CN113435450A - Product number verification system and method based on OCR recognition - Google Patents
Product number verification system and method based on OCR recognition Download PDFInfo
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- CN113435450A CN113435450A CN202110718111.6A CN202110718111A CN113435450A CN 113435450 A CN113435450 A CN 113435450A CN 202110718111 A CN202110718111 A CN 202110718111A CN 113435450 A CN113435450 A CN 113435450A
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- G06K7/00—Methods or arrangements for sensing record carriers, e.g. for reading patterns
- G06K7/10—Methods or arrangements for sensing record carriers, e.g. for reading patterns by electromagnetic radiation, e.g. optical sensing; by corpuscular radiation
- G06K7/10544—Methods or arrangements for sensing record carriers, e.g. for reading patterns by electromagnetic radiation, e.g. optical sensing; by corpuscular radiation by scanning of the records by radiation in the optical part of the electromagnetic spectrum
- G06K7/10821—Methods or arrangements for sensing record carriers, e.g. for reading patterns by electromagnetic radiation, e.g. optical sensing; by corpuscular radiation by scanning of the records by radiation in the optical part of the electromagnetic spectrum further details of bar or optical code scanning devices
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Abstract
The invention discloses a product number checking system and method based on OCR (optical character recognition), belonging to the technical field of product number recognition, wherein the system comprises a bar code scanning module, a bar code recognition module, a product number recognition module and a checking module; the bar code scanning module is used for scanning bar codes of products; the bar code identification module is used for analyzing the bar codes of the products scanned by the bar code scanning module and automatically searching the corresponding product numbers stored in the system database; the product number identification module is used for performing OCR identification on the product number; the checking module is used for comparing and checking the product numbers obtained by the bar code identification module and the product number identification module. The method adopts the system to check the product serial number, and automatically identifies the product through equipment, thereby avoiding the instability of manual identification, improving the working efficiency and the accuracy of product serial number check, and being a low-cost realization method.
Description
Technical Field
The invention belongs to the technical field of product number identification, and particularly relates to a product number verification system and method based on OCR identification.
Background
Currently there are several display forms for product numbers: bar code, two-dimensional code, text. Special identification equipment exists for bar codes and two-dimensional codes, most characters are identified through manual checking, efficiency is low, and errors are easy to occur. The technology of character recognition by OCR has been used in some scenarios, and the related technology has been mature.
However, the current OCR character recognition technology generally aims at specific scenes, such as license plate recognition, certificate recognition and the like, and the verification of product numbers needs to be simultaneously provided with OCR recognition, barcode recognition and related system coordination.
Disclosure of Invention
In order to solve the problems, the invention provides a product number verification system and a product number verification method based on OCR recognition.
The technical scheme of the invention is as follows:
a product number verification system based on OCR recognition comprises a bar code scanning module, a bar code recognition module, a product number recognition module and a verification module; wherein,
the bar code scanning module is used for scanning bar codes of products;
the bar code identification module is used for analyzing the bar codes of the products scanned by the bar code scanning module and automatically searching the corresponding product numbers stored in the system database;
the product number identification module is used for carrying out OCR identification on the product number, including setting a focus frame in an identification area for positioning, and carrying out corresponding processing on an image intercepted during identification so as to identify a character number in the image;
the checking module is used for comparing and checking the product numbers obtained by the bar code identification module and the product number identification module.
Preferably, the barcode scanning module is implemented by using an SDK of an Android device with a scanning head, and the scanning head equipped for the Android device is called to scan a barcode.
Preferably, the system database has stored therein the barcodes and their corresponding numbers for all products.
Preferably, the product number recognition module calls a camera of the Android device to photograph in real time when performing OCR recognition, and aligns the product number to be recognized in the area of the focus frame when photographing.
Preferably, the focus frame is a rectangular long frame.
Preferably, when the product number identification module processes the image, the selected part of the focus frame is firstly intercepted, then the intercepted image is subjected to gray scale processing and binarization processing, and finally noise is removed through corrosion and expansion operations.
Preferably, the related technology of image processing is realized by an OpenCV library, and specifically, a camera photographing and image processing related algorithm provided by the OpenCV library is adopted.
