning the image to be detected and the standard image by adopting a surface defect detection module, and detecting the surface defects of the mobile phone battery.
As an embodiment of the present invention, the specific detection process in the step two is as follows: in a surface defect detection module, ROI extraction is carried out at a place where characteristic information of an image to be detected is obvious, an affine transformation matrix is obtained through registration information of the ROI, then the whole image to be detected is transformed, the adopted ROI is not changed, then the image to be detected and a standard image are aligned, gray difference is carried out on the image to be detected and the initially defined standard image after the image is aligned, and binarization is carried out on the image after difference to carry out defect detection on the image.
As an embodiment of the present invention, the defect detection process further includes: and (3) performing mathematical form exit on the image to be detected, analyzing the defects by adopting Blob, performing related calculation on the connected components after the image to be detected is divided into a target image and a background image, performing connectivity analysis, and finally judging the defects.
While embodiments of the invention have been described above, it is not limited to the applications set forth in the description and the embodiments, which are fully applicable in various fields of endeavor to which the invention pertains, and further modifications may readily be made by those skilled in the art, it being understood that the invention is not limited to the details shown and described herein without departing from the general concept defined by the appended claims and their equivalents.
Claims (8)
1. A surface defect detection device for a mobile phone battery is characterized by comprising:
the machine vision measurement system is used for carrying out image acquisition and preprocessing on the mobile phone battery so as to obtain an image to be detected; and
the surface defect detection module is used for aligning the image to be detected and the standard image in an affine transformation mode and detecting the surface defects of the mobile phone battery;
wherein the machine vision measurement system comprises:
the image acquisition device is used for acquiring images of the mobile phone battery to be detected;
the light source comprises a foreground light source and a background light source, the foreground light source is used for enabling the illumination of the mobile phone battery to be uniform, and the background light source is used for improving the contrast ratio of the mobile phone battery and the background;
a data processor for pre-processing the acquired image;
an image storage device for storing images, communicatively coupled to the data processor; and
and the detection platform is used for supporting and positioning the mobile phone battery to be detected.
2. The apparatus for detecting surface defects of a mobile phone battery as claimed in claim 1, wherein the image capturing device is a camera or an image sensor.
3. The apparatus of claim 1, wherein the data processor is a computer capable of processing images, the computer comprising a hardware system and a software system.
4. The apparatus of claim 1, wherein the light source is a collimated light source, and the image storage device is a magnetic disk or a flash memory.
5. The apparatus of claim 1, wherein the preprocessing comprises image denoising and edge detection.
6. Method for detecting surface defects of a mobile phone battery using a detection device according to any one of claims 1 to 5, characterized in that it comprises the following steps:
firstly, a machine vision measuring system is adopted to collect and process images of a mobile phone battery to be detected; fixing a mobile phone battery on a detection platform, adjusting the positions of an image acquisition device and a light source relative to the mobile phone battery, and acquiring the image of the mobile phone battery; then, preprocessing the acquired image, namely, denoising the image and detecting the edge to obtain an image to be detected;
and step two, aligning the image to be detected and the standard image by adopting a surface defect detection module, and detecting the surface defects of the mobile phone battery.
7. The method for detecting surface defects of a mobile phone battery as claimed in claim 6, wherein the defect detecting process in the second step is: in a surface defect detection module, ROI extraction is carried out at a place where characteristic information of an image to be detected is obvious, an affine transformation matrix is obtained through registration information of the ROI, then the whole image to be detected is transformed, the adopted ROI is not changed, then the image to be detected and a standard image are aligned, gray difference is carried out on the image to be detected and the initially defined standard image after the image is aligned, and binarization is carried out on the image after difference to carry out defect detection on the image.
8. The method for detecting surface defects of a mobile phone battery as claimed in claim 7, wherein the defect detection process further comprises: and (3) performing mathematical form exit on the image to be detected, analyzing the defects by adopting Blob, performing related calculation on the connected components after the image to be detected is divided into a target image and a background image, performing connectivity analysis, and finally judging the defects.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011549567.6A CN112763496A (en) | 2020-12-24 | 2020-12-24 | Mobile phone battery surface defect detection device and detection method thereof |
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| Application Number | Priority Date | Filing Date | Title |
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| CN202011549567.6A CN112763496A (en) | 2020-12-24 | 2020-12-24 | Mobile phone battery surface defect detection device and detection method thereof |
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| CN112763496A true CN112763496A (en) | 2021-05-07 |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113624952A (en) * | 2021-10-13 | 2021-11-09 | 深圳市帝迈生物技术有限公司 | In-vitro diagnosis device, detection method thereof and computer readable storage medium |
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| CN110246122A (en) * | 2019-05-20 | 2019-09-17 | 江苏理工学院 | Small size bearing quality determining method, apparatus and system based on machine vision |
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2020
- 2020-12-24 CN CN202011549567.6A patent/CN112763496A/en active Pending
Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110246122A (en) * | 2019-05-20 | 2019-09-17 | 江苏理工学院 | Small size bearing quality determining method, apparatus and system based on machine vision |
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| CN113624952A (en) * | 2021-10-13 | 2021-11-09 | 深圳市帝迈生物技术有限公司 | In-vitro diagnosis device, detection method thereof and computer readable storage medium |
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