WO2020179055A1 - Voucher analysis device, accounting system, voucher analysis method, and voucher analysis program - Google Patents

Voucher analysis device, accounting system, voucher analysis method, and voucher analysis program Download PDF

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Publication number
WO2020179055A1
WO2020179055A1 PCT/JP2019/009077 JP2019009077W WO2020179055A1 WO 2020179055 A1 WO2020179055 A1 WO 2020179055A1 JP 2019009077 W JP2019009077 W JP 2019009077W WO 2020179055 A1 WO2020179055 A1 WO 2020179055A1
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Prior art keywords
issuer
area
voucher
unit
journal
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PCT/JP2019/009077
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French (fr)
Japanese (ja)
Inventor
森啓太郎
小嶋勇志
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ファーストアカウンティング株式会社
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Priority to JP2019513461A priority Critical patent/JP6646308B1/en
Priority to PCT/JP2019/009077 priority patent/WO2020179055A1/en
Publication of WO2020179055A1 publication Critical patent/WO2020179055A1/en

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    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06QINFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q40/00Finance; Insurance; Tax strategies; Processing of corporate or income taxes

Definitions

  • the present invention relates to a voucher analysis device, an accounting processing system, a voucher analysis method, and a voucher analysis program that can estimate the issuer of a voucher from image data of a voucher such as an invoice or a receipt.
  • tax accountants, accountants, and bookkeepers read the information described in the voucher one by one as accounting processing of vouchers, and enter journal entry elements such as date, business partner, amount, etc. in the ledger and respond to the journal entry elements.
  • the journal entry was made by empirically judging the account that was created.
  • the voucher data captured by a mobile terminal or the like is analyzed by the journal element extracting means and the journal element information is extracted as text format data.
  • the character information group recorded in the image data of the voucher such as a receipt is recognized and converted into text data composed of items such as a user ID, a date, a purchaser name, and a purchased product name. ..
  • a product group corresponding to the product name included in the journal element information converted into text data is obtained from the product master, and a recommended journal is indicated using the mapping table corresponding to the product group (paragraph of Patent Document 1). See 0118 to paragraph 0128).
  • journal element is extracted from the voucher using the OCR device in the above-mentioned Patent Document 1
  • the display format of the voucher is various, and the information described in the voucher is also various, so the accuracy of extracting the journal element is high. It's not easy to do. For example, when a plurality of company names are described in one voucher, it may not be possible to determine which company name is the issuer of the voucher.
  • invoices and receipts often have a company seal or the like stamped on the part where the issuer information is written.
  • foreign matter may be mixed in when reading the voucher, the voucher itself may be scratched, the voucher may be a copy type and the characters may be faint, or the voucher may contain handwritten characters.
  • the journal element is extracted from the voucher using the OCR device, the information of the issuer is partially lost and extracted, and the issuer cannot be accurately recognized. If the publisher cannot be accurately recognized in this way, there is a problem that humans must eventually confirm the voucher and work efficiency cannot be improved.
  • the present invention has been made to solve such a problem, and an object of the present invention is to be able to recognize the voucher issuer more quickly and accurately from the voucher image data, and the voucher issuer. It is intended to provide a voucher analysis device, an accounting processing system, a voucher analysis method, and a voucher analysis program capable of improving the efficiency of the input work.
  • the voucher analysis apparatus uses an area identification unit for identifying a journal element area including a journal element from image data of the voucher, and a journal element area identified by the area identification unit.
  • An issuer element extraction unit that extracts an issuer element indicating the issuer of the trademark, a storage unit that stores supplier information, an issuer element extracted by the issuer element extraction unit, and a storage unit that stores the supplier information.
  • An issuer estimation unit that estimates the issuer of the voucher by collating with the obtained supplier information.
  • the issuer estimation unit issues the voucher according to the degree of agreement between the issuer element extracted by the issuer element extraction unit and the business partner information stored in the storage unit.
  • the origin may be estimated.
  • the area identification unit identifies an area of a seal imprint from the image data of the voucher, identifies an issuer area that includes an issuer element and overlaps the area of the imprint, and issues the issue.
  • the source element extraction unit may extract the issuer element from the issuer area identified by the area identification unit.
  • the area identification unit can identify, as the journal entry element area, a FAX information area in which outgoing information is described when FAX is received from image data of the voucher, and the issuer element extraction is performed.
  • the unit can extract the issuer element from the FAX information area identified by the area identification unit, and the issuer estimation unit includes the issuer element extracted from the FAX information area in the storage unit. You may collate with the stored supplier information.
  • the area identification unit can identify an account information area in which bank account information is described as the journal element area, and the issuer element extraction unit can be used by the area identification unit.
  • the issuer element can be extracted from the identified account information area, and the issuer estimation unit includes the issuer element extracted from the account information area and is associated with the business partner information stored in the storage unit. You may collate.
  • the area identification unit can identify the number information area in which the unique number information peculiar to the business partner is described as the journal element area
  • the issuer element extraction unit can identify the number information area.
  • the issuer element can be extracted from the unique number information area identified by the area identification unit, and the issuer estimation unit stores the issuer element including the issuer element extracted from the unique number information area in the storage unit. You may collate with supplier information.
  • the area identification unit can identify the e-mail address information area in which the e-mail address information is described as the journal element area
  • the issuer element extraction unit can identify the area identification unit.
  • the issuer element can be extracted from the e-mail address information area identified by, and the issuer estimation unit includes the issuer element extracted from the e-mail address information area and is stored in the storage unit. You may collate with information.
  • the accounting system according to the present invention, the voucher analysis device described above, a journalizing unit that outputs an account item corresponding to the journalizing element of the voucher including the issuer element, Equipped with.
  • the voucher analysis method is such that a computer identifies an area of a seal imprint from image data of the voucher, and an issuer including an issuer element that overlaps the area of the imprint.
  • An area identification step for identifying an area an issuer element extraction step for extracting the issuer element from the issuer area identified by the area identification step, and an issuer element extracted by the issuer element extraction step.
  • the issuer estimation step of estimating the issuer of the voucher by collating with the business partner information stored in the storage unit is executed.
  • the computer is made to execute the above-mentioned voucher analysis method.
  • the issuer of the voucher can be recognized more quickly and accurately from the image data of the voucher, and the efficiency of the input work of the issuer of the voucher can be improved.
  • FIG. 1 is a system configuration diagram showing an accounting processing system including a voucher analysis unit according to an embodiment of the present invention, and the configuration of the present embodiment will be described based on the same diagram.
  • the accounting processing system 1 accounts for each device on the user side and accounting processing on the accounting processing service provider side via a communication network 2 such as the Internet and a VPN (Virtual Private Network). It is configured to be connected to the device 10. Although only one user is shown in FIG. 1 for simplification of description, the accounting processing device 10 can be connected to a plurality of users via the communication network 2.
  • a communication network 2 such as the Internet and a VPN (Virtual Private Network).
  • the user is, for example, an expert such as a tax accountant and an accountant, or a corporation or an individual who directly performs accounting processing, and has at least the reading device 3 and the information terminal 4.
  • the reading device 3 is an optical device such as a scanner or a camera, and is a device that can capture a voucher as image data.
  • the wording "voucher" in the present embodiment and the claims means receipts and receipts, other receipts, invoices, delivery notes, bankbooks of financial institutions, documents that are proof of financial transfer in accounting, electronic Transaction information using IC cards such as money shall also be included.
  • the information terminal 4 is, for example, a personal computer (hereinafter referred to as a PC), a mobile terminal such as a smartphone, a tablet PC, and a mobile phone, and is a terminal capable of displaying at least web information.
  • a PC personal computer
  • a mobile terminal such as a smartphone, a tablet PC, and a mobile phone
  • the user can acquire the image data of the voucher by the reading device 3 and transmit it to the accounting processing device 10 by the information terminal 4, and can also receive the information from the accounting processing device 10.
  • the reading device 3 and the information terminal 4 are shown as separate bodies in FIG. 1, the reading device 3 and the information terminal 4 may be integrated as in a mobile terminal with a camera. Further, the user does not have to own the reading device 3, and for example, the image data of the voucher read by an external reading device may be acquired via an e-mail or a web.
  • the accounting processing service provider (hereinafter, also simply referred to as a service provider) is a business operator that provides accounting processing services by so-called cloud computing, and is a person who manages the accounting processing device 10.
  • the accounting processing device 10 has one or more servers (computers) that execute journalizing processing based on a program, and functionally mainly extracts journal entry elements including a voucher issuer element from voucher image data.
  • the voucher analyzing section 11 (certificate analyzing device) for performing the analysis according to the above
  • the display section 12 for displaying the analysis result of the journalizing element
  • the journalizing element confirming section 13 for confirming the analyzed journalizing element
  • It has a journal unit 14 that performs automatic journalizing, and a learning system 15 that generates AI such as an area identification AI and a journal AI.
  • the voucher analysis unit 11 has an image acquisition unit 20, an area identification unit 21, a journal element extraction unit 22 (issuer element extraction unit), a supplier database 23 (storage unit), and an issuer estimation unit 24. ing.
  • the image acquisition unit 20 has a function of receiving the image data of the voucher read by the reading device 3 of the user. Although not shown, the image acquisition unit 20 may have a storage means for storing received image data.
  • the area identification unit 21 has an image analysis function of identifying the journal element area corresponding to the journal element from the image data of the voucher acquired by the image acquisition unit 20.
  • Journal elements include, for example, date, amount, business partner, description (including proviso and product name), business source (including address), and the corresponding numbers, letters, graphics (for example, logo mark, imprint, and other companies). There is a identifiable pattern) and the appearance of the voucher (eg, the size and color of a passbook or receipt).
  • the area identification unit 21 can specify the numbers before and after the characters such as "date”, “year”, “month”, “day”, and the symbols such as "/”.
  • the symbols such as “ ⁇ ” and the numerical parts before and after or above and below the characters such as “amount of money”, “payment”, “deposit”, “balance” and “yen”.
  • the character parts before and after the characters such as "Co., Ltd.”, “Co., Ltd.”, "(F)", logo mark, telephone number, FAX number, and voucher appearance, and these It is possible to identify the part corresponding to the company name or personal name based on the information.
  • the abstract it is possible to specify the character part following the character such as "however”.
  • the part of the character before the character such as "sama" can be specified.
  • journal elements are not limited to this, and the numbers, letters, and figures used to extract the journal elements are not limited to this.
  • the quantity may be included as a journal entry factor, and if information such as the names and number of attendees is stated, the attendees and the number of attendees. May be included as a journal entry element.
