CN110929083A - Visual footwear identification method based on artificial intelligence - Google Patents
Visual footwear identification method based on artificial intelligence Download PDFInfo
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- CN110929083A CN110929083A CN201911264411.0A CN201911264411A CN110929083A CN 110929083 A CN110929083 A CN 110929083A CN 201911264411 A CN201911264411 A CN 201911264411A CN 110929083 A CN110929083 A CN 110929083A
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- G06F16/50—Information retrieval; Database structures therefor; File system structures therefor of still image data
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Abstract
The invention discloses a visual footwear identification method based on artificial intelligence, which comprises the following steps: s1, attaching bar codes to the shoes to be identified at proper positions, and sequentially sending the shoes to an identification area by using transmission equipment; s2, scanning the bar code on the shoe through the code scanning module to obtain the information recorded in the bar code, transmitting the information to an information processing module in the upper computer by the code scanning module, calling a database in the upper computer by the information processing module, and inquiring the information of the production batch, the model and the like corresponding to the code-scanned shoe; s3, acquiring high-definition patterns of the shoes through the image acquisition module, processing the high-definition patterns through the image processing module, and transmitting the patterns to a comparison module in the upper computer; s4, the comparison module compares the collected pattern with the standard pattern, and the invention automatically detects the shoes through artificial intelligent visual identification, thereby saving a large amount of manpower, reducing the labor cost and having high identification accuracy.
Description
Technical Field
The invention relates to the technical field of shoe production, in particular to a visual shoe identification method based on artificial intelligence.
Background
Shoes have a long history of development. Approximately 5000 years ago in the yangshao culture period, the most primitive shoe made of hide appeared. Shoes are a tool for protecting feet of people from being injured. At first, in order to overcome special conditions and prevent feet from being difficult or injured, fur shoes are invented. The shoes are developed to the present and become an indispensable article in daily life, and shoes with various styles and functions are visible everywhere. In traditional shoes manufacturing enterprise, shoes outward appearance detects and specification detection and relies on artifical the completion basically, and artifical intensity of labour is great, and the cost is higher.
Disclosure of Invention
The invention aims to provide a visual footwear identification method based on artificial intelligence to solve the problems in the background technology.
In order to achieve the purpose, the invention provides the following technical scheme:
a visual footwear identification method based on artificial intelligence comprises the following steps:
s1, attaching bar codes to the shoes to be identified at proper positions, and sequentially sending the shoes to an identification area by using transmission equipment;
s2, scanning the bar code on the shoe through the code scanning module to obtain the information recorded in the bar code, transmitting the information to an information processing module in the upper computer by the code scanning module, calling a database in the upper computer by the information processing module, and inquiring the information of the production batch, the model and the like corresponding to the code-scanned shoe;
s3, acquiring high-definition patterns of the shoes through the image acquisition module, processing the high-definition patterns through the image processing module, and transmitting the patterns to a comparison module in the upper computer;
s4, the comparison module compares the collected pattern with a standard pattern, judges whether the outline, size and color of the shoe have deviation with the standard pattern, if the deviation is below a threshold value, a qualified signal is output through the alarm module, and if the deviation exceeds the threshold value, an unqualified signal is output through the alarm module.
As a further scheme of the invention: the barcode in step S1 is a two-dimensional code or a barcode.
As a further scheme of the invention: the bar code in the step S1 is generated by the following steps: according to the model, the production date and the sequence of each pair of shoes, a group of serial numbers are automatically generated in the upper computer to serve as material numbers and are recorded in the database, meanwhile, the material numbers are transmitted to the bar code generation module by the upper computer, and the material numbers are generated into bar code patterns by the bar code generation module and are printed into attachable bar codes by the printing module.
As a further scheme of the invention: the pattern acquisition module in the step S3 is an industrial camera.
As a further scheme of the invention: the standard pattern in the step S4 is obtained by manually acquiring images of qualified products in advance, and the images are recorded in a database one by one according to different models of shoes.
