WO2021229822A1 - Electronic data determination system, electronic data determination device, electronic data determination method, and electronic data determination program - Google Patents

Electronic data determination system, electronic data determination device, electronic data determination method, and electronic data determination program Download PDF

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Publication number
WO2021229822A1
WO2021229822A1 PCT/JP2020/019556 JP2020019556W WO2021229822A1 WO 2021229822 A1 WO2021229822 A1 WO 2021229822A1 JP 2020019556 W JP2020019556 W JP 2020019556W WO 2021229822 A1 WO2021229822 A1 WO 2021229822A1
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Prior art keywords
image
image data
unit
electronic data
reading method
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PCT/JP2020/019556
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French (fr)
Japanese (ja)
Inventor
啓太郎 森
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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 JP2020527118A priority Critical patent/JP6835382B1/en
Priority to PCT/JP2020/019556 priority patent/WO2021229822A1/en
Priority to JP2021008089A priority patent/JP2021179968A/en
Publication of WO2021229822A1 publication Critical patent/WO2021229822A1/en

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION 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
    • G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T1/00—General purpose image data processing
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N1/00—Scanning, transmission or reproduction of documents or the like, e.g. facsimile transmission; Details thereof

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  • the present invention relates to an electronic data determination system, an electronic data determination server, an electronic data determination method, and an electronic data determination program for determining electronic data in order to store electronic data related to documents such as vouchers.
  • time stamps can be easily added by the technology shown in Patent Document 1, electronic data storage is not permitted unless other requirements are met.
  • the storage requirements for electronic data may differ depending on whether the data is image data read by a scanner or image data read by a camera such as a smartphone or a digital camera. It takes time to check whether the image data meets the requirements for storing electronic books, and the accuracy of the manual check may vary.
  • the present invention has been made to solve such a problem, and an object of the present invention is to improve the accuracy and work efficiency of digitization of documents when storing electronic data of documents. It is an object of the present invention to provide a data determination system, an electronic data determination device, an electronic data determination method, and an electronic data determination program.
  • the electronic data determination system has an image discrimination unit that discriminates a reading method of the image data from the image data obtained by reading a document by an image analysis process, and the image discrimination unit.
  • a distribution unit for distributing the image data according to the determined reading method is provided.
  • the receipt date extraction unit that extracts the receipt date of the document from the image data by the image analysis process and the period from the receipt date extracted by the receipt date extraction unit to the reading date of the image data are Alert processing is performed on the period determination unit that determines whether or not the image data is within the predetermined period determined according to the reading method, and the image data that is determined by the period determination unit to be outside the predetermined period.
  • An alert processing unit may be further provided.
  • the reading method for discrimination by the image discrimination unit may include a reading method by a scanner and a reading method by a camera.
  • the predetermined period determined according to the reading method is the second predetermined period defined by the camera reading method rather than the first predetermined period defined by the scanning method by the scanner.
  • the predetermined period of may be shorter.
  • an image requirement determination unit for determining whether or not the image data satisfies a predetermined image requirement is further provided, and the alert processing unit is the predetermined image by the image requirement determination unit. Alert processing may be performed on the image data determined not to satisfy the requirements.
  • the predetermined image requirement may be determined based on the resolution of the image.
  • the predetermined image requirement may be determined based on the color gradation of the image.
  • the predetermined image requirement may be determined based on the size of the image.
  • the electronic data determination device has an image discrimination unit that discriminates a reading method of the image data from the image data obtained by reading a document by an image analysis process, and the image discrimination unit.
  • a distribution unit for distributing and storing the image data according to the determined reading method is provided.
  • the electronic data determination method comprises an image discrimination step of discriminating the reading method of the image data from the image data obtained by reading the document by an image analysis process, and the image discrimination unit.
  • the computer executes a distribution step of distributing and storing the image data according to the determined reading method.
  • the electronic data determination program has an image discrimination step of discriminating the reading method of the image data from the image data obtained by reading the document by an image analysis process, and the image discrimination unit.
  • a computer is made to execute a distribution step of distributing and storing the image data according to the determined reading method.
  • FIG. 1 is a system configuration diagram showing an electronic data determination system according to an embodiment of the present invention, and the configuration of the present embodiment will be described based on the same diagram.
  • the electronic data determination system 1 is configured by connecting an information terminal 2 and a management server 3 (electronic data determination device) via a wired or wireless communication means. ..
  • the information terminal 2 and the management server 3 may be connected to each other via a communication network such as a VPN (Virtual Private Network), an intranet, or the Internet.
  • the management server 3 is connected to one information terminal 2 in FIG. 1, but the management server 3 can be connected to a plurality of information terminals 2.
  • the person who uses the information terminal 2 is, for example, an accountant of a company, a tax accountant, an accountant, or an expert, or a corporation or an individual who directly performs accounting processing.
  • a person who creates or receives national tax-related documents hereinafter referred to as a recipient, etc.
  • a person other than the recipient, etc. reads national tax-related documents
  • the requirements for time stamping are different.
  • a person other than the recipient reads the national tax documents, it is generally within 7 business days after the documents are prepared or received (for example, from the date of receipt), or within the normal business processing period (up to 2 months) and 7 business days. Need to be time stamped.
  • the electronic data determination system 1 of the present embodiment will be described as a system used by a person other than the recipient or the like (for example, a person in charge of accounting of a company).
  • the information terminal 2 is, for example, a mobile terminal such as a smartphone, a tablet PC, and a mobile phone, or a personal computer (hereinafter referred to as a PC), and has a reading unit 10 and a display unit 11.
  • the information terminal 2 may be a scanner.
  • the reading unit 10 is an optical device including a scanner and a camera such as a smartphone or a digital camera, and is a portion capable of capturing documents as image data.
  • the "documents" in the present embodiment and claims are, for example, national tax-related book documents stipulated in the Electronic Bookkeeping Law. Specifically, the documents include general ledger, journal, cash account book, accounts receivable / accounts receivable ledger, fixed asset ledger, sales / purchase book, inventory table, balance sheet, income statement, etc. Other financial statements such as documents created for financial statements, receipts and receipts, other receipts, invoices, invoices, financial institution ledgers, accounting proof of money transfer, IC cards such as electronic money Includes vouchers including transaction information by.
  • the display unit 11 is, for example, a display for visually displaying information such as a message from the management server 3.
  • the information terminal 2 can transmit the image data of the document read by the reading unit 10 to the management server 3.
