CN111445458B - Method for detecting printing quality of mobile phone battery label - Google Patents
Method for detecting printing quality of mobile phone battery label Download PDFInfo
- Publication number
- CN111445458B CN111445458B CN202010228513.3A CN202010228513A CN111445458B CN 111445458 B CN111445458 B CN 111445458B CN 202010228513 A CN202010228513 A CN 202010228513A CN 111445458 B CN111445458 B CN 111445458B
- Authority
- CN
- China
- Prior art keywords
- area
- text information
- image
- mobile phone
- standard
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 34
- 238000001914 filtration Methods 0.000 claims description 11
- 238000011946 reduction process Methods 0.000 claims 1
- 238000001514 detection method Methods 0.000 abstract description 22
- 230000002950 deficient Effects 0.000 abstract description 5
- 238000004364 calculation method Methods 0.000 description 4
- 230000007547 defect Effects 0.000 description 4
- 238000004519 manufacturing process Methods 0.000 description 4
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 238000004064 recycling Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR 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
- G06T7/001—Industrial image inspection using an image reference approach
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/50—Information retrieval; Database structures therefor; File system structures therefor of still image data
- G06F16/58—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
- G06F16/583—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
-
- G06T5/70—
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/60—Analysis of geometric attributes
- G06T7/62—Analysis of geometric attributes of area, perimeter, diameter or volume
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30108—Industrial image inspection
- G06T2207/30144—Printing quality
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E60/00—Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
- Y02E60/10—Energy storage using batteries
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Library & Information Science (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Geometry (AREA)
- Quality & Reliability (AREA)
- Data Mining & Analysis (AREA)
- Databases & Information Systems (AREA)
- General Engineering & Computer Science (AREA)
- Accessory Devices And Overall Control Thereof (AREA)
- Printers Characterized By Their Purpose (AREA)
Abstract
The invention discloses a method for detecting the printing quality of a mobile phone battery label, which comprises the following steps: establishing a standard area database; acquiring a label image of a mobile phone battery to be detected; carrying out noise reduction treatment on the tag image, and calculating the area of text information pixel points in the tag image; calculating the error area between the text information pixel point in the tag image and the text information pixel point in the standard quality tag image of the corresponding type; calculating the absolute value of the ratio of the error area to the area of the text information pixel point in the standard quality label image of the corresponding type, and judging whether the absolute value is larger than a preset critical threshold value or not; if so, determining that the printing quality of the label image is unqualified. The invention can effectively detect the printing quality of the label with complex content, can detect whether the text characters are defective or not more accurately, greatly improves the detection efficiency of the printing quality of the mobile phone battery label, and greatly saves the labor cost and the time cost.
Description
Technical Field
The invention relates to the technical field of label printing detection, in particular to a detection method for mobile phone battery label printing quality.
Background
The label is an effective carrier for enterprise tracking products, quality monitoring and production management, and is an effective tool for checking products by common consumers, but the label is affected by uncertain factors such as production process, environment and equipment in the printing production process, and various printing defects and errors exist. Taking the mobile phone battery label printing quality detection as an example, many manufacturers still take manpower as a dominant mode at present, and the mode is low in efficiency and improves the manpower cost.
In order to solve the above problems, a machine vision-based print image quality detection system is raised, which mainly comprises three parts: hardware devices such as cameras, image processing algorithms, software components that display adjustment outputs, which capture images of the printed matter. The main image processing algorithm related to the detection system is an image registration and defect detection algorithm, and a label with smaller similarity is judged to be a defect label by performing similarity matching on a label image to be detected and a standard label image. Practice shows that the detection method based on template matching is easy to be affected by noise, has a good detection effect on labels with relatively single content, but for labels with complex content, such as logo graphics, illustrative case graphics, bar code graphics and character graphics, the importance of the graphic content in the labels is not completely related to the size of the graphic content, and the detection process does not purposefully detect different weights of different types of content areas, so that the false judgment rate is often too high.
Disclosure of Invention
The invention provides a method for detecting the printing quality of a mobile phone battery label, which can effectively detect the printing quality of the label with complex content, can detect whether text characters are defective or not more accurately, greatly improves the detection efficiency of the printing quality of the mobile phone battery label, and greatly saves labor cost and time cost.
