Automatic code scanning identification and data processing method, system and device and medium

Abstract

The invention discloses an automatic code scanning identification and data processing method. According to the method, an automatic closed loop from image acquisition to business execution is constructed to solve the problem that the flow is split and depends on manpower in the prior art. The method comprises the steps of firstly collecting an image containing a target code; performing intelligent processing on the image, positioning and extracting a target code area, and providing accurate input for decoding; decoding the region to obtain original information; the original information is verified and corrected to generate reliable effective data, and the step directly solves the problem of recognition errors caused by code image quality; and finally, matching the valid data with preset business logic and automatically triggering execution. According to the method, through automatic and intelligent connection of the whole process, manual intervention is remarkably reduced, and the processing efficiency and the data accuracy are improved.

Description

Technical Field

[0001] This application relates to the fields of computer vision and automation technology, specifically to an automatic barcode scanning and data processing method and system, which is particularly suitable for various application scenarios that require efficient and accurate identification of target codes such as barcodes and QR codes and automatic triggering of subsequent business processes. Background Technology

[0002] With the widespread adoption of the Internet of Things (IoT) and mobile internet, barcode scanning technology has become a key data entry point in logistics, retail, manufacturing, asset management, and other fields. Currently, most common barcode scanning methods rely on dedicated hardware barcode scanners or manual scanning using mobile devices. This approach has significant limitations: First, efficiency is highly dependent on the speed and accuracy of manual operation, making it difficult to handle high-frequency, continuous scanning tasks; second, post-scanning data analysis and business processing usually require manual intervention or manual operation between different systems, resulting in fragmented processes, prone to errors, and time-consuming; third, hardware compatibility and deployment costs also limit its application flexibility.

[0003] Therefore, there is an urgent need for a software-driven, fully automated barcode scanning and data processing solution. Summary of the Invention

[0004] This application aims to provide an automatic barcode scanning and data processing method and system to solve the problems of fragmented processes, reliance on manual labor, low efficiency, and insufficient adaptability in existing technologies. To achieve the above objective, this application adopts the following technical solution:

[0005] In a first aspect, embodiments of this application provide an automatic barcode scanning and data processing method, including:

[0006] Acquire images containing the target code;

[0007] The image is preprocessed to locate and extract the image region where the target code is located;

[0008] The extracted image regions are decoded to obtain the original encoded information;

[0009] The original encoded information is verified and corrected to generate valid data;

[0010] The valid data is matched with the pre-configured business logic to trigger and execute the corresponding business processing actions.

[0011] Further, the image is preprocessed to locate and extract the image region where the target code is located, including:

[0012] The image is then subjected to grayscale conversion and noise reduction filtering.

[0013] Candidate regions are determined from the processed image based on edge detection algorithms;

[0014] The candidate region is subjected to image enhancement processing to improve the contrast between the target code and the background, thereby completing the extraction of the image region.

[0015] Furthermore, the extracted image regions are decoded to obtain the original encoded information, including:

[0016] A multi-threaded parallel processing mechanism is adopted to simultaneously decode multiple image regions extracted from different images or the same image.

[0017] Further, the original encoded information is verified and corrected to generate valid data, including:

[0018] The original encoded information is format-validated based on the encoding specification of the target code;

[0019] If the verification fails, then based on the image region, at least one alternative decoding algorithm or image restoration algorithm is used to retry decoding;

[0020] If the decoding attempt succeeds, the successfully decoded data is output as valid data; if it fails, the unprocessed record containing the image is output.

[0021] Furthermore, the business processing actions include at least one of the following: generating business documents, updating inventory status, recording logistics trajectory, triggering payment process, or sending notification messages.

[0022] Furthermore, after matching the valid data with the pre-configured business logic, triggering and executing the corresponding business processing action, the process also includes:

[0023] The execution results of the business processing actions are synchronized to at least one external business system through a preset data interface.

[0024] Furthermore, when acquiring images containing the target code, the images are acquired by calling the interface of at least one image acquisition device in the form of video streaming or continuous image capture; the acquisition parameters are dynamically adjusted according to the ambient light or the clarity of the target code during the acquisition process.