  • a unique number (corporate number, business office number) set to identify each company may be extracted.
  • Other unique numbers of business partners that can identify business partners in this way include transaction codes, billing numbers, quotation numbers, order numbers, and the like.
  • the area identification unit 21 specifies an area including a part corresponding to a date, transaction details, payment, deposit, balance, and the like.
  • the part corresponding to the journal entry element is specified. If the image data is a scan of a receipt or receipt, specify the area including the date part, logo or company name part, amount part, and proviso part to identify the part corresponding to the journal element. To do.
  • the area identification unit 21 identifies such a journal element area by the area identification AI.
  • the area identification AI uses teacher data (learning data) consisting of image data of various vouchers and data indicating each journal element area in the image data, and uses machine learning in the image data. It is an AI learned to identify an area including a part corresponding to a journal element from.
  • the area identification unit 21 in the present embodiment identifies the area of the imprint in the image data of the voucher having the imprint indicating the issuer such as an invoice or a receipt, and further identifies the area of the imprint in the image data. It overlaps with the area and has a function to identify the issuer area including the issuer element.
  • the identification of such a seal imprint area and the issuer area may be performed by image analysis other than AI, or may be performed by area identification AI.
  • area identification AI in the learning system 15, the teacher data (learning data) consisting of the image data of the voucher including the imprint and the data indicating the imprint area and the issuer area in the image data is used.
  • the area identification AI is generated by learning to identify the seal imprint area and the issuing area from the image data by machine learning.
  • the imprint is mainly a company seal for a corporation, a shop name seal for a sole proprietor, etc., and may be a circle seal in addition to a square seal.
  • the issuer element corresponds to the business partner in the above journal element, and specifically, the company name, personal name (store name), address, telephone number, fax number, e-mail address, department name, person in charge, Etc. information is included.
  • the area identification unit 21 in the present embodiment can identify the fax information area in which the starting information such as the fax number of the sender is described at the time of receiving the fax from the image data of the voucher.
  • the FAX information area is mainly printed on the end of the voucher (for example, header or footer), and the area identification unit 21 may identify the area by area identification AI or image analysis, and regardless of these, the end of the voucher.
  • the part area may be set as the FAX information area for identification.
  • the journal element extraction unit 22 has a character recognition function of outputting the journal elements in the area corresponding to each journal element identified by the area identification unit 21 as text. For example, the journal element extraction unit 22 recognizes numbers in the date part and the amount part, outputs the text of the date and the amount, and recognizes the characters in the part corresponding to the business partner and the part corresponding to the description. To output the text of the supplier or summary.
  • the character recognition function may use the conventional OCR technology, or in the learning system 15, the teacher data (learning data) including the journal element portion in the image data and the text corresponding to the journal element is used. Alternatively, a text-based AI learned to output the text of the journal element by machine learning may be used.
  • journal element extraction unit 22 in the present embodiment refers to the image data of the voucher having the imprint indicating the issuer, such as an invoice or a receipt, from the issuer area identified by the area identification unit 21. Extract elements. That is, the journal entry element extraction unit 22 extracts, as an issuer element, a text in the issuer area that overlaps with the seal imprint area.
  • journal entry element extraction unit 22 extracts the issuer element while excluding the seal imprint area in the issuer area. Therefore, the issuer element that partially overlaps the imprint area is extracted in a partially missing state.
  • journal entry element extraction unit 22 in this embodiment can also extract the issuer element from the FAX information area.
  • the issuer element included in the FAX information area is mainly the FAX number of the issuer (FAX sender).
  • the business partner database 23 (hereinafter, the database is referred to as "DB") is a so-called business partner master, and the company name, personal name (store name), address, telephone number, fax number, and mail corresponding to the issuer element.
  • Business partner information such as address, department name, person in charge, etc. is stored.
  • the issuer estimation unit 24 collates the issuer element extracted by the journal element extraction unit 22 with the supplier information stored in the supplier DB 23, estimates the issuer of the voucher, and outputs the estimation result. It has a function. Note that the issuer estimation unit 24 may output only the estimation result, or may output the estimation result together with other journal elements extracted by the journal element extraction unit 22.
  • the issuer estimation unit 24 estimates the issuer of the voucher according to the degree of agreement between the extracted issuer element and the supplier information of the supplier DB23. That is, even if the issuer element is partially missing, the supplier information having a higher degree of agreement than the other supplier information is estimated as the issuer of the voucher.
  • the estimation result is not necessarily limited to one issuer, and a plurality of issuer candidates may be listed in accordance with the rank having a high degree of coincidence. Further, the estimation result may be accompanied by information on the degree of matching indicated by, for example, a percentage display, in addition to the supplier information.
  • the issuer estimation unit 24 can collate with the supplier information including the issuer element extracted from the FAX information area. Since the issuer information of the FAX information area is located at the end of the voucher, it is unlikely to be lost due to imprint or the like, and a higher degree of matching can be obtained.
  • the display unit 12 is, for example, a display of the accounting processing device 10, and has a function of displaying the journal elements extracted by the journal element extraction unit 22 and the estimation result of the issuer estimated by the issuer estimation unit 24. There is.
  • the journal element and the estimation result of the issuer are transmitted not only to the display unit 12 of the accounting processing device 10 but also to the user's information terminal 4, so that the user can also check the extraction result of the journal element and the estimation result of the issuer. You can
  • the journal element determination unit 13 has a function of performing a confirmation process for determining the journal element displayed on the display unit 12 by the service provider or the program for determining the journal element. That is, in the journal element determination unit 13, for example, the person in charge on the service provider side confirms the journal element displayed on the display unit 12 and the estimation result of the issuer, and confirms the journal element without any problem as it is. , For the problematic journal element, correct it and then perform the confirmation operation. Further, when a plurality of issuer candidates are listed as the estimation result of the issuer estimation unit 24, the person in charge selects and determines one issuer candidate in the journal element determination unit 13.
  • the journal unit 14 has a function of outputting an account item corresponding to the journal element determined by the journal element determination unit 13.
  • the output of the account item corresponding to this journal element is performed by, for example, the journal AI.
  • the journal AI is an automatic journal AI that has learned in advance to output an account item for a journal element by machine learning in the learning system 15.
  • the account items output by the journalizing unit 14 are transmitted to the user's information terminal 4 as the journalizing result together with the journalizing elements.
  • the learning system 15 has a function of learning the area identification AI, the journal AI, and the text AI, and supplying the learned AI. Specifically, the learning system 15 generates journal entry element extraction AI by performing machine learning (so-called deep learning) based on teacher data (learning data) including the voucher image data and journal entry elements included in the image data. .. Further, the learning system 15 generates a journal AI by performing machine learning based on teacher data (learning data) composed of a journal element and an account item corresponding to the journal element.
  • the voucher analysis unit 11 extracts journal elements from the voucher image data and converts them into texts, and particularly identifies the imprint area for the voucher including the imprint. , The issuer area that overlaps with the imprint area is identified, the issuer element is extracted from the issuer area, and the issuer of the voucher is estimated by collating with the customer information of the customer DB23.
  • the voucher analysis starts when the image acquisition unit 20 receives the voucher image data from the user.
  • step S1 the voucher analysis unit 11 identifies a region corresponding to a journal element from the voucher image data by the region identification unit 21.
  • step S2 the journal element extraction unit 22 extracts the journal elements in the identified area and converts them into text.
  • step S3 the voucher analysis unit 11 determines whether or not the imprint region is identified in the image data of the voucher by the region identification unit 21. If the determination result is false (No), that is, if the received image data is a voucher without imprint, the process proceeds to step S4.
  • step S4 the voucher analysis unit 11 outputs the text of the journal element extracted by the journal element extraction unit 22 to the display unit 12 and ends the routine.
  • step S3 determines whether the voucher has an imprint such as an invoice or a receipt. If the determination result in step S3 is true (Yes), that is, if the voucher has an imprint such as an invoice or a receipt, the process proceeds to step S5.
  • step S5 the voucher analysis unit 11 identifies the imprint area in the image data of the voucher by the area identification unit 21, and identifies the issuer area that overlaps with the imprint area (area identification step).
  • step S6 the journal element extraction unit 22 extracts the issuer element from the issuer area (issuer element extraction step).
  • step S7 the voucher analysis unit 11 determines whether or not the fax information is described in the FAX information area in the image data of the voucher identified by the area identification unit 21. If the determination result is false (No), the process proceeds to step S9, and if the determination result is true (Yes), the process proceeds to step S8.
  • step S8 the journal element extraction unit 22 extracts the issuing source element (for example, FAX number) in the FAX information area, and the process proceeds to step S9.
  • the issuing source element for example, FAX number
  • step S9 the voucher analysis unit 11 collates the issuer element extracted in steps S6 and S8 with the supplier information stored in the supplier DB 23 by the issuer estimation unit 24 (issuer). Estimation process).
  • step S10 the voucher analysis unit 11 outputs the supplier information having a high degree of agreement with the extracted issuer element to the display unit 12 as the issuer estimation result by the issuer estimation unit 24 (issuer estimation step). ..
  • step S10 the voucher analysis unit 11 also outputs the text of the journal element other than the publisher element extracted by the journal element extraction unit 22 to the display unit 12 as in step S4, and the routine To finish.
  • the voucher analysis unit 11 extracts and displays the journal element including the publisher element from each image data by executing the routine every time the image acquisition unit 20 acquires the image data of the voucher. It can be output to the unit 12.
  • FIG. 3 an explanatory diagram for estimating the issuer from the invoice including the imprint is shown, and a specific procedure for estimating the issuer from the invoice will be described based on the diagram.
  • the area identification unit 21 identifies the area corresponding to the journal element as shown by the dotted line. For example, an area containing a "invoice” indicating the type of voucher, a "subject” corresponding to a description, a “billing date” corresponding to a date, and a “total amount” corresponding to an amount is identified.
  • the voucher analysis unit 11 identifies the imprint area S by the area identification unit 21 and identifies the issuer area A overlapping with the imprint area S. Further, the journal element extraction unit 22 extracts the publisher element in the publisher area A as text. In the case of FIG. 3, the issuer elements extracted here are “ABCDEFG Co., Ltd.”, “ ⁇ 100-100”, “Kasumigaseki, Chiyoda-ku, Tokyo”, “TEL:03-1234”, and “FAX:03”. -9876-5432".
  • the voucher analysis unit 11 identifies the FAX information area F by the area identification unit 21, and the journal element extraction unit 22 prints the FAX information area F in the FAX information area F, ie, “FAX number: 03-9876-”. 5432” is extracted as text.