As a further scheme of the invention: before comparison, the step S4 further includes replacing the standard image, and the specific steps are as follows: after the information processing module obtains the code scanning information in step S2, the upper computer sends the standard pattern of the corresponding shoe from the database to the comparison module according to the code scanning information, the comparison module determines whether the sent standard pattern is consistent with the currently used standard pattern, if so, the upper computer continues to use the shoe, and if not, the upper computer downloads a new standard pattern again.
As a further scheme of the invention: a human-computer interaction interface is arranged on the upper computer, and workers check various information through the human-computer interaction interface and can change the size of a threshold value in the comparison module.
As a further scheme of the invention: the alarm module is an alarm lamp, the qualified signal is green light, and the unqualified signal is red light.
Compared with the prior art, the invention has the beneficial effects that:
according to the invention, shoes are automatically detected through artificial intelligent visual identification, so that a large amount of manpower is saved, the labor cost is reduced, and the identification accuracy is high.
Drawings
FIG. 1 is a real-time display image of a human-machine interface;
FIG. 2 is an image of a human-machine interface when mismatched shoes are detected;
FIG. 3 is an image of a human-machine interface when a matching shoe is detected.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
A visual footwear identification method based on artificial intelligence comprises the following steps:
s1, attaching bar codes to the shoes to be identified at proper positions, and sequentially sending the shoes to an identification area by using transmission equipment;
s2, scanning the bar code on the shoe through the code scanning module to obtain the information recorded in the bar code, transmitting the information to an information processing module in the upper computer by the code scanning module, calling a database in the upper computer by the information processing module, and inquiring the information of the production batch, the model and the like corresponding to the code-scanned shoe;
s3, acquiring high-definition patterns of the shoes through the image acquisition module, processing the high-definition patterns through the image processing module, and transmitting the patterns to a comparison module in the upper computer;
s4, the comparison module compares the collected pattern with a standard pattern, judges whether the outline, size and color of the shoe have deviation with the standard pattern, if the deviation is below a threshold value, a qualified signal is output through the alarm module, and if the deviation exceeds the threshold value, an unqualified signal is output through the alarm module.
The barcode in step S1 is a two-dimensional code or a barcode.
The bar code in the step S1 is generated by the following steps: according to the model, the production date and the sequence of each pair of shoes, a group of serial numbers are automatically generated in the upper computer to serve as material numbers and are recorded in the database, meanwhile, the material numbers are transmitted to the bar code generation module by the upper computer, and the material numbers are generated into bar code patterns by the bar code generation module and are printed into attachable bar codes by the printing module.
The pattern acquisition module in the step S3 is an industrial camera.
The standard pattern in the step S4 is obtained by manually acquiring images of qualified products in advance, and the images are recorded in a database one by one according to different models of shoes.
Before comparison, the step S4 further includes replacing the standard image, and the specific steps are as follows: after the information processing module obtains the code scanning information in step S2, the upper computer sends the standard pattern of the corresponding shoe from the database to the comparison module according to the code scanning information, the comparison module determines whether the sent standard pattern is consistent with the currently used standard pattern, if so, the upper computer continues to use the shoe, and if not, the upper computer downloads a new standard pattern again.
A human-computer interaction interface is arranged on the upper computer, workers check various information through the human-computer interaction interface, the size of a threshold value in the comparison module can be changed, as shown in figures 1-3, shot patterns are displayed on the human-computer interaction interface, information such as shoe sizes, colors, left and right feet, material numbers and the like is displayed on the right side of the patterns, and the checking of the workers is facilitated. Fig. 1 shows a pair of matched shoes outputting a qualified signal, while fig. 2 shows a pair of black and white unmatched shoes, the size and color information of the two shoes displayed in the information bar on the right side are not consistent, and an unqualified signal is output.
The alarm module is an alarm lamp, the qualified signal is green light, and the unqualified signal is red light.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned.
Furthermore, it should be understood that although the present description refers to embodiments, not every embodiment may contain only a single embodiment, and such description is for clarity only, and those skilled in the art should integrate the description, and the embodiments may be combined as appropriate to form other embodiments understood by those skilled in the art.