  • the information of the sender that is, the information of the information terminal 2, the information of the accounting staff using the information terminal 2, and the information of the recipient of the national tax-related documents (for example, personal ID) are also linked to the image data. It is possible to recognize who sent the image data of what kind of document.
  • the management server 3 is composed of one or a plurality of servers (computers) that execute storage processing of electronic data of documents based on a program.
  • an image discrimination unit 20 that discriminates the reading method of the image data from the image data of the document
  • a distribution unit 21 that distributes the discriminated image data
  • an image such as the date of receipt of the document from the image data.
  • An image element extraction unit 22 (receipt date extraction unit) for extracting elements, a period determination unit 23 for determining a requirement for a period from a receipt date to a reading date, an image requirement determination unit 24 for determining an image requirement, and an alert. It has an alert processing unit 25 for processing.
  • the management server 3 includes a learning system 26 that generates an image discrimination AI and an image element extraction AI, a requirement database 27 that stores requirements for a period from a receipt date to a reading date, and requirements for images, and electronic data of documents. It has various databases (hereinafter, the database is referred to as "DB") such as a document database 28 in which data is stored.
  • DB database
  • the image discrimination unit 20 has a function of receiving the image data of the document read by the reading unit 10 of the information terminal 2 and discriminating the reading method of the image data by the image analysis process.
  • the image discrimination unit 20 has an image discrimination AI for discriminating the reading method from the image data of the document as an image analysis process, and the image discrimination AI can discriminate the reading method from the image data of the document. Is.
  • the image discrimination unit 20 may discriminate the reading method by using another image analysis process without using the image discrimination AI.
  • a reading method using a scanner there are two types of reading methods, a reading method using a scanner and a reading method using a scanner such as a smartphone or a digital camera. To determine if it is.
  • the distribution unit 21 has a function of distributing image data according to the reading method determined by the image discrimination unit 20. Specifically, the distribution unit 21 of the present embodiment distributes image data that is a reading method by a scanner and image data that is a reading method by a camera. The distribution unit 21 may output the distributed image data so as to be stored in the document DB 28, or may be output so as to be displayed on the display unit 11 of the information terminal 2.
  • the image element extraction unit 22 has a function of receiving the image data distributed by the distribution unit 21 and extracting a judgment element related to the image (hereinafter referred to as an image element) from the image data by an image analysis process.
  • the image element is an element corresponding to the item of the storage requirement described later, and is, for example, the date when the document is received (receipt date), the date when the image data is read, the date and time when the image data is transmitted, the resolution and color gradation of the image data. And image size, data format (JPEG, GIF, PNG, TIFF, BMP, PDF, etc.), and at least one of the text information and numerical information described in the document.
  • each document may be recognized and an image element may be extracted for each document.
  • the image element extraction unit 22 has an image element extraction AI for extracting an image element from the image data of the document, and the image element can be extracted from the image data of the document by the image element extraction AI. ..
  • image elements related to the image data itself metadata
  • the image element extraction AI may be extracted by image analysis without using.
  • Image element extraction AI specifies the part (position) corresponding to the image element from the image data for the image element in the document, and extracts the image element corresponding to the content of the specified part as text. That is, in the image element extraction AI, in the learning system 26, an area including a portion corresponding to the image element is designated from the image data by machine learning, and the image element corresponding to the content of the specified portion is output as text. It is AI who learned that. For example, the image element extraction AI can recognize the position and number of the date portion corresponding to the receipt date in the image data of the document, and can extract the text such as the date as the receipt date of the document.
  • the image element extraction AI specifies the appearance such as the shape, size, and color of the document, the document name part, the amount part, the customer part, and the description part, and recognizes the number in the amount part to recognize the amount.
  • the text of the document name, the business partner, and the description may be extracted by recognizing the characters in the part corresponding to the document name and the business partner and the part corresponding to the description.
  • the image element extraction unit 22 uses the image element extraction AI to, for example, for a date, display the numbers before, after, and above the characters such as "date”, “year”, “month”, “day”, and the symbols such as "/”. Identify. Amounts include symbols such as " ⁇ ", product names, “amount”, “deposit”, “subtotal”, “total”, “tax”, “change”, “discount”, “yen”, “payment”, “deposit”, “balance”, etc. Identify the numbers before, after, and above and below the letters related to.
  • the image element extraction unit 22 can also recognize the meaning of the extracted characters, and for example, the "subtotal” can specify the accounting relationship such as the total amount of the prices of the products.
  • the character parts before and after the characters such as "Co., Ltd.”, “Co., Ltd.”, "(F)", and the appearance of the logo mark, telephone number, and voucher are specified and based on this information. Identify the part that corresponds to the company name or personal name. For the abstract, specify the character part following the character such as "However”. For the transaction source, specify the part of the character before the character such as "sama”.
  • the image elements are not limited to this, and the numbers, characters, and figures used for extracting the image elements are not limited to this.
  • the quantity may be included as an image element, and the signature of the recipient or the like and information such as the name and number of attendees are described. If so, the signature of the recipient or the like, the attendees, and the number of people may be included as image elements.
  • a number corporate number, business establishment number set to identify each company may be extracted.
  • the image element extraction AI is an image recognition AI that specifies a part (position) corresponding to the image element from the image data of the voucher, and a character recognition AI that extracts the image element corresponding to the content of the specified part as text. It may be composed of two AIs.
  • the image element extraction unit 22 outputs the image data of the document and the data including the information about the image element extracted from the image data to the period determination unit 23 as electronic data of the document.
  • a predetermined period (reading date-receipt date) from the receiving date of the document in the image data extracted by the image element extracting unit 22 to the reading date of the image data is determined according to the reading method. It has a function to determine whether or not it is inside.
  • the predetermined period determined according to this reading method is stored in the requirement DB 27, and for example, a second predetermined period specified in the reading method by the camera is more than the first predetermined period defined in the reading method by the scanner. Is set shorter.
  • the first predetermined period is 2 months and 7 business days
  • the second predetermined period is 7 business days.
  • the image requirement determination unit 24 has a function of determining whether or not the image data satisfies a predetermined image requirement.
  • This predetermined image requirement is stored in the requirement DB 27, and for example, a requirement based on the resolution of the image, a requirement based on the gradation of the color of the image, and a requirement based on the size of the image are set.
  • predetermined image requirements may be individually set according to the image data reading method. In this embodiment, it is not set individually according to the reading method, and in any reading method, the requirement based on the resolution is 200 dpi (predetermined resolution) or more, or the requirement based on the color gradation of the image is red.
  • the image requirement determination unit 24 stores the image data satisfying these image requirements in the document DB 28.