[0025] Secondly, embodiments of this application provide a system capable of implementing the automatic barcode scanning and data processing method described in any of the foregoing claims, comprising:

[0026] The image acquisition module is used to acquire images containing the target code;

[0027] The image preprocessing module is used to preprocess the image, locate and extract the image region where the target code is located;

[0028] The decoding module is used to decode the extracted image regions to obtain the original encoded information;

[0029] The data correction module is used to verify and correct the original encoded information to generate valid data;

[0030] The business integration module is used to match the valid data with the pre-configured business logic, trigger and execute the corresponding business processing actions.

[0031] Thirdly, embodiments of this application provide an electronic device, including: one or more processors;

[0032] A memory for storing one or more programs; when the one or more programs are executed by the one or more processors, the one or more processors are able to implement the steps in the automatic barcode scanning and data processing method described in any of the preceding claims.

[0033] Fourthly, embodiments of this application provide a computer-readable medium storing a computer program, which, when executed by a processor, can implement the steps of the automatic barcode scanning and data processing method described in any of the preceding claims.

[0034] This application addresses the problems of fragmented processes and reliance on manual labor in existing technologies by constructing an automated closed loop from image acquisition to business execution. It significantly reduces manual intervention, greatly improving processing speed and system throughput, and ensuring data accuracy through built-in verification and correction mechanisms. Furthermore, its software-centric architecture allows for flexible deployment and easy integration with existing business systems, making it widely applicable across various scenarios such as production, logistics, retail, and services, demonstrating significant practical value. Attached Figure Description

[0035] Figure 1 This application provides a core flowchart of an automatic barcode scanning and data processing method.

[0036] Figure 2 A flowchart illustrating an automatic barcode scanning and data processing method provided in the application embodiment;

[0037] Figure 3 This is a structural block diagram of an electronic device provided in an embodiment of this application. Detailed Implementation

[0038] To enable those skilled in the art to better understand the technical solutions of this application, exemplary embodiments of this application are described below with reference to the accompanying drawings, including various details of the embodiments of this application to aid understanding. These should be considered merely exemplary. Therefore, those skilled in the art should recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of this application. Similarly, for clarity and conciseness, descriptions of well-known functions and structures are omitted in the following description. Unless otherwise specified, the various embodiments of this application and the features within those embodiments can be combined with each other.

[0039] As used herein, the term “and / or” includes any and all combinations of one or more of the associated enumerated entries. The terminology used herein is for describing particular embodiments only and is not intended to limit the application. As used herein, the singular forms “a” and “the” are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that when the terms “comprising” and / or “made of” are used in this specification, the presence of the stated features, integrals, steps, operations, elements, and / or components is specified, but the presence or addition of one or more other features, integrals, steps, operations, elements, components, and / or groups thereof is not excluded. Terms such as “connected” or “linked” are not limited to physical or mechanical connections but can include electrical connections, whether direct or indirect.

[0040] Unless otherwise specified, all terms used herein (including technical and scientific terms) have the same meaning as commonly understood by one of ordinary skill in the art. It should also be understood that terms such as those defined in commonly used dictionaries should be interpreted as having the meaning consistent with their meaning in the context of the relevant art and this application, and will not be interpreted as having an idealized or overly formal meaning, unless expressly so defined herein.

[0041] refer to Figure 1 and Figure 2 One embodiment of this application proposes a fully automated barcode scanning and traceability method at the end of an electronic product assembly line, which may include the following steps.

[0042] S1. Acquire images containing the target code by calling the interface of at least one image acquisition device to acquire images in the form of video stream or continuous image capture; during the acquisition process, dynamically adjust the acquisition parameters according to the ambient light or the clarity of the target code.

[0043] Specifically, a high-resolution industrial camera is fixedly deployed above the conveyor belt, its field of view covering a specific location on the product packaging box. When a photoelectric sensor detects the product's arrival, it triggers the camera to capture a clear image containing the product's serial number (QR code). Camera parameters (such as exposure time and gain) can be adaptively fine-tuned via PLC feedback based on ambient light intensity to ensure stable image quality.

[0044] S2. Preprocess the image to locate and extract the image region where the target code is located.

[0045] Specifically, after receiving the image, the central processing unit first performs grayscale conversion and Gaussian filtering to suppress noise. Then, it uses the Canny edge detection algorithm to find all contours in the image. The system pre-defines the geometric features of the QR code (such as approximate rectangle and specific aspect ratio), and filters the most likely target region from candidate regions through contour analysis. After locking onto this region, perspective transformation is performed to correct deformation caused by angles, and adaptive histogram equalization is used to enhance the contrast of the region, ultimately cropping out a regular, high-quality QR code sub-image.

