CN113807256A - Bill data processing method and device, electronic equipment and storage medium - Google Patents
Bill data processing method and device, electronic equipment and storage medium Download PDFInfo
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- CN113807256A CN113807256A CN202111095245.3A CN202111095245A CN113807256A CN 113807256 A CN113807256 A CN 113807256A CN 202111095245 A CN202111095245 A CN 202111095245A CN 113807256 A CN113807256 A CN 113807256A
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Abstract
The application provides a bill data processing method, a bill data processing device, an electronic device and a storage medium, wherein the bill data processing method comprises the following steps: acquiring image data of a bill to be verified; carrying out image recognition on the image data to obtain data information on the bill to be verified; judging whether the bill to be verified exists in a database or not according to the data information; and if the bill to be verified exists in the database, marking the bill to be verified as a repeated bill. Therefore, the image data of the bill to be verified is subjected to image recognition, so that the data information on the bill to be verified can be extracted quickly, whether the bill to be verified is a repeated bill or not can be judged quickly according to the data information, and the efficiency, the feedback speed and the accuracy of bill data processing are improved.
Description
Technical Field
The present application relates to the field of image processing technologies, and in particular, to a method and an apparatus for processing ticket data, an electronic device, and a storage medium.
Background
The medical charging bill is an effective reimbursement certificate for medical income after medical services such as outpatient service, emergency treatment, first aid and hospitalization are provided for patients by medical and health institutions. Generally, a medical charging bill is composed of basic elements such as a bill name, a bill code, a bill number, a drawer, a billing date, a billing amount and the like.
In the medical toll bill reimbursement process, for avoiding repeated reimbursement, bill information needs to be verified, the medical toll bill is often verified by manpower in the existing verification mode, along with the increasing of the number of the medical toll bill, a large amount of manpower and material resources are needed to be spent to complete bill verification, the efficiency is low, the feedback speed is low, and the accuracy is low.
Disclosure of Invention
An object of the embodiments of the present application is to provide a method and an apparatus for processing ticket data, an electronic device, and a storage medium, so as to automatically determine whether a ticket is repeated, and improve efficiency, feedback speed, and accuracy of processing the ticket data.
In a first aspect, the present application provides a method for processing ticket data, including: acquiring image data of a bill to be verified; carrying out image recognition on the image data to obtain data information on the bill to be verified; judging whether the bill to be verified exists in a database or not according to the data information; and if the bill to be verified exists in the database, marking the bill to be verified as a repeated bill.
In an embodiment, the performing image recognition on the image data to obtain data information on the to-be-verified bill includes: inputting the image data into a preset separation model, and outputting a plurality of segmentation areas on the image data; and performing character recognition on the image data according to the segmentation area to obtain data information on the bill to be verified.
In an embodiment, the data information includes an identification code of the to-be-verified bill, payment information, and account information; the judging whether the bill to be verified exists in a database according to the data information comprises the following steps: judging whether a first bill set identical to the identification code and the payment information of the bill to be verified exists in the database; if the first bill set exists in the database, judging whether a first target bill which is the same as the account information of the bill to be verified exists in the first bill set; and if the first target bill exists in the first bill set, determining that the bill to be verified exists in the database.
In one embodiment, the data information further includes: attribution hospital information of the bill to be verified; the judging whether the bill to be verified exists in the database according to the data information further comprises: if the first bill set does not exist in the database, judging whether a second target bill which is the same as the identification code of the bill to be verified and the attribution hospital information exists in the database or not; and if the second target bill exists in the database, determining that the bill to be verified exists in the database.
In one embodiment, the data information further includes: the account information and diagnosis and treatment date of the bill to be verified; the method further comprises the following steps: if the first target bill does not exist in the first bill set or if the second target bill does not exist in the database, judging whether a second bill set identical to the account information of the bill to be verified exists in the database or not; if the second bill set exists in the database, judging whether a third target bill which is the same as the diagnosis and treatment date of the bill to be verified exists in the second bill set; and if the third target bill exists in the database, outputting prompt information.
In one embodiment, the method further comprises: if the third target bill does not exist in the database, judging whether a fourth target bill which is the same as the identification code of the bill to be verified exists in the database or not; and if the fourth target bill exists in the database, outputting prompt information.