  • the image data stored in the document DB 28 includes a reading method determined by the image discrimination unit 20, an image element extracted by the image element extraction unit 22, a determination result of the period determination unit 23 and the image requirement determination unit 24, and the like. Information is given.
  • the alert processing unit 25 alerts the image data determined by the period determination unit 23 to be out of the predetermined period, or the image data determined by the image requirement determination unit 24 not to satisfy the predetermined image requirement. Has a function to perform.
  • the alert processing for example, the display unit 11 of the information terminal 2 is presented with the image data that does not meet the requirements and the requirements that are not met, and the image data that does not meet the requirements in the image data list is displayed differently from the others (for example, the image data that does not meet the requirements is displayed. By performing marker display, flag display, etc.), the user of the information terminal 2 is urged to check the image data.
  • the learning system 26 has a function of learning the above-mentioned image discrimination AI and image element extraction AI and supplying the learned AI. Specifically, the learning system 26 generates an image discrimination AI by performing machine learning (so-called deep learning) based on learning data consisting of image data of a document and information on a reading method of the image data. Further, the learning system 26 performs machine learning based on the image data of the document and the learning data including information on the receipt date, resolution, color gradation, image size, etc. included in the image data, thereby performing machine learning, thereby performing image elements. Generate an extract AI.
  • the requirement DB 27 has a function of storing a predetermined period for making a determination by the above-mentioned period determination unit 23 and a predetermined image requirement for making a determination by the image requirement determination unit 24. These predetermined periods and predetermined image requirements can be updated when the storage requirements for electronic data are changed due to amendments to the law.
  • the document DB 28 is sorted by the distribution unit 21, and has a function of storing image data satisfying each requirement in the period determination unit 23 and the image requirement determination unit 24.
  • the image data of the document stored in the document DB 28 is stored separately in a scanning method by a scanner and a reading method by a camera.
  • the electronic data determination method starts by receiving the image data of the document from the information terminal 2.
  • the image discrimination unit 20 of the management server 3 discriminates the reading method of the image data by the image analysis process. Specifically, the image discrimination unit 20 uses the image discrimination AI to determine whether the image data is a scanning method by a scanner or a reading method by a camera.
  • step S2 the distribution unit 21 determines whether or not the image data is read by the scanner as a result of the determination by the image discrimination unit 20. If the determination result is true (Yes), the process proceeds to step S3.
  • step S3 the image element extraction unit 22 extracts an image element from the image data by an image analysis process. Specifically, the image element extraction unit 22 uses the image element extraction AI to receive the document (receipt date), the image data reading date, the image data resolution, and the color gradation in the image data. And the size of the image, etc.
  • step S4 the period determination unit 23 has a first predetermined period in which the period (reading date-receipt date) from the receiving date of the document in the image data to the reading date of the image data is defined by the scanning method by the scanner. (2 months and 7 business days) Determine if it is less than or equal to. If the determination result is true (Yes), the process proceeds to step S5.
  • step S5 the image requirement determination unit 24 determines whether or not the resolution of the image data is equal to or higher than the predetermined resolution (200 dpi). If the determination result is true (Yes), the process proceeds to step S6.
  • step S6 the image requirement determination unit 24 determines whether or not the color gradation of the image data is equal to or higher than a predetermined gradation (256 gradations). If the determination result is true (Yes), the process proceeds to step S7.
  • step S7 the image requirement determination unit 24 determines whether or not the size of the image of the image data is a predetermined size (A4 size) or more. If the determination result is true (Yes), the process proceeds to step S8.
  • step S8 the image requirement determination unit 24 sets the image data of the document acquired this time as image data satisfying the storage requirement, and obtains information such as a reading method of the image data, an image element, and determination results of steps S4 to S7. It is saved in the document DB 28, and the routine is terminated.
  • step S4 to S7 determines whether the period from the receipt date of the document to the reading date (reading date-receipt date) exceeds the first predetermined period.
  • the resolution is less than the predetermined resolution, the color gradation is less than the predetermined gradation, or the size of the image is smaller than the predetermined size, the process proceeds to step S9.
  • step S9 the alert processing unit 25 performs alert processing according to the determination results of steps S4 to S7, assuming that the image data of the document acquired this time is image data that does not satisfy the storage requirement, and ends the routine.
  • step S2 determines whether the image data is determined by the distribution unit 21 to be a reading method by the camera. If the determination result in step S2 is false (No), that is, if the image data is determined by the distribution unit 21 to be a reading method by the camera, the process proceeds to step S10.
  • step S10 as in step S3, the image element extraction unit 22 extracts an image element such as a receipt date from the image data by image analysis processing.
  • step S11 the period determination unit 23 has a second predetermined period (reading date-receipt date) defined in the reading method by the camera, from the receiving date of the document in the image data to the reading date of the image data. 7 business days) Determine if it is less than or equal to. If the determination result is true (Yes), the process proceeds to step S12, and if the determination result is false (No), the process proceeds to step SS9 described above.
  • a second predetermined period (reading date-receipt date) defined in the reading method by the camera, from the receiving date of the document in the image data to the reading date of the image data. 7 business days) Determine if it is less than or equal to. If the determination result is true (Yes), the process proceeds to step S12, and if the determination result is false (No), the process proceeds to step SS9 described above.
  • steps S12 to S15 are the same as steps S5 to S8 described above.
  • the reading method of the image data of the document is first determined, and the image data is distributed according to the reading method.
  • the image data is distributed according to the reading method.
  • the electronic data determination system 1 determines whether or not the period from the date of receipt of the document to the date of reading the image data is within a predetermined period determined according to the reading method, and determines that the period is out of the predetermined period.
  • the reading method for discrimination includes a reading method using a scanner and a reading method using a camera as in the present embodiment, for example, the reading method using a scanner and the reading method using a camera are the same data method and cannot be distinguished. Even in this case, the reading method can be determined and sorted by the image analysis process.
  • the predetermined period determined according to the reading method is a second predetermined period defined by the reading method by the camera rather than the first predetermined period defined by the reading method by the scanner.
  • the image requirement determination unit 24 determines whether the image data satisfies predetermined image requirements such as a requirement based on the resolution of the image, a requirement based on the gradation of the color of the image, and a requirement based on the size of the image. By performing alert processing when the predetermined image requirement is not satisfied, not only the period determination unit 23 can determine the period but also the image requirement can be determined, and the number of manual checks can be reduced. Can be done.
  • predetermined image requirements such as a requirement based on the resolution of the image, a requirement based on the gradation of the color of the image, and a requirement based on the size of the image.