[0046] S3. Decode the extracted image region to obtain the original encoded information.

[0047] Specifically, the integrated ZBar library and a decoder optimized for this model's QR code are used to decode the cropped sub-images. A multi-threaded parallel processing mechanism is employed to simultaneously decode multiple image regions extracted from different images or the same image. That is, the decoding process is executed in an independent thread, without affecting the image acquisition of the next product. A string containing the product model, batch number, and serial number is successfully parsed.

[0048] S4. Verify and correct the original encoded information to generate valid data.

[0049] Specifically, the decoded string is sent to the verification module. This module has a built-in checksum algorithm and the format rules for this model of QR code. Assuming the parsing passes the verification successfully, valid data is generated directly. Consider a scenario where the QR code fails to decode initially due to oil stains. The system will trigger a correction process: First, it uses an image restoration algorithm (such as neighbor-based pixel filling) to repair the sub-image; then, it uses a more fault-tolerant decoding algorithm for a second attempt; if successful, valid data is output; if it still fails, the system records the file path, timestamp, and reason for failure of the abnormal image, stores it in the database to be reviewed, and sends a "skip" signal to the upstream PLC, allowing the product to enter the manual processing station to avoid production line congestion.

[0050] S5. Match valid data with pre-configured business logic to trigger and execute corresponding business processing actions. Business processing actions include at least one of the following: generating business documents, updating inventory status, recording logistics trajectory, triggering payment process, or sending notification messages.

[0051] Specifically, valid data (product serial number) that passes verification is sent to the business integration engine. The engine is pre-configured with the rule: "If it is a type A product, update the production status of the MES system to 'packaged' and send an inbound reservation request to the WMS system." The system automatically calls the RESTful APIs provided by MES and WMS to complete the status update and reservation operations, and the entire process is completed within milliseconds.

[0052] S6. Synchronize the execution results of business processing actions to at least one external business system through a preset data interface.

[0053] Specifically, the results of business execution (such as the confirmation of successful MES update) are recorded in the local log and synchronized to the ERP system via the Enterprise Service Bus (ESB) to update the product inventory status.

[0054] This embodiment realizes unmanned automatic collection and system synchronization of product information on the production line, which completely automates the traditional work that required manual scanning, visual verification, and manual entry into multiple systems. The processing speed can reach hundreds of pieces per minute, and the data accuracy rate reaches more than 99.9%, which significantly improves production efficiency and traceability accuracy.

[0055] An embodiment of this application also proposes an automatic barcode scanning and data processing method for parcel sorting scenarios in logistics warehouses (in logistics sorting centers, parcels move at high speed on cross-belt sorting machines), which may specifically include the following steps.

[0056] S201. Two sets of linear scanning cameras are installed above the key nodes to form a stereo vision system, ensuring that at least one camera can capture the barcode image on the waybill regardless of the package's orientation. The cameras continuously acquire data at a high frame rate.

[0057] S202. Due to the complex background (various package colors), the system employs a pre-trained deep learning-based semantic segmentation model (such as the lightweight UNet) specifically designed to segment the "barcode" region from the complex background. The model quickly locates the barcode regions on multiple packages.

[0058] S203 employs multi-threaded parallel decoding technology, assigning each identified barcode area to an independent decoding thread, while simultaneously calling the Zxing library for decoding, quickly outputting tracking numbers for multiple packages.

[0059] S204. For individual barcodes that fail to be recognized due to wrinkles on the label, the system will perform orientation correction and affine transformation on the captured original area image, and then retry using a combination of various decoding parameters.

[0060] S205. The successfully parsed waybill number is immediately matched with the sorting path planning system. Based on the destination information corresponding to the waybill number, the system calculates the optimal sorting point in real time and issues a command milliseconds before the package arrives at the corresponding slot to control the ejector action and accurately sort the package.

[0061] This embodiment achieves real-time and accurate sorting of massive amounts of parcels through parallel processing and intelligent error correction. The sorting efficiency far exceeds that of manual sorting, and the error rate is greatly reduced, fully meeting the stringent requirements of modern logistics for timeliness and accuracy.

[0062] An embodiment of this application also proposes an automatic barcode scanning and data processing method for mobile device inspection and maintenance scenarios (where maintenance personnel use tablet computers with a dedicated APP installed to inspect data center equipment), which may specifically include the following steps.