Preferably, when performing OCR recognition, a corresponding white list and a corresponding black list are set according to the rule of the product number, and the related technology of OCR recognition is realized through a tess-two library.
Preferably, the workflow used by the modules of the system in cooperation is as follows: the bar code scanning module scans bar codes of products, and the bar code identification module carries out system query according to the scanned bar codes to obtain product numbers corresponding to the bar codes of the products and temporarily store the product numbers in the system; the product number identification module carries out OCR identification on the product number; and the checking module compares the product number obtained by OCR recognition with the product number inquired by the product bar code for checking.
A product number verification method based on OCR recognition adopts the product number verification system based on OCR recognition, and the method specifically comprises the following steps:
s1, opening a bar code scanning function of a system, and scanning a bar code of a product by a scanning head equipped in Android equipment;
s2, the system analyzes the scanned product bar code, inquires a product number corresponding to the bar code from a system database, and temporarily stores the product number in the system;
s3, performing OCR (optical character recognition) on the product number through a camera of the Android device;
s4, comparing the product number obtained by OCR recognition with the product number inquired in S2;
s5, if the two are consistent, passing the check; otherwise, the system prompts for an error.
The invention has the following beneficial technical effects:
the invention can complete the identification of the product number in the form of pure characters and the verification of the product number corresponding to the product bar code; the equipment is used for automatic identification, so that the instability of manual identification is avoided, the mismatching of the product number can be prevented, the working efficiency can be improved compared with the traditional manual verification, and the accuracy of product number verification is improved; the method makes full use of the relevant functions of the Android scanning equipment and the existing open source technology, and is a low-cost implementation method.
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FIG. 1 is a schematic diagram of the product number verification system and method based on OCR recognition according to the present invention.
Detailed Description
The invention is described in further detail below with reference to the following figures and detailed description:
a product number verification system based on OCR recognition comprises a bar code scanning module, a bar code recognition module, a product number recognition module and a verification module. The barcode scanning module calls a scanning head equipped with Android equipment to scan a barcode; the bar code identification module is used for analyzing the bar code of the product scanned by the scanning head and automatically searching the product number corresponding to the bar code of the product stored in the database; the product number identification module calls a camera of the Android device to take a picture in real time, a rectangular focus frame is drawn in a picture taking area for accurate positioning, characters to be identified are aligned in the area of the focus frame, and then an identification button in an interface is clicked to take a picture; the checking module checks the product numbers obtained by the bar code identification module and the product number identification module and judges whether the product numbers are consistent.
The related technologies for designing, implementing and using the specific software system include: firstly, calling a camera of an Android device to take a picture and perform corresponding image processing, wherein the related technology is realized through an OpenCV (open content description language) library, and the camera taking and image processing related algorithm provided by OpenCV is mainly adopted; OCR recognition related technology is realized through a tess-two library; and realizing other barcode scanning functions by adopting the SDK of the Android equipment with the scanning head.
The specific work flow of the product number verification system based on OCR recognition to complete one-time verification is as follows:
(1) the original data is imported. And importing the product bar codes and the corresponding product numbers of all the products into a system database.
(2) The product barcode is scanned. And opening a functional interface of scanning bar codes in the system, calling a scanning head equipped in the Android equipment to scan the bar codes of the products, performing system query according to the scanned bar codes, acquiring product numbers corresponding to the bar codes of the products, and temporarily storing the product numbers in the system.
(3) And identifying and checking the product number. And calling a camera of the Android device to perform OCR recognition on the product number, comparing the product number obtained by OCR recognition with the product number inquired through the product bar code, and if the product number is consistent with the product number, passing the verification, otherwise, prompting an error by the system.
As shown in fig. 1, a product number verification method based on OCR recognition adopts the above system to verify a product number, and the specific implementation process is as follows:
s1, opening a bar code scanning function of a system, and scanning a bar code of a product by a scanning head equipped in Android equipment;
s2, the system analyzes the scanned product bar code, inquires a product number corresponding to the bar code from a system database, and temporarily stores the product number in the system;
s3, performing OCR (optical character recognition) on the product number through a camera of the Android device;
s4, comparing the product number obtained by OCR recognition with the product number inquired in S2;
s5, if the two are consistent, passing the check; otherwise, the system prompts for an error.
