WO2019165870A1 - 一种识别条码的方法、装置及设备 - Google Patents

一种识别条码的方法、装置及设备 Download PDF

Info

Publication number
WO2019165870A1
WO2019165870A1 PCT/CN2019/073592 CN2019073592W WO2019165870A1 WO 2019165870 A1 WO2019165870 A1 WO 2019165870A1 CN 2019073592 W CN2019073592 W CN 2019073592W WO 2019165870 A1 WO2019165870 A1 WO 2019165870A1
Authority
WO
WIPO (PCT)
Prior art keywords
image
processor
barcode
processing
original
Prior art date
Application number
PCT/CN2019/073592
Other languages
English (en)
French (fr)
Inventor
杨磊磊
方刚
Original Assignee
阿里巴巴集团控股有限公司
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by 阿里巴巴集团控股有限公司 filed Critical 阿里巴巴集团控股有限公司
Publication of WO2019165870A1 publication Critical patent/WO2019165870A1/zh

Links

Images

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06K—GRAPHICAL DATA READING; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • 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
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06K—GRAPHICAL DATA READING; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • 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
    • G06K7/14—Methods or arrangements for sensing record carriers, e.g. for reading patterns by electromagnetic radiation, e.g. optical sensing; by corpuscular radiation using light without selection of wavelength, e.g. sensing reflected white light
    • G06K7/1404—Methods for optical code recognition
    • G06K7/1408—Methods for optical code recognition the method being specifically adapted for the type of code
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06K—GRAPHICAL DATA READING; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • 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
    • G06K7/14—Methods or arrangements for sensing record carriers, e.g. for reading patterns by electromagnetic radiation, e.g. optical sensing; by corpuscular radiation using light without selection of wavelength, e.g. sensing reflected white light
    • G06K7/1404—Methods for optical code recognition