  • the issuer estimation unit 24 collates these extracted issuer elements with the supplier information stored in the supplier DB 23, and outputs the supplier with a high degree of matching as the issuer estimation result. Since the issuer estimation result is based on the supplier information stored in the supplier DB 23, it is output as information without any loss, and the information is utilized for journal entry by, for example, the journal unit 14.
  • the journal element area including the journal element is identified from the image data of the voucher, and the issuer indicating the issuer of the voucher is issued from the journal element area.
  • the issuer can be estimated by extracting the original element and collating it with the supplier information of the supplier DB23.
  • the issuer is estimated according to the degree of matching between the issuer element and the supplier information, so that, for example, imprints, foreign substances, handwritten characters, etc. are covered with the issuer information, or the voucher itself is damaged. , Even if the characters of the issuer information are faint and the issuer information is partially missing, it is possible to estimate and output the accurate issuer element that compensates for the loss from the supplier information.
  • the issuer element is included even when a plurality of company names are described. It is possible to quickly recognize the area to be covered.
  • the voucher analysis unit 11 identifies the fax information area in the image data of the voucher by the area identification unit 21, and extracts the issuer information from the fax information area to more reliably estimate the issuer. it can.
  • the accounting processing system 1 can realize an accurate journal entry.
  • the invoice shown in FIG. 3 has been described as an example, but the voucher is not limited to the invoice, and can be similarly applied to a voucher including other imprints such as a receipt. ..
  • journalizing unit 14 uses the journalizing AI to perform automatic journalizing, but the journalizing may be performed by an automatic journalizing program that does not use AI.
  • the issuer information extracted from the issuer area is included in the issuer element extracted from the FAX information area to be compared with the supplier information, but the issuer information is not limited to this.
  • Other information stored in the business partner DB may be used instead of the information stored in the business partner DB.
  • the voucher analysis unit may identify the account information area B including the bank account information of the transfer destination shown in FIG. 3, and extract the bank account information of the account information area as the issuer information.
  • the voucher analysis unit may identify the number information area including the billing number (invoice No.) shown in FIG. 3, and extract the billing number of the number information area as the issuer information.
  • Such number information is not limited to the billing number, and may be an estimate number if it is a quotation and an order number if it is a purchase order.
  • numbers such as a corporate number, a business establishment number, and a transaction code may be used as issuer information.
  • the voucher analysis unit may identify the mail address information area including the mail address information and extract the mail address information of the mail address information area as the issuer information.
  • the issuer can be more accurately estimated.

Abstract

A voucher analysis unit 11 of an accounting system 1 is provided with: a region identification unit 21 which identifies an imprint region from image data of a voucher, and identifies a region that overlaps the imprint region and that corresponds to a journal entry element, such as an issuer region including an issuer element; a journal entry element extraction unit 22 which extracts journal entry elements including the issuer element from the issuer region identified by the region identification unit 21; a client database 23 which stores client information; and an issuer estimation unit 24 which compares the issuer element extracted by the journal entry element extraction unit 22 with the client information stored in the client database 23 to estimate the issuer of the voucher.

Description

証憑解析装置、会計処理システム、証憑解析方法、証憑解析プログラムVoucher analysis device, accounting system, voucher analysis method, voucher analysis program
 本発明は請求書や領収書等の証憑の画像データから証憑の発行元を推定可能な証憑解析装置、会計処理システム、証憑解析方法、証憑解析プログラムに関する。 The present invention relates to a voucher analysis device, an accounting processing system, a voucher analysis method, and a voucher analysis program that can estimate the issuer of a voucher from image data of a voucher such as an invoice or a receipt.
 従来、証憑の会計処理として、税理士や会計士、簿記担当者が証憑に記載の情報を一件一件読み取り、例えば日付、取引先、金額等の仕訳要素を帳簿に入力し、当該仕訳要素に対応した勘定科目を経験的に判断して仕訳の入力を行っていた。 Conventionally, tax accountants, accountants, and bookkeepers read the information described in the voucher one by one as accounting processing of vouchers, and enter journal entry elements such as date, business partner, amount, etc. in the ledger and respond to the journal entry elements. The journal entry was made by empirically judging the account that was created.
 このように、証憑を人間が一件一件読み取って仕訳を行うのでは作業効率が悪い上、仕訳の精度は担当者の経験に依存するところが大きく、仕訳の精度にばらつきが生じるという問題があった。 In this way, if a human reads the voucher one by one and makes a journal entry, the work efficiency is poor, and the accuracy of the journal entry largely depends on the experience of the person in charge, and there is a problem that the accuracy of the journal entry varies. It was
 そこで、OCR(Optical Character Reader)装置を用いて、証憑の内容を電子データとして読み取り、インターネットを介して仕訳解析センターシステムに送信するだけで、その証憑に示される簿記上の取引についての仕訳の結果をユーザが参照することが可能となるいわゆるクラウド型の会計処理システムが開発されている(特許文献1参照)。 Therefore, by using an OCR (Optical Character Reader) device, the contents of the voucher can be read as electronic data and transmitted to the journal analysis center system via the Internet. A so-called cloud-type accounting system has been developed that allows users to refer to (see Patent Document 1).
 詳しくは、特許文献1に記載された技術では、携帯端末等で撮影した証憑データを仕訳要素抽出手段によって解析して仕訳要素情報をテキスト形式のデータとして抽出している。具体的には、レシート等の証憑の画像データに記録されている文字情報群を認識し、ユーザID、日付、購入先名称、購入商品名等の項目から構成されるテキストデータに変換している。そして、テキストデータに変換した仕訳要素情報に含まれる商品名に対応する商品グループを商品マスタから得て、その商品グループに対応するマッピングテーブルを用いて推奨仕訳を示している(特許文献1の段落0118~段落0128参照)。 Specifically, in the technique described in Patent Document 1, the voucher data captured by a mobile terminal or the like is analyzed by the journal element extracting means and the journal element information is extracted as text format data. Specifically, the character information group recorded in the image data of the voucher such as a receipt is recognized and converted into text data composed of items such as a user ID, a date, a purchaser name, and a purchased product name. .. Then, a product group corresponding to the product name included in the journal element information converted into text data is obtained from the product master, and a recommended journal is indicated using the mapping table corresponding to the product group (paragraph of Patent Document 1). See 0118 to paragraph 0128).
特開2014-235484号公報JP, 2014-235484, A
 上記特許文献1では、OCR装置を用いて証憑から仕訳要素を抽出しているが、証憑の表示形式は様々であり、証憑に記載されている情報も様々であるため仕訳要素の抽出精度を高くすることは容易ではない。例えば、一つの証憑内に複数の会社名が記載されていると、どの会社名が当該証憑の発行元であるのか、判別できない場合がある。 Although the journal element is extracted from the voucher using the OCR device in the above-mentioned Patent Document 1, the display format of the voucher is various, and the information described in the voucher is also various, so the accuracy of extracting the journal element is high. It's not easy to do. For example, when a plurality of company names are described in one voucher, it may not be possible to determine which company name is the issuer of the voucher.
 一方で、請求書や領収書には発行元の情報が記載されている部分には、重ねて社印等が押印されている場合が多い。また、証憑読み取り時に異物が混入したり、証憑自体に傷が付いていたり、証憑が複写式で文字がかすれていたり、証憑に手書き文字が含まれている場合がある。このような場合、OCR装置を用いて証憑から仕訳要素を抽出した際に、発行元の情報が一部欠損して抽出されてしまい、正確に発行元を認識することができない。このように発行元が正確に認識できない場合は、結局人間が証憑を確認しなければならず、作業効率の改善が図られないという問題がある。 On the other hand, invoices and receipts often have a company seal or the like stamped on the part where the issuer information is written. In addition, foreign matter may be mixed in when reading the voucher, the voucher itself may be scratched, the voucher may be a copy type and the characters may be faint, or the voucher may contain handwritten characters. In such a case, when the journal element is extracted from the voucher using the OCR device, the information of the issuer is partially lost and extracted, and the issuer cannot be accurately recognized. If the publisher cannot be accurately recognized in this way, there is a problem that humans must eventually confirm the voucher and work efficiency cannot be improved.
 本発明はこのような問題点を解決するためになされたもので、その目的とするところは、証憑の画像データからより迅速かつ正確に証憑の発行元を認識することができ、証憑の発行元の入力作業の効率を向上させることができる証憑解析装置、会計処理システム、証憑解析方法、及び証憑解析プログラムを提供することにある。 The present invention has been made to solve such a problem, and an object of the present invention is to be able to recognize the voucher issuer more quickly and accurately from the voucher image data, and the voucher issuer. It is intended to provide a voucher analysis device, an accounting processing system, a voucher analysis method, and a voucher analysis program capable of improving the efficiency of the input work.
 上記した目的を達成するために、本発明に係る証憑解析装置は、証憑の画像データから仕訳要素を含む仕訳要素領域を識別する領域識別部と、前記領域識別部により識別された仕訳要素領域から前記商標の発行元を示す発行元要素を抽出する発行元要素抽出部と、取引先情報を記憶する記憶部と、前記発行元要素抽出部により抽出された発行元要素と、前記記憶部に記憶された取引先情報とを照合して前記証憑の発行元を推定する発行元推定部と、を備える。 In order to achieve the above-mentioned object, the voucher analysis apparatus according to the present invention uses an area identification unit for identifying a journal element area including a journal element from image data of the voucher, and a journal element area identified by the area identification unit. An issuer element extraction unit that extracts an issuer element indicating the issuer of the trademark, a storage unit that stores supplier information, an issuer element extracted by the issuer element extraction unit, and a storage unit that stores the supplier information. An issuer estimation unit that estimates the issuer of the voucher by collating with the obtained supplier information.
 上述の証憑解析装置において、前記発行元推定部は、前記発行元要素抽出部により抽出された発行元要素と、前記記憶部に記憶された取引先情報との一致度合いに応じて前記証憑の発行元を推定してもよい。 In the voucher analysis device described above, the issuer estimation unit issues the voucher according to the degree of agreement between the issuer element extracted by the issuer element extraction unit and the business partner information stored in the storage unit. The origin may be estimated.
 また、上述の証憑解析装置において、前記領域識別部は、前記証憑の画像データから印影の領域を識別し、当該印影の領域と重なっており発行元要素を含む発行元領域を識別し、前記発行元要素抽出部は、前記領域識別部により識別された発行元領域から前記発行元要素を抽出してもよい。 Further, in the above-described voucher analysis device, the area identification unit identifies an area of a seal imprint from the image data of the voucher, identifies an issuer area that includes an issuer element and overlaps the area of the imprint, and issues the issue. The source element extraction unit may extract the issuer element from the issuer area identified by the area identification unit.