In one embodiment, the method further comprises: and if the third target bill does not exist in the database or if the fourth target bill does not exist in the database, determining that the bill to be verified does not exist in the database.
In a second aspect, the present application provides a ticket data processing apparatus, comprising: the device comprises an acquisition module, an identification module, a judgment module and a marking module; the acquisition module is used for acquiring image data of a bill to be verified; the identification module is used for carrying out image identification on the image data to obtain data information on the bill to be verified; the judging module is used for judging whether the bill to be verified exists in a database or not according to the data information; and the marking module is used for marking the bill to be verified as a repeated bill when the bill to be verified exists in the database.
In one embodiment, the identification module is further configured to: inputting the image data into a preset separation model, and outputting a plurality of segmentation areas on the image data; and performing character recognition on the image data according to the segmentation area to obtain data information on the bill to be verified.
In an embodiment, the data information includes an identification code of the to-be-verified bill, payment information, and account information; the judging module is further configured to: judging whether a first bill set identical to the identification code and the payment information of the bill to be verified exists in the database; if the first bill set exists in the database, judging whether a first target bill which is the same as the account information of the bill to be verified exists in the first bill set; and if the first target bill exists in the first bill set, determining that the bill to be verified exists in the database.
In one embodiment, the data information further includes: attribution hospital information of the bill to be verified; the judging module is further configured to: if the first bill set does not exist in the database, judging whether a second target bill which is the same as the identification code of the bill to be verified and the attribution hospital information exists in the database or not; and if the second target bill exists in the database, determining that the bill to be verified exists in the database.
In one embodiment, the data information further includes: the account information and diagnosis and treatment date of the bill to be verified; the judging module is further configured to: if the first target bill does not exist in the first bill set or if the second target bill does not exist in the database, judging whether a second bill set identical to the account information of the bill to be verified exists in the database or not; if the second bill set exists in the database, judging whether a third target bill which is the same as the diagnosis and treatment date of the bill to be verified exists in the second bill set; and if the third target bill exists in the database, outputting prompt information.
In an embodiment, the determining module is further configured to: if the third target bill does not exist in the database, judging whether a fourth target bill which is the same as the identification code of the bill to be verified exists in the database or not; and if the fourth target bill exists in the database, outputting prompt information.
In an embodiment, the determining module is further configured to: and if the third target bill does not exist in the database or if the fourth target bill does not exist in the database, determining that the bill to be verified does not exist in the database.
In a third aspect, the present application provides an electronic device, comprising:
a memory to store a computer program;
a processor configured to execute the computer program to implement the method according to any of the preceding embodiments.
In a fourth aspect, the present application provides a non-transitory computer-readable storage medium comprising: a program which, when run by an electronic device, causes the electronic device to perform the method of any of the preceding embodiments.
According to the bill data processing method, the bill data processing device, the electronic equipment and the storage medium, image recognition is carried out on the image data of the bill to be verified, so that the data information on the bill to be verified can be extracted quickly, whether the bill to be verified is a repeated bill or not can be judged quickly according to the data information, and the bill data processing efficiency, the feedback speed and the accuracy are improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are required to be used in the embodiments of the present application will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and that those skilled in the art can also obtain other related drawings based on the drawings without inventive efforts.
Fig. 1 is a schematic structural diagram of an electronic device according to an embodiment of the present application;
FIG. 2 is a schematic flow chart illustrating a method for processing ticket data according to an embodiment of the present application;
FIG. 3 is a schematic flow chart illustrating a method for processing ticket data according to an embodiment of the present application;
FIG. 4 is a schematic flowchart of a method for processing ticket data according to an embodiment of the present application;
fig. 5 is a schematic structural diagram of a ticket data processing apparatus according to an embodiment of the present application.
Icon: 100-an electronic device; 101-a bus; 102-a memory; 103-a processor; 200-bill data processing means; 210-an obtaining module; 220-an identification module; 230-a judgment module; 240-marking module.
Detailed Description
The technical solutions in the embodiments of the present application will be described below with reference to the drawings in the embodiments of the present application. In the description of the present application, the terms "first," "second," and the like are used solely to distinguish one from another and are not to be construed as indicating or implying relative importance.