According to one aspect of the invention, a method for detecting the printing quality of a mobile phone battery tag is provided, which comprises the following steps:
establishing a standard area database; the database stores area data of text information pixels in standard quality label images of a plurality of types of mobile phone batteries;
acquiring a label image of a mobile phone battery to be detected;
carrying out noise reduction treatment on the tag image, and calculating the area of text information pixel points in the tag image;
calculating the error area between the text information pixel point in the tag image and the text information pixel point in the standard quality tag image of the corresponding type; the error area is the difference between the area of the text information pixel point in the tag image and the area of the text information pixel point in the standard quality tag image of the corresponding type;
calculating the absolute value of the ratio of the error area to the area of the text information pixel point in the standard quality label image of the corresponding type, and judging whether the absolute value is larger than a preset critical threshold value or not;
if yes, determining that the printing quality of the label image is unqualified.
Preferably, the standard area database is established, comprising the steps of:
selecting standard quality label images of a plurality of types of mobile phone batteries as sample data; each of the plurality of types comprises standard quality tag images of a plurality of mobile phone batteries;
carrying out noise reduction treatment on standard quality label images of each type of mobile phone battery;
and calculating the area of text information pixels in the standard quality label image of each type of mobile phone battery after noise reduction, and storing the area in a standard area database.
Preferably, after establishing the standard area database, the method further comprises the steps of:
calculating the minimum circumscribed rectangular area containing text information in the standard quality label image of each type of mobile phone battery after noise reduction;
and calculating the proportion of the area of the text information pixel point in the standard quality label image of each type of mobile phone battery after noise reduction to the minimum circumscribed rectangular area of the standard quality label image, and storing the proportion as area proportion data of the text information pixel point in the standard quality label image in the standard area database.
Preferably, the noise reduction processing is performed on the tag image, and the area of the text information pixel point in the tag image is calculated, including the following steps:
converting the label image into a binary image;
carrying out Gaussian filtering treatment on the binary image;
carrying out noise point removing treatment on the binary image subjected to Gaussian filtering treatment to obtain a noise-reducing label image;
calculating a minimum circumscribed rectangle containing text information in the noise reduction tag image;
and calculating the area of the text information pixel point in the minimum circumscribed rectangle.
Preferably, after the noise reduction processing is performed on the tag image and the area of the text information pixel point in the tag image is calculated, the method further includes the following steps:
determining the type of the acquired label image of the mobile phone battery to be detected;
and selecting the area data of the text information pixel points in the standard quality label image with the same type as the label image of the mobile phone battery to be detected from the standard area database as the area of the text information pixel points in the standard quality label image with the corresponding type.
Preferably, after selecting the area data of the text information pixel point in the standard quality label image with the same type as the label image of the mobile phone battery to be detected from the standard area database as the area of the text information pixel point in the standard quality label image with the corresponding type, the method further comprises the following steps:
determining a preset critical threshold according to the corresponding type area occupation ratio data stored in the standard area database; and the corresponding type area ratio data is the area ratio data of text information pixels in the standard quality label image, which is the same as the type of the label image of the mobile phone battery to be detected.
Preferably, each of the several types includes standard quality label images of 100 mobile phone batteries.
Preferably, the size of the filter in the gaussian filtering is set to 3*3 and the variance is set to 1.5.
Compared with the prior art, the invention has the following beneficial effects:
the invention is insensitive to the content of the label (bar code pattern area, character pattern area and standard pattern area) and the change characteristics thereof in the detection process, can effectively detect the printing quality of the label with complex content, carries out noise reduction treatment on the acquired label image, and can more accurately detect whether the text characters are defective by judging the detection mode of the printing quality of the label. The invention greatly improves the efficiency of detecting the printing quality of the mobile phone battery label and greatly saves the labor cost and the time cost.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiments of the invention and together with the description serve to explain the invention and do not constitute a limitation on the invention. In the accompanying drawings:
fig. 1 is a flowchart of a method for detecting printing quality of a mobile phone battery tag according to an embodiment of the present invention;
fig. 2 is a flowchart of another method for detecting printing quality of a mobile phone battery tag according to the first embodiment of the present invention;
fig. 3 is a matlab code of a noise reduction algorithm in another method for detecting printing quality of a mobile phone battery tag according to the first embodiment of the present invention;
fig. 4 is an implementation image of a step of calculating a minimum circumscribed rectangle containing text information in a noise reduction label image in another method for detecting printing quality of a mobile phone battery label according to the first embodiment of the present invention.