Definitions

  • the embodiments of the present disclosure relate to the field of information processing technologies, and in particular, to a method, an apparatus, and a device for identifying a barcode.
  • bar codes, QR codes and other bar codes are widely used in life, which provides convenience for our lives.
  • the merchant settlement system can quickly determine the name, price, and the like of the product by scanning the barcode of the product.
  • the payment can be made to the merchant by scanning the QR code provided by the merchant through the payment application of the mobile device.
  • the application of the mobile device scans the QR code corresponding to the public facility to enable the borrowing, leasing, and return of the public facilities.
  • FIG. 1 is a schematic diagram of a conventional identification bar code using various components of a device.
  • the barcode device when the barcode software recognizes the barcode, the barcode device usually acquires the barcode image by using the camera device. Since the acquired QR image is affected by light, fading, etc., the application software needs to obtain the original. The barcode image is image preprocessed, and then the preprocessed barcode image is identified. Since the data of the acquired barcode image is usually relatively large, for example, when the input size of the image is 1024 pixels*800 pixels, the number of pixels of the image is about 100,000, and therefore, the calculation amount of image preprocessing is usually large.
  • the purpose of the embodiments of the present specification is to provide a method, device and device for identifying a barcode, which can improve the rate at which the device recognizes the barcode.
  • a method of identifying a barcode comprising:
  • An apparatus for identifying a bar code comprising: a memory and a processor; the processor comprising a central processor and an image processor; the memory storing computer program instructions executed by the processor, the computer program instructions being executable The following steps:
  • the central processor acquires an original barcode image
  • the image processor performs an image pre-processing operation on the original barcode image according to a pre-processing instruction to obtain a pre-processed barcode image;
  • the central processor identifies an object code value of the preprocessed barcode image.
  • An apparatus for identifying a barcode includes: an original picture acquisition module, a preprocessing module, and a code value determination module;
  • the original image obtaining module is configured to obtain an original barcode image
  • the pre-processing module is configured to perform an image pre-processing operation on the original barcode image according to the pre-processing instruction to obtain a pre-processed barcode image;
  • the code value determining module is configured to identify an object code value of the preprocessed barcode image.
  • the pre-processing operation of the original barcode image is implemented by using an image processor. Since the image processor processes the image data faster, the pre-processing speed of the barcode image can be improved. At the same time, the preprocessing operation of the original barcode image by the image processor can reduce the occupation of CPU resources by the image preprocessing operation, and improve the efficiency of the CPU to recognize the barcode image after preprocessing. Therefore, the embodiments provided in this specification can improve the rate at which barcodes are identified.
  • FIG. 1 is a schematic diagram of a conventional identification bar code using various components of a device
  • FIG. 2 is a schematic diagram of the identification bar code of each component of the device provided by the present specification.
  • FIG. 3 is a schematic flow chart of an embodiment of a method for identifying a barcode provided by the present specification
  • FIG. 4 is a block diagram showing the hardware structure of a mobile terminal in the embodiment of the present specification.
  • FIG. 5 is a block diagram showing the structure of an apparatus for identifying a barcode provided by the present specification.
  • Embodiments of the present specification provide a method, device, and device for identifying a barcode.
  • Application software such as Alipay can realize functions such as collection, payment, and adding friends by scanning the QR code.
  • the application software In the process of identifying the barcode by scanning, the application software usually needs to perform image pre-processing on the original barcode image acquired by the camera device, and then recognize the pre-processed barcode image.
  • the application software on the existing mobile device performs the above-mentioned pre-processing and identification process, which needs to be implemented by using a CPU.
  • a plurality of application software are usually installed on the mobile device, and the operation of multiple application software also depends on the operation.
  • the CPU of the device is implemented, and therefore, the resource competing with the image pre-processing operation described above, and the application of scanning and identifying the barcode cannot fully utilize the computing resources of the device, which may affect the efficiency of image pre-processing.
  • the data of the barcode image acquired by the image capturing apparatus is generally large, when the image is preprocessed by the CPU, a large amount of calculation requires a large amount of CPU usage, and the rate of the device identification barcode is also reduced.
  • the preprocessing operation of the barcode image can be implemented by using a graphics processing chip, which can improve the processing speed of the image preprocessing, and can reduce the occupation of the CPU resources by the image preprocessing operation.
  • the efficiency of the bar code picture after pre-processing of the CPU is improved, thereby improving the rate at which the device recognizes the bar code.
  • FIG. 2 is a schematic diagram of the identification bar code of each component of the device provided by the present specification.
  • 3 is a schematic flow chart of an embodiment of a method for identifying a barcode provided by the present specification.
  • the present specification provides method operation steps as described in the embodiment or the flowchart, but the routine or non-creative labor may include more or Fewer steps.
  • the order of the steps recited in the embodiments is only one of the many steps of the order of execution, and does not represent a single order of execution.
  • the method can include the following steps.
  • the device used to identify the barcode can obtain the original barcode image.
  • the original barcode picture can be captured using an imaging device of the device.
  • the original barcode image may include a barcode image or a two-dimensional code image.
  • S304 Perform an image pre-processing operation on the original barcode image according to the pre-processing instruction by using an image processor to obtain a pre-processed barcode image.
  • the image preprocessing operation may be performed on the original barcode image according to a preprocessing instruction by using an image processor.
  • the image processor may represent a device that is good at performing image data processing.
  • the image processor may include: a graphics processing unit (GPU), a digital signal processing (DSP) chip, and/or an image signal processing (ISP) chip.
  • GPU graphics processing unit
  • DSP digital signal processing
  • ISP image signal processing
  • the graphics processor usually a microprocessor that performs image computing operations exclusively on the device, can be used to undertake the task of outputting display graphics.
  • the digital signal processor is a processor composed of large-scale or very large-scale integrated circuit chips for performing digital signal processing tasks.
  • the image information processing chip is an image processing dedicated engine that can process image signals at high speed.
  • the image pre-processing operation may be processing performed before code value recognition of the original barcode image.
  • all or part of the acquired barcode image may be white due to overexposure or dark due to insufficient light, resulting in
  • the bar code image has a low contrast and cannot quickly and accurately identify the code value of the bar code image.
  • the detectability of the barcode image can be enhanced, thereby improving the reliability of the code value recognition.
  • the image pre-processing operation may include: average luminance statistics and binarization processing.
  • the brightness distribution of the original picture can be determined by the brightness statistics operation.
  • the original barcode image may be further subjected to binarization processing.
  • one or more thresholds may be determined according to the result of the average luminance statistical operation, and the original image is binarized according to the threshold.
  • the pre-processing instruction may be: a computer instruction compiled by a coded language for implementing the pre-processing operation.
  • the pre-processing instructions may be computer instructions in a machine language executable by the image processor.
  • the coded language for implementing the pre-processing operation may adopt a Renderscript programming language.
  • the coded language for implementing the pre-processing operation may adopt an OpenCL programming language.
  • the image processor generally processes image data at a relatively fast speed, the processing speed of the original barcode image pre-processing can be improved by using the image processor.
  • the device for identifying a barcode may identify an object code value of the preprocessed barcode image. Since the bar code picture after the pre-processing operation is highly detectable, the target code value of the pre-processed bar code picture can be quickly identified.
  • the preprocessing operation of the original barcode image is implemented by using an image processor. Since the image processor processes the image data faster, the preprocessing speed of the barcode image can be improved. At the same time, the preprocessing operation of the original barcode image by the image processor can reduce the occupation of CPU resources by the image preprocessing operation, and improve the efficiency of the CPU to recognize the barcode image after preprocessing. Therefore, the embodiments provided in this specification can improve the rate at which barcodes are identified.
  • FIG. 2 is a block diagram showing the hardware structure of a mobile terminal in the embodiment of the present specification.
  • the mobile terminal may include at least two (only two shown in the figure) processor 102, a memory 104 for storing data, and a transmission module 106 for communication functions.
  • the processor 102 can include at least one central processing unit (CPU) and at least one graphics processing unit (GPU). Of course, the processor 102 may also include other microcontrollers, logic gates, integrated circuits, etc. having logic processing capabilities, or a suitable combination thereof.