  • the electronic data determination system 1 can improve the accuracy and work efficiency of digitizing documents when storing electronic data of documents.
  • the electronic data determination system 1 of the above embodiment is composed of two computers, an information terminal 2 and a management server 3, but may be composed of only one computer (for example, a PC) or three computers, for example.
  • the functions may be divided and configured by the above computers.
  • the documents to be stored as electronic data are the national tax-related book documents stipulated in the Electronic Bookkeeping Law, but the present invention is also applied to other documents as long as the documents have storage requirements. It is possible.

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Abstract

This electronic data determination system 1 comprises an image decision unit 20 which decides, from image data obtained by reading a document, a reading manner of the image data by image analysis processing, and a distribution unit 21 which distributes the image data according to the reading manner decided by the image decision unit 20, and further comprises: an image element extraction unit 22 which extracts, from the image data, an image element such as a date of receipt of the document by the image analysis processing; a period determination unit 23 which determines whether a period from the extracted date of receipt to a reading date of the image data is within a prescribed period determined according to the reading manner; and an alert processing unit 25 which performs an alert process on the image data in a period determined to be outside a prescribed period by the period determination unit 23.

Description

電子データ判定システム、電子データ判定装置、電子データ判定方法、電子データ判定プログラムElectronic data judgment system, electronic data judgment device, electronic data judgment method, electronic data judgment program
　本発明は証憑等の書類に係る電子データを保存するため、当該電子データの判定を行う電子データ判定システム、電子データ判定サーバ、電子データ判定方法、電子データ判定プログラムに関する。 The present invention relates to an electronic data determination system, an electronic data determination server, an electronic data determination method, and an electronic data determination program for determining electronic data in order to store electronic data related to documents such as vouchers.
　近年、紙の書類を電子化し、紙資源の節約、印刷コストの削減、業務の効率化を図るペーパーレス化が進んでいるが、重要な書類の電子化には一定の要件が必要となる場合がある。 In recent years, paperless documents have been digitized to save paper resources, reduce printing costs, and improve work efficiency. However, there are cases where certain requirements are required for digitizing important documents. be.
　例えば、レシートや領収書等の証憑を含む国税関係帳簿書類については、その全部又は一部について電子データによる保存を認める電子帳簿保存法が制定されている。当該電子帳簿保存法では、記録の真実性及び可視性等の確保に必要となる所定の要件を具備することで、スキャナや、スマートフォン又はデジタルカメラで読取した書類の電子データとしての保存が許されている。 For example, regarding national tax-related book documents including vouchers such as receipts and receipts, the Electronic Book Preservation Law has been enacted, which allows all or part of them to be saved as electronic data. Under the Electronic Bookkeeping Law, it is permitted to save documents read by a scanner, smartphone or digital camera as electronic data by satisfying the prescribed requirements necessary for ensuring the authenticity and visibility of records. ing.
　当該電子帳簿保存要件としては、真実性の確保のために書類の電子データにタイムスタンプを付与することが規定されている。そこで、携帯端末を用いて作成した電子データに対して容易にタイムスタンプを発行し、これを管理可能な技術も開発されている（特許文献１参照）。 The requirement for keeping the electronic book is to add a time stamp to the electronic data of the document to ensure the authenticity. Therefore, a technique has been developed in which a time stamp can be easily issued to electronic data created by using a mobile terminal and can be managed (see Patent Document 1).
特開２０１７－１７５３７７号公報Japanese Unexamined Patent Publication No. 2017-175377
　上記特許文献１で示す技術等により、タイムスタンプを容易に付与することはできるが、その他の要件も具備していなければ電子データによる保存は許されない。 Although time stamps can be easily added by the technology shown in Patent Document 1, electronic data storage is not permitted unless other requirements are met.
　例えば、スキャナで読取した画像データであるか、スマートフォン又はデジタルカメラのようなカメラにより読取した画像データであるか等によって、電子データとしての保存要件が異なる場合がある。画像データが電子帳簿保存要件を具備しているかをチェックするには手間がかかり、人手によるチェックは精度のばらつきが生じるおそれもある。 For example, the storage requirements for electronic data may differ depending on whether the data is image data read by a scanner or image data read by a camera such as a smartphone or a digital camera. It takes time to check whether the image data meets the requirements for storing electronic books, and the accuracy of the manual check may vary.
　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、書類の電子データの保存に際して、書類の電子化の正確性及び作業効率を向上させることのできる電子データ判定システム、電子データ判定装置、電子データ判定方法、電子データ判定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 improve the accuracy and work efficiency of digitization of documents when storing electronic data of documents. It is an object of the present invention to provide a data determination system, an electronic data determination device, an electronic data determination method, and an electronic data determination program.
　上記した目的を達成するために、本発明に係る電子データ判定システムは、書類を読取した画像データから、画像解析処理により当該画像データの読取方式を判別する画像判別部と、前記画像判別部により判別された読取方式に応じて前記画像データの振り分けを行う振分部と、を備える。 In order to achieve the above object, the electronic data determination system according to the present invention has an image discrimination unit that discriminates a reading method of the image data from the image data obtained by reading a document by an image analysis process, and the image discrimination unit. A distribution unit for distributing the image data according to the determined reading method is provided.
　上記電子データ判定システムにおいて、前記画像データから画像解析処理により書類の受領日を抽出する受領日抽出部と、前記受領日抽出部により抽出された受領日から前記画像データの読取日までの期間が前記読取方式に応じて定められた所定期間内であるか否かを判定する期間判定部と、前記期間判定部により前記所定期間外であると判定された前記画像データに対してアラート処理を行うアラート処理部と、をさらに備えてもよい。 In the electronic data determination system, the receipt date extraction unit that extracts the receipt date of the document from the image data by the image analysis process and the period from the receipt date extracted by the receipt date extraction unit to the reading date of the image data are Alert processing is performed on the period determination unit that determines whether or not the image data is within the predetermined period determined according to the reading method, and the image data that is determined by the period determination unit to be outside the predetermined period. An alert processing unit may be further provided.
　また、上記電子データ判定システムにおいて、画像判別部により判別する読取方式には、スキャナによる読取方式と、カメラによる読取方式とが含まれてもよい。 Further, in the electronic data determination system, the reading method for discrimination by the image discrimination unit may include a reading method by a scanner and a reading method by a camera.