Detailed Description
The technical solutions of the present invention will be described below with reference to the accompanying drawings, but the described embodiments are only some embodiments of the present invention, and all other embodiments obtained by those skilled in the art without making any inventive effort based on the embodiments of the present invention are within the scope of the protection of the present invention.
The embodiment of the invention provides a method for detecting the printing quality of a mobile phone battery tag, and fig. 1 is a flow chart of the method for detecting the printing quality of the mobile phone battery tag according to the embodiment of the invention, as shown in fig. 1, and the method comprises the following steps:
step S101: establishing a standard area database;
step S102: acquiring a label image of a mobile phone battery to be detected;
step S103: carrying out noise reduction treatment on the tag image, and calculating the area of text information pixel points in the tag image;
step S104: calculating the error area between the text information pixel point in the tag image and the text information pixel point in the standard quality tag image of the corresponding type;
step S105: calculating the absolute value of the ratio of the error area to the area of the text information pixel point in the standard quality label image of the corresponding type;
step S106: judging whether the absolute value is larger than a preset critical threshold value or not; if yes, step S107 is performed; if not, ending the flow;
step S107: and determining that the printing quality of the label image is unqualified.
In the implementation process, in step S101, first, standard quality tag images of several types of mobile phone batteries are selected as sample data; each of the plurality of types includes a standard quality label image of a plurality of mobile phone batteries; the standard quality label images of the plurality of mobile phone batteries can be 100; carrying out noise reduction treatment on standard quality label images of each type of mobile phone battery; and calculating the area of text information pixels in the standard quality label image of each type of mobile phone battery after noise reduction, and storing the area in a standard area database.
After step S101, calculating the minimum circumscribed rectangular area containing text information in the standard quality label image of each type of mobile phone battery after noise reduction; and calculating the proportion of the area of the text information pixel point in the standard quality label image of each type of mobile phone battery after noise reduction to the minimum circumscribed rectangular area of the standard quality label image, and storing the proportion as area proportion data of the text information pixel point in the standard quality label image in a standard area database.
In step S103, a specific embodiment is to convert the label image into a binary image; carrying out Gaussian filtering treatment on the binary image; carrying out noise point removing treatment on the binary image subjected to Gaussian filtering treatment to obtain a noise-reducing label image; calculating a minimum circumscribed rectangle containing text information in the noise reduction label image; and calculating the area of the text information pixel point in the minimum circumscribed rectangle.
Specifically, the size of the filter in the above gaussian filtering is set to 3*3 and the variance is set to 1.5.
After step S103, determining the type of the acquired label image of the mobile phone battery to be detected; and selecting the area data of the text information pixel points in the standard quality label image, which is the same as the label image of the mobile phone battery to be detected in type, from the standard area database as the area of the text information pixel points in the standard quality label image of the corresponding type.
Further, a preset critical threshold value can be determined according to the corresponding type area ratio data stored in the standard area database; the corresponding type area ratio data is the area ratio data of text information pixel points in the standard quality tag image, which is the same as the type of the tag image of the mobile phone battery to be detected.
Through the steps, the printing quality detection of the label with the complex content can be effectively performed, whether the text characters are defective or not can be accurately detected, the detection efficiency of the printing quality of the mobile phone battery label is greatly improved, and the labor cost and the time cost are greatly saved.
In order to make the technical scheme and implementation method of the present invention more clear, the following describes its implementation process in detail in connection with a preferred embodiment.