Fig. 1 is a schematic structural diagram of an electronic device 100 according to an embodiment of the present disclosure. The electronic apparatus 100 includes: at least one processor 103 and a memory 102, one processor 103 being exemplified in fig. 1. The processor 103 and the memory 102 are connected by the bus 101, and the memory 102 stores instructions executable by the processor 103, and the instructions are executed by the processor 103, so that the electronic device 100 can execute all or part of the flow of the method in the embodiments described below, to automatically determine whether the bill is repeated, and improve the efficiency, feedback speed and accuracy of bill data processing.
In one embodiment, the Processor 103 may be a general-purpose Processor 103, including but not limited to a Central Processing Unit (CPU) 103, a Network Processor 103 (NP), etc., a Digital Signal Processor (DSP) 103, an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components, etc. The general purpose processor 103 may be a microprocessor 103 or the processor 103 may be any conventional processor 103 or the like, the processor 103 being the control center of the electronic device 100 and the various parts of the entire electronic device 100 being connected by various interfaces and lines. The processor 103 may implement or perform the methods, steps, and logic blocks disclosed in the embodiments of the present application.
In one embodiment, the Memory 102 may be implemented by any type of volatile or non-volatile Memory device or combination thereof, including but not limited to, a Random Access Memory (RAM) 102, a Read Only Memory (ROM) 102, a Static Random Access Memory (SRAM) 102, a Programmable Read Only Memory (PROM) 102, an Erasable Read Only Memory (EPROM) 102, and an electrically Erasable Read Only Memory (EEPROM) 102.
The electronic device 100 may be a mobile phone, a notebook computer, a desktop computer, or an operation system composed of multiple computers. Electronic device 100 may also include more or fewer components than shown in FIG. 1, or have a different configuration than shown in FIG. 1. For example, electronic device 100 may also include input and output devices for human interaction.
Please refer to fig. 2, which is a flowchart illustrating a method for processing ticket data according to an embodiment of the present application, wherein the method can be executed by the electronic device 100 shown in fig. 1, and can be applied in a processing scenario of reimbursement of a medical charging ticket to automatically determine whether a ticket is duplicated, so as to improve efficiency, feedback speed and accuracy of processing the ticket data. The method comprises the following steps:
step S110: and acquiring image data of the bill to be verified.
The image data of the bill to be verified in this step may be a scanned image or a photograph of the medical fee bill or the like. The image data can also be entered by the reimburser through the terminal in real time.
Step S120: and carrying out image recognition on the image data to obtain data information on the bill to be verified.
The basic elements in the image data can be automatically identified through a machine, and information such as characters, marks, symbols and the like in the image data is extracted. The data information may include one or more of an identification code of a bill to be verified, payment information, account information, home hospital information, account information, and a diagnosis date.
In an embodiment, step S120 may first perform automatic recognition by using an image character recognition technology (OCR character technology) to obtain the original data information. And after automatic identification, a prompt for manual verification may be issued. And then receiving a return instruction of manual verification, and finally automatically correcting the original data information according to the return instruction, thereby improving the accuracy of the data information identified in the step, improving the speed of data identification, and improving the efficiency, feedback speed and accuracy of bill data processing.
Step S130: and judging whether the bill to be verified exists in the database or not according to the data information.
In this step, the database may be a pre-established medical database, a local database, or a cloud database. The database stores data in the form of a plurality of tickets that have been entered (or reimbursed), either in the form of images or in the form of text data.
In an embodiment, the step S140 is executed if the data information of the to-be-verified bill obtained in the step S120 is compared with the data stored in the database, and if a bill having the same data as the to-be-verified bill exists in the database.
Step S140: and marking the bill to be verified as a repeated bill.
If the bill with the same data as the bill to be verified exists in the database, the bill to be verified is indicated to be reimbursed, the bill to be verified is forcibly marked as the repeated bill in the step, the case can be transferred to a problem case processing flow and fed back to an insurance company or a service staff for manual processing.
According to the bill data processing method, the image recognition is carried out on the image data of the bill to be verified, so that the data information on the bill to be verified can be extracted quickly, whether the bill to be verified is a repeated bill or not can be judged quickly according to the data information, and the bill data processing efficiency, the feedback speed and the accuracy are improved.