 また、上述の証憑解析装置において、前記領域識別部は、前記仕訳要素領域として、前記証憑の画像データからFAX受信時に発信情報が記載されるFAX情報領域を識別可能であり、前記発行元要素抽出部は、前記領域識別部により識別されたFAX情報領域から前記発行元要素を抽出可能であり、前記発行元推定部は、前記FAX情報領域から抽出した発行元要素を含めて、前記記憶部に記憶された取引先情報との照合を行ってもよい。 Further, in the above-described voucher analysis apparatus, the area identification unit can identify, as the journal entry element area, a FAX information area in which outgoing information is described when FAX is received from image data of the voucher, and the issuer element extraction is performed. The unit can extract the issuer element from the FAX information area identified by the area identification unit, and the issuer estimation unit includes the issuer element extracted from the FAX information area in the storage unit. You may collate with the stored supplier information.
 また、上述の証憑解析装置において、前記領域識別部は、前記仕訳要素領域として、銀行口座情報が記載される口座情報領域を識別可能であり、前記発行元要素抽出部は、前記領域識別部により識別された口座情報領域から前記発行元要素を抽出可能であり、前記発行元推定部は、前記口座情報領域から抽出した発行元要素を含めて、前記記憶部に記憶された取引先情報との照合を行ってもよい。 Further, in the voucher analysis device described above, the area identification unit can identify an account information area in which bank account information is described as the journal element area, and the issuer element extraction unit can be used by the area identification unit. The issuer element can be extracted from the identified account information area, and the issuer estimation unit includes the issuer element extracted from the account information area and is associated with the business partner information stored in the storage unit. You may collate.
 また、上述の証憑解析装置において、前記領域識別部は、前記仕訳要素領域として、取引先特有の固有番号情報が記載される番号情報領域を識別可能であり、前記発行元要素抽出部は、前記領域識別部により識別された固有番号情報領域から前記発行元要素を抽出可能であり、前記発行元推定部は、前記固有番号情報領域から抽出した発行元要素を含めて、前記記憶部に記憶された取引先情報との照合を行ってもよい。 Further, in the voucher analysis device described above, the area identification unit can identify the number information area in which the unique number information peculiar to the business partner is described as the journal element area, and the issuer element extraction unit can identify the number information area. The issuer element can be extracted from the unique number information area identified by the area identification unit, and the issuer estimation unit stores the issuer element including the issuer element extracted from the unique number information area in the storage unit. You may collate with supplier information.
 また、上述の証憑解析装置において、前記領域識別部は、前記仕訳要素領域として、メールアドレス情報が記載されるメールアドレス情報領域を識別可能であり、前記発行元要素抽出部は、前記領域識別部により識別されたメールアドレス情報領域から前記発行元要素を抽出可能であり、前記発行元推定部は、前記メールアドレス情報領域から抽出した発行元要素を含めて、前記記憶部に記憶された取引先情報との照合を行ってもよい。 Further, in the voucher analysis device described above, the area identification unit can identify the e-mail address information area in which the e-mail address information is described as the journal element area, and the issuer element extraction unit can identify the area identification unit. The issuer element can be extracted from the e-mail address information area identified by, and the issuer estimation unit includes the issuer element extracted from the e-mail address information area and is stored in the storage unit. You may collate with information.
 また、上記した目的を達成するために、本発明に係る会計処理システムは、上述の証憑解析装置と、前記発行元要素を含む前記証憑の仕訳要素に応じた勘定科目を出力する仕訳部と、を備える。 Further, in order to achieve the above object, the accounting system according to the present invention, the voucher analysis device described above, a journalizing unit that outputs an account item corresponding to the journalizing element of the voucher including the issuer element, Equipped with.
 また、上記した目的を達成するために、本発明に係る証憑解析方法は、コンピュータにより、証憑の画像データから印影の領域を識別し、当該印影の領域と重なっており発行元要素を含む発行元領域を識別する領域識別工程と、前記領域識別工程により識別された発行元領域から前記発行元要素を抽出する発行元要素抽出工程と、前記発行元要素抽出工程により抽出された発行元要素と、記憶部に記憶された取引先情報とを照合して前記証憑の発行元を推定する発行元推定工程と、を実行する。 In order to achieve the above-mentioned object, the voucher analysis method according to the present invention is such that a computer identifies an area of a seal imprint from image data of the voucher, and an issuer including an issuer element that overlaps the area of the imprint. An area identification step for identifying an area, an issuer element extraction step for extracting the issuer element from the issuer area identified by the area identification step, and an issuer element extracted by the issuer element extraction step. The issuer estimation step of estimating the issuer of the voucher by collating with the business partner information stored in the storage unit is executed.
 また、上記した目的を達成するために、証憑解析プログラムでは、コンピュータに、上述の証憑解析方法を実行させる。 Further, in order to achieve the above-mentioned purpose, in the voucher analysis program, the computer is made to execute the above-mentioned voucher analysis method.
 上記手段を用いる本発明によれば、証憑の画像データからより迅速かつ正確に証憑の発行元を認識することができ、証憑の発行元の入力作業の効率を向上させることができる。 According to the present invention using the above means, the issuer of the voucher can be recognized more quickly and accurately from the image data of the voucher, and the efficiency of the input work of the issuer of the voucher can be improved.
本発明の一実施形態に係る証憑解析部を含む会計処理システムを示したシステム構成図である。It is a system block diagram which showed the accounting processing system including the voucher analysis part which concerns on one Embodiment of this invention. 証憑解析部により実行される証憑解析の流れを示したフローチャートである。It is a flowchart which showed the flow of the voucher analysis executed by the voucher analysis unit. 印影を含む請求書から発行元を推定する説明図である。It is explanatory drawing which estimates the issuer from the invoice including the imprint.
 以下、本発明の一実施形態を図面に基づき説明する。 Hereinafter, an embodiment of the present invention will be described with reference to the drawings.
 図1は本発明の一実施形態に係る証憑解析部を含む会計処理システムを示したシステム構成図であり、同図に基づき本実施形態の構成について説明する。 FIG. 1 is a system configuration diagram showing an accounting processing system including a voucher analysis unit according to an embodiment of the present invention, and the configuration of the present embodiment will be described based on the same diagram.
 図1に示すように、本実施形態に係る会計処理システム1は、インターネット、VPN(Virtual Private Network)等の通信網2を介して、ユーザ側の各装置と会計処理サービス提供者側の会計処理装置10とが接続されて構成されている。なお、説明の簡略化のため図1では一人のユーザのみを示しているが、会計処理装置10は通信網2を介して複数のユーザと接続可能である。 As shown in FIG. 1, the accounting processing system 1 according to the present embodiment accounts for each device on the user side and accounting processing on the accounting processing service provider side via a communication network 2 such as the Internet and a VPN (Virtual Private Network). It is configured to be connected to the device 10. Although only one user is shown in FIG. 1 for simplification of description, the accounting processing device 10 can be connected to a plurality of users via the communication network 2.
 ユーザは、例えば税理士及び会計士等の専門家であったり、直接会計処理を行う法人や個人等であり、少なくとも読取装置3と情報端末4を有している。 The user is, for example, an expert such as a tax accountant and an accountant, or a corporation or an individual who directly performs accounting processing, and has at least the reading device 3 and the information terminal 4.
 読取装置3は、例えばスキャナ又はカメラ等の光学機器であり、証憑を画像データとして取り込める装置である。なお、本実施形態及び特許請求の範囲における「証憑」という文言は、領収書やレシート、その他の受領書、請求書、納品書、金融機関の通帳、会計上金銭授受の証明となる書類、電子マネー等のICカードによる取引情報も含むものとする。 The reading device 3 is an optical device such as a scanner or a camera, and is a device that can capture a voucher as image data. In addition, the wording "voucher" in the present embodiment and the claims means receipts and receipts, other receipts, invoices, delivery notes, bankbooks of financial institutions, documents that are proof of financial transfer in accounting, electronic Transaction information using IC cards such as money shall also be included.
 情報端末4は、例えばパーソナルコンピュータ(以下、PCという)や、スマートフォン、タブレットPC、及び携帯電話のような携帯端末であり、少なくともweb情報を表示可能な端末である。 The information terminal 4 is, for example, a personal computer (hereinafter referred to as a PC), a mobile terminal such as a smartphone, a tablet PC, and a mobile phone, and is a terminal capable of displaying at least web information.
 ユーザは、読取装置3により証憑の画像データを取得して、情報端末4により会計処理装置10に送信可能であるとともに、会計処理装置10からの情報を受信可能である。なお、図1では読取装置3と情報端末4とが別体のように示しているが、カメラ付きの携帯端末のように読取装置3と情報端末4とが一体であってもよい。また、ユーザ自身が読取装置3を所有している必要はなく、例えば外部の読取装置により読み取った証憑の画像データをメールやwebを介して取得してもよい。 The user can acquire the image data of the voucher by the reading device 3 and transmit it to the accounting processing device 10 by the information terminal 4, and can also receive the information from the accounting processing device 10. Although the reading device 3 and the information terminal 4 are shown as separate bodies in FIG. 1, the reading device 3 and the information terminal 4 may be integrated as in a mobile terminal with a camera. Further, the user does not have to own the reading device 3, and for example, the image data of the voucher read by an external reading device may be acquired via an e-mail or a web.
 一方、会計処理サービス提供者(以下、単にサービス提供者ともいう)は、いわゆるクラウドコンピューティングにより会計処理サービスを提供する事業者であり、会計処理装置10を管理する者である。 On the other hand, the accounting processing service provider (hereinafter, also simply referred to as a service provider) is a business operator that provides accounting processing services by so-called cloud computing, and is a person who manages the accounting processing device 10.
 会計処理装置10は、プログラムに基づき仕訳処理を実行する1又は複数のサーバ(コンピュータ)を有し、機能的には主に、証憑の画像データから証憑の発行元要素を含む仕訳要素を抽出して解析を行う証憑解析部11(証憑解析装置)と、仕訳要素の解析結果を表示する表示部12と、解析した仕訳要素を確定する仕訳要素確定部13と、確定された仕訳要素に基づいて自動仕訳を行う仕訳部14と、領域識別AI及び仕訳AI等のAIを生成する学習システム15と、を有している。 The accounting processing device 10 has one or more servers (computers) that execute journalizing processing based on a program, and functionally mainly extracts journal entry elements including a voucher issuer element from voucher image data. Based on the confirmed journalizing element, the voucher analyzing section 11 (certificate analyzing device) for performing the analysis according to the above, the display section 12 for displaying the analysis result of the journalizing element, the journalizing element confirming section 13 for confirming the analyzed journalizing element It has a journal unit 14 that performs automatic journalizing, and a learning system 15 that generates AI such as an area identification AI and a journal AI.