Example 1
The embodiment provides another method for detecting the printing quality of a mobile phone battery tag, as shown in fig. 2, fig. 2 is a flowchart of another method for detecting the printing quality of a mobile phone battery tag according to the first embodiment of the invention, which includes the following steps:
step S201: selecting standard quality label images of a plurality of types of mobile phone batteries as sample data;
in the embodiment of the invention, each of a plurality of types comprises a plurality of standard quality tag images of mobile phone batteries; specifically, each type may include standard quality tag images of 100 mobile phone batteries, so that standard data stored in the database may be more accurate;
step S202: carrying out noise reduction treatment on standard quality label images of each type of mobile phone battery;
step S203: calculating the area of text information pixels in the standard quality label image of each type of mobile phone battery after noise reduction, and storing the area in a standard area database;
in the embodiment of the invention, the standard quality label image of the mobile phone battery has more noise points before being processed, and the area error of the calculated text pixel points is larger at the moment, so that the image can be firstly subjected to noise reduction treatment, other noise points except the text information pixel points are removed, the calculated text information pixel point area is more accurate, and the judgment of whether the label printing quality of the mobile phone battery is qualified or not is facilitated;
step S204: calculating the minimum circumscribed rectangular area containing text information in the standard quality label image of each type of mobile phone battery after noise reduction;
step S205: calculating the proportion of the area of the text information pixel point in the standard quality label image of each type of mobile phone battery after noise reduction to the minimum circumscribed rectangular area of the standard quality label image, and storing the proportion as area proportion data of the text information pixel point in the standard quality label image in a standard area database;
step S206: acquiring a label image of a mobile phone battery to be detected;
in the embodiment of the present invention, the step S206 specifically adopts a proslica GX1050 industrial digital high-resolution megapixel camera or an industrial camera with the same functional quality, adopts a digital camera, a special LED light source, an industrial computer, etc.; in the embodiment, all the label images to be detected are collected at the same angle as the standard quality label images, so that the comparability of the label images to be detected and the standard quality label images can be ensured, and the printing quality judgment result of the label images to be detected can be more accurate;
step S207: converting the label image into a binary image;
step S208: carrying out Gaussian filtering treatment on the binary image;
in the embodiment of the invention, the size of a filter in Gaussian filtering is set to 3*3, and the variance is set to 1.5;
step S209: carrying out noise point removing treatment on the binary image subjected to Gaussian filtering treatment to obtain a noise-reducing label image;
in the embodiment of the invention, noise reduction processing is carried out on the acquired tag image by adopting a noise point removing algorithm aiming at the tag image of the mobile phone battery, specifically, each row of pixels of the tag image is assigned with 0 vector, the number of pixels with 1 in the row is smaller than 30, the value 30 is set according to the processing experience of the tag image of the mobile phone battery of the same type, and different types of tag images can be set differently; for each column, the number of pixel values of 1 in the column is less than 30 and is assigned as a 0 vector;
the matlab code of the noise reduction algorithm is shown in fig. 3, and BW represents a corresponding binary image; xline represents the number of row pixels, ycolumn represents the number of column pixels, and can be adjusted according to the requirement of a mobile phone battery;
step S210: calculating a minimum circumscribed rectangle containing text information in the noise reduction label image;
in the embodiment of the present invention, an image illustrating the above step S210 is shown in fig. 4;
step S211: calculating the area of text information pixel points in the minimum circumscribed rectangle;
in the embodiment of the invention, the minimum circumscribed rectangle is calculated firstly, then the minimum circumscribed rectangle is taken as a new calculation area, and the area of the text information pixel point in the minimum circumscribed rectangle is calculated, so that the calculation area of the text information pixel point area is converted into the minimum circumscribed rectangle from the whole background of the mobile phone battery printed label, the calculation area is effectively reduced, the noise point areas outside the minimum circumscribed rectangle are prevented from being calculated together when the text information pixel point area is calculated, and the calculated text information pixel point area can be further more accurate;
step S212: determining the type of the acquired label image of the mobile phone battery to be detected;
step S213: selecting area data of text information pixels in a standard quality tag image with the same type as the tag image of the mobile phone battery to be detected from a standard area database as the area of the text information pixels in the standard quality tag image with the corresponding type;
in the embodiment of the invention, before judging whether the label image to be detected is qualified, the type of the acquired label image to be detected is determined, and the area data of the same type is selected from the standard area database according to the type of the label image to be detected to carry out subsequent calculation, so that the method for judging the label of the mobile phone battery of different types in a targeted manner can be adopted, the judgment result of the printing quality of the label of the mobile phone battery of different types can be more accurate, and the method can be suitable for detecting the printing quality of the label of the mobile phone battery of different types and has stronger adaptability and practicability;
step S214: determining a preset critical threshold according to the corresponding type area occupation ratio data stored in the standard area database;
in the embodiment of the invention, the corresponding type area ratio data is area ratio data of text information pixel points in a standard quality label image with the same type as that of the label image of the mobile phone battery to be detected; different preset critical thresholds are determined for different types of mobile phone batteries, so that the detection result is more accurate;
step S215: calculating the error area between the text information pixel point in the tag image and the text information pixel point in the standard quality tag image of the corresponding type;
in the embodiment of the invention, the error area is the difference between the area of the text information pixel point in the tag image and the area of the text information pixel point in the standard quality tag image of the corresponding type;
step S216: calculating the absolute value of the ratio of the error area to the area of the text information pixel point in the standard quality label image of the corresponding type;
step S217: judging whether the absolute value is larger than a preset critical threshold value or not; if yes, go to step S218; if not, ending the flow;
step S218: and determining that the printing quality of the label image is unqualified.