Please refer to fig. 3, which is a flowchart illustrating a method for processing ticket data according to an embodiment of the present application, wherein the method can be executed by the electronic device 100 shown in fig. 1, and can be applied in a processing scenario of reimbursement of a medical charging ticket to automatically determine whether a ticket is duplicated, so as to improve efficiency, feedback speed and accuracy of processing the ticket data. The method comprises the following steps:
step S210: and acquiring image data of the bill to be verified. Please refer to the description of step S110 in the above embodiment for details.
Step S220: inputting the image data into a preset separation model, and outputting a plurality of segmentation areas on the image data.
The preset partition model in this step may be pre-established, and is used for performing the general text line detection and the partition model detection, that is, the image data may be cut according to a plurality of preset partitions (for example, a head of a user including province information, etc.), and each partition area is labeled, so that the step S230 may be facilitated to quickly identify the text attribute corresponding to each partition area according to the label of each partition area.
The separation model may include several types corresponding to the plurality of bill categories, and the step S220 may be pre-selected according to the bill category of the bill to be verified.
In an embodiment, step S220 may further include the following specific implementation steps:
s1: the image data obtained in step S210 is preprocessed, and each image is transformed into an image with a preset size (e.g., 1248 × 800 pixels).
S2: the position of each word line is determined by adopting a word detection algorithm (DB for short) based on deep learning. Converting each image into an image with 1248 × 800 pixels, extracting depth characteristic information by using a CNN (convolutional neural network), predicting a probability map and a threshold map, finally performing self-adaptive binarization on each pixel point of the two maps, obtaining a binarization threshold value by network learning, and calculating the coordinates of a boundary frame by obtaining an approximate binary map.
Step S230: and performing character recognition on the image data according to the segmentation area to obtain data information on the bill to be verified.
The method comprises the following steps of firstly, analyzing and processing image data of each segmentation area by utilizing a character recognition technology (OCR) to recognize character information in the image.
Then, keyword extraction (IE extraction) is assisted using Named Entity Recognition (NER) in NLP (neural-linear Programming), transliteration to neural grammar Programming, subdomain. The Named Entity Recognition (NER) aims to recognize named entities such as names of people, places, organizational structures and the like in the corpus and recognize entities with specific meanings in the text.
And at the same time, quickly identifying the text attribute corresponding to each separation area according to the label of each separation area in the step S230 or the coordinate information in the step S2, and finally integrating to obtain the data information on the bill to be verified, which is favorable for the judgment of the step S240.
Step S240: and judging whether the bill to be verified exists in the database or not according to the data information. Please refer to the description of step S130 in the above embodiment for details. If the to-be-verified bill exists in the database, step S250 is executed, and if the to-be-verified bill does not exist in the database, step S260 is executed.
Step S250: and marking the bill to be verified as a repeated bill. For details, refer to the description of step S140 in the above embodiment.
Step S260: and storing the bill to be verified in a database.
If the bill with the same data as the bill to be verified does not exist in the database, the bill to be verified is indicated to have not been reimbursed, and the bill to be verified is stored in the database in the step and can be used for being compared with the next bill to be verified, so that the next repeated bill inspection process is facilitated.
After the step, the flow can be normally circulated downwards, and the processes of reimbursement and the like are continuously carried out. Meanwhile, prompt information such as 'repeated ticket check pass' and the like can be sent out.
Please refer to fig. 4, which is a flowchart illustrating a method for processing ticket data according to an embodiment of the present application, wherein the method can be executed by the electronic device 100 shown in fig. 1 and can be applied to a processing scenario of reimbursement of a medical charging ticket to automatically determine whether a ticket is duplicated, so as to improve efficiency, feedback speed and accuracy of processing the ticket data. The method comprises the following steps:
step S301: and acquiring image data of the bill to be verified. Please refer to the description of step S110 in the above embodiment for details.
Step S302: and carrying out image recognition on the image data to obtain data information on the bill to be verified. Please refer to the description of step S120 in the above embodiment for details.
Step S303: and judging whether a first bill set identical to the identification code and the payment information of the bill to be verified exists in the database.
Step S304: and if the first bill set exists in the database, judging whether a first target bill which has the same account information with the bill to be verified exists in the first bill set.
Step S305: and determining that the bill to be verified exists in the database.
Step S306: and marking the bill to be verified as a repeated bill. For details, refer to the description of step S140 in the above embodiment.