 さらに、証憑解析部11は、画像取得部20、領域識別部21、仕訳要素抽出部22(発行元要素抽出部)、取引先データベース23(記憶部)、発行元推定部24と、を有している。 Further, the voucher analysis unit 11 has an image acquisition unit 20, an area identification unit 21, a journal element extraction unit 22 (issuer element extraction unit), a supplier database 23 (storage unit), and an issuer estimation unit 24. ing.
 画像取得部20は、ユーザの読取装置3により読み取った証憑の画像データを受信する機能を有している。なお、画像取得部20は、図示しないが受信した画像データを保存する記憶手段を有していてもよい。 The image acquisition unit 20 has a function of receiving the image data of the voucher read by the reading device 3 of the user. Although not shown, the image acquisition unit 20 may have a storage means for storing received image data.
 領域識別部21は、画像取得部20において取得した証憑の画像データから仕訳要素に対応する仕訳要素領域を識別する画像解析機能を有している。 The area identification unit 21 has an image analysis function of identifying the journal element area corresponding to the journal element from the image data of the voucher acquired by the image acquisition unit 20.
 仕訳要素としては、例えば日付、金額、取引先、摘要(但し書き、商品名含む)、取引元(宛名含む)があり、これらに対応する数字、文字、図形(例えばロゴマーク、印影、その他企業を特定可能な図柄)、及び証憑の外観(例えば通帳や領収書の大きさ、色)がある。 Journal elements include, for example, date, amount, business partner, description (including proviso and product name), business source (including address), and the corresponding numbers, letters, graphics (for example, logo mark, imprint, and other companies). There is a identifiable pattern) and the appearance of the voucher (eg, the size and color of a passbook or receipt).
 領域識別部21は、例えば日付については、「日付」「年」「月」「日」等の文字や「/」等の記号の前後や上下の数字部分を特定可能である。金額については「¥」等の記号や「金額」「支払い」「預り」「残高」「円」等の文字の前後や上下の数字部分を特定可能である。また、取引先については、「株式会社」「(株)」「(カ)」等の文字の前後の文字部分や、ロゴマーク、電話番号、FAX番号、証憑の外観を特定して、これらの情報に基づく会社名や個人名に対応する部分を特定可能である。摘要については、「但」等の文字に続く文字部分を特定可能である。取引元については、「様」等の文字の前にある文字の部分を特定可能である。 For example, for a date, the area identification unit 21 can specify the numbers before and after the characters such as "date", "year", "month", "day", and the symbols such as "/". Regarding the amount of money, it is possible to specify the symbols such as “¥” and the numerical parts before and after or above and below the characters such as “amount of money”, “payment”, “deposit”, “balance” and “yen”. For business partners, specify the character parts before and after the characters such as "Co., Ltd.", "Co., Ltd.", "(F)", logo mark, telephone number, FAX number, and voucher appearance, and these It is possible to identify the part corresponding to the company name or personal name based on the information. As for the abstract, it is possible to specify the character part following the character such as "however". For the trading source, the part of the character before the character such as "sama" can be specified.
 なお、仕訳要素はこれに限られるものではなく、また仕訳要素の抽出に用いる数字、文字、図形もこれに限られるものではない。例えば、証憑に、購入品の数量が記載されている場合には数量を仕訳要素として含めてもよいし、同席者の名前や人数等の情報が記載されている場合には、同席者及び人数を仕訳要素として含めてもよい。また、各企業を特定するために設定された固有の番号(法人番号、事業所番号)を抽出してもよい。このように取引先を特定可能な取引先の固有の番号としては、この他にも取引コード、請求番号、見積番号、発注番号等がある。 Note that the journal elements are not limited to this, and the numbers, letters, and figures used to extract the journal elements are not limited to this. For example, if the voucher contains the quantity of purchased items, the quantity may be included as a journal entry factor, and if information such as the names and number of attendees is stated, the attendees and the number of attendees. May be included as a journal entry element. In addition, a unique number (corporate number, business office number) set to identify each company may be extracted. Other unique numbers of business partners that can identify business partners in this way include transaction codes, billing numbers, quotation numbers, order numbers, and the like.
 具体的には、領域識別部21は、入力された画像データが通帳をスキャンしたものである場合は、日付、取引内容、支払い、預り、残高等に対応した部分を含む領域を指定することで仕訳要素に対応する部分の特定を行う。また、画像データがレシートや領収書をスキャンしたものである場合は、日付部分、ロゴや会社名の部分、金額部分、但し書き部分を含む領域を指定することで仕訳要素に対応する部分の特定を行う。 Specifically, when the input image data is a scan of a passbook, the area identification unit 21 specifies an area including a part corresponding to a date, transaction details, payment, deposit, balance, and the like. The part corresponding to the journal entry element is specified. If the image data is a scan of a receipt or receipt, specify the area including the date part, logo or company name part, amount part, and proviso part to identify the part corresponding to the journal element. To do.
 領域識別部21は、このような仕訳要素領域の識別を領域識別AIにより行う。領域識別AIは、学習システム15において、各種証憑の画像データと、その画像データ内における各仕訳要素領域を示したデータとからなる教師データ(学習用データ)を用いて、機械学習により画像データ内から仕訳要素に対応する部分を含む領域を識別することを学習したAIである。 The area identification unit 21 identifies such a journal element area by the area identification AI. In the learning system 15, the area identification AI uses teacher data (learning data) consisting of image data of various vouchers and data indicating each journal element area in the image data, and uses machine learning in the image data. It is an AI learned to identify an area including a part corresponding to a journal element from.
 特に本実施形態における領域識別部21は、請求書や領収書のように発行元を示す印影がある証憑の画像データに対して、当該画像データ内における印影の領域を識別し、さらに当該印影の領域と重なっており発行元要素を含む発行元領域を識別する機能を有している。 In particular, the area identification unit 21 in the present embodiment identifies the area of the imprint in the image data of the voucher having the imprint indicating the issuer such as an invoice or a receipt, and further identifies the area of the imprint in the image data. It overlaps with the area and has a function to identify the issuer area including the issuer element.
 このような印影の領域の識別及び発行元領域の識別は、AI以外の画像解析により行ってもよいし、領域識別AIにより行ってもよい。領域識別AIの場合、学習システム15において、印影を含む証憑の画像データと、その画像データ内における印影の領域及び発行元領域を示したデータとからなる教師データ(学習用データ)を用いて、機械学習により画像データ内から印影の領域と発行元領域を識別することを学習させて領域識別AIを生成する。 The identification of such a seal imprint area and the issuer area may be performed by image analysis other than AI, or may be performed by area identification AI. In the case of the area identification AI, in the learning system 15, the teacher data (learning data) consisting of the image data of the voucher including the imprint and the data indicating the imprint area and the issuer area in the image data is used. The area identification AI is generated by learning to identify the seal imprint area and the issuing area from the image data by machine learning.
 なお、印影は、主に法人における社印や個人事業主における屋号印等であり角印の他、丸印であってもよい。また、発行元要素は、上記仕訳要素における取引先に該当し、具体的には企業名、個人名(屋号名)、住所、電話番号、FAX番号、メールアドレス、担当部署名、担当者名、等の情報が含まれる。 Note that the imprint is mainly a company seal for a corporation, a shop name seal for a sole proprietor, etc., and may be a circle seal in addition to a square seal. In addition, the issuer element corresponds to the business partner in the above journal element, and specifically, the company name, personal name (store name), address, telephone number, fax number, e-mail address, department name, person in charge, Etc. information is included.
 さらに、本実施形態における領域識別部21は、証憑の画像データからFAX受信時に発信元のFAX番号等の発進情報が記載されるFAX情報領域を識別可能である。当該FAX情報領域は主に証憑の端部(例えばヘッダー又はフッター)に印字され、領域識別部21は領域識別AI又は画像解析により当該領域を識別してもよいし、これらに関係なく証憑の端部領域をFAX情報領域と設定して識別してもよい。 Further, the area identification unit 21 in the present embodiment can identify the fax information area in which the starting information such as the fax number of the sender is described at the time of receiving the fax from the image data of the voucher. The FAX information area is mainly printed on the end of the voucher (for example, header or footer), and the area identification unit 21 may identify the area by area identification AI or image analysis, and regardless of these, the end of the voucher. The part area may be set as the FAX information area for identification.
 仕訳要素抽出部22は、領域識別部21により識別された各仕訳要素に対応した領域内の仕訳要素をテキストとして出力する文字認識機能を有している。例えば、仕訳要素抽出部22は、日付部分や金額部分においては数字を認識して年月日や金額のテキストを出力し、取引先に対応する部分や摘要に対応する部分においては文字を認識して取引先や摘要のテキストを出力する。文字認識機能は、従来のOCR技術を用いてもよいし、学習システム15において、画像データ内の仕訳要素部分と、その仕訳要素に対応するテキストととからなる教師データ(学習用データ)を用いて、機械学習により仕訳要素のテキストを出力することを学習したテキスト化AIを用いてもよい。 The journal element extraction unit 22 has a character recognition function of outputting the journal elements in the area corresponding to each journal element identified by the area identification unit 21 as text. For example, the journal element extraction unit 22 recognizes numbers in the date part and the amount part, outputs the text of the date and the amount, and recognizes the characters in the part corresponding to the business partner and the part corresponding to the description. To output the text of the supplier or summary. The character recognition function may use the conventional OCR technology, or in the learning system 15, the teacher data (learning data) including the journal element portion in the image data and the text corresponding to the journal element is used. Alternatively, a text-based AI learned to output the text of the journal element by machine learning may be used.
 特に本実施形態における仕訳要素抽出部22は、請求書や領収書のように発行元を示す印影がある証憑の画像データに対しては、領域識別部21により識別された発行元領域から発行元要素を抽出する。つまり、仕訳要素抽出部22は、印影の領域と重なっている発行元領域内にあるテキストを発行元要素として抽出する。 In particular, the journal element extraction unit 22 in the present embodiment refers to the image data of the voucher having the imprint indicating the issuer, such as an invoice or a receipt, from the issuer area identified by the area identification unit 21. Extract elements. That is, the journal entry element extraction unit 22 extracts, as an issuer element, a text in the issuer area that overlaps with the seal imprint area.