By way of example, the detection method of the invention can be directly used on a production line without special operation, when a mobile phone battery flows into a track to trigger a photoelectric sensor, the system automatically detects the front printing area of the battery, mainly detects the printing defects of the mobile phone battery label such as missing characters, multiple characters, missing strokes, multiple strokes, spots, pollution and the like, and the detection is completed, and the printing quality is normal, a green light is turned on and the battery directly flows out; when the printing quality is in a problem, a red light is lighted, and the battery is pushed into the recycling box by the quality problem removing device. The detection speed mainly depends on the belt conveying speed, the picture collecting speed of the camera and the image processing algorithm speed, and the detection accuracy depends on the resolution of the collected pictures.
In summary, the method is insensitive to the content (bar code type graphic area, character type graphic area and standard type graphic area) and the change characteristics of the label in the detection process, can effectively detect the printing quality of the label with complex content, carries out noise reduction treatment on the acquired label image, and can more accurately detect whether the text characters are defective or not by judging the detection mode of the printing quality of the label. The invention greatly improves the efficiency of detecting the printing quality of the mobile phone battery label and greatly saves the labor cost and the time cost.
Claims (6)
1. The method for detecting the printing quality of the mobile phone battery tag is characterized by comprising the following steps of:
establishing a standard area database; the database stores area data of text information pixels in standard quality label images of a plurality of types of mobile phone batteries; after the standard area database is established, the method further comprises the following steps: calculating the minimum circumscribed rectangular area containing text information in the standard quality label image of each type of mobile phone battery after noise reduction; calculating the proportion of the area of the text information pixel point in the standard quality label image of each type of mobile phone battery after noise reduction to the minimum circumscribed rectangular area of the standard quality label image, and storing the proportion as area proportion data of the text information pixel point in the standard quality label image in the standard area database;
acquiring a label image of a mobile phone battery to be detected;
noise reduction processing is carried out on the tag image, and the area of text information pixels in the tag image is calculated, and the method comprises the following steps: converting the label image into a binary image; carrying out Gaussian filtering treatment on the binary image; carrying out noise point removing treatment on the binary image subjected to Gaussian filtering treatment to obtain a noise-reducing label image; calculating a minimum circumscribed rectangle containing text information in the noise reduction tag image; calculating the area of text information pixel points in the minimum circumscribed rectangle;
calculating the error area between the text information pixel point in the tag image and the text information pixel point in the standard quality tag image of the corresponding type; the error area is the difference between the area of the text information pixel point in the tag image and the area of the text information pixel point in the standard quality tag image of the corresponding type;
calculating the absolute value of the ratio of the error area to the area of the text information pixel point in the standard quality label image of the corresponding type, and judging whether the absolute value is larger than a preset critical threshold value or not;
if yes, determining that the printing quality of the label image is unqualified.
2. The method of claim 1, wherein building a standard area database comprises the steps of:
selecting standard quality label images of a plurality of types of mobile phone batteries as sample data; each of the plurality of types comprises standard quality tag images of a plurality of mobile phone batteries;
carrying out noise reduction treatment on standard quality label images of each type of mobile phone battery;
and calculating the area of text information pixels in the standard quality label image of each type of mobile phone battery after noise reduction, and storing the area in a standard area database.
3. The method of claim 1, further comprising the steps of, after performing a noise reduction process on the label image and calculating an area of a text information pixel in the label image:
determining the type of the acquired label image of the mobile phone battery to be detected;
and selecting the area data of the text information pixel points in the standard quality label image with the same type as the label image of the mobile phone battery to be detected from the standard area database as the area of the text information pixel points in the standard quality label image with the corresponding type.