　さらに、上記電子データ判定システムにおいて、前記読取方式に応じて定められた所定期間は、前記スキャナによる読取方式に定められた第１の所定期間よりも、前記カメラによる読取方式に定められた第２の所定期間の方が短くてもよい。 Further, in the electronic data determination system, the predetermined period determined according to the reading method is the second predetermined period defined by the camera reading method rather than the first predetermined period defined by the scanning method by the scanner. The predetermined period of may be shorter.
　また、上記電子データ判定システムにおいて、前記画像データが所定の画像要件を満たしているか否かを判定する画像要件判定部をさらに備え、前記アラート処理部は、前記画像要件判定部により前記所定の画像要件を満たしていないと判定された前記画像データに対してアラート処理を行ってもよい。 Further, in the electronic data determination system, an image requirement determination unit for determining whether or not the image data satisfies a predetermined image requirement is further provided, and the alert processing unit is the predetermined image by the image requirement determination unit. Alert processing may be performed on the image data determined not to satisfy the requirements.
　また、上記電子データ判定システムにおいて、前記所定の画像要件は、画像の解像度に基づき定められていてもよい。 Further, in the electronic data determination system, the predetermined image requirement may be determined based on the resolution of the image.
　また、上記電子データ判定システムにおいて、前記所定の画像要件は、画像の色の階調に基づき定められていてもよい。 Further, in the electronic data determination system, the predetermined image requirement may be determined based on the color gradation of the image.
　また、上記電子データ判定システムにおいて、前記所定の画像要件は、画像の大きさに基づき定められていてもよい。 Further, in the electronic data determination system, the predetermined image requirement may be determined based on the size of the image.
　上記した目的を達成するために、本発明に係る電子データ判定装置は、書類を読み取りした画像データから、画像解析処理により当該画像データの読取方式を判別する画像判別部と、前記画像判別部により判別された読取方式に応じて前記画像データを振り分けて保存する振分部と、を備える。 In order to achieve the above object, the electronic data determination device according to the present invention has an image discrimination unit that discriminates a reading method of the image data from the image data obtained by reading a document by an image analysis process, and the image discrimination unit. A distribution unit for distributing and storing the image data according to the determined reading method is provided.
　上記した目的を達成するために、本発明に係る電子データ判定方法は、書類を読取した画像データから、画像解析処理により当該画像データの読取方式を判別する画像判別ステップと、前記画像判別部により判別された読取方式に応じて前記画像データを振り分けて保存する振分ステップと、をコンピュータが実行する。 In order to achieve the above object, the electronic data determination method according to the present invention comprises an image discrimination step of discriminating the reading method of the image data from the image data obtained by reading the document by an image analysis process, and the image discrimination unit. The computer executes a distribution step of distributing and storing the image data according to the determined reading method.
　上記した目的を達成するために、本発明に係る電子データ判定プログラムは、書類を読取した画像データから、画像解析処理により当該画像データの読取方式を判別する画像判別ステップと、前記画像判別部により判別された読取方式に応じて前記画像データを振り分けて保存する振分ステップと、をコンピュータに実行させる。 In order to achieve the above object, the electronic data determination program according to the present invention has an image discrimination step of discriminating the reading method of the image data from the image data obtained by reading the document by an image analysis process, and the image discrimination unit. A computer is made to execute a distribution step of distributing and storing the image data according to the determined reading method.
　上記手段を用いる本発明によれば、書類の電子データの保存に際して、書類の電子化の正確性及び作業効率を向上させることができる。 According to the present invention using the above means, it is possible to improve the accuracy and work efficiency of digitizing a document when storing the electronic data of the document.
本発明の一実施形態に係る電子データ判定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 electronic data determination system which concerns on one Embodiment of this invention. 管理サーバにより実行される書類の電子データ判定処理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 electronic data determination process of a document executed by a management server.
　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電子データ判定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 electronic data determination system 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、本実施形態に係る電子データ判定システム１は、情報端末２と管理サーバ３（電子データ判定装置）とが有線又は無線の通信手段を介して接続されて構成されている。なお、情報端末２と管理サーバ３とは、ＶＰＮ（Virtual Private Network）、イントラネット、又はインターネット等の通信網を介して接続されていてもよい。また、説明の簡略化のため図１では管理サーバ３は一つの情報端末２と接続されているが、管理サーバ３は複数の情報端末２と接続可能である。 As shown in FIG. 1, the electronic data determination system 1 according to the present embodiment is configured by connecting an information terminal 2 and a management server 3 (electronic data determination device) via a wired or wireless communication means. .. The information terminal 2 and the management server 3 may be connected to each other via a communication network such as a VPN (Virtual Private Network), an intranet, or the Internet. Further, for the sake of simplification of the explanation, the management server 3 is connected to one information terminal 2 in FIG. 1, but the management server 3 can be connected to a plurality of information terminals 2.
　情報端末２を使用する者は、例えば企業の経理担当者、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る。なお、電子帳簿保存法では、国税関係書類の作成又は受領をする者（以下、受領者等という）が国税関係書類を読み取る場合と、受領者等以外の者が国税関係書類を読み取る場合とで、タイムスタンプを付する要件が異なる。受領者等以外の者が国税関係書類を読み取る場合は、書類を作成又は受領後（例えば受領日から）、おおむね７営業日以内、又は通常の業務処理期間（最大２ヵ月）と７営業日以内にタイムスタンプを付する必要がある。本実施形態の電子データ判定システム１は、受領者等以外の者（例えば企業の経理担当者）が使用するシステムとして説明する。 The person who uses the information terminal 2 is, for example, an accountant of a company, a tax accountant, an accountant, or an expert, or a corporation or an individual who directly performs accounting processing. According to the Electronic Bookkeeping Law, there are cases where a person who creates or receives national tax-related documents (hereinafter referred to as a recipient, etc.) reads national tax-related documents, and cases where a person other than the recipient, etc. reads national tax-related documents. , The requirements for time stamping are different. When a person other than the recipient reads the national tax documents, it is generally within 7 business days after the documents are prepared or received (for example, from the date of receipt), or within the normal business processing period (up to 2 months) and 7 business days. Need to be time stamped. The electronic data determination system 1 of the present embodiment will be described as a system used by a person other than the recipient or the like (for example, a person in charge of accounting of a company).
　情報端末２は、例えばスマートフォン、タブレットＰＣ、及び携帯電話のような携帯端末や、パーソナルコンピュータ（以下、ＰＣという）であり、読取部１０と表示部１１とを有している。なお、情報端末２は、スキャナであってもよい。 The information terminal 2 is, for example, a mobile terminal such as a smartphone, a tablet PC, and a mobile phone, or a personal computer (hereinafter referred to as a PC), and has a reading unit 10 and a display unit 11. The information terminal 2 may be a scanner.