 なお、仕訳要素抽出部22は、発行元領域内における印影の領域内は除外して、発行元要素を抽出する。そのため、印影の領域と一部重なっている発行元要素については一部欠損した状態で抽出されることとなる。 Note that the journal entry element extraction unit 22 extracts the issuer element while excluding the seal imprint area in the issuer area. Therefore, the issuer element that partially overlaps the imprint area is extracted in a partially missing state.
 また、本実施形態における仕訳要素抽出部22は、FAX情報領域からも発行元要素を抽出可能である。FAX情報領域に含まれる発行元要素は主に発行元(FAX発信者)のFAX番号である。 Further, the journal entry element extraction unit 22 in this embodiment can also extract the issuer element from the FAX information area. The issuer element included in the FAX information area is mainly the FAX number of the issuer (FAX sender).
 取引先データベース23(以下、データベースを「DB」と表記する)は、いわゆる取引先マスタであり、発行元要素に対応する企業名、個人名(屋号名)、住所、電話番号、FAX番号、メールアドレス、担当部署名、担当者名、等の取引先情報が記憶されている。 The business partner database 23 (hereinafter, the database is referred to as "DB") is a so-called business partner master, and the company name, personal name (store name), address, telephone number, fax number, and mail corresponding to the issuer element. Business partner information such as address, department name, person in charge, etc. is stored.
 発行元推定部24は、仕訳要素抽出部22により抽出された発行元要素と、取引先DB23に記憶された取引先情報とを照合して証憑の発行元を推定し、当該推定結果を出力する機能を有している。なお、発行元推定部24は、推定結果のみを出力してもよいし、推定結果を上記仕訳要素抽出部22において抽出された他の仕訳要素とともに出力してもよい。 The issuer estimation unit 24 collates the issuer element extracted by the journal element extraction unit 22 with the supplier information stored in the supplier DB 23, estimates the issuer of the voucher, and outputs the estimation result. It has a function. Note that the issuer estimation unit 24 may output only the estimation result, or may output the estimation result together with other journal elements extracted by the journal element extraction unit 22.
 具体的には発行元推定部24は、抽出された発行元要素と取引先DB23の取引先情報との一致度合いに応じて証憑の発行元を推定する。つまり、一部欠損した発行元要素であっても、他の取引先情報に比べて一致度合いの高い取引先情報を、当該証憑の発行元として推定する。推定結果は、必ずしも1つの発行元に限られず、一致度合いの高い順位に応じて複数の発行元候補を挙げてもよい。また、推定結果には、取引先情報とともに、例えばパーセント表示等で示した一致度合いの情報を付加してもよい。 Specifically, the issuer estimation unit 24 estimates the issuer of the voucher according to the degree of agreement between the extracted issuer element and the supplier information of the supplier DB23. That is, even if the issuer element is partially missing, the supplier information having a higher degree of agreement than the other supplier information is estimated as the issuer of the voucher. The estimation result is not necessarily limited to one issuer, and a plurality of issuer candidates may be listed in accordance with the rank having a high degree of coincidence. Further, the estimation result may be accompanied by information on the degree of matching indicated by, for example, a percentage display, in addition to the supplier information.
 また、発行元推定部24は、FAX情報領域から抽出した発行元要素を含めて、取引先情報との照合を行うことが可能である。FAX情報領域の発行元情報は証憑の端部に位置するため、印影等で欠損する可能性が低く、より高い一致度合いを得ることが可能である。 Further, the issuer estimation unit 24 can collate with the supplier information including the issuer element extracted from the FAX information area. Since the issuer information of the FAX information area is located at the end of the voucher, it is unlikely to be lost due to imprint or the like, and a higher degree of matching can be obtained.
 表示部12は、例えば会計処理装置10のディスプレイであり、仕訳要素抽出部22により抽出された仕訳要素、及び発行元推定部24により推定された発行元の推定結果を表示する機能を有している。なお、仕訳要素や発行元の推定結果は、会計処理装置10の表示部12だけでなく、ユーザの情報端末4に送信し、ユーザも仕訳要素の抽出結果や発行元の推定結果を確認できるようにしてもよい。 The display unit 12 is, for example, a display of the accounting processing device 10, and has a function of displaying the journal elements extracted by the journal element extraction unit 22 and the estimation result of the issuer estimated by the issuer estimation unit 24. There is. The journal element and the estimation result of the issuer are transmitted not only to the display unit 12 of the accounting processing device 10 but also to the user's information terminal 4, so that the user can also check the extraction result of the journal element and the estimation result of the issuer. You can
 次に、仕訳要素確定部13は、サービス提供者又は仕訳要素確定用のプログラムにより、表示部12に表示された仕訳要素を確定させる確定処理を行う機能を有している。つまり、仕訳要素確定部13は、例えばサービス提供者側の担当者が表示部12に表示された仕訳要素や発行元の推定結果を確認して、問題のない仕訳要素についてはそのまま確定操作を行い、問題のある仕訳要素については修正作業を行った上で確定操作を行う。また、発行元推定部24の推定結果として、複数の発行元候補が挙げられた場合には、当該仕訳要素確定部13において、担当者が一つの発行元候補を選択して確定する。 Next, the journal element determination unit 13 has a function of performing a confirmation process for determining the journal element displayed on the display unit 12 by the service provider or the program for determining the journal element. That is, in the journal element determination unit 13, for example, the person in charge on the service provider side confirms the journal element displayed on the display unit 12 and the estimation result of the issuer, and confirms the journal element without any problem as it is. , For the problematic journal element, correct it and then perform the confirmation operation. Further, when a plurality of issuer candidates are listed as the estimation result of the issuer estimation unit 24, the person in charge selects and determines one issuer candidate in the journal element determination unit 13.
 仕訳部14は、仕訳要素確定部13により確定された仕訳要素に応じた勘定科目を出力する機能を有している。この仕訳要素に応じた勘定科目の出力は、例えば仕訳AIにより行う。仕訳AIは、学習システム15において、予め機械学習により仕訳要素に対する勘定科目を出力することを学習した自動仕訳のAIである。当該仕訳部14において出力された勘定科目は、仕訳要素とともに、仕訳結果としてユーザの情報端末4に送信される。 The journal unit 14 has a function of outputting an account item corresponding to the journal element determined by the journal element determination unit 13. The output of the account item corresponding to this journal element is performed by, for example, the journal AI. The journal AI is an automatic journal AI that has learned in advance to output an account item for a journal element by machine learning in the learning system 15. The account items output by the journalizing unit 14 are transmitted to the user's information terminal 4 as the journalizing result together with the journalizing elements.
 学習システム15は、上述した領域識別AI、仕訳AI、テキスト化AI等を学習させ、学習済みのAIを供給する機能を有している。詳しくは、学習システム15は、証憑の画像データと当該画像データに含まれる仕訳要素からなる教師データ(学習用データ)に基づき機械学習(いわゆるディープラーニング)させることで、仕訳要素抽出AIを生成する。また、学習システム15は、仕訳要素と当該仕訳要素に対応する勘定科目からなる教師データ(学習用データ)に基づき機械学習させることで、仕訳AIを生成する。 The learning system 15 has a function of learning the area identification AI, the journal AI, and the text AI, and supplying the learned AI. Specifically, the learning system 15 generates journal entry element extraction AI by performing machine learning (so-called deep learning) based on teacher data (learning data) including the voucher image data and journal entry elements included in the image data. .. Further, the learning system 15 generates a journal AI by performing machine learning based on teacher data (learning data) composed of a journal element and an account item corresponding to the journal element.
 このように構成された会計処理装置10は、証憑解析部11において、証憑の画像データから仕訳要素を抽出してテキスト化するとともに、特に印影を含む証憑に対しては、印影の領域を識別し、当該印影の領域と重なった発行元領域を識別して、当該発行元領域から発行元要素を抽出し、取引先DB23の取引先情報と照合することで証憑の発行元を推定する。 In the accounting processing device 10 configured as described above, the voucher analysis unit 11 extracts journal elements from the voucher image data and converts them into texts, and particularly identifies the imprint area for the voucher including the imprint. , The issuer area that overlaps with the imprint area is identified, the issuer element is extracted from the issuer area, and the issuer of the voucher is estimated by collating with the customer information of the customer DB23.
 ここで図2を参照すると、証憑解析部11により実行される証憑解析の流れを示したフローチャートが示されており、以下同フローチャートに沿って、証憑解析方法について詳しく説明する。なお、当該証憑解析は、画像取得部20にてユーザからの証憑の画像データを受信すると、解析をスタートする。 Here, referring to FIG. 2, a flowchart showing the flow of voucher analysis executed by the voucher analysis unit 11 is shown, and the voucher analysis method will be described in detail below with reference to the same flowchart. The voucher analysis starts when the image acquisition unit 20 receives the voucher image data from the user.
 まず、ステップS1として、証憑解析部11は、領域識別部21が証憑の画像データから仕訳要素に対応する領域を識別する。 First, in step S1, the voucher analysis unit 11 identifies a region corresponding to a journal element from the voucher image data by the region identification unit 21.
 そして、ステップS2において、仕訳要素抽出部22が識別された領域内の仕訳要素を抽出してテキスト化する。 Then, in step S2, the journal element extraction unit 22 extracts the journal elements in the identified area and converts them into text.
 また、ステップS3において、証憑解析部11は、領域識別部21により証憑の画像データ内に印影の領域が識別されたか否かを判定する。当該判定結果が偽(No)である場合、即ち受信した画像データが印影のない証憑である場合は、ステップS4に進む。 Further, in step S3, the voucher analysis unit 11 determines whether or not the imprint region is identified in the image data of the voucher by the region identification unit 21. If the determination result is false (No), that is, if the received image data is a voucher without imprint, the process proceeds to step S4.
 ステップS4において、証憑解析部11は、仕訳要素抽出部22により抽出された仕訳要素のテキストを表示部12に出力し当該ルーチンを終了する。 In step S4, the voucher analysis unit 11 outputs the text of the journal element extracted by the journal element extraction unit 22 to the display unit 12 and ends the routine.
 一方、上記ステップS3の判別結果が真(Yes)である場合、即ち、請求書や領収書のように印影がある証憑である場合は、ステップS5に進む。 On the other hand, if the determination result in step S3 is true (Yes), that is, if the voucher has an imprint such as an invoice or a receipt, the process proceeds to step S5.
 ステップS5において、証憑解析部11は、領域識別部21により証憑の画像データ内の印影の領域を識別し、当該印影の領域と重なる発行元領域を識別する(領域識別工程)。 In step S5, the voucher analysis unit 11 identifies the imprint area in the image data of the voucher by the area identification unit 21, and identifies the issuer area that overlaps with the imprint area (area identification step).