Step S307: and judging whether a second target bill which is the same as the identification code of the bill to be verified and the information of the belonging hospital exists in the database.
Step S308: and judging whether a second bill set with the same account information as the bill to be verified exists in the database.
Step S309: and judging whether a third target bill with the same diagnosis and treatment date as the bill to be verified exists in the second bill set.
Step S310: and outputting prompt information.
Step S311: and judging whether a fourth target bill which is the same as the identification code of the bill to be verified exists in the database.
Step S313: and determining that the bill to be verified does not exist in the database.
Step S315: and storing the bill to be verified in a database. For details, refer to the description of step S260 in the above embodiment.
In the above steps S303 to S315, the identification code is a bill number, and the payment information may be a bill amount; the account information is the name of the ticket, i.e., the name of the drawer, and may be the patient. The information of the belonging hospital is a bill hospital; the diagnosis and treatment date can be the date of the doctor seeing the patient, the date of the patient's admission and the date of the patient's discharge. The query parameters such as the identification code, the payment information, the account information, and the diagnosis and treatment date are respectively identified as a set of character strings in step S302.
In the application scene of the medical charging bill, the bill number has uniqueness in the same province, and the design is inconsistent in different provinces, so that the uniqueness may not exist. Therefore, inquiry parameters such as bill sum and the like are added to the rule for judging the repeated bills for multiple verification.
Wherein, steps S303 to S307 may be referred to as a forced ticket checking process, and the steps S305 to S306 are performed by checking mainly using a first determination rule "the ticket is necessarily a duplicate ticket if the ticket number, the ticket amount, and the ticket name are consistent" and a second determination rule "the ticket is necessarily a duplicate ticket if the ticket number and the ticket hospital are consistent"; if neither of the two determination rules is satisfied, the ticket to be verified is preliminarily excluded as a duplicate ticket, but it cannot be said that the ticket is not a duplicate ticket, so the next determination process is performed to execute step S308.
Steps S308 to S313 may be referred to as a reminder ticket checking process, and the third determination rule "if the ticket name, the ticket amount, the date of visit, the date of admission and the date of discharge are consistent, the ticket is likely to be a duplicate ticket" and the fourth determination rule "if the ticket number is consistent, the ticket is likely to be a duplicate ticket" are mainly used for checking, and a ticket satisfying any one of the two determination rules may be a duplicate ticket, and the possibility that the ticket to be checked is a duplicate ticket cannot be completely excluded, and step S310 is executed, and verification and investigation need to be performed manually. If neither of these two decision rules is satisfied, then it can be assumed that the ticket to be verified has been excluded as a duplicate ticket, and steps S312-S313 are performed.
In an embodiment, a forced ticket checking process is performed first, and the database is screened in step S303 according to the "identification code" and the "payment information" of the ticket to be checked, so as to screen out the first ticket set that may include the ticket to be checked.
If the first bill set exists in the database, a query parameter "account information" needs to be added to perform the screening of the step S304, and if the screening of the step S304 can be passed, this indicates that at least one bill which is consistent with the account information, the identification code and the payment information of the bill to be verified exists in the database, and meets the first determination rule, at this time, it may be determined that the bill to be verified is a duplicate bill, and the steps S305 to 306 are performed. If the ticket cannot pass the screening of step S304, the possibility that the ticket to be verified is a duplicate ticket is preliminarily excluded, and the next reminding ticket checking process is performed to execute step S308.
If the first bill set does not exist in the database, 2 query parameters of the identification code and the attribution hospital information need to be replaced to perform the screening in the step S307, if the screening in the step S307 can be passed, this indicates that at least one bill which is consistent with the identification code and the attribution hospital information of the bill to be verified exists in the database, and when the second determination rule is satisfied, the bill to be verified can be determined to be a repeated bill, and the steps S305-306 are executed. If the ticket cannot pass the screening of step S307, the possibility that the ticket to be verified is a duplicate ticket is preliminarily excluded, and the next reminding ticket checking process is performed to execute step S308.
The ticket to be verified passing through the forced ticket checking process can enter the next reminding ticket checking process. And (4) according to the 'account information' of the bill to be verified, screening the database in the step (S308) to screen out a second bill set which possibly comprises the bill to be verified.