　読取部１０は、スキャナ、及び、スマートフォンやデジタルカメラ等のカメラを含む光学機器であり、書類を画像データとして取り込み可能な部分である。なお、本実施形態及び特許請求の範囲における「書類」は、例えば、電子帳簿保存法に定められる国税関係帳簿書類である。具体的には、書類には、総勘定元帳、仕訳帳、現金出納帳、売掛金・買掛金元帳固定資産台帳、売上・仕入帳等の帳簿や、棚卸表、貸借対照表、損益計算書、その他決算に関して作成した書類等の決算関係書類や、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を含む証憑類が含まれる。 The reading unit 10 is an optical device including a scanner and a camera such as a smartphone or a digital camera, and is a portion capable of capturing documents as image data. The "documents" in the present embodiment and claims are, for example, national tax-related book documents stipulated in the Electronic Bookkeeping Law. Specifically, the documents include general ledger, journal, cash account book, accounts receivable / accounts receivable ledger, fixed asset ledger, sales / purchase book, inventory table, balance sheet, income statement, etc. Other financial statements such as documents created for financial statements, receipts and receipts, other receipts, invoices, invoices, financial institution ledgers, accounting proof of money transfer, IC cards such as electronic money Includes vouchers including transaction information by.
　表示部１１は、例えばディスプレイであり、管理サーバ３からのメッセージ等の情報を視認可能に表示するものである。 The display unit 11 is, for example, a display for visually displaying information such as a message from the management server 3.
　情報端末２は、管理サーバ３に読取部１０にて読み取った書類の画像データを送信可能である。また当該画像データには送信元の情報、つまり情報端末２の情報、当該情報端末２を使用している経理担当者の情報や国税関係書類の受領者等の情報（例えば個人ＩＤ）も紐づけされており、誰がどのような書類の画像データを送ってきたか認識可能となっている。 The information terminal 2 can transmit the image data of the document read by the reading unit 10 to the management server 3. In addition, the information of the sender, that is, the information of the information terminal 2, the information of the accounting staff using the information terminal 2, and the information of the recipient of the national tax-related documents (for example, personal ID) are also linked to the image data. It is possible to recognize who sent the image data of what kind of document.
　一方、管理サーバ３は、プログラムに基づき書類の電子データの保存処理を実行する１又は複数のサーバ（コンピュータ）から構成されている。機能的には主に、書類の画像データから、画像データの読取方式を判別する画像判別部２０と、判別された画像データを振り分ける振分部２１と、画像データから書類の受領日等の画像要素を抽出する画像要素抽出部２２（受領日抽出部）と、受領日から読取日までの期間に関する要件を判定する期間判定部２３と、画像に関する要件を判定する画像要件判定部２４と、アラート処理を行うアラート処理部２５とを有している。また管理サーバ３は、画像判別ＡＩ及び画像要素抽出ＡＩを生成する学習システム２６と、受領日から読取日までの期間に関する要件、及び画像に関する要件が記憶されている要件データベース２７、書類の電子データが記憶される書類データベース２８、等の各種データベース（以下、データベースを「ＤＢ」と表記する）を有している。 On the other hand, the management server 3 is composed of one or a plurality of servers (computers) that execute storage processing of electronic data of documents based on a program. Functionally, mainly, an image discrimination unit 20 that discriminates the reading method of the image data from the image data of the document, a distribution unit 21 that distributes the discriminated image data, and an image such as the date of receipt of the document from the image data. An image element extraction unit 22 (receipt date extraction unit) for extracting elements, a period determination unit 23 for determining a requirement for a period from a receipt date to a reading date, an image requirement determination unit 24 for determining an image requirement, and an alert. It has an alert processing unit 25 for processing. Further, the management server 3 includes a learning system 26 that generates an image discrimination AI and an image element extraction AI, a requirement database 27 that stores requirements for a period from a receipt date to a reading date, and requirements for images, and electronic data of documents. It has various databases (hereinafter, the database is referred to as "DB") such as a document database 28 in which data is stored.
　詳しくは、画像判別部２０は、情報端末２の読取部１０にて読み取った書類の画像データを受信し、画像解析処理により当該画像データの読取方式を判別する機能を有している。 Specifically, the image discrimination unit 20 has a function of receiving the image data of the document read by the reading unit 10 of the information terminal 2 and discriminating the reading method of the image data by the image analysis process.
　具体的には、画像判別部２０は、画像解析処理として、書類の画像データから読取方式を判別するための画像判別ＡＩを有し、当該画像判別ＡＩにより書類の画像データから読取方式を判別可能である。なお、画像判別部２０は、画像判別ＡＩを用いずに、他の画像解析処理を用いて読取方式を判別してもよい。 Specifically, the image discrimination unit 20 has an image discrimination AI for discriminating the reading method from the image data of the document as an image analysis process, and the image discrimination AI can discriminate the reading method from the image data of the document. Is. The image discrimination unit 20 may discriminate the reading method by using another image analysis process without using the image discrimination AI.
　本実施形態では、読取方式には、スキャナによる読取方式と、スマートフォンやデジタルカメラ等のスキャナによる読取方式の２種類があり、画像判別部２０は、画像データからいずれの読取方式で読み取られたデータであるかを判別する。 In the present embodiment, there are two types of reading methods, a reading method using a scanner and a reading method using a scanner such as a smartphone or a digital camera. To determine if it is.
　振分部２１は、画像判別部２０により判別された読取方式に応じて画像データの振り分けを行う機能を有している。本実施形態の振分部２１は、具体的には、スキャナによる読取方式である画像データと、カメラによる読取方式である画像データとを振り分ける。なお、振分部２１は、振り分けた画像データを書類ＤＢ２８に保存するよう出力してもよいし、情報端末２の表示部１１に表示させるよう出力してもよい。 The distribution unit 21 has a function of distributing image data according to the reading method determined by the image discrimination unit 20. Specifically, the distribution unit 21 of the present embodiment distributes image data that is a reading method by a scanner and image data that is a reading method by a camera. The distribution unit 21 may output the distributed image data so as to be stored in the document DB 28, or may be output so as to be displayed on the display unit 11 of the information terminal 2.