[0063] S301. Maintenance personnel open the app and point it at the device asset tag (which may be a QR code or Data Matrix code). The app uses the tablet's rear camera to activate augmented reality (AR) preview mode and automatically enables continuous autofocus and exposure lock to quickly obtain a clear image. The user interface will display a green box indicating whether the code image has been successfully locked in real time.

[0064] The S302 and the APP's built-in image processing module process the preview frames. In poorly lit corners of the server room, the system automatically increases the image gamma value and sharpens it to enhance the details of the code image.

[0065] S303. After successfully extracting the region, the mobile-optimized decoding engine is called to quickly decode and obtain the device asset number.

[0066] S304. The decoding result is initially compared with the locally cached asset database. If a non-existent asset number is found, the APP will prompt "Number abnormal, try rescanning or manual entry" and provide a re-scan button.

[0067] S305. The identified valid asset number is automatically filled into the corresponding field of the inspection work order. The APP automatically associates the device with the current inspection item list according to preset rules and may trigger a preset test script (such as reading operating parameters via Bluetooth connection to the device). After the maintenance personnel complete the inspection, the data is saved locally.

[0068] S306. When the inspection personnel return to an area with network coverage, the APP automatically uploads the batch inspection data to the central operation and maintenance management platform via HTTPS protocol.

[0069] This embodiment expands the application of the method in mobile and offline scenarios. By using the intelligent processing of mobile devices, it simplifies the cumbersome process of traditional paper records and manual data entry, and improves the efficiency and digitalization level of outdoor or facility inspection work.

[0070] An embodiment of this application also proposes a system capable of implementing the aforementioned automatic barcode scanning and data processing method, which may specifically include the following functional modules.

[0071] The image acquisition module is used to acquire images containing the target code. Specifically, the image acquisition module consists of an industrial camera, a webcam, or a mobile device camera and its driving control software. It is responsible for executing step S1 in the aforementioned embodiments, adjusting parameters, and responding to trigger signals.

[0072] The image preprocessing module is used to preprocess the image, locate and extract the image region where the target code is located. Specifically, the image preprocessing module is connected to the image acquisition module, integrates libraries such as OpenCV, and includes sub-units such as grayscale conversion, filtering, edge detection, and image enhancement. It is responsible for executing step S2 in the aforementioned embodiment and outputting a high-quality image of the target code region.

[0073] The decoding module is used to decode the extracted image regions to obtain the original encoded information. Specifically, the decoding module is connected to the image preprocessing module, integrates various decoding libraries (such as ZBar, Zxing) and possible deep learning decoding models, and is responsible for executing step S3 in the aforementioned embodiment to output the original encoded string.

[0074] The data correction module is used to verify and correct the original encoded information to generate valid data. Specifically, the data correction module is connected to the decoding module and includes a format verifier, an image restoration unit, and a retry decoding controller. It is responsible for executing step S4 in the aforementioned embodiment and outputting verified "valid data".

[0075] The business integration module matches valid data with pre-configured business logic, triggering and executing corresponding business processing actions. Specifically, the business integration module is connected to the data correction module, and has a built-in rule engine and API call adapter, responsible for executing step S5 in the aforementioned embodiments. It can parse business rules and map valid data to specific API calls, database operations, or message queue events.

[0076] Optionally, the automatic barcode scanning and data processing system may also include a data interface module, which is connected to the business integration module and is responsible for executing step S6 in the aforementioned embodiments, providing various external data synchronization capabilities such as HTTP Client, WebSocketClient, and database connection pool.

[0077] These modules can be deployed on the same server in software form or in a distributed manner. They communicate through message middleware and work together to complete the entire automated process from image to business action.

[0078] The core of this application lies in constructing a fully automated processing closed loop encompassing image acquisition, region extraction, decoding, correction, and business triggering. First, raw visual information is acquired by acquiring images. Next, the images are intelligently processed to locate and extract the target code region. This step provides a precise input for subsequent decoding and is fundamental to improving recognition accuracy. Then, the extracted region is decoded to obtain the original information. The key improvement lies in not directly outputting the original information, but rather verifying and correcting it to generate reliable and valid data. This step directly solves the problem of recognition errors or data loss caused by code image quality. Finally, the valid data is automatically matched with pre-set business logic and triggered for execution, enabling the scanning action to directly drive specific business operations. Through the organic connection and synergy of the above technical features, this application achieves seamless automated integration from "scanning" to "business execution," effectively overcoming the technical problems of low efficiency and high error rates caused by fragmented processes and reliance on manual labor in traditional methods.