  • CPU central processing unit
  • GPU graphics processing unit
  • the processor 102 may also include other microcontrollers, logic gates, integrated circuits, etc. having logic processing capabilities, or a suitable combination thereof.
  • the memory 104 can be used to store software programs and modules of application software, such as program instructions/modules corresponding to the search method in the embodiment of the present invention, and the central processor 102 executes by executing software programs and modules stored in the memory 104.
  • Various functional applications and data processing that is, a method of realizing the identification of barcodes in the above embodiments.
  • Memory 104 may include high speed random access memory, and may also include non-volatile memory such as one or more magnetic storage devices, flash memory, or other non-volatile solid state memory.
  • memory 104 can further include memory remotely located relative to processor 102, which can be connected to the page display device over a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.
  • the memory may also be implemented by using a cloud memory. The specific implementation manner is not limited in this specification.
  • the transmission module 106 can be configured to receive or transmit data via a network.
  • the network specific example described above may include a wireless network provided by a communication provider of the page display device.
  • the transport module 106 includes a Network Interface Controller (NIC) that can be connected to other network devices through a base station to communicate with the Internet.
  • the transmission module 106 can be a Radio Frequency (RF) module for communicating with the Internet wirelessly.
  • NIC Network Interface Controller
  • RF Radio Frequency
  • the structure shown in FIG. 4 is merely illustrative, and does not limit the structure of the above mobile terminal.
  • the mobile terminal may further include more or less components than those shown in FIG. 4, such as a digital signal processing (DSP) chip, an image signal processing (ISP) chip, and the like. Or have a different configuration than that shown in FIG.
  • DSP digital signal processing
  • ISP image signal processing
  • the present specification also provides an apparatus based on the method of identifying a barcode as described above.
  • the apparatus may include a system (including a distributed system), software (applications), modules, components, devices, etc., using the methods described in the embodiments of the present specification, in conjunction with necessary device hardware for implementing the hardware.
  • the apparatus provided in this specification is as described in the following embodiments. Since the implementation and the method for solving the problem are similar, the implementation of the specific device in the embodiment of the present specification can be referred to the implementation of the foregoing method, and the repeated description is not repeated.
  • the apparatus described in the following embodiments is preferably implemented in software, hardware, or a combination of software and hardware, is also possible and contemplated.
  • FIG. 5 is a block diagram showing the structure of an apparatus for identifying a barcode provided by the present specification.
  • the apparatus for identifying a barcode may include: an original picture obtaining module 502, a pre-processing module 504, and a code value determining module 506.
  • the original picture obtaining module 502 can be configured to obtain an original barcode picture.
  • the pre-processing module 504 can be configured to perform an image pre-processing operation on the original barcode image according to the pre-processing instruction to obtain a pre-processed barcode image.
  • the image pre-processing operation may include: average luminance statistics and binarization processing.
  • the pre-processing module is implemented using an image processor.
  • the pre-processing instructions are computer instructions of a machine language executable by the image processor.
  • the pre-processing instructions may be computer instructions compiled for use in a coded language for implementing the pre-processing operations.
  • the image processor may include a graphics processor, a digital signal processing chip, and/or an image signal processing chip.
  • the code value determining module 506 can be configured to identify an object code value of the preprocessed barcode image.
  • the foregoing method or apparatus for identifying a barcode provided by an embodiment of the present specification may be implemented by a processor executing a corresponding program instruction in a computer, for example, using an android, iOS system programming language in an intelligent terminal, and a processing function based on a quantum computer. Wait.
  • an apparatus for identifying a barcode including a processor and a memory.
  • the processor includes a central processing unit and an image processor.
  • the memory stores computer program instructions executed by the processor, and the executing the computer program instructions may implement the steps of: the central processor acquiring an original barcode image; the image processor to the original barcode according to a pre-processing instruction The image is subjected to an image pre-processing operation to obtain a pre-processed barcode image; the central processor identifies an object code value of the pre-processed barcode image.
  • the pre-processing instructions may be computer instructions compiled for use in a coded language implementation of the pre-processing operations. If the device for identifying a barcode uses an Android operating system, the coded language for implementing the pre-processing operation may adopt a Renderscript programming language. If the device for identifying a barcode uses an iOS operating system, the coded language for implementing the pre-processing operation may adopt an OpenCL programming language.
  • the embodiment of the apparatus and device for identifying the barcode provided by the present specification and the method embodiment of the present specification are based on the same innovative concept. Therefore, the embodiment of the apparatus and device for identifying the barcode provided by the present specification can be implemented in the specification. The technical effect of the method embodiment.
  • PLD Programmable Logic Device
  • FPGA Field Programmable Gate Array
  • HDL Hardware Description Language
  • the controller can be implemented in any suitable manner, for example, the controller can take the form of, for example, a microprocessor or processor and a computer readable medium storing computer readable program code (eg, software or firmware) executable by the (micro)processor.
  • computer readable program code eg, software or firmware
  • examples of controllers include, but are not limited to, the following microcontrollers: ARC 625D, Atmel AT91SAM, The Microchip PIC18F26K20 and the Silicone Labs C8051F320, the memory controller can also be implemented as part of the memory's control logic.
  • the controller can be logically programmed by means of logic gates, switches, ASICs, programmable logic controllers, and embedding.
  • Such a controller can therefore be considered a hardware component, and the means for implementing various functions included therein can also be considered as a structure within the hardware component.
  • a device for implementing various functions can be considered as a software module that can be both a method of implementation and a structure within a hardware component.
  • the apparatus, module or unit set forth in the above embodiments may be implemented by a computer chip or an entity, or by a product having a certain function.
  • a typical implementation device is a computer.
  • the computer can be, for example, a personal computer, a laptop computer, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or A combination of any of these devices.
  • the computer program instructions can also be stored in a computer readable memory that can direct a computer or other programmable data processing device to operate in a particular manner, such that the instructions stored in the computer readable memory produce an article of manufacture comprising the instruction device.
  • the apparatus implements the functions specified in one or more blocks of a flow or a flow and/or block diagram of the flowchart.
  • These computer program instructions can also be loaded onto a computer or other programmable data processing device such that a series of operational steps are performed on a computer or other programmable device to produce computer-implemented processing for execution on a computer or other programmable device.
  • the instructions provide steps for implementing the functions specified in one or more of the flow or in a block or blocks of a flow diagram.
  • a computing device includes one or more processors, input/output interfaces, network interfaces, and memory.
  • the memory may include non-persistent memory, random access memory (RAM), and/or non-volatile memory in a computer readable medium, such as read only memory (ROM) or flash memory.
  • RAM random access memory
  • ROM read only memory
  • Memory is an example of a computer readable medium.
  • Computer readable media includes both permanent and non-persistent, removable and non-removable media.
  • Information storage can be implemented by any method or technology.
  • the information can be computer readable instructions, data structures, modules of programs, or other data.
  • Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read only memory.
  • PRAM phase change memory
  • SRAM static random access memory
  • DRAM dynamic random access memory
  • RAM random access memory
  • ROM read only memory
  • EEPROM electrically erasable programmable read only memory
  • flash memory or other memory technology
  • compact disk read only memory CD-ROM
  • DVD digital versatile disk
  • Magnetic cassette tape magnetic tape storage
  • graphene storage or other magnetic storage devices or any other non-transportable media
  • computer readable media does not include temporary storage of computer readable media, such as modulated data signals and carrier waves.
  • embodiments of the present specification can be provided as a method, apparatus, or computer program product. Accordingly, the present description may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment in combination of software and hardware. Moreover, the description may take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) including computer usable program code.
  • computer-usable storage media including but not limited to disk storage, CD-ROM, optical storage, etc.
  • program modules include routines, programs, objects, components, data structures, and the like that perform particular tasks or implement particular abstract data types.
  • the present specification can also be practiced in distributed computing environments where tasks are performed by remote processing devices that are connected through a communication network.
  • program modules can be located in both local and remote computer storage media including storage devices.

Landscapes

  • Physics & Mathematics (AREA)
  • Engineering & Computer Science (AREA)
  • Electromagnetism (AREA)
  • Health & Medical Sciences (AREA)
  • General Health & Medical Sciences (AREA)
  • Toxicology (AREA)
  • Artificial Intelligence (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Stored Programmes (AREA)
  • Image Processing (AREA)

Abstract

本说明书实施例提供一种识别条码的方法、装置及设备，所述方法包括：获取原始条码图片；利用图像处理器根据预处理指令对所述原始条码图片进行图像预处理操作，得到预处理后条码图片；识别所述预处理后条码图片的目标码值。

Description

一种识别条码的方法、装置及设备 技术领域
本说明书实施例涉及信息处理技术领域，特别涉及一种识别条码的方法、装置及设备。
背景技术
随着信息数字化发展，条形码、二维码等条码在生活中被广泛使用，为我们的生活提供了便捷。例如，在结算商品的过程中，商家结算系统通过扫码商品的条形码可以快速确定商品的名称、价格等信息。在支付过程中，通过移动设备的支付应用扫描商家提供的二维码可以向商家进行付款。在公共设施的使用方面，通过移动设备的应用软件扫描公共设施对应的二维码可以实现公共设施的借用、租赁、退还等操作。
图1是现有的利用设备各部件识别条码的示意图。参照图1，目前，具有条码识别功能的应用软件在识别条码时，通常是先利用摄像装置设备获取条码图片，由于获取的二维码图片受到光线、褪色等影响，应用软件需要对获取的原始条码图片进行图像预处理，再识别预处理后的条码图片。由于获取的条码图片的数据通常数据量比较大，例如，当图片的输入尺寸在1024像素*800像素时，图像的像素数在10万左右，因此，图像预处理的运算量通常较大。由于应用软件的运行都是依靠设备的中央处理器(Central Processing Unit，CPU)来实现，而用户设备系统的交互式操作，例如应用页面的切换、系统状态的监听、应用广播的收发操作等，也需要依靠设备的CPU来实现，对前述的图像预处理会产生资源竞争，影响图像预处理的效率，降低了设备识别条码的速率。因此，需要提供一种更快速的识别条码的方法。
发明内容
本说明书实施例的目的是提供一种识别条码的方法、装置及设备，可以提高设备识别条码的速率。
本说明书实施例是这样实现的：
一种识别条码的方法，包括：
获取原始条码图片；
利用图像处理器根据预处理指令对所述原始条码图片进行图像预处理操作，得到预处理后条码图片；
识别所述预处理后条码图片的目标码值。
一种识别条码的设备，包括：存储器和处理器；所述处理器包括中央处理器和图像处理器；所述存储器存储由所述处理器执行的计算机程序指令，执行所述计算机程序指令可以实现以下步骤：
所述中央处理器获取原始条码图片；
所述图像处理器根据预处理指令对所述原始条码图片进行图像预处理操作得到预处理后条码图片；
所述中央处理器识别所述预处理后条码图片的目标码值。
一种识别条码的装置，包括：原始图片获取模块、预处理模块和码值确定模块；
所述原始图片获取模块，用于获取原始条码图片；
所述预处理模块，用于根据所述预处理指令对所述原始条码图片进行图像预处理操作得到预处理后条码图片；
所述码值确定模块，用于识别出所述预处理后条码图片的目标码值。
由以上可见，本说明书一个或多个实施例中，将对原始条码图片的预处理操作利用图像处理器来实现，由于图像处理器处理图像数据速度较快，可以提高条码图片的预处理速度。同时，利用图像处理器对原始条码图片进行预处理操作可以减少图像预处理操作对CPU资源的占用，提高了CPU识别预处理后条码图片的效率。因此，本说明书提供的实施例利可以提高识别条码的速率。
附图说明
为了更清楚地说明本说明书一个或多个实施例或现有技术中的技术方案，下面将对实施例或现有技术描述中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图仅仅是本说明书中记载的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据这些附图获得其他的附图。
图1是现有的利用设备各部件识别条码的示意图；
图2是本说明书提供的利用设备各部件识别条码的一个示意图；
图3是本说明书提供的识别条码的方法一种实施例的流程示意图；
图4是本说明书实施例中一种移动终端的硬件结构框图；
图5是本说明书提供的识别条码的装置一个实施例的模块结构示意图。
具体实施方式
本说明书实施例提供一种识别条码的方法、装置及设备。
为了使本技术领域的人员更好地理解本说明书中的技术方案，下面将结合本说明书实施例中的附图，对本说明书实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例仅仅是本说明书一部分实施例，而不是全部的实施例。基于本说明书中的实施例，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例，都应当属于本说明书保护的范围。
支付宝等应用软件通过扫描二维码，可以实现收款、付款、添加好友等功能。这些应用软件在通过扫描识别条码的过程中，通常需要先对摄像装置获取的原始条码图片进行图像预处理，再识别预处理后的条码图片。一方面现有的移动设备上的应用软件执行上述预处理和识别的过程都需要利用CPU来实现，但是，移动设备上通常安装有多个应用软件，多个应用软件的运行也都是依靠该设备的CPU来实现，因此，会和前述的图像预处理操作产生资源竞争，扫描识别条码的应用无法完全利用设备的计算资源，会影响图像预处理的效率。另一方面，由于摄像装置获取的条码图片的数据通常数据量比较大，利用CPU进行图像预处理时，较大的运算量需要占用CPU的时长较多，也降低了设备识别条码的速率。基于此，本说明书实施例中可以将对条码图片的预处理操作利用图形处理芯片来实现，一方面可以提高图像预处理的处理速度，另一方面可以减少图像预处理操作对CPU资源的占用，提高了CPU识别预处理后条码图片的效率，从而可以提高设备识别条码的速率。
以下介绍本说明书一种识别条码的方法的一种具体实施例。图2是本说明书提供的利用设备各部件识别条码的一个示意图。图3是本说明书提供的识别条码的方法的一种实施例的流程示意图，本说明书提供了如实施例或流程图所述的方法操作步骤，但基于常规或者无创造性的劳动可以包括更多或者更少的操作步骤。实施例中列举的步骤顺序仅仅为众多步骤执行顺序中的一种方式，不代表唯一的执行顺序。在实际中的系统或设备产品执行时，可以按照实施例或者附图所示的方法顺序执行或者并行执行(例如并行 处理器或者多线程处理的环境)。具体的参照图2和图3，所述方法可以包括以下步骤。
S302：获取原始条码图片。
用于识别条码的设备可以获取原始条码图片。具体地，可以利用所述设备的摄像装置拍摄所述原始条码图片。
所述原始条码图片可以包括：条形码图片或二维码图片。
S304：利用图像处理器根据预处理指令对所述原始条码图片进行图像预处理操作，得到预处理后条码图片。
可以利用图像处理器根据预处理指令对所述原始条码图片进行图像预处理操作。
所述图像处理器可以表示擅长进行图像数据处理的装置。具体地，所述图像处理器可以包括：图形处理器(Graphics Processing Unit，GPU)、数字信号处理(Digital Signal Processing，DSP)芯片和/或图像信号处理(Image Signal Processing，ISP)芯片。
所述图形处理器，通常是专门在设备上执行图像运算工作的微处理器，可以用于承担输出显示图形的任务。
所述数字信号处理器，是由大规模或超大规模集成电路芯片组成的用来完成数字信号处理任务的处理器。
所述图像信息处理芯片是一种图像处理专用引擎，其可以高速处理图像信号。
所述图像预处理操作可以是对所述原始条码图片进行码值识别之前所进行的处理。
在实际获取条码图片的过程中，由于光线过亮或过暗、光照不均等原因，可能导致获取的条码图片的全部或部分由于被过度曝光显得很白，或者由于光线不足显得很暗，从而导致条码图片的对比度较低，无法快速、准确地识别条码图片的码值。通过所述图像预处理操作，可以增强条码图片的可检测性，从而提高码值识别的可靠性。
在一个实施方式中，所述图像预处理操作可以包括：平均亮度统计和二值化处理。
通过所述亮度统计操作可以确定所述原始图片的亮度分布情况。根据所述平均亮度统计操作的结果，可以进一步对所述原始条码图片进行二值化处理。例如，可以根据所述平均亮度统计操作的结果，确定一个或多个阈值，根据所述阈值对所述原始图片进行二值化处理。
所述预处理指令可以为：用于实现所述预处理操作的代码化语言编译得到的计算机 指令。所述预处理指令可以是所述图像处理器可执行的机器语言的计算机指令。
在一个实施方式中，若所述用于识别条码的设备采用Android操作系统，所述用于实现所述预处理操作的代码化语言可以采用Renderscript编程语言。
在另一个实施方式中，若所述用于识别条码的设备采用iOS操作系统，所述用于实现所述预处理操作的代码化语言可以采用OpenCL编程语言。
由于所述图像处理器通常处理图像数据速度较快，因此，利用所述图像处理器可以提高原始条码图片预处理的处理速度。
S306：识别所述预处理后条码图片的目标码值。
所述用于识别条码的设备可以识别所述预处理后条码图片的目标码值。由于经过预处理操作后的条码图片可检测性较强，可以快速识别出所述预处理后条码图片的目标码值。
本说明书提供的实施例中，将对原始条码图片的预处理操作利用图像处理器来实现，由于图像处理器处理图像数据速度较快，可以提高条码图片的预处理速度。同时，利用图像处理器对原始条码图片进行预处理操作可以减少图像预处理操作对CPU资源的占用，提高了CPU识别预处理后条码图片的效率。因此，本说明书提供的实施例利可以提高识别条码的速率。
本申请实施例所提供的方法实施例可以在移动终端、计算机终端、服务器或者类似的运算装置中执行。以运行在移动终端上为例，图2是本说明书实施例中一种移动终端的硬件结构框图。如图2所示，所述移动终端可以包括至少2个(图中仅示出两个)处理器102、用于存储数据的存储器104以及用于通信功能的传输模块106。
所述处理器102可以包括至少一个中央处理器(CPU)和至少一个图形处理器(Graphics Processing Unit，GPU)。当然所述处理器102也可以包括其他的具有逻辑处理能力的单片机、逻辑门电路、集成电路等，或其适当组合。
所述存储器104可用于存储应用软件的软件程序以及模块，如本发明实施例中的搜索方法对应的程序指令/模块，中央处理器102通过运行存储在存储器104内的软件程序以及模块，从而执行各种功能应用以及数据处理，即实现上述实施例中的识别条码的方法。存储器104可包括高速随机存储器，还可包括非易失性存储器，如一个或者多个磁性存储装置、闪存、或者其他非易失性固态存储器。在一些实例中，存储器104可进一步包括相对于处理器102远程设置的存储器，这些远程存储器可以通过网络连接至所述 页面显示设备。上述网络的实例包括但不限于互联网、企业内部网、局域网、移动通信网及其组合。实现的时候，该存储器也可以采用云存储器的方式实现，具体实现方式，本说明书不作出限定。
所述传输模块106可以用于经由一个网络接收或者发送数据。上述的网络具体实例可包括所述页面显示设备的通信供应商提供的无线网络。在一个实例中，传输模块106包括一个网络适配器(Network Interface Controller，NIC)，其可通过基站与其他网络设备相连从而可与互联网进行通讯。在一个实例中，传输模块106可以为射频(Radio Frequency，RF)模块，其用于通过无线方式与互联网进行通讯。
本领域普通技术人员可以理解，图4所示的结构仅为示意，其并不对上述移动终端的结构造成限定。例如，所述移动终端还可包括比图4中所示更多或者更少的组件，例如数字信信号处理(Digital Signal Processing，DSP)芯片、图像信号处理(Image Signal Processing，ISP)芯片等，或者具有与图4所示不同的配置。
基于上述所述的识别条码的方法，本说明书还提供一种装置。所述的装置可以包括使用了本说明书实施例所述方法的系统(包括分布式系统)、软件(应用)、模块、组件、设备等并结合必要的实施硬件的设备装置。基于同一创新构思，本说明书提供的装置如下面的实施例所述。由于和方法解决问题的实现方案与方法相似，因此本说明书实施例具体的装置实施可以参见前述方法的实施，重复之处不再赘述。尽管以下实施例所描述的装置较佳地以软件来实现，但是硬件，或者软件和硬件的组合的实现也是可能并被构想的。
图5是本说明书提供的识别条码的装置一个实施例的模块结构示意图。如图5所示，所述识别条码的装置可以包括：原始图片获取模块502、预处理模块504和码值确定模块506。
所述原始图片获取模块502，可以用于获取原始条码图片。
所述预处理模块504，可以用于根据所述预处理指令对所述原始条码图片进行图像预处理操作得到预处理后条码图片。所述图像预处理操作可以包括：平均亮度统计和二值化处理。
在一个实施方式中，所述预处理模块采用图像处理器实现。所述预处理指令是所述图像处理器可执行的机器语言的计算机指令。所述预处理指令可以是用于实现所述预处理操作的代码化语言编译得到的计算机指令。
在一个实施方式中，所述图像处理器可以包括：图形处理器、数字信号处理芯片和/或图像信号处理芯片。
所述码值确定模块506，可以用于识别出所述预处理后条码图片的目标码值。
本说明书实施例提供的上述识别条码的方法或装置可以在计算机中由处理器执行相应的程序指令来实现，例如使用android、iOS系统程序设计语言在智能终端实现，以及基于量子计算机的处理逻辑实现等。
具体的，本说明书另一方面还提供一种识别条码的设备，包括处理器及存储器。所述处理器包括中央处理器和图像处理器。所述存储器存储由所述处理器执行的计算机程序指令，执行所述计算机程序指令可以实现以下步骤：所述中央处理器获取原始条码图片；所述图像处理器根据预处理指令对所述原始条码图片进行图像预处理操作得到预处理后条码图片；所述中央处理器识别所述预处理后条码图片的目标码值。
在一个实施方式中，所述预处理指令可以是用于实现所述预处理操作的代码化语言编译得到的计算机指令。若所述用于识别条码的设备采用Android操作系统，所述用于实现所述预处理操作的代码化语言可以采用Renderscript编程语言。若所述用于识别条码的设备采用iOS操作系统，所述用于实现所述预处理操作的代码化语言可以采用OpenCL编程语言。
由此可见，本说明书提供的识别条码的装置和设备的实施例与本说明书中的方法实施例是基于同一创新构思，因此，本说明书提供的识别条码的装置和设备的实施例可以实现说明书中方法实施例的技术效果。
上述对本说明书特定实施例进行了描述。其它实施例在所附权利要求书的范围内。在一些情况下，在权利要求书中记载的动作或步骤可以按照不同于实施例中的顺序来执行并且仍然可以实现期望的结果。另外，在附图中描绘的过程不一定要求示出的特定顺序或者连续顺序才能实现期望的结果。在某些实施方式中，多任务处理和并行处理也是可以的或者可能是有利的。
在20世纪90年代，对于一个技术的改进可以很明显地区分是硬件上的改进(例如，对二极管、晶体管、开关等电路结构的改进)还是软件上的改进(对于方法流程的改进)。然而，随着技术的发展，当今的很多方法流程的改进已经可以视为硬件电路结构的直接改进。设计人员几乎都通过将改进的方法流程编程到硬件电路中来得到相应的硬件电路结构。因此，不能说一个方法流程的改进就不能用硬件实体模块来实现。例如，可编程 逻辑器件(Programmable Logic Device，PLD)(例如现场可编程门阵列(Field Programmable Gate Array，FPGA))就是这样一种集成电路，其逻辑功能由用户对器件编程来确定。由设计人员自行编程来把一个数字系统“集成”在一片PLD上，而不需要请芯片制造厂商来设计和制作专用的集成电路芯片。而且，如今，取代手工地制作集成电路芯片，这种编程也多半改用“逻辑编译器(logic compiler)”软件来实现，它与程序开发撰写时所用的软件编译器相类似，而要编译之前的原始代码也得用特定的编程语言来撰写，此称之为硬件描述语言(Hardware Description Language，HDL)，而HDL也并非仅有一种，而是有许多种，如ABEL(Advanced Boolean Expression Language)、AHDL(Altera Hardware Description Language)、Confluence、CUPL(Cornell University Programming Language)、HDCal、JHDL(Java Hardware Description Language)、Lava、Lola、MyHDL、PALASM、RHDL(Ruby Hardware Description Language)等，目前最普遍使用的是VHDL(Very-High-Speed Integrated Circuit Hardware Description Language)与Verilog。本领域技术人员也应该清楚，只需要将方法流程用上述几种硬件描述语言稍作逻辑编程并编程到集成电路中，就可以很容易得到实现该逻辑方法流程的硬件电路。
控制器可以按任何适当的方式实现，例如，控制器可以采取例如微处理器或处理器以及存储可由该(微)处理器执行的计算机可读程序代码(例如软件或固件)的计算机可读介质、逻辑门、开关、专用集成电路(Application Specific Integrated Circuit，ASIC)、可编程逻辑控制器和嵌入微控制器的形式，控制器的例子包括但不限于以下微控制器：ARC 625D、Atmel AT91SAM、Microchip PIC18F26K20以及Silicone Labs C8051F320，存储器控制器还可以被实现为存储器的控制逻辑的一部分。本领域技术人员也知道，除了以纯计算机可读程序代码方式实现控制器以外，完全可以通过将方法步骤进行逻辑编程来使得控制器以逻辑门、开关、专用集成电路、可编程逻辑控制器和嵌入微控制器等的形式来实现相同功能。因此这种控制器可以被认为是一种硬件部件，而对其内包括的用于实现各种功能的装置也可以视为硬件部件内的结构。或者甚至，可以将用于实现各种功能的装置视为既可以是实现方法的软件模块又可以是硬件部件内的结构。
上述实施例阐明的装置、模块或单元，具体可以由计算机芯片或实体实现，或者由具有某种功能的产品来实现。一种典型的实现设备为计算机。具体的，计算机例如可以为个人计算机、膝上型计算机、蜂窝电话、相机电话、智能电话、个人数字助理、媒体播放器、导航设备、电子邮件设备、游戏控制台、平板计算机、可穿戴设备或者这些设备中的任何设备的组合。
为了描述的方便，描述以上装置时以功能分为各种单元分别描述。当然，在实施本说明书时可以把各单元的功能在同一个或多个软件和/或硬件中实现。
本发明是参照根据本发明实施例的方法、设备(装置)、和计算机程序产品的流程图和/或方框图来描述的。应理解可由计算机程序指令实现流程图和/或方框图中的每一流程和/或方框、以及流程图和/或方框图中的流程和/或方框的结合。可提供这些计算机程序指令到通用计算机、专用计算机、嵌入式处理机或其他可编程数据处理设备的处理器以产生一个机器，使得通过计算机或其他可编程数据处理设备的处理器执行的指令产生用于实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的装置。
这些计算机程序指令也可存储在能引导计算机或其他可编程数据处理设备以特定方式工作的计算机可读存储器中，使得存储在该计算机可读存储器中的指令产生包括指令装置的制造品，该指令装置实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能。
这些计算机程序指令也可装载到计算机或其他可编程数据处理设备上，使得在计算机或其他可编程设备上执行一系列操作步骤以产生计算机实现的处理，从而在计算机或其他可编程设备上执行的指令提供用于实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的步骤。
在一个典型的配置中，计算设备包括一个或多个处理器、输入/输出接口、网络接口和内存。
内存可能包括计算机可读介质中的非永久性存储器，随机存取存储器(RAM)和/或非易失性内存等形式，如只读存储器(ROM)或闪存(flash RAM)。内存是计算机可读介质的示例。
计算机可读介质包括永久性和非永久性、可移动和非可移动媒体可以由任何方法或技术来实现信息存储。信息可以是计算机可读指令、数据结构、程序的模块或其他数据。计算机的存储介质的例子包括，但不限于相变内存(PRAM)、静态随机存取存储器(SRAM)、动态随机存取存储器(DRAM)、其他类型的随机存取存储器(RAM)、只读存储器(ROM)、电可擦除可编程只读存储器(EEPROM)、快闪记忆体或其他内存技术、只读光盘只读存储器(CD-ROM)、数字多功能光盘(DVD)或其他光学存储、磁盒式磁带，磁带磁磁盘存储、石墨烯存储或其他磁性存储设备或任何其他非传输介质，可用于存储可 以被计算设备访问的信息。按照本文中的界定，计算机可读介质不包括暂存电脑可读媒体(transitory media)，如调制的数据信号和载波。
还需要说明的是，术语“包括”、“包含”或者其任何其他变体意在涵盖非排他性的包含，从而使得包括一系列要素的过程、方法、商品或者设备不仅包括那些要素，而且还包括没有明确列出的其他要素，或者是还包括为这种过程、方法、商品或者设备所固有的要素。在没有更多限制的情况下，由语句“包括一个……”限定的要素，并不排除在包括所述要素的过程、方法、商品或者设备中还存在另外的相同要素。
本领域技术人员应明白，本说明书的实施例可提供为方法、装置或计算机程序产品。因此，本说明书可采用完全硬件实施例、完全软件实施例或结合软件和硬件方面的实施例的形式。而且，本说明书可采用在一个或多个其中包含有计算机可用程序代码的计算机可用存储介质(包括但不限于磁盘存储器、CD-ROM、光学存储器等)上实施的计算机程序产品的形式。
本说明书可以在由计算机执行的计算机可执行指令的一般上下文中描述，例如程序模块。一般地，程序模块包括执行特定任务或实现特定抽象数据类型的例程、程序、对象、组件、数据结构等等。也可以在分布式计算环境中实践本说明书，在这些分布式计算环境中，由通过通信网络而被连接的远程处理设备来执行任务。在分布式计算环境中，程序模块可以位于包括存储设备在内的本地和远程计算机存储介质中。
本说明书中的各个实施例均采用递进的方式描述，各个实施例之间相同相似的部分互相参见即可，每个实施例重点说明的都是与其他实施例的不同之处。尤其，对于装置和服务器实施例而言，由于其基本相似于方法实施例，所以描述的比较简单，相关之处参见方法实施例的部分说明即可。
以上所述仅为本说明书的实施例而已，并不用于限制本说明书。对于本领域技术人员来说，本说明书可以有各种更改和变化。凡在本说明书的精神和原理之内所作的任何修改、等同替换、改进等，均应包含在权利要求范围之内。

Claims (10)

  1. 一种识别条码的方法，包括：
    获取原始条码图片；
    利用图像处理器根据预处理指令对所述原始条码图片进行图像预处理操作，得到预处理后条码图片；
    识别所述预处理后条码图片的目标码值。
  2. 根据权利要求1所述的方法，其中，所述图像预处理操作包括：平均亮度统计操作和二值化处理操作。
  3. 根据权利要求1所述的方法，其中，所述预处理指令为：用于实现所述预处理操作的代码化语言编译得到的计算机指令。
  4. 根据权利要求3所述的方法，其中，所述预处理代码化语言包括：用于实现所述图像预处理操作的代码化语言。
  5. 根据权利要求3所述的方法，其中，所述用于实现所述预处理操作的代码化语言采用Renderscript编程语言或者OpenCL编程语言。
  6. 根据权利要求1所述的方法，其中，所述图像处理器包括：图形处理器、数字信号处理芯片和/或图像信号处理芯片。
  7. 一种识别条码的设备，包括：存储器和处理器；所述处理器包括中央处理器和图像处理器；所述存储器存储由所述处理器执行的计算机程序指令，执行所述计算机程序指令可以实现以下步骤：
    所述中央处理器获取原始条码图片；
    所述图像处理器根据预处理指令对所述原始条码图片进行图像预处理操作得到预处理后条码图片；
    所述中央处理器识别所述预处理后条码图片的目标码值。
  8. 根据权利要求7所述的设备，其中，所述图像处理器包括：图形处理器、数字信号处理芯片和/或图像信号处理芯片。
  9. 一种识别条码的装置，包括：原始图片获取模块、预处理模块和码值确定模块；
    所述原始图片获取模块，用于获取原始条码图片；
    所述预处理模块，用于根据所述预处理指令对所述原始条码图片进行图像预处理操作得到预处理后条码图片；
    所述码值确定模块，用于识别出所述预处理后条码图片的目标码值。
  10. 根据权利要求9所述的装置，所述预处理模块采用图像处理器实现；所述图像处理器包括：图形处理器、数字信号处理芯片和/或图像信号处理芯片。
PCT/CN2019/073592 2018-03-02 2019-01-29 一种识别条码的方法、装置及设备 WO2019165870A1 (zh)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
CN201810174440.7A CN108520188A (zh) 2018-03-02 2018-03-02 一种识别条码的方法、装置及设备
CN201810174440.7 2018-03-02

Publications (1)

Publication Number Publication Date
WO2019165870A1 true WO2019165870A1 (zh) 2019-09-06

Family

ID=63433503

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/CN2019/073592 WO2019165870A1 (zh) 2018-03-02 2019-01-29 一种识别条码的方法、装置及设备

Country Status (3)

Country Link
CN (1) CN108520188A (zh)
TW (1) TW201939346A (zh)
WO (1) WO2019165870A1 (zh)

Families Citing this family (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108520188A (zh) * 2018-03-02 2018-09-11 阿里巴巴集团控股有限公司 一种识别条码的方法、装置及设备
CN111435414B (zh) * 2019-01-14 2024-04-05 北京京东尚科信息技术有限公司 识别二维码的方法、系统、设备及储存介质

Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101504716A (zh) * 2009-03-13 2009-08-12 重庆大学 基于现场可编程门阵列的qr二维条码识别方法及系统
CN102184378A (zh) * 2011-04-27 2011-09-14 茂名职业技术学院 一种pdf417标准二维条码图像切割的办法
CN102737214A (zh) * 2011-04-15 2012-10-17 上海真石信息技术有限公司 条形码图像阀值频率手机识别技术
CN104809422A (zh) * 2015-04-27 2015-07-29 江苏中科贯微自动化科技有限公司 基于图像处理的qr码识别方法
CN105678206A (zh) * 2015-12-29 2016-06-15 东软集团股份有限公司 识别条码的方法和装置
CN107545207A (zh) * 2017-09-28 2018-01-05 云南电网有限责任公司电力科学研究院 基于图像处理的dm二维码识别方法及装置
CN108520188A (zh) * 2018-03-02 2018-09-11 阿里巴巴集团控股有限公司 一种识别条码的方法、装置及设备

Patent Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101504716A (zh) * 2009-03-13 2009-08-12 重庆大学 基于现场可编程门阵列的qr二维条码识别方法及系统
CN102737214A (zh) * 2011-04-15 2012-10-17 上海真石信息技术有限公司 条形码图像阀值频率手机识别技术
CN102184378A (zh) * 2011-04-27 2011-09-14 茂名职业技术学院 一种pdf417标准二维条码图像切割的办法
CN104809422A (zh) * 2015-04-27 2015-07-29 江苏中科贯微自动化科技有限公司 基于图像处理的qr码识别方法
CN105678206A (zh) * 2015-12-29 2016-06-15 东软集团股份有限公司 识别条码的方法和装置
CN107545207A (zh) * 2017-09-28 2018-01-05 云南电网有限责任公司电力科学研究院 基于图像处理的dm二维码识别方法及装置
CN108520188A (zh) * 2018-03-02 2018-09-11 阿里巴巴集团控股有限公司 一种识别条码的方法、装置及设备

Also Published As

Publication number Publication date
TW201939346A (zh) 2019-10-01
CN108520188A (zh) 2018-09-11

Similar Documents

Publication Publication Date Title
WO2017148275A1 (zh) 信息显示方法及装置
WO2019034039A1 (zh) 一种目标图形码识别方法和装置
WO2019169965A1 (zh) 一种扫码图像识别方法、装置以及设备
WO2019137196A1 (zh) 图像标注信息助理方法、装置、服务器及系统
WO2019149020A1 (zh) 一种信息识别方法、服务器、客户端及系统
TWI717644B (zh) 業務資訊獲取方法、裝置以及設備
US8965051B2 (en) Method and apparatus for providing hand detection
WO2019196542A1 (zh) 一种图像处理的方法及装置
WO2019085587A1 (zh) 一种公共交通支付的方法、装置及设备
WO2018059365A9 (zh) 图形码处理方法及装置、存储介质
WO2019165870A1 (zh) 一种识别条码的方法、装置及设备
US10168192B2 (en) Determining values of angular gauges
CN110516494A (zh) 一种二维码识别方法、装置、设备及系统
CN113051950A (zh) 一种多条码识别方法以及相关设备
US9760764B2 (en) Methods, apparatuses and computer program products for efficiently recognizing faces of images associated with various illumination conditions
US20200356830A1 (en) Method and system for applying barcode, and server
CN116994007B (zh) 商品纹理检测处理方法及装置
WO2021185232A1 (zh) 一种条码识别方法以及相关设备
CN113657245B (zh) 一种用于人脸活体检测的方法、设备、介质及程序产品
CN110751003B (zh) 一种获取二维码的目标数据信息的方法与设备
US11755859B2 (en) Apparatus and method for enabling decoding of remotely sourced and visually presented encoded data markers
CN116206228A (zh) 图像的结构化识别方法、装置、电子设备及可读存储介质
CN111091016B (zh) 一种鼎九码识读方法、装置及移动终端
Kang A rectification method for quick response code image
US20230161989A1 (en) Method and system for setting dynamic image threshold for two-dimensional identification code detection

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 19760482

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE

122 Ep: pct application non-entry in european phase

Ref document number: 19760482

Country of ref document: EP

Kind code of ref document: A1