　画像要素抽出部２２は、振分部２１にて振り分けた画像データを受信し、画像解析処理により当該画像データから画像に関する判断要素（以下、画像要素という）を抽出する機能を有している。画像要素は後述する保存要件の項目に対応した要素であり、例えば、当該書類を受領した日（受領日）、画像データの読取日、画像データの送信日時、画像データの解像度や色の階調や画像の大きさやデータ形式（JPEG、GIF、PNG、TIFF、BMP、PDF等）、書類内に記載されている文字情報や数字情報の少なくとも１つが含まれる。なお、１つの画像データに複数の書類が写り込んでいる場合は、それぞれの書類を認識し、各書類毎に画像要素を抽出してもよい。 The image element extraction unit 22 has a function of receiving the image data distributed by the distribution unit 21 and extracting a judgment element related to the image (hereinafter referred to as an image element) from the image data by an image analysis process. The image element is an element corresponding to the item of the storage requirement described later, and is, for example, the date when the document is received (receipt date), the date when the image data is read, the date and time when the image data is transmitted, the resolution and color gradation of the image data. And image size, data format (JPEG, GIF, PNG, TIFF, BMP, PDF, etc.), and at least one of the text information and numerical information described in the document. When a plurality of documents are reflected in one image data, each document may be recognized and an image element may be extracted for each document.
　具体的には、画像要素抽出部２２は、書類の画像データから画像要素を抽出するための画像要素抽出ＡＩを有し、当該画像要素抽出ＡＩにより書類の画像データから画像要素を抽出可能である。なお、画像データの読取日、画像データの送信日時、画像データの解像度や色の階調や画像の大きさやデータ形式等の画像データ自体（メタデータ）に係る画像要素については、画像要素抽出ＡＩを用いずに画像データを画像解析することで抽出してもよい。 Specifically, the image element extraction unit 22 has an image element extraction AI for extracting an image element from the image data of the document, and the image element can be extracted from the image data of the document by the image element extraction AI. .. For image elements related to the image data itself (metadata) such as the reading date of the image data, the transmission date and time of the image data, the resolution and color gradation of the image data, the size of the image, and the data format, the image element extraction AI The image data may be extracted by image analysis without using.
　画像要素抽出ＡＩは、書類内の画像要素については、画像データ内から画像要素に対応する部分（位置）を特定し、特定された部分の内容に対応する画像要素をテキストとして抽出する。つまり、画像要素抽出ＡＩは、学習システム２６において、機械学習により画像データ内から画像要素に対応する部分を含む領域を指定し、当該指定された部分の内容に対応する画像要素をテキストとして出力することを学習したＡＩである。例えば、画像要素抽出ＡＩは、書類の画像データ内において、受領日に相当する日付部分の位置及び数字を認識して、年月日等のテキストを当該書類の受領日として抽出可能である。この他にも、画像要素抽出ＡＩは、書類の形状、大きさ、色等の外観、書類名部分、金額部分、取引先部分、摘要部分を指定し、金額部分においては数字を認識して金額のテキストを抽出し、書類名や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書類名、取引先、摘要のテキストを抽出してもよい。 Image element extraction AI specifies the part (position) corresponding to the image element from the image data for the image element in the document, and extracts the image element corresponding to the content of the specified part as text. That is, in the image element extraction AI, in the learning system 26, an area including a portion corresponding to the image element is designated from the image data by machine learning, and the image element corresponding to the content of the specified portion is output as text. It is AI who learned that. For example, the image element extraction AI can recognize the position and number of the date portion corresponding to the receipt date in the image data of the document, and can extract the text such as the date as the receipt date of the document. In addition to this, the image element extraction AI specifies the appearance such as the shape, size, and color of the document, the document name part, the amount part, the customer part, and the description part, and recognizes the number in the amount part to recognize the amount. The text of the document name, the business partner, and the description may be extracted by recognizing the characters in the part corresponding to the document name and the business partner and the part corresponding to the description.
　画像要素抽出部２２は、画像要素抽出ＡＩを用いて、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する。金額については「￥」等の記号や商品名、「金額」「預り金」「小計」「合計」「税」「お釣り」「割引」「円」「支払い」「預り」「残高」等の金額に関係する文字の前後や上下の数字部分を特定する。なお、画像要素抽出部２２は、抽出された文字の意味についても認識可能であり、例えば「小計」は商品の価格を合算した金額である等の会計上の関係性まで特定可能である。 The image element extraction unit 22 uses the image element extraction AI to, for example, for a date, display the numbers before, after, and above the characters such as "date", "year", "month", "day", and the symbols such as "/". Identify. Amounts include symbols such as "¥", product names, "amount", "deposit", "subtotal", "total", "tax", "change", "discount", "yen", "payment", "deposit", "balance", etc. Identify the numbers before, after, and above and below the letters related to. The image element extraction unit 22 can also recognize the meaning of the extracted characters, and for example, the "subtotal" can specify the accounting relationship such as the total amount of the prices of the products.
　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、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する。摘要については、「但」等の文字に続く文字部分を特定する。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する。 In addition, regarding business partners, the character parts before and after the characters such as "Co., Ltd.", "Co., Ltd.", "(F)", and the appearance of the logo mark, telephone number, and voucher are specified and based on this information. Identify the part that corresponds to the company name or personal name. For the abstract, specify the character part following the character such as "However". For the transaction source, specify the part of the character before the character such as "sama".
　なお、画像要素はこれに限られるものではなく、また画像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画像要素として含めてもよいし、受領者等の本人の署名や、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、受領者等の本人の署名や同席者及び人数を画像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番号（法人番号、事業所番号）を抽出してもよい。 Note that the image elements are not limited to this, and the numbers, characters, and figures used for extracting the image elements are not limited to this. For example, if the voucher describes the quantity of the purchased item, the quantity may be included as an image element, and the signature of the recipient or the like and information such as the name and number of attendees are described. If so, the signature of the recipient or the like, the attendees, and the number of people may be included as image elements. In addition, a number (corporate number, business establishment number) set to identify each company may be extracted.
　なお、画像要素抽出ＡＩは、証憑の画像データ内から画像要素に対応する部分（位置）を特定する画像認識ＡＩと、特定された部分の内容に対応する画像要素をテキストとして抽出する文字認識ＡＩの２つのＡＩで構成してもよい。 The image element extraction AI is an image recognition AI that specifies a part (position) corresponding to the image element from the image data of the voucher, and a character recognition AI that extracts the image element corresponding to the content of the specified part as text. It may be composed of two AIs.
　画像要素抽出部２２は、書類の画像データと、当該画像データから抽出した画像要素に関する情報を含めたデータを書類の電子データとして、期間判定部２３に出力する。 The image element extraction unit 22 outputs the image data of the document and the data including the information about the image element extracted from the image data to the period determination unit 23 as electronic data of the document.