If the second bill set exists in the database, a query parameter "diagnosis and treatment date" needs to be added to perform the screening in step S309, if the screening in step S309 can be passed, this indicates that at least one bill which is consistent with the diagnosis and treatment date and the account information of the bill to be verified exists in the database, and a third determination rule is satisfied, at this time, it can be determined that the bill to be verified is possibly a duplicate bill, the verification and the investigation need to be performed manually, step S310 is executed, if the screening in step S309 cannot be passed, it can be considered that the bill to be verified is excluded as the duplicate bill, and steps S312 to S313 are executed.
If the first bill set does not exist in the database, the screening of step S311 needs to be performed by replacing 1 query parameter "identification code", if the screening of step S311 can be passed, which indicates that at least one bill consistent with the identification code of the bill to be verified exists in the database, and the fourth determination rule is satisfied, at this time, it can be determined that the bill to be verified is possibly a duplicate bill, the verification and the investigation need to be performed manually, step S310 is executed, if the screening of step S311 cannot be passed, it can be considered that the bill to be verified is excluded as the duplicate bill, and steps S312 to S313 are executed.
In any of the query and filtering steps, such as step S303, step S304, step S307, step S308, step S309, step S311, etc., the "case status" of the ticket in the required search range may be queried first, and pre-selection may be performed according to the "case status", so as to improve the efficiency of data processing.
The 'case state' is a parameter query and input state of a bill, and for example, some bills input all query parameters including identification codes, payment information, account information, belonging hospital information, account information, diagnosis and treatment dates and the like; some bills only enter individual query parameters. Therefore, according to the inquiry screening conditions of the subsequent steps, the case state of the bill in the search range is firstly inquired, and therefore whether the bill in the search range has the input specified inquiry parameters or not can be pre-selected.
For example, in step S303, it is determined whether a first bill set identical to the identification code and the payment information of the bill to be verified exists in the database, and then in step S303, the case state of the bill stored in the database is firstly queried, the bill in which the identification code and the payment information are simultaneously entered in the database is picked out, and then it is determined whether the first bill set identical to the identification code and the payment information of the bill to be verified exists in the picked-out bill; if the database does not have the bill with the case state meeting the condition, the bill with the identification code and the payment information simultaneously recorded does not exist in the database, and the first bill set does not exist.
Step S304 is to determine whether a first target ticket with the same account information as the ticket to be verified exists in the first ticket set, and if so, the case status of the ticket in the first ticket set is first queried, the ticket with the account information entered in the first ticket set is picked out, and then it is determined whether the first target ticket with the same account information as the ticket to be verified exists in the picked-out ticket; if the first bill set does not have the bill with the case state meeting the condition, the fact that the bill with the account information recorded in the first bill set does not exist, and the first target bill does not exist.
Step S307 is to determine whether a second target ticket identical to the identification code of the ticket to be verified and the information of the home hospital exists in the database, and if yes, the case state of the ticket stored in the database is firstly queried, the ticket in which the identification code and the information of the home hospital are simultaneously entered in the database is picked out, and then it is determined whether a second target ticket identical to the identification code of the ticket to be verified and the information of the home hospital exists in the picked-out ticket; if the database does not have the bill with the case state meeting the condition, the bill with the identification code and the information of the belonging hospital simultaneously recorded does not exist in the database, and the second target bill does not exist.
Step S308 is to determine whether a second ticket set identical to the account information of the ticket to be verified exists in the database, and then, in step S308, the case status of the ticket stored in the database is firstly queried, the ticket with the account information entered in the database is picked out, and then, whether the second ticket set identical to the account information of the ticket to be verified exists in the picked-out ticket is determined; if the database does not have the bill with the case state meeting the condition, the bill with the account information input into the database does not exist, and the second bill set does not exist.
Step S309 is to determine whether a third target note with the same diagnosis and treatment date as the note to be verified exists in the second note set, and then in step S309, the case state of the note in the second note set is firstly queried, the note with the diagnosis and treatment date entered in the second note set is picked out, and then it is determined whether the third target note with the same diagnosis and treatment date as the note to be verified exists in the picked-out note; if the second bill set does not have the bill with the case state meeting the condition, the second bill set does not have the bill with the diagnosis and treatment date recorded in the second bill set, and the third target bill does not exist.