[0079] The aforementioned embodiments of the automatic barcode scanning and data processing method and the embodiments of the automatic barcode scanning and data processing system are technically related, and they can be referred to each other in terms of technical details and technical effectiveness, which will not be repeated here.

[0080] Based on the same inventive concept, embodiments of this application also provide an electronic device. Figure 3 This is a structural block diagram of an electronic device provided in an embodiment of this application. Figure 3 As shown in the embodiments of this application, an electronic device includes: one or more processors 101, a memory 102, and one or more I / O interfaces 103. The memory 102 stores one or more programs, which, when executed by the one or more processors, enable the one or more processors to implement any of the automatic barcode scanning and data processing methods described in the above embodiments; the one or more I / O interfaces 103 are connected between the processor and the memory, configured to enable information interaction between the processor and the memory.

[0081] The processor 101 is a device with data processing capabilities, including but not limited to a central processing unit (CPU); the memory 102 is a device with data storage capabilities, including but not limited to random access memory (RAM, more specifically SDRAM, DDR, etc.), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), and flash memory (FLASH); the I / O interface (read / write interface) 103 is connected between the processor 101 and the memory 102, and can realize information interaction between the processor 101 and the memory 102, including but not limited to a data bus (Bus).

[0082] In some embodiments, the processor 101, memory 102, and I / O interface 103 are interconnected via bus 104, and thus connected to other components of the computing device.

[0083] In some embodiments, the one or more processors 101 include a field-programmable gate array.

[0084] This application also provides a computer-readable medium. The computer-readable medium stores a computer program, which, when executed by a processor, implements the steps of any of the automatic barcode scanning and data processing methods described in the above embodiments. The computer-readable storage medium can be volatile or non-volatile.

[0085] This application also provides a computer program product, including computer-readable code, or a non-volatile computer-readable storage medium carrying computer-readable code. When the computer-readable code is run in the processor of an electronic device, the processor in the electronic device executes the above-described automatic barcode scanning and data processing method.

[0086] Those skilled in the art will understand that all or some of the steps, systems, and apparatuses disclosed above, and their functional modules / units, can be implemented as software, firmware, hardware, or suitable combinations thereof. In hardware implementations, the division between functional modules / units mentioned above does not necessarily correspond to the division of physical components; for example, a physical component may have multiple functions, or a function or step may be performed collaboratively by several physical components. Some or all physical components may be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application-specific integrated circuit (ASIC). Such software can be distributed on a computer-readable storage medium, which may include computer storage media (or non-transitory media) and communication media (or transient media).

[0087] As is known to those skilled in the art, the term computer storage medium includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information, such as computer-readable program instructions, data structures, program modules, or other data. Computer storage media includes, but is not limited to, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), static random access memory (SRAM), flash memory or other memory technologies, portable compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical disc storage, magnetic cartridges, magnetic tape, disk storage or other magnetic storage devices, or any other medium that can be used to store desired information and is accessible to a computer. Furthermore, it is known to those skilled in the art that communication media typically contain computer-readable program instructions, data structures, program modules, or other data in modulated data signals such as carrier waves or other transmission mechanisms, and may include any information delivery medium.

[0088] The computer-readable program instructions described herein can be downloaded from computer-readable storage media to various computing / processing devices, or downloaded via a network, such as the Internet, local area network, wide area network, and / or wireless network, to an external computer or external storage device. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers, and / or edge servers. A network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards them to the computer-readable storage media in the respective computing / processing device.

[0089] The computer program instructions used to perform the operations of this application may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, status setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Smalltalk, C++, etc., and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The computer-readable program instructions may be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or may be connected to an external computer (e.g., via the Internet using an Internet service provider). In some embodiments, electronic circuits, such as programmable logic circuits, field-programmable gate arrays (FPGAs), or programmable logic arrays (PLAs), are personalized by utilizing the status information of the computer-readable program instructions. These electronic circuits can execute the computer-readable program instructions to implement various aspects of this application.

[0090] The computer program product described herein can be implemented specifically through hardware, software, or a combination thereof. In one alternative embodiment, the computer program product is specifically embodied in a computer storage medium; in another alternative embodiment, the computer program product is specifically embodied in a software product, such as a software development kit (SDK), etc.

[0091] Various aspects of this application are described herein with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It should be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer-readable program instructions.