Claims (8)
1. A visual footwear identification method based on artificial intelligence is characterized by comprising the following steps:
s1, attaching bar codes to the shoes to be identified at proper positions, and sequentially sending the shoes to an identification area by using transmission equipment;
s2, scanning the bar code on the shoe through the code scanning module to obtain the information recorded in the bar code, transmitting the information to an information processing module in the upper computer by the code scanning module, calling a database in the upper computer by the information processing module, and inquiring the information of the production batch, the model and the like corresponding to the code-scanned shoe;
s3, acquiring high-definition patterns of the shoes through the image acquisition module, processing the high-definition patterns through the image processing module, and transmitting the patterns to a comparison module in the upper computer;
s4, the comparison module compares the collected pattern with a standard pattern, judges whether the outline, size and color of the shoe have deviation with the standard pattern, if the deviation is below a threshold value, a qualified signal is output through the alarm module, and if the deviation exceeds the threshold value, an unqualified signal is output through the alarm module.
2. The artificial intelligence based visual footwear identification method according to claim 1, wherein the barcode in step S1 is a two-dimensional code or a barcode.
3. An artificial intelligence based visual footwear identification method according to claim 1 wherein the bar code of step S1 is generated by the steps of: according to the model, the production date and the sequence of each pair of shoes, a group of serial numbers are automatically generated in the upper computer to serve as material numbers and are recorded in the database, meanwhile, the material numbers are transmitted to the bar code generation module by the upper computer, and the material numbers are generated into bar code patterns by the bar code generation module and are printed into attachable bar codes by the printing module.
4. The artificial intelligence based visual footwear identification method according to claim 1, wherein the pattern capturing module in step S3 is an industrial camera.
5. The artificial intelligence based visual footwear identification method according to claim 1, wherein the standard pattern in step S4 is obtained by manually capturing images of qualified products in advance, and is recorded in the database one by one according to different models of shoes.
6. The artificial intelligence based visual footwear identification method according to claim 5, wherein step S4 further comprises, before the comparison, replacing the standard image, the specific steps being as follows: after the information processing module obtains the code scanning information in step S2, the upper computer sends the standard pattern of the corresponding shoe from the database to the comparison module according to the code scanning information, the comparison module determines whether the sent standard pattern is consistent with the currently used standard pattern, if so, the upper computer continues to use the shoe, and if not, the upper computer downloads a new standard pattern again.
7. The artificial intelligence based visual footwear identification method according to claim 1, wherein a human-computer interface is provided on the host computer, and a worker views various information through the human-computer interface and can change the threshold value in the comparison module.
8. The artificial intelligence based visual footwear identification method of claim 1, wherein the alarm module is an alarm light, the acceptable signal is green light, and the unacceptable signal is red light.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112347866A (en) * | 2020-10-22 | 2021-02-09 | 上海铂端科技有限公司 | System and method for realizing attachment assembly fool-proof detection processing based on machine vision |
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| CN104636703A (en) * | 2015-02-14 | 2015-05-20 | 中国科学院合肥物质科学研究院 | Seed information acquisition method and system based on two-dimension code |
| CN109916913A (en) * | 2019-04-04 | 2019-06-21 | 哈尔滨理工大学 | A kind of intelligence manufacture product identification and detection method based on machine vision |
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- 2019-12-11 CN CN201911264411.0A patent/CN110929083A/en active Pending
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN104636703A (en) * | 2015-02-14 | 2015-05-20 | 中国科学院合肥物质科学研究院 | Seed information acquisition method and system based on two-dimension code |
| CN109916913A (en) * | 2019-04-04 | 2019-06-21 | 哈尔滨理工大学 | A kind of intelligence manufacture product identification and detection method based on machine vision |
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| CN112347866A (en) * | 2020-10-22 | 2021-02-09 | 上海铂端科技有限公司 | System and method for realizing attachment assembly fool-proof detection processing based on machine vision |
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