 そして、ステップS6において、仕訳要素抽出部22により、発行元領域から発行元要素を抽出する(発行元要素抽出工程)。 Then, in step S6, the journal element extraction unit 22 extracts the issuer element from the issuer area (issuer element extraction step).
 また、ステップS7において、証憑解析部11は、領域識別部21により識別される証憑の画像データ内のFAX情報領域にFAX情報が記載されているか否かを判定する。当該判定結果が偽(No)である場合はステップS9に進み、当該判定結果が真(Yes)である場合は、ステップS8に進む。 Further, in step S7, the voucher analysis unit 11 determines whether or not the fax information is described in the FAX information area in the image data of the voucher identified by the area identification unit 21. If the determination result is false (No), the process proceeds to step S9, and if the determination result is true (Yes), the process proceeds to step S8.
 ステップS8では、仕訳要素抽出部22によりFAX情報領域にある発行元要素(例えばFAX番号)を抽出して、ステップS9に進む。 In step S8, the journal element extraction unit 22 extracts the issuing source element (for example, FAX number) in the FAX information area, and the process proceeds to step S9.
 ステップS9において、証憑解析部11は、発行元推定部24により、ステップS6やステップS8にて抽出された発行元要素と、取引先DB23に記憶された取引先情報との照合を行う(発行元推定工程)。 In step S9, the voucher analysis unit 11 collates the issuer element extracted in steps S6 and S8 with the supplier information stored in the supplier DB 23 by the issuer estimation unit 24 (issuer). Estimation process).
 ステップS10において、証憑解析部11は、発行元推定部24により、抽出された発行元要素と一致度合いの高い取引先情報を発行元の推定結果として表示部12に出力する(発行元推定工程)。なお、証憑解析部11は、当該ステップS10において、ステップS4と同様に、仕訳要素抽出部22により抽出された発行元要素以外の仕訳要素のテキストも一緒に表示部12に出力して、当該ルーチンを終了する。 In step S10, the voucher analysis unit 11 outputs the supplier information having a high degree of agreement with the extracted issuer element to the display unit 12 as the issuer estimation result by the issuer estimation unit 24 (issuer estimation step). .. In step S10, the voucher analysis unit 11 also outputs the text of the journal element other than the publisher element extracted by the journal element extraction unit 22 to the display unit 12 as in step S4, and the routine To finish.
 このように、証憑解析部11は、画像取得部20にて証憑の画像データを取得する毎に、当該ルーチンを実行することで、各画像データから発行元要素を含む仕訳要素を抽出して表示部12に出力可能である。 In this way, the voucher analysis unit 11 extracts and displays the journal element including the publisher element from each image data by executing the routine every time the image acquisition unit 20 acquires the image data of the voucher. It can be output to the unit 12.
 次に図3を参照すると、印影を含む請求書から発行元を推定する説明図が示されており、同図に基づき請求書から発行元を推定する具体的な手順について説明する。 Next, referring to FIG. 3, an explanatory diagram for estimating the issuer from the invoice including the imprint is shown, and a specific procedure for estimating the issuer from the invoice will be described based on the diagram.
 図3の左部に示すような請求書の画像データPが画像取得部20にて受信すると、領域識別部21により、点線で示すような仕訳要素に対応する領域が識別される。例えば、証憑の種類を示す「請求書」や、摘要に該当する「件名」、日付に該当する「請求日」、金額に該当する「合計金額」の仕訳要素を含む領域が識別される。 When the image data P of the invoice as shown in the left part of FIG. 3 is received by the image acquisition unit 20, the area identification unit 21 identifies the area corresponding to the journal element as shown by the dotted line. For example, an area containing a "invoice" indicating the type of voucher, a "subject" corresponding to a description, a "billing date" corresponding to a date, and a "total amount" corresponding to an amount is identified.
 また証憑解析部11は、領域識別部21により印影領域Sを識別し、当該印影領域Sと重なる発行元領域Aを識別する。さらに仕訳要素抽出部22により発行元領域A内にある発行元要素をテキストとして抽出する。当該図3の場合、ここで抽出される発行元要素は、「株式会社ABCDEFG」、「〒100-100」、「東京都千代田区霞が関」、「TEL:03-1234-」、「FAX:03-9876-5432」である。 Further, the voucher analysis unit 11 identifies the imprint area S by the area identification unit 21 and identifies the issuer area A overlapping with the imprint area S. Further, the journal element extraction unit 22 extracts the publisher element in the publisher area A as text. In the case of FIG. 3, the issuer elements extracted here are “ABCDEFG Co., Ltd.”, “〒100-100”, “Kasumigaseki, Chiyoda-ku, Tokyo”, “TEL:03-1234”, and “FAX:03”. -9876-5432".
 さらに、証憑解析部11は、領域識別部21によりFAX情報領域Fを識別し、仕訳要素抽出部22により、FAX情報領域F内に印字された発行元要素である「FAX番号:03-9876-5432」をテキストとして抽出する。 Further, the voucher analysis unit 11 identifies the FAX information area F by the area identification unit 21, and the journal element extraction unit 22 prints the FAX information area F in the FAX information area F, ie, “FAX number: 03-9876-”. 5432” is extracted as text.
 そして、発行元推定部24において、これらの抽出された発行元要素と、取引先DB23に記憶された取引先情報とを照合させ、一致度合いの高い取引先を発行元推定結果として出力する。発行元推定結果は、取引先DB23に記憶された取引先情報に基づくものなので、欠損のない情報として出力され、当該情報は例えば仕訳部14により仕訳に活用される。 Then, the issuer estimation unit 24 collates these extracted issuer elements with the supplier information stored in the supplier DB 23, and outputs the supplier with a high degree of matching as the issuer estimation result. Since the issuer estimation result is based on the supplier information stored in the supplier DB 23, it is output as information without any loss, and the information is utilized for journal entry by, for example, the journal unit 14.
 図3の場合であれば、発行元領域Aより抽出された「株式会社ABCDEFG」、「東京都千代田区霞が関」、「TEL:03-1234-」は、取引先情報に対して一部欠損した情報であるが、他の取引先情報よりも一致度合いが高い。また、発行元領域Aにおいても、FAX情報領域F内において、FAX番号は欠損なく抽出できていることから、特に当該FAX番号により一致度合いは高くなる。 In the case of FIG. 3, "ABCDEFG Co., Ltd.", "Kasumigaseki, Chiyoda-ku, Tokyo" and "TEL: 03-1234-" extracted from the publisher area A were partially missing from the supplier information. Although it is information, the degree of matching is higher than that of other business partner information. Further, even in the issuer area A, since the FAX number can be extracted in the FAX information area F without any loss, the degree of coincidence becomes particularly high depending on the FAX number.
 なお、取引先情報の「株式会社ABCABC」も取引先名、住所、電話番号、FAX番号とも一部一致していることから、例えば当該「株式会社ABCABC」と「株式会社ABCDEFGH」の情報も含めた複数の候補を発行元推定結果として出力してもよい。また、この場合は、各候補の一致度合いをパーセント表示等で定量的に示してもよい。 Since "ABCABC Co., Ltd." in the supplier information also partially matches the supplier name, address, telephone number, and FAX number, for example, the information on the "ABCABC" and "ABCDEFGH" companies is also included. Alternatively, a plurality of candidates may be output as the issuer estimation result. Further, in this case, the degree of agreement of each candidate may be quantitatively indicated by a percentage display or the like.
 以上のように、本実施形態に係る証憑解析部11を含む会計処理システム1では、証憑の画像データから仕訳要素を含む仕訳要素領域を識別し、当該仕訳要素領域から証憑の発行元を示す発行元要素を抽出して、取引先DB23の取引先情報と照合させることで、発行元を推定することができる。 As described above, in the accounting processing system 1 including the voucher analysis unit 11 according to the present embodiment, the journal element area including the journal element is identified from the image data of the voucher, and the issuer indicating the issuer of the voucher is issued from the journal element area. The issuer can be estimated by extracting the original element and collating it with the supplier information of the supplier DB23.
 また、発行元の推定は、発行元要素と取引先情報との一致度合いに応じて行うことで、例えば印影、異物、手書き文字等が発行元情報と被っていたり、証憑自体に傷がついていたり、発行元情報の文字がかすれていたりして、発行元情報が一部欠損している場合でも、取引先情報から欠損を補填した正確な発行元要素を推定し、出力することができる。 In addition, the issuer is estimated according to the degree of matching between the issuer element and the supplier information, so that, for example, imprints, foreign substances, handwritten characters, etc. are covered with the issuer information, or the voucher itself is damaged. , Even if the characters of the issuer information are faint and the issuer information is partially missing, it is possible to estimate and output the accurate issuer element that compensates for the loss from the supplier information.
 特に本実施形態では、印影の領域を識別し、当該印影の領域を重なる発行元領域を識別することで、たとえ複数の会社名が記載されている場合等であっても、発行元要素が含まれる領域を迅速に認識することができる。 In particular, in the present embodiment, by identifying the imprint area and identifying the issuer area that overlaps the imprint area, the issuer element is included even when a plurality of company names are described. It is possible to quickly recognize the area to be covered.
 さらに、証憑解析部11は領域識別部21により証憑の画像データ内のFAX情報領域を識別し、当該FAX情報領域からも発行元情報を抽出することで、より確実に発行元を推定することができる。 Further, the voucher analysis unit 11 identifies the fax information area in the image data of the voucher by the area identification unit 21, and extracts the issuer information from the fax information area to more reliably estimate the issuer. it can.
 このようにして、証憑の画像データからより迅速かつ正確に証憑の発行元を認識することができることで、人手による証憑の発行元の確認や入力を軽減することができ、発行元の入力作業の効率を向上させることができる。 In this way, by being able to recognize the issuer of the voucher more quickly and accurately from the image data of the voucher, it is possible to reduce the manual confirmation and input of the issuer of the voucher, and it is possible to reduce the input work of the issuer. The efficiency can be improved.
 そして、このように正確に推定された発行元要素を含む証憑の仕訳要素に基づいて仕訳部14による仕訳が行われることで、会計処理システム1としては正確な仕訳を実現することができる。 Then, by performing the journal entry by the journal entry unit 14 based on the journal entry element of the voucher including the issuer element accurately estimated in this way, the accounting processing system 1 can realize an accurate journal entry.
 以上で本発明の実施形態の説明を終えるが、本発明の態様はこの実施形態に限定されるものではない。 The above is the description of the embodiment of the present invention, but the aspect of the present invention is not limited to this embodiment.