When OCR recognition is carried out on the image, a corresponding white list and a corresponding black list are set according to the rule of the product number, and the recognition accuracy is improved.
How to set the white list and the black list is to improve the accuracy is described as a specific example.
Wherein, the number of a certain product only contains numbers and characters "-" and does not contain letters or other special symbols, the white list identified by OCR is set as "0123456789-" and the black list is "ABCDEFGHIJKLMNOPQRTUVWXYZ abcdefghinghi jklmpqprst wxyz! @ # $% & () _+ [ ] } {; ' \\ \ | -,/<? ". Confusion of some similar characters can be avoided through the arrangement of the white list and the black list, and the situation that the number 0 is identified as the letter O does not occur. In actual use, the white list and the black list are set according to the specific situation of the product number.
In conclusion, the invention can finish product numbering in the form of characters, and can accurately identify and verify product numbering in the forms of letters, numbers, pure characters, other special symbols and the like.
It is to be understood that the above description is not intended to limit the present invention, and the present invention is not limited to the above examples, and those skilled in the art may make modifications, alterations, additions or substitutions within the spirit and scope of the present invention.
Claims (10)
1. A product number verification system based on OCR recognition is characterized by comprising a bar code scanning module, a bar code recognition module, a product number recognition module and a verification module; wherein,
the bar code scanning module is used for scanning bar codes of products;
the bar code identification module is used for analyzing the bar codes of the products scanned by the bar code scanning module and automatically searching the corresponding product numbers stored in the system database;
the product number identification module is used for carrying out OCR identification on the product number, including setting a focus frame in an identification area for positioning, and carrying out corresponding processing on an image intercepted during identification so as to identify a character number in the image;
the checking module is used for comparing and checking the product numbers obtained by the bar code identification module and the product number identification module.
2. The product number verification system based on OCR recognition as claimed in claim 1, wherein the barcode scanning module is implemented by using an SDK of an Android device with a scanning head, and the scanning head equipped with the Android device is called to perform barcode scanning.
3. An OCR recognition based product number verification system as claimed in claim 1, wherein the system database has stored therein barcodes and their corresponding numbers for all products.
4. The system for checking the product number based on the OCR recognition according to claim 1, wherein the product number recognition module calls a camera of the Android device to photograph in real time during the OCR recognition, and aligns the product number to be recognized in an area of a focus frame during photographing.
5. An OCR recognition-based product number verification system as claimed in claim 4, wherein the focus frame is a rectangular long frame.
6. An OCR recognition-based product number verification system as claimed in claim 1, wherein the product number recognition module, when processing the image, first intercepts the selected portion of the focus frame, then performs gray scale processing and binarization processing on the intercepted image, and finally removes noise through erosion and dilation operations.
7. The product number verification system based on OCR recognition according to claim 6, wherein a related technology of image processing is implemented by an OpenCV library, and specifically, a camera photographing and image processing related algorithm provided by the OpenCV library is adopted.
8. An OCR recognition-based product number verification system as claimed in claim 1, wherein when performing OCR recognition, the corresponding white list and black list are set according to the rule of product number, and the related technology of OCR recognition is realized by the tess-two library.
9. An OCR recognition based product number verification system as claimed in claim 1, wherein the workflow used cooperatively among the modules of the system is: the bar code scanning module scans bar codes of products, and the bar code identification module carries out system query according to the scanned bar codes to obtain product numbers corresponding to the bar codes of the products and temporarily store the product numbers in the system; the product number identification module carries out OCR identification on the product number; and the checking module compares the product number obtained by OCR recognition with the product number inquired by the product bar code for checking.
10. A product number verification method based on OCR recognition, characterized in that, the product number verification system based on OCR recognition as claimed in any one of claims 1-9 is adopted, the method specifically includes the following steps:
s1, opening a bar code scanning function of a system, and scanning a bar code of a product by a scanning head equipped in Android equipment;
s2, the system analyzes the scanned product bar code, inquires a product number corresponding to the bar code from a system database, and temporarily stores the product number in the system;
s3, performing OCR (optical character recognition) on the product number through a camera of the Android device;
s4, comparing the product number obtained by OCR recognition with the product number inquired in S2;
s5, if the two are consistent, passing the check; otherwise, the system prompts for an error.
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Application publication date: 20210924 |