[0092] These computer-readable program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine such that, when executed by the processor of the computer or other programmable data processing apparatus, they create means for implementing the functions / actions specified in one or more blocks of the flowchart and / or block diagram. These computer-readable program instructions can also be stored in a computer-readable storage medium that causes a computer, programmable data processing apparatus, and / or other device to operate in a particular manner; thus, the computer-readable medium storing the instructions comprises an article of manufacture that includes instructions for implementing aspects of the functions / actions specified in one or more blocks of the flowchart and / or block diagram.

[0093] Computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, thereby causing the instructions executed on the computer, other programmable data processing apparatus, or other device to perform the functions / actions specified in one or more boxes of a flowchart and / or block diagram.

[0094] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of an instruction containing one or more executable instructions for implementing a specified logical function. In some alternative implementations, the functions marked in the blocks may occur in a different order than those marked in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0095] Exemplary embodiments have been disclosed herein, and while specific terminology has been used, it is used and should be interpreted only in a general illustrative sense and is not intended to be limiting. In some embodiments, it will be apparent to those skilled in the art that features, characteristics, and / or elements described in conjunction with particular embodiments may be used alone, or in combination with features, characteristics, and / or elements described in conjunction with other embodiments, unless otherwise expressly indicated. Therefore, those skilled in the art will understand that various changes in form and detail may be made without departing from the scope of this application as set forth by the appended claims.

Claims

1. An automatic barcode scanning and data processing method, characterized in that, include: Acquire images containing the target code; The image is preprocessed to locate and extract the image region where the target code is located; The extracted image regions are decoded to obtain the original encoded information; The original encoded information is verified and corrected to generate valid data; The valid data is matched with the pre-configured business logic to trigger and execute the corresponding business processing actions.

2. The automatic barcode scanning and data processing method according to claim 1, characterized in that, The image is preprocessed to locate and extract the image region where the target code is located, including: The image is then subjected to grayscale conversion and noise reduction filtering. Candidate regions are determined from the processed image based on edge detection algorithms; The candidate region is subjected to image enhancement processing to improve the contrast between the target code and the background, thereby completing the extraction of the image region.

3. The automatic barcode scanning and data processing method according to claim 1, characterized in that, The extracted image regions are decoded to obtain the original encoded information, including: A multi-threaded parallel processing mechanism is adopted to simultaneously decode multiple image regions extracted from different images or the same image.

4. The automatic barcode scanning and data processing method according to claim 1, characterized in that, The original encoded information is verified and corrected to generate valid data, including: The original encoded information is format-validated based on the encoding specification of the target code; If the verification fails, then based on the image region, at least one alternative decoding algorithm or image restoration algorithm is used to retry decoding; If the decoding attempt succeeds, the successfully decoded data is output as valid data; if it fails, the unprocessed record containing the image is output.

5. The automatic barcode scanning and data processing method according to claim 1, characterized in that, The business processing actions include at least one of the following: generating business documents, updating inventory status, recording logistics trajectory, triggering payment process, or sending notification messages.

6. The automatic barcode scanning and data processing method according to claim 1, characterized in that, After matching the valid data with the pre-configured business logic, triggering and executing the corresponding business processing action, the process also includes: The execution results of the business processing actions are synchronized to at least one external business system through a preset data interface.

7. The automatic barcode scanning and data processing method according to claim 1, characterized in that, When acquiring an image containing the target code, the image is acquired by calling the interface of at least one image acquisition device in the form of a video stream or continuous image capture; the acquisition parameters are dynamically adjusted according to the ambient light or the clarity of the target code during the acquisition process.

8. A system capable of implementing the automatic barcode scanning and data processing method according to any one of claims 1-7, characterized in that, include: The image acquisition module is used to acquire images containing the target code; The image preprocessing module is used to preprocess the image, locate and extract the image region where the target code is located; The decoding module is used to decode the extracted image regions to obtain the original encoded information; The data correction module is used to verify and correct the original encoded information to generate valid data; The business integration module is used to match the valid data with the pre-configured business logic, trigger and execute the corresponding business processing actions.

9. An electronic device, characterized in that, include: One or more processors; Memory, used to store one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors are enabled to implement the steps in the automatic barcode scanning and data processing method as described in any one of claims 1 to 7.

10. A computer-readable medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it can implement the steps of the automatic barcode scanning and data processing method as described in any one of claims 1 to 7.

Images