 例えば、上記実施形態では、図3に示した請求書を例に説明したが、証憑は請求書に限られるものではなく、領収書等のその他の印影を含む証憑にも同様に適用可能である。 For example, in the above embodiment, the invoice shown in FIG. 3 has been described as an example, but the voucher is not limited to the invoice, and can be similarly applied to a voucher including other imprints such as a receipt. ..
 また、上記実施形態では、仕訳部14において仕訳AIを用いて自動仕訳を行っているが、AIを用いない自動仕訳用プログラムにより仕訳を行ってもよい。 Further, in the above embodiment, the journalizing unit 14 uses the journalizing AI to perform automatic journalizing, but the journalizing may be performed by an automatic journalizing program that does not use AI.
 また、上記実施形態では、発行元領域から抽出した発行元情報に、FAX情報領域から抽出した発行元要素を含めて、取引先情報との照合を行っているが、発行元情報はこれに限られるものではなく、取引先DBに記憶される他の情報を用いてもよい。 In the above embodiment, the issuer information extracted from the issuer area is included in the issuer element extracted from the FAX information area to be compared with the supplier information, but the issuer information is not limited to this. Other information stored in the business partner DB may be used instead of the information stored in the business partner DB.
 例えば、証憑解析部が、図3に記載されている振込先の銀行口座情報を含む口座情報領域Bを識別し、当該口座情報領域の銀行口座情報を発行元情報として抽出してもよい。 For example, the voucher analysis unit may identify the account information area B including the bank account information of the transfer destination shown in FIG. 3, and extract the bank account information of the account information area as the issuer information.
 さらに、証憑解析部が、図3に記載されている請求番号(請求書No.)を含む番号情報領域を識別し、当該番号情報領域の請求番号を発行元情報として抽出してもよい。このような番号情報は請求番号に限られず、見積書であれば見積番号、発注書であれば発注番号であってもよい。この他にも、法人番号、事業所番号、取引コード等の番号を発行元情報としてもよい。 Further, the voucher analysis unit may identify the number information area including the billing number (invoice No.) shown in FIG. 3, and extract the billing number of the number information area as the issuer information. Such number information is not limited to the billing number, and may be an estimate number if it is a quotation and an order number if it is a purchase order. In addition to this, numbers such as a corporate number, a business establishment number, and a transaction code may be used as issuer information.
 また、図3の例に限られず、証憑解析部が、メールアドレス情報を含むメールアドレス情報領域を識別し、当該メールアドレス情報領域のメールアドレス情報を発行元情報として抽出してもよい。 Further, not limited to the example of FIG. 3, the voucher analysis unit may identify the mail address information area including the mail address information and extract the mail address information of the mail address information area as the issuer information.
 このように、発行元領域B以外の領域における発行元要素も用いることで、より正確に発行元を推定することができる。 In this way, by using the issuer elements in areas other than issuer area B, the issuer can be more accurately estimated.
 1 会計処理システム
 2 通信網
 3 読取装置
 4 情報端末
 10 会計処理装置
 11 証憑解析部(証憑解析装置)
 12 表示部
 13 仕訳要素確定部
 14 仕訳部
 15 学習システム
 20 画像取得部
 21 領域識別部
 22 仕訳要素抽出部(発行元抽出部)
 23 取引先データベース(記憶部)
 24 発行元推定部
1 Accounting Processing System 2 Communication Network 3 Reading Device 4 Information Terminal 10 Accounting Processing Device 11 Voucher Analysis Unit (Voucher Analysis Device)
12 display section 13 journal element determining section 14 journal section 15 learning system 20 image acquiring section 21 area identifying section 22 journal element extracting section (issuer extracting section)
23 Business partner database (storage unit)
24 Publisher estimation section

Claims (10)

  1.  証憑の画像データから仕訳要素を含む仕訳要素領域を識別する領域識別部と、
     前記領域識別部により識別された仕訳要素領域から前記証憑の発行元を示す発行元要素を抽出する発行元要素抽出部と、
     取引先情報を記憶する記憶部と、
     前記発行元要素抽出部により抽出された発行元要素と、前記記憶部に記憶された取引先情報とを照合して前記証憑の発行元を推定する発行元推定部と、
    を備える証憑解析装置。
    An area identification unit that identifies the journal element area including the journal element from the image data of the voucher,
    An issuer element extraction unit that extracts an issuer element indicating the issuer of the voucher from the journal element region identified by the region identification unit;
    A storage unit that stores customer information,
    An issuer estimator that estimates the issuer of the voucher by comparing the issuer element extracted by the issuer element extractor with the supplier information stored in the storage;
    Voucher analyzer equipped with.
  2.  前記発行元推定部は、前記発行元要素抽出部により抽出された発行元要素と、前記記憶部に記憶された取引先情報との一致度合いに応じて前記証憑の発行元を推定する請求項1記載の証憑解析装置。 Claim 1 that the issuer estimation unit estimates the issuer of the voucher according to the degree of agreement between the issuer element extracted by the issuer element extraction unit and the business partner information stored in the storage unit. The described voucher analyzer.
  3.  前記領域識別部は、前記証憑の画像データから印影の領域を識別し、当該印影の領域と重なっており発行元要素を含む発行元領域を識別し、
     前記発行元要素抽出部は、前記領域識別部により識別された発行元領域から前記発行元要素を抽出する請求項1又は2記載の証憑解析装置。
    The area identification unit identifies an area of a seal imprint from the image data of the voucher, and identifies an issuer area including an issuer element that overlaps the area of the imprint,
    The voucher analysis apparatus according to claim 1, wherein the issuer element extraction unit extracts the issuer element from the issuer area identified by the area identification unit.
  4.  前記領域識別部は、前記仕訳要素領域として、FAX受信時に発信情報が記載されるFAX情報領域を識別可能であり、
     前記発行元要素抽出部は、前記領域識別部により識別されたFAX情報領域から前記発行元要素を抽出可能であり、
     前記発行元推定部は、前記FAX情報領域から抽出した発行元要素を含めて、前記記憶部に記憶された取引先情報との照合を行う請求項1から3のいずれか一項に記載の証憑解析装置。
    The area identification unit can identify the FAX information area in which the transmission information is described at the time of receiving the FAX as the journal element area.
    The issuer element extraction unit can extract the issuer element from the FAX information area identified by the area identification unit.
    The voucher according to any one of claims 1 to 3, wherein the issuer estimation unit compares the issuer element extracted from the FAX information area with the supplier information stored in the storage unit. Analyzer.
  5.  前記領域識別部は、前記仕訳要素領域として、銀行口座情報が記載される口座情報領域を識別可能であり、
     前記発行元要素抽出部は、前記領域識別部により識別された口座情報領域から前記発行元要素を抽出可能であり、
     前記発行元推定部は、前記口座情報領域から抽出した発行元要素を含めて、前記記憶部に記憶された取引先情報との照合を行う請求項1から4のいずれか一項に記載の証憑解析装置。
    The area identification unit can identify an account information area in which bank account information is described as the journal element area.
    The issuer element extraction unit can extract the issuer element from the account information area identified by the area identification unit.
    The voucher according to any one of claims 1 to 4, wherein the issuer estimation unit compares the issuer element extracted from the account information area with the supplier information stored in the storage unit. Analyzer.
  6.  前記領域識別部は、前記仕訳要素領域として、取引先固有の固有番号情報が記載される番号情報領域を識別可能であり、
     前記発行元要素抽出部は、前記領域識別部により識別された固有番号情報領域から前記発行元要素を抽出可能であり、
     前記発行元推定部は、前記固有番号情報領域から抽出した発行元要素を含めて、前記記憶部に記憶された取引先情報との照合を行う請求項1から5のいずれか一項に記載の証憑解析装置。
    The area identification unit can identify a number information area in which unique number information unique to a business partner is described as the journal element area.
    The issuer element extraction unit can extract the issuer element from the unique number information area identified by the area identification unit.
    6. The issuer estimation unit collates with the supplier information stored in the storage unit, including the issuer element extracted from the unique number information area, according to claim 1. Voucher analyzer.
  7.  前記領域識別部は、前記仕訳要素領域として、メールアドレス情報が記載されるメールアドレス情報領域を識別可能であり、
     前記発行元要素抽出部は、前記領域識別部により識別されたメールアドレス情報領域から前記発行元要素を抽出可能であり、
     前記発行元推定部は、前記メールアドレス情報領域から抽出した発行元要素を含めて、前記記憶部に記憶された取引先情報との照合を行う請求項1から6のいずれか一項に記載の証憑解析装置。
    The area identification unit can identify the e-mail address information area in which the e-mail address information is described as the journal element area.
    The issuer element extraction unit can extract the issuer element from the e-mail address information area identified by the area identification unit.
    7. The issuer estimation unit compares the issuer element extracted from the email address information area with the supplier information stored in the storage unit, according to claim 1. Voucher analyzer.
  8.  請求項1から請求項7のいずれか一項に記載の証憑解析装置と、
     前記発行元要素を含む前記証憑の仕訳要素に応じた勘定科目を出力する仕訳部と、を備える会計処理システム。
    The voucher analysis device according to any one of claims 1 to 7.
    And a journalizing section that outputs an account item corresponding to the journalizing element of the voucher including the issuer element.
  9.  コンピュータにより、
     証憑の画像データから仕訳要素を含む仕訳要素領域を識別する領域識別工程と、
     前記領域識別工程により識別された仕訳要素領域から前記証憑の発行元を示す発行元要素を抽出する発行元要素抽出工程と、
     前記発行元要素抽出工程により抽出された発行元要素と、記憶部に記憶された取引先情報とを照合して前記証憑の発行元を推定する発行元推定工程と、
     を実行する証憑解析方法。
    By computer
    An area identification process that identifies the journal element area including the journal element from the image data of the voucher,
    An issuer element extracting step of extracting an issuer element indicating the issuer of the voucher from the journal element area identified by the area identifying step;
    An issuer element extraction step of estimating the issuer element of the voucher by collating the issuer element extracted by the issuer element extraction step with the supplier information stored in the storage unit;
    A voucher analysis method for executing.
  10.  コンピュータに、請求項9に記載の証憑解析方法を実行させるための証憑解析プログラム。

     
    A voucher analysis program for causing a computer to execute the voucher analysis method according to claim 9.

PCT/JP2019/009077 2019-03-07 2019-03-07 Voucher analysis device, accounting system, voucher analysis method, and voucher analysis program WO2020179055A1 (en)

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