4. The method according to claim 3, further comprising the steps of, after selecting, from the standard area database, area data of text information pixels in a standard quality label image of the same type as the label image of the mobile phone battery to be detected as the area of text information pixels in a standard quality label image of a corresponding type:
determining a preset critical threshold according to the corresponding type area occupation ratio data stored in the standard area database; and the corresponding type area ratio data is the area ratio data of text information pixels in the standard quality label image, which is the same as the type of the label image of the mobile phone battery to be detected.
5. The method of claim 2, wherein each of the plurality of types includes standard quality label images of 100 cell phone batteries.
6. The method of claim 1, wherein the size of the filter in the gaussian filter is set to 3*3 and the variance is set to 1.5.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010228513.3A CN111445458B (en) | 2020-03-27 | 2020-03-27 | Method for detecting printing quality of mobile phone battery label |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010228513.3A CN111445458B (en) | 2020-03-27 | 2020-03-27 | Method for detecting printing quality of mobile phone battery label |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN111445458A CN111445458A (en) | 2020-07-24 |
| CN111445458B true CN111445458B (en) | 2023-07-04 |
Family
ID=71654786
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010228513.3A Active CN111445458B (en) | 2020-03-27 | 2020-03-27 | Method for detecting printing quality of mobile phone battery label |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111445458B (en) |
Family Cites Families (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH1185991A (en) * | 1997-09-04 | 1999-03-30 | Sanyo Electric Co Ltd | Printed matter inspecting method |
| CN109308700A (en) * | 2017-07-27 | 2019-02-05 | 南京敏光视觉智能科技有限公司 | A kind of visual identity defect inspection method based on printed matter character |
| CN109085176A (en) * | 2018-08-20 | 2018-12-25 | 深圳科瑞技术股份有限公司 | A kind of label print quality inspection and data verification method |
| CN109934809A (en) * | 2019-03-08 | 2019-06-25 | 深慧视(深圳)科技有限公司 | A kind of paper labels character defect inspection method |
| CN110705531B (en) * | 2019-09-29 | 2022-03-18 | 北京猎户星空科技有限公司 | Missing character detection and missing character detection model establishing method and device |
-
2020
- 2020-03-27 CN CN202010228513.3A patent/CN111445458B/en active Active
Also Published As
| Publication number | Publication date |
|---|---|
| CN111445458A (en) | 2020-07-24 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN114240939B (en) | Method, system, equipment and medium for detecting appearance defects of mainboard components | |
| CN102348128A (en) | Surveillance camera system having camera malfunction detection function | |
| CN109752392B (en) | PCB defect type detection system and method | |
| CN114202543B (en) | Method, device, equipment and medium for detecting dirt defects of PCB (printed circuit board) | |
| CN112419298B (en) | Bolt node plate rust detection method, device, equipment and storage medium | |
| CN111814776B (en) | Image processing method, device, server and storage medium | |
| CN114266764A (en) | Character integrity detection method and device for printed label | |
| CN114820626B (en) | Intelligent detection method for automobile front face part configuration | |
| CN111882547A (en) | PCB missing part detection method based on neural network | |
| WO2022227103A1 (en) | Intelligent detection and mark system and method for parts | |
| CN116485779A (en) | Adaptive wafer defect detection method and device, electronic equipment and storage medium | |
| CN114998217A (en) | Method for determining defect grade of glass substrate, computer device and storage medium | |
| CN114187247A (en) | Ampoule bottle printing character defect detection method based on image registration | |
| CN114332622A (en) | Label detection method based on machine vision | |
| CN113780484A (en) | Industrial product defect detection method and device | |
| CN110596118A (en) | Print pattern detection method and print pattern detection device | |
| CN111445458B (en) | Method for detecting printing quality of mobile phone battery label | |
| CN111626104B (en) | Cable hidden trouble point detection method and device based on unmanned aerial vehicle infrared thermal image | |
| CN112561875A (en) | Photovoltaic cell panel coarse grid detection method based on artificial intelligence | |
| CN116993725A (en) | Intelligent patch information processing system of flexible circuit board | |
| CN110796099A (en) | Vehicle overrun detection method and device | |
| CN116309532A (en) | Method, device, equipment and medium for detecting quality of target object | |
| CN115731208A (en) | High-precision defect detection method, device and equipment for metal complex surface and storage medium | |
| CN115984197A (en) | Defect detection method based on standard PCB image and related device | |
| CN116977241A (en) | Method, apparatus, computer readable storage medium and computer program product for detecting defects in a vehicle component |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |