CN116451720A - Warehouse material scanning and identifying method and identifying system thereof - Google Patents
Warehouse material scanning and identifying method and identifying system thereof Download PDFInfo
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- 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
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- 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
- G06K7/1439—Methods for optical code recognition including a method step for retrieval of the optical code
- G06K7/1456—Methods for optical code recognition including a method step for retrieval of the optical code determining the orientation of the optical code with respect to the reader and correcting therefore
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- G06K—GRAPHICAL DATA READING; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
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- G06K7/1404—Methods for optical code recognition
- G06K7/1408—Methods for optical code recognition the method being specifically adapted for the type of code
- G06K7/1413—1D bar codes
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- G06K7/1404—Methods for optical code recognition
- G06K7/1408—Methods for optical code recognition the method being specifically adapted for the type of code
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- G06K7/1404—Methods for optical code recognition
- G06K7/146—Methods for optical code recognition the method including quality enhancement steps
- G06K7/1482—Methods for optical code recognition the method including quality enhancement steps using fuzzy logic or natural solvers, such as neural networks, genetic algorithms and simulated annealing
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Abstract
The invention relates to the technical field of storage equipment, in particular to a storage material scanning and identifying method and a storage material scanning and identifying system. The method comprises the following steps: acquiring bar code information to be identified, wherein the bar code information comprises two-dimensional code information and bar code information; determining the image content deflection angle of the image content in each piece of bar code information, and adjusting the angle of the bar code information; identifying the type of the bar code information with the angle adjusted, and determining the type of the bar code information; determining an identification mode corresponding to the bar code information according to the category; and outputting article information corresponding to the bar code information based on the bar code information and the identification mode. The invention realizes quick and accurate identification of bar code information with different inclination angles, and simultaneously can identify two-dimensional codes and bar codes, thereby avoiding the need of separate identification of two sets of systems in the prior art.
Description
Technical Field
The invention relates to the technical field of storage equipment, in particular to a storage material scanning and identifying method and a storage material scanning and identifying system.
Background
Warehouse storage is an important component of modern logistics, plays a crucial role in logistics systems and is the focus of manufacturer research and planning. The efficient and reasonable storage can help manufacturers to accelerate the material flowing speed, reduce the cost, ensure the smooth production, and realize effective control and management of resources. Warehousing plays a critical role in the whole supply chain of an enterprise, and if proper stock intake and stock control and delivery cannot be guaranteed, the management cost will be increased, and the service quality is difficult to guarantee, so that the competitiveness of the enterprise is affected.
In the prior art, in the process of scanning and identifying the storage materials, a certain angle requirement exists on the angle of bar code information on the materials, and then a certain requirement exists on the placement of the materials, if the placement of the materials is not in accordance with the requirement, the scanning and identifying precision is further affected, and in order to solve the technical problem, a storage material scanning and identifying method and a storage material scanning and identifying system are provided.
Disclosure of Invention
In order to solve the technical problems in the prior art, the invention provides a warehouse material scanning and identifying method and an identifying system thereof.
In order to achieve the above object, the embodiment of the present invention provides the following technical solutions:
in a first aspect, in one embodiment provided by the present invention, there is provided a warehouse material scanning and identifying method, the method including the steps of:
acquiring bar code information to be identified, wherein the bar code information comprises two-dimensional code information and bar code information;
determining the image content deflection angle of the image content in each piece of bar code information, and adjusting the angle of the bar code information;
identifying the type of the bar code information with the angle adjusted, and determining the type of the bar code information;
determining an identification mode corresponding to the bar code information according to the category;
and outputting article information corresponding to the bar code information based on the bar code information and the identification mode.
As a further scheme of the invention, the types of the bar code information with the adjusted angles are identified, and the types of the bar code information are determined by a pre-trained correction mode selection model;
the determining the image content deflection angle of the image content in each bar code information comprises the following steps:
inputting each piece of bar code information into a pre-trained correction mode selection model, and determining an image content deflection angle of the image content corresponding to each piece of bar code information;
identifying the type of the bar code information with the angle adjusted, and determining the type of the bar code information comprises the following steps:
inputting the bar code information into the correction mode selection model trained in advance, and determining the category of the bar code information.
As a further aspect of the present invention, the training mode of the correction mode selection model includes:
acquiring an initial training data set, and performing rotation processing on the initial training data set to generate a rotation sample data set;
and training the correction mode selection model through the initial training data set and the rotation sample data set to obtain a trained correction mode selection model.
As a further aspect of the present invention, the determining, according to the category, an identification mode corresponding to the barcode information includes:
when the category indicates that the bar code information is consistent with a preset recognition mode, the bar code information is used as target bar code information;
when the category indicates that the bar code information is inconsistent with a preset recognition mode, the recognition mode is automatically switched to obtain target bar code information corresponding to the recognition mode.
As a further aspect of the present invention, the automatically switching the identification mode to obtain target barcode information corresponding to the identification mode includes:
determining the content format of the target bar code information;
based on the content format, an identification mode is selected.
As a further aspect of the present invention, the outputting, based on the barcode information and the identification mode, article information corresponding to the barcode information includes:
based on each image content deflection angle, the correction mode selection model automatically adjusts the angle of the image content deflection angle;
and traversing a pre-stored content database according to the image content and the category after the deflection angle is adjusted, matching the pre-stored content database with the image content, and outputting article information corresponding to the bar code information.
As a further aspect of the present invention, outputting article information corresponding to the barcode information based on the barcode information and the identification mode includes:
and identifying the two-dimensional code information by adopting a two-dimensional code identification model to obtain a two-dimensional code identification result, and obtaining corresponding article information based on the two-dimensional code identification result.
As a further scheme of the invention, the two-dimensional code recognition model is obtained by training a preprocessed two-dimensional code image training set, and the two-dimensional code image training set comprises images in a correcting state under various illumination conditions;
the training step of the two-dimensional code recognition model comprises the following steps:
acquiring a two-dimensional code image training set;
pre-training the deep convolutional neural network to obtain training parameters; the deep convolutional neural network is pre-trained through an ImageNet data set;
training the deep convolutional neural network according to the preprocessed two-dimensional code image training set and the training parameters to obtain the two-dimensional code recognition model.
As a further scheme of the invention, the acquiring the two-dimensional code image training set comprises the following steps:
acquiring a sample two-dimensional code image set, wherein the sample two-dimensional code image set comprises two-dimensional code images of each two-dimensional code under different illumination conditions and a negative sample image;
carrying out noise reduction pretreatment on the sample two-dimensional code image set to obtain a sample two-dimensional code image set subjected to noise reduction pretreatment;
remarks are made on the preprocessed sample two-dimensional code image set, and a preprocessed two-dimensional code image training set is obtained.
In a second aspect, in yet another embodiment provided by the present invention, there is provided a warehouse material scanning identification system, the system comprising: the system comprises a bar code information acquisition module, a correction mode selection module and an identification module.
The bar code information acquisition module is used for acquiring bar code information to be identified, wherein the bar code information comprises two-dimensional code information and bar code information;
the correction mode selection module is used for determining the image content deflection angle of the image content in each piece of bar code information and adjusting the angle of the bar code information; identifying the type of the bar code information with the angle adjusted, and determining the type of the bar code information; determining an identification mode corresponding to the bar code information according to the category;
the identification module is used for outputting article information corresponding to the bar code information based on the bar code information and the identification mode.
The technical scheme provided by the invention has the following beneficial effects:
according to the warehouse goods scanning and identifying method and the identifying system thereof, bar code information to be identified is obtained, wherein the bar code information comprises two-dimensional code information and bar code information; determining the image content deflection angle of the image content in each piece of bar code information, and adjusting the angle of the bar code information; identifying the type of the bar code information with the angle adjusted, and determining the type of the bar code information; determining an identification mode corresponding to the bar code information according to the category; and outputting article information corresponding to the bar code information based on the bar code information and the identification mode. The bar code information of different inclination angles can be identified rapidly and accurately, and meanwhile, two-dimensional codes and bar codes can be identified, so that the problem that two sets of systems are required to be identified separately in the prior art is solved.
These and other aspects of the invention will be more readily apparent from the following description of the embodiments. It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the invention as claimed.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are necessary for the description of the embodiments or the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention and that other embodiments may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flowchart of a warehouse material scanning and identifying method according to an embodiment of the present invention.
Fig. 2 is a flowchart showing a specific step S20 in the warehouse material scanning and identifying method according to an embodiment of the present invention.
Fig. 3 is a flowchart showing a specific step S202 in the warehouse material scanning and identifying method according to an embodiment of the present invention.
Fig. 4 is a flowchart showing a specific step S30 in the warehouse material scanning and identification according to an embodiment of the present invention.
Fig. 5 is a block diagram of a warehouse material scanning and identifying system according to an embodiment of the present invention.
In the figure: the system comprises a 100-bar code information acquisition module, a 200-correction mode selection module and a 300-identification module.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are some, but not all embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The flow diagrams depicted in the figures are merely illustrative and not necessarily all of the elements and operations/steps are included or performed in the order described. For example, some operations/steps may be further divided, combined, or partially combined, so that the order of actual execution may be changed according to actual situations.
It is to be understood that the terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in this specification and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
In particular, embodiments of the present invention are further described below with reference to the accompanying drawings.
Referring to fig. 1, fig. 1 is a flowchart of a warehouse material scanning and identifying method according to an embodiment of the present invention, as shown in fig. 1, the warehouse material scanning and identifying method includes steps S10 to S30.
Step S10, bar code information to be identified is obtained, wherein the bar code information comprises two-dimensional code information and bar code information.
Step S20, determining the image content deflection angle of the image content in each piece of bar code information, and adjusting the angle of the bar code information; identifying the type of the bar code information with the angle adjusted, and determining the type of the bar code information; and determining an identification mode corresponding to the bar code information according to the category.
Referring to fig. 2, in the embodiment of the present invention, the type of the barcode information with the adjusted angle is identified, and the determination of the type of the barcode information is performed through a pre-trained correction mode selection model;
step S201, determining an image content deflection angle of the image content in each barcode information, including:
inputting each piece of bar code information into a pre-trained correction mode selection model, and determining an image content deflection angle of the image content corresponding to each piece of bar code information;
step S202, identifying the type of the bar code information with the adjusted angle, and determining the type of the bar code information, including:
inputting the bar code information into the correction mode selection model trained in advance, and determining the category of the bar code information.
Referring to fig. 3, in an embodiment of the present invention, the training manner of the correction mode selection model includes:
step S2021, acquiring an initial training data set, and performing rotation processing on the initial training data set to generate a rotation sample data set;
step S2022, training the correction mode selection model through the initial training data set and the rotation sample data set, to obtain a trained correction mode selection model.
In an embodiment of the present invention, the determining, according to the category, an identification mode corresponding to the barcode information includes:
when the category indicates that the bar code information is consistent with a preset recognition mode, the bar code information is used as target bar code information;
when the category indicates that the bar code information is inconsistent with a preset recognition mode, the recognition mode is automatically switched to obtain target bar code information corresponding to the recognition mode.
The automatic switching of the identification mode to obtain the target bar code information corresponding to the identification mode comprises the following steps:
determining the content format of the target bar code information;
based on the content format, an identification mode is selected.
In an embodiment of the present invention, the outputting, based on the barcode information and the identification mode, article information corresponding to the barcode information includes:
based on each image content deflection angle, the correction mode selection model automatically adjusts the angle of the image content deflection angle;
and traversing a pre-stored content database according to the image content and the category after the deflection angle is adjusted, matching the pre-stored content database with the image content, and outputting article information corresponding to the bar code information.
In an embodiment of the present invention, outputting corresponding item information of the barcode information based on the barcode information and the identification mode includes:
and identifying the two-dimensional code information by adopting a two-dimensional code identification model to obtain a two-dimensional code identification result, and obtaining corresponding article information based on the two-dimensional code identification result.
And step S30, outputting article information corresponding to the bar code information based on the bar code information and the identification mode.
Referring to fig. 4, in the embodiment of the present invention, the two-dimensional code recognition model is obtained by training a preprocessed two-dimensional code image training set, where the two-dimensional code image training set includes images in an alignment state under various illumination conditions;
the training step of the two-dimensional code recognition model comprises the following steps:
step S301, acquiring a two-dimensional code image training set;
step S302, pre-training a deep convolutional neural network to obtain training parameters; the deep convolutional neural network is pre-trained through an ImageNet data set;
it should be noted that the ImageNet dataset was used for pre-training to obtain model initial parameters. And (3) fine tuning the model parameters by using the pre-training parameters and using the two-dimensional code image training set. Therefore, the two-dimensional code recognition model can be obtained more quickly.
And step S303, training the deep convolutional neural network according to the preprocessed two-dimensional code image training set and the training parameters to obtain the two-dimensional code recognition model.
In an embodiment of the present invention, the acquiring a two-dimensional code image training set includes:
acquiring a sample two-dimensional code image set, wherein the sample two-dimensional code image set comprises two-dimensional code images of each two-dimensional code under different illumination conditions and a negative sample image; the negative sample image may be a texture image. So then can provide comprehensive training set, guarantee training effect.
And carrying out noise reduction pretreatment on the sample two-dimensional code image set to obtain a sample two-dimensional code image set after the noise reduction pretreatment.
Remarks are made on the preprocessed sample two-dimensional code image set, and a preprocessed two-dimensional code image training set is obtained.
The two-dimensional code recognition model can be trained by acquiring the two-dimensional code image for training, and the recognition accuracy of the two-dimensional code recognition model is guaranteed.
The method comprises the steps of obtaining bar code information to be identified, wherein the bar code information comprises two-dimensional code information and bar code information; determining the image content deflection angle of the image content in each piece of bar code information, and adjusting the angle of the bar code information; identifying the type of the bar code information with the angle adjusted, and determining the type of the bar code information; determining an identification mode corresponding to the bar code information according to the category; and outputting article information corresponding to the bar code information based on the bar code information and the identification mode. The bar code information of different inclination angles can be identified rapidly and accurately, and meanwhile, two-dimensional codes and bar codes can be identified, so that the problem that two sets of systems are required to be identified separately in the prior art is solved.
It should be understood that although described in a certain order, the steps are not necessarily performed sequentially in the order described. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, some steps of the present embodiment may include a plurality of steps or stages, which are not necessarily performed at the same time, but may be performed at different times, and the order of the steps or stages is not necessarily sequential, but may be performed alternately or alternately with at least a part of the steps or stages in other steps or other steps.
In one embodiment, referring to fig. 5, a warehouse material scanning and identification system is also provided in an embodiment of the present invention, which includes a bar code information acquisition module 100, a correction pattern selection module 200, and an identification module 300.
The bar code information acquisition module 100 is configured to acquire bar code information to be identified, where the bar code information includes two-dimensional code information and bar code information;
the correction mode selection module 200 is configured to determine an image content deflection angle of the image content in each piece of barcode information, and adjust an angle of the barcode information; identifying the type of the bar code information with the angle adjusted, and determining the type of the bar code information; and determining an identification mode corresponding to the bar code information according to the category.
The identification module 300 is configured to output article information corresponding to the barcode information based on the barcode information and the identification mode.
The method comprises the steps of obtaining bar code information to be identified, wherein the bar code information comprises two-dimensional code information and bar code information; determining the image content deflection angle of the image content in each piece of bar code information, and adjusting the angle of the bar code information; identifying the type of the bar code information with the angle adjusted, and determining the type of the bar code information; determining an identification mode corresponding to the bar code information according to the category; and outputting corresponding article information of the bar code information based on the bar code information and the identification mode. The bar code information of different inclination angles can be identified rapidly and accurately, and meanwhile, two-dimensional codes and bar codes can be identified, so that the problem that two sets of systems are required to be identified separately in the prior art is solved.
In one embodiment, a computer device is also provided in an embodiment of the present invention, including a processor, a communication interface, a memory, and a communication bus, where the processor, the communication interface, and the memory communicate with each other via the communication bus.
A memory for storing a computer program;
the processor is used for executing the storage material scanning and identifying method when executing the computer program stored in the memory, and the steps in the method embodiment are realized when the processor executes the instructions:
step S10, bar code information to be identified is obtained, wherein the bar code information comprises two-dimensional code information and bar code information.
Step S20, determining the image content deflection angle of the image content in each piece of bar code information, and adjusting the angle of the bar code information; identifying the type of the bar code information with the angle adjusted, and determining the type of the bar code information; and determining an identification mode corresponding to the bar code information according to the category.
And step S30, outputting article information corresponding to the bar code information based on the bar code information and the identification mode.
The communication bus mentioned by the above terminal may be a peripheral component interconnect standard (Peripheral Component Interconnect, abbreviated as PCI) bus or an extended industry standard architecture (Extended InduStry Standard Architecture, abbreviated as EISA) bus, etc. The communication bus may be classified as an address bus, a data bus, a control bus, or the like.
The communication interface is used for communication between the terminal and other devices.
The memory may include random access memory (Random Access Memory, RAM) or non-volatile memory (non-volatile memory), such as at least one disk memory. Optionally, the memory may also be at least one memory device located remotely from the aforementioned processor.
The processor may be a general-purpose processor, including a central processing unit (Central Processing Unit, CPU for short), a network processor (Network Processor, NP for short), etc.; but also digital signal processors (Digital Signal Processing, DSP for short), application specific integrated circuits (Application SpecificIntegrated Circuit, ASIC for short), field-programmable gate arrays (Field-Programmable Gate Array, FPGA for short) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.
The computer device includes a user device and a network device. Wherein the user equipment includes, but is not limited to, a computer, a smart phone, a PDA, etc.; the network device includes, but is not limited to, a single network server, a server group of multiple network servers, or a Cloud based Cloud Computing (Cloud Computing) consisting of a large number of computers or network servers, where Cloud Computing is one of distributed Computing, and is a super virtual computer consisting of a group of loosely coupled computer sets. The computer device can be used for realizing the invention by running alone, and can also be accessed into a network and realized by interaction with other computer devices in the network. Wherein the network where the computer device is located includes, but is not limited to, the internet, a wide area network, a metropolitan area network, a local area network, a VPN network, and the like.
It should also be understood that the term "and/or" as used in the present specification and the appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes such combinations.
In one embodiment of the present invention there is also provided a storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of the method embodiments described above:
step S10, bar code information to be identified is obtained, wherein the bar code information comprises two-dimensional code information and bar code information.
Step S20, determining the image content deflection angle of the image content in each piece of bar code information, and adjusting the angle of the bar code information; identifying the type of the bar code information with the angle adjusted, and determining the type of the bar code information; and determining an identification mode corresponding to the bar code information according to the category.
And step S30, outputting article information corresponding to the bar code information based on the bar code information and the identification mode.
Finally, it should be noted that the computer-readable storage media (e.g., memory) herein can be either volatile memory or nonvolatile memory, or can include both volatile and nonvolatile memory. By way of example, and not limitation, nonvolatile memory can include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM), which acts as external cache memory. By way of example, and not limitation, RAM may be available in a variety of forms such as synchronous RAM (DRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), and direct Rambu SRAM (DRRAM). Storage devices of the disclosed aspects include, but are not limited to, these and other suitable types of memory.
The various illustrative logical blocks, modules, and circuits described in connection with the disclosure herein may be implemented or performed with the following components designed to perform the functions herein: a general purpose processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof. A general purpose processor may be a microprocessor, but in the alternative, the processor may be any conventional processor, controller, microcontroller, or state machine. A processor may also be implemented as a combination of computing devices, e.g., a combination of a DSP and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a DSP and/or any other such configuration.
It should be noted that, for simplicity of description, the foregoing embodiments are all illustrated as a series of acts, but it should be understood by those skilled in the art that the present invention is not limited by the order of acts, as some steps may be performed in other order or concurrently in accordance with the present invention. Further, those skilled in the art will also appreciate that the embodiments described in the specification are all preferred embodiments, and that the acts and modules referred to are not necessarily required for the present invention.
In the several embodiments provided in the present application, it should be understood that the disclosed apparatus may be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, such as the above-described division of units, merely a division of logic functions, and there may be additional manners of dividing in actual implementation, such as multiple units or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or communication connection shown or discussed as being between each other may be an indirect coupling or communication connection between devices or elements via some interfaces, which may be in the form of telecommunications or otherwise.
The units described above as separate components may or may not be physically separate, and components shown as units may or may not be physical units, may be located in one place, or may be distributed over a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
The above embodiments are only for illustrating the technical solution of the present invention, and not for limiting the scope of the present invention. It will be apparent that the described embodiments are merely some, but not all, embodiments of the invention. Based on these embodiments, all other embodiments that may be obtained by one of ordinary skill in the art without inventive effort are within the scope of the invention. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art may still combine, add or delete features of the embodiments of the present invention or make other adjustments according to circumstances without any conflict, so as to obtain different technical solutions without substantially departing from the spirit of the present invention, which also falls within the scope of the present invention.
Claims (10)
1. A warehouse material scanning and identifying method, which is characterized by comprising the following steps:
acquiring bar code information to be identified, wherein the bar code information comprises two-dimensional code information and bar code information;
determining the image content deflection angle of the image content in each piece of bar code information, and adjusting the angle of the bar code information; identifying the type of the bar code information with the angle adjusted, and determining the type of the bar code information; determining an identification mode corresponding to the bar code information according to the category;
and outputting article information corresponding to the bar code information based on the bar code information and the identification mode.
2. The warehouse material scan identification method as claimed in claim 1, wherein the angle-adjusted type of the bar code information is identified, and the determination of the type of the bar code information is performed through a pre-trained correction mode selection model;
the determining the image content deflection angle of the image content in each bar code information comprises the following steps:
inputting each piece of bar code information into a pre-trained correction mode selection model, and determining an image content deflection angle of the image content corresponding to each piece of bar code information;
identifying the type of the bar code information with the angle adjusted, and determining the type of the bar code information comprises the following steps:
inputting the bar code information into the correction mode selection model trained in advance, and determining the category of the bar code information.
3. The method for scanning and identifying warehouse materials according to claim 2, wherein the training mode of the correction pattern selection model comprises:
acquiring an initial training data set, and performing rotation processing on the initial training data set to generate a rotation sample data set;
and training the correction mode selection model through the initial training data set and the rotation sample data set to obtain a trained correction mode selection model.
4. The method of claim 1, wherein determining the identification pattern corresponding to the barcode information according to the category comprises:
when the category indicates that the bar code information is consistent with a preset recognition mode, the bar code information is used as target bar code information;
when the category indicates that the bar code information is inconsistent with a preset recognition mode, the recognition mode is automatically switched to obtain target bar code information corresponding to the recognition mode.
5. The method for scanning and identifying warehouse materials according to claim 4, wherein the automatically switching the identification mode to obtain the target bar code information corresponding to the identification mode comprises:
determining the content format of the target bar code information;
based on the content format, an identification mode is selected.
6. The warehouse material scan identification method as claimed in claim 3, wherein the outputting the item information corresponding to the barcode information based on the barcode information and the identification mode comprises:
based on each image content deflection angle, the correction mode selection model automatically adjusts the angle of the image content deflection angle;
and traversing a pre-stored content database according to the image content and the category after the deflection angle is adjusted, matching the pre-stored content database with the image content, and outputting article information corresponding to the bar code information.
7. The warehouse supply scanning and identification method as claimed in claim 1, wherein outputting the corresponding item information of the barcode information based on the barcode information and the identification pattern comprises:
and identifying the two-dimensional code information by adopting a two-dimensional code identification model to obtain a two-dimensional code identification result, and obtaining corresponding article information based on the two-dimensional code identification result.
8. The warehouse material scanning and identifying method according to claim 7, wherein the two-dimensional code identifying model is obtained by training a preprocessed two-dimensional code image training set, and the two-dimensional code image training set comprises images in an alignment state under various illumination conditions;
the training step of the two-dimensional code recognition model comprises the following steps:
acquiring a two-dimensional code image training set;
pre-training the deep convolutional neural network to obtain training parameters; the deep convolutional neural network is pre-trained through an ImageNet data set;
training the deep convolutional neural network according to the preprocessed two-dimensional code image training set and the training parameters to obtain the two-dimensional code recognition model.
9. The method for scanning and identifying warehouse materials according to claim 8, wherein the acquiring the training set of two-dimensional code images comprises:
acquiring a sample two-dimensional code image set, wherein the sample two-dimensional code image set comprises two-dimensional code images of each two-dimensional code under different illumination conditions and a negative sample image;
carrying out noise reduction pretreatment on the sample two-dimensional code image set to obtain a sample two-dimensional code image set subjected to noise reduction pretreatment;
remarks are made on the preprocessed sample two-dimensional code image set, and a preprocessed two-dimensional code image training set is obtained.
10. A warehouse material scanning and identifying system, characterized in that the warehouse material scanning and identifying system comprises: the system comprises a bar code information acquisition module, a correction mode selection module and an identification module;
the bar code information acquisition module is used for acquiring bar code information to be identified, wherein the bar code information comprises two-dimensional code information and bar code information;
the correction mode selection module is used for determining the image content deflection angle of the image content in each piece of bar code information and adjusting the angle of the bar code information; identifying the type of the bar code information with the angle adjusted, and determining the type of the bar code information; determining an identification mode corresponding to the bar code information according to the category;
the identification module is used for outputting article information corresponding to the bar code information based on the bar code information and the identification mode.
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