Step S311 is to determine whether a fourth target bill identical to the identification code of the bill to be verified exists in the database, and then in step S311, the case state of the bills stored in the database is firstly queried, the bills with the identification codes entered in the database are picked out, and then it is determined whether the fourth target bill identical to the identification code of the bill to be verified exists in the picked-out bills; if the database does not have the bill with the case state meeting the condition, the bill with the identification code recorded in the database does not exist, and the fourth target bill does not exist.
In an embodiment, the forced ticket checking process may be implemented as follows:
first, a first judgment rule is utilized to force ticket checking:
and then, forcing ticket checking by using a second judgment rule:
in an embodiment, the reminding ticket checking process may be implemented as follows:
the code check using the third decision rule is as follows:
the check code using the fourth decision rule is as follows:
in summary, the bill data processing method of the application utilizes four judgment rules to perform a forced ticket checking process on the bill to be verified firstly and then perform a reminding ticket checking process on the bill to be verified, so that the ticket checking process is simplified, whether the bill to be verified is a repeated bill or not can be judged quickly, and the accuracy of bill data processing is improved.
Fig. 5 is a schematic structural diagram of a ticket data processing apparatus 200 according to an embodiment of the present application. The apparatus is applicable to the electronic device 100 shown in fig. 1, and includes: an acquisition module 210, a recognition module 220, a judgment module 230, and a marking module 240. The principle relationship of the modules is as follows: the acquiring module 210 is configured to acquire image data of a bill to be verified; the identification module 220 is used for performing image identification on the image data to obtain data information on the bill to be verified; the judging module 230 is configured to judge whether the bill to be verified exists in the database according to the data information; and the marking module 240 is used for marking the bill to be verified as a repeated bill when the bill to be verified exists in the database.
In one embodiment, the identification module 220 is further configured to: inputting image data into a preset separation model, and outputting a plurality of segmentation areas on the image data; and performing character recognition on the image data according to the segmentation area to obtain data information on the bill to be verified.
In one embodiment, the data information includes an identification code of the bill to be verified, payment information and account information; the determining module 230 is further configured to: judging whether a first bill set identical to the identification code and the payment information of the bill to be verified exists in the database; if the first bill set exists in the database, judging whether a first target bill which has the same account information with the bill to be verified exists in the first bill set; and if the first target bill exists in the first bill set, determining that the bill to be verified exists in the database.
In one embodiment, the data information further includes: attribution hospital information of the bill to be verified; the determining module 230 is further configured to: if the first bill set does not exist in the database, judging whether a second target bill which is the same as the identification code of the bill to be verified and the attributive hospital information exists in the database or not; and if the second target bill exists in the database, determining that the bill to be verified exists in the database.
In one embodiment, the data information further includes: account information and diagnosis and treatment date of the bill to be verified; the determining module 230 is further configured to: if the first target bill does not exist in the first bill set or if the second target bill does not exist in the database, judging whether a second bill set with the same account information as the bill to be verified exists in the database or not; if the second bill set exists in the database, judging whether a third target bill which is the same as the diagnosis and treatment date of the bill to be verified exists in the second bill set; and if the third target bill exists in the database, outputting prompt information.
In one embodiment, the determining module 230 is further configured to: if the third target bill does not exist in the database, judging whether a fourth target bill which is the same as the identification code of the bill to be verified exists in the database or not; and if the fourth target bill exists in the database, outputting prompt information.
In one embodiment, the determining module 230 is further configured to: and if the third target bill does not exist in the database or if the fourth target bill does not exist in the database, determining that the bill to be verified does not exist in the database.
For a detailed description of the above bill data processing device 200, please refer to the description of the related method steps in the above embodiment.
Embodiments of the present application further provide a non-transitory computer-readable storage medium, including: the program, when executed on the electronic device 100, causes the electronic device 100 to perform all or part of the flow of the method in the above-described embodiments. The storage medium may be a magnetic Disk, an optical Disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a Flash Memory 102(Flash Memory), a Hard Disk Drive (Hard Disk Drive, abbreviated as HDD), a Solid State Drive (SSD), or the like. The storage medium may also include a combination of memories 102 of the sort described above.
In the embodiments provided in the present application, the disclosed apparatus and method can be implemented in other ways. The apparatus embodiments described above are merely illustrative, and for example, the flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s).
In some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
In addition, functional modules in the embodiments of the present application may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. The above description is only a preferred embodiment of the present application, and is only for the purpose of illustrating the technical solutions of the present application, and not for the purpose of limiting the present application. Any modification, equivalent replacement, improvement or the like, which would be obvious to one of ordinary skill in the art and would be within the spirit and principle of the present application, should be included within the scope of the present application.
Claims (10)
1. A bill data processing method is characterized in that: the method comprises the following steps:
acquiring image data of a bill to be verified;
carrying out image recognition on the image data to obtain data information on the bill to be verified;
judging whether the bill to be verified exists in a database or not according to the data information;
and if the bill to be verified exists in the database, marking the bill to be verified as a repeated bill.
2. The method according to claim 1, wherein the image recognition of the image data to obtain the data information on the bill to be verified comprises:
inputting the image data into a preset separation model, and outputting a plurality of segmentation areas on the image data;
and performing character recognition on the image data according to the segmentation area to obtain data information on the bill to be verified.
3. The method of claim 1, wherein the data information includes an identification code of the ticket to be verified, payment information, and account information;
the judging whether the bill to be verified exists in a database according to the data information comprises the following steps:
judging whether a first bill set identical to the identification code and the payment information of the bill to be verified exists in the database;
if the first bill set exists in the database, judging whether a first target bill which is the same as the account information of the bill to be verified exists in the first bill set;
and if the first target bill exists in the first bill set, determining that the bill to be verified exists in the database.
4. The method of claim 3, wherein the data information further comprises: attribution hospital information of the bill to be verified;
the judging whether the bill to be verified exists in the database according to the data information further comprises:
if the first bill set does not exist in the database, judging whether a second target bill which is the same as the identification code of the bill to be verified and the attribution hospital information exists in the database or not;
and if the second target bill exists in the database, determining that the bill to be verified exists in the database.
5. The method of claim 4, wherein the data information further comprises: the account information and diagnosis and treatment date of the bill to be verified; the method further comprises the following steps:
if the first target bill does not exist in the first bill set or if the second target bill does not exist in the database, judging whether a second bill set identical to the account information of the bill to be verified exists in the database or not;
if the second bill set exists in the database, judging whether a third target bill which is the same as the diagnosis and treatment date of the bill to be verified exists in the second bill set;
and if the third target bill exists in the database, outputting prompt information.
6. The method of claim 5, further comprising:
if the third target bill does not exist in the database, judging whether a fourth target bill which is the same as the identification code of the bill to be verified exists in the database or not;
and if the fourth target bill exists in the database, outputting prompt information.
7. The method of claim 6, further comprising:
and if the third target bill does not exist in the database or if the fourth target bill does not exist in the database, determining that the bill to be verified does not exist in the database.
8. A bill data processing apparatus characterized by: the method comprises the following steps:
the acquisition module is used for acquiring image data of a bill to be verified;
an identification module: the image recognition module is used for carrying out image recognition on the image data to obtain data information on the bill to be verified;
the judging module is used for judging whether the bill to be verified exists in a database or not according to the data information;
and the marking module is used for marking the bill to be verified as a repeated bill when the bill to be verified exists in the database.
9. An electronic device, comprising:
a memory to store a computer program;
a processor to execute the computer program to implement the method of any one of claims 1 to 7.
10. A non-transitory computer-readable storage medium, comprising: program which, when run by an electronic device, causes the electronic device to perform the method of any one of claims 1 to 7.
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| Application Number | Priority Date | Filing Date | Title |
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| CN202111095245.3A CN113807256A (en) | 2021-09-17 | 2021-09-17 | Bill data processing method and device, electronic equipment and storage medium |
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| CN202111095245.3A CN113807256A (en) | 2021-09-17 | 2021-09-17 | Bill data processing method and device, electronic equipment and storage medium |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115169335A (en) * | 2022-09-07 | 2022-10-11 | 深圳高灯计算机科技有限公司 | Invoice data calibration method and device, computer equipment and storage medium |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115169335A (en) * | 2022-09-07 | 2022-10-11 | 深圳高灯计算机科技有限公司 | Invoice data calibration method and device, computer equipment and storage medium |
| CN115169335B (en) * | 2022-09-07 | 2023-01-13 | 深圳高灯计算机科技有限公司 | Invoice data calibration method and device, computer equipment and storage medium |
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