　期間判定部２３は、画像要素抽出部２２により抽出された画像データ内の書類の受領日から画像データの読取日までの期間（読取日－受領日）が読取方式に応じて定められた所定期間内であるか否かを判定する機能を有している。この読取方式に応じて定められた所定期間は要件ＤＢ２７に記憶されており、例えばスキャナによる読取方式に定められた第１の所定期間よりも、カメラによる読取方式に定められた第２の所定期間の方が短く設定されている。本実施形態では第１の所定期間を２カ月と７営業日、第２の所定期間を７営業日とする。 In the period determination unit 23, a predetermined period (reading date-receipt date) from the receiving date of the document in the image data extracted by the image element extracting unit 22 to the reading date of the image data is determined according to the reading method. It has a function to determine whether or not it is inside. The predetermined period determined according to this reading method is stored in the requirement DB 27, and for example, a second predetermined period specified in the reading method by the camera is more than the first predetermined period defined in the reading method by the scanner. Is set shorter. In the present embodiment, the first predetermined period is 2 months and 7 business days, and the second predetermined period is 7 business days.
　画像要件判定部２４は、画像データが所定の画像要件を満たしているか否かを判定する機能を有している。この所定の画像要件は、要件ＤＢ２７に記憶されており、例えば画像の解像度に基づく要件、画像の色の階調に基づく要件、画像の大きさに基づく要件が設定されている。また、所定の画像要件は画像データの読取方式に応じて個別に設定されていてもよい。本実施形態では、読取方式に応じて個別に設定せず、いずれの読取方式においても、解像度に基づく要件は２００ｄｐｉ（所定解像度）以上であるか、画像の色の階調に基づく要件は赤色、緑色及び青色の階調がそれぞれ２５６階調（所定階調）以上（２４ビットカラー）であるか、画像の大きさに基づく要件はＡ４サイズ（所定の大きさ）以上であるか、とする。そして、画像要件判定部２４は、これらの画像要件を具備した画像データについては書類ＤＢ２８に保存する。この書類ＤＢ２８に保存する画像データには、が画像判別部２０により判別された読取方式、画像要素抽出部２２により抽出された画像要素、期間判定部２３及び画像要件判定部２４の判定結果、等の情報が付与されている。 The image requirement determination unit 24 has a function of determining whether or not the image data satisfies a predetermined image requirement. This predetermined image requirement is stored in the requirement DB 27, and for example, a requirement based on the resolution of the image, a requirement based on the gradation of the color of the image, and a requirement based on the size of the image are set. Further, predetermined image requirements may be individually set according to the image data reading method. In this embodiment, it is not set individually according to the reading method, and in any reading method, the requirement based on the resolution is 200 dpi (predetermined resolution) or more, or the requirement based on the color gradation of the image is red. It is determined whether the gradations of green and blue are 256 gradations (predetermined gradation) or more (24-bit color), respectively, and the requirement based on the size of the image is A4 size (predetermined size) or more. Then, the image requirement determination unit 24 stores the image data satisfying these image requirements in the document DB 28. The image data stored in the document DB 28 includes a reading method determined by the image discrimination unit 20, an image element extracted by the image element extraction unit 22, a determination result of the period determination unit 23 and the image requirement determination unit 24, and the like. Information is given.
　アラート処理部２５は、期間判定部２３により所定期間外であると判定された画像データ、又は、画像要件判定部２４により所定の画像要件を満たしていないと判定された画像データに対してアラート処理を行う機能を有している。アラート処理としては、例えば情報端末２の表示部１１に要件を満たしていない画像データとともに満たしていない要件を提示したり、画像データのリストにおいて要件を満たしていない画像データについては他と異なる表示（マーカー表示、フラグ表示、等）を行うことで、情報端末２の使用者に対して当該画像データのチェックを促す。 The alert processing unit 25 alerts the image data determined by the period determination unit 23 to be out of the predetermined period, or the image data determined by the image requirement determination unit 24 not to satisfy the predetermined image requirement. Has a function to perform. As the alert processing, for example, the display unit 11 of the information terminal 2 is presented with the image data that does not meet the requirements and the requirements that are not met, and the image data that does not meet the requirements in the image data list is displayed differently from the others (for example, the image data that does not meet the requirements is displayed. By performing marker display, flag display, etc.), the user of the information terminal 2 is urged to check the image data.
　学習システム２６は、上述した画像判別ＡＩ及び画像要素抽出ＡＩ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２６は、書類の画像データと当該画像データの読取方式に関する情報からなる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、画像判別ＡＩを生成する。また、学習システム２６は、書類の画像データと当該画像データに含まれる受領日、解像度、色の階調、画像の大きさ等に関する情報からなる学習用データに基づき機械学習させることで、画像要素抽出ＡＩを生成する。 The learning system 26 has a function of learning the above-mentioned image discrimination AI and image element extraction AI and supplying the learned AI. Specifically, the learning system 26 generates an image discrimination AI by performing machine learning (so-called deep learning) based on learning data consisting of image data of a document and information on a reading method of the image data. Further, the learning system 26 performs machine learning based on the image data of the document and the learning data including information on the receipt date, resolution, color gradation, image size, etc. included in the image data, thereby performing machine learning, thereby performing image elements. Generate an extract AI.
　要件ＤＢ２７は、上述した期間判定部２３にて判定を行うための所定期間や、画像要件判定部２４にて判定を行うための所定の画像要件を記憶する機能を有している。これらの所定期間や所定の画像要件は法律の改正等に応じて電子データの保存要件に変更があった場合等に更新が可能である。 The requirement DB 27 has a function of storing a predetermined period for making a determination by the above-mentioned period determination unit 23 and a predetermined image requirement for making a determination by the image requirement determination unit 24. These predetermined periods and predetermined image requirements can be updated when the storage requirements for electronic data are changed due to amendments to the law.
　書類ＤＢ２８は、振分部２１により振り分けられ、期間判定部２３及び画像要件判定部２４にてそれぞれの要件を満たした画像データを記憶する機能を有している。例えば、当該書類ＤＢ２８に記憶されている書類の画像データは、スキャナによる読取方式とカメラによる読取方式とに分けて記憶されている。 The document DB 28 is sorted by the distribution unit 21, and has a function of storing image data satisfying each requirement in the period determination unit 23 and the image requirement determination unit 24. For example, the image data of the document stored in the document DB 28 is stored separately in a scanning method by a scanner and a reading method by a camera.
　ここで図２を参照すると、管理サーバ３により実行される書類の電子データ判定方法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、電子データ判定方法について詳しく説明する。なお、当該電子データ判定方法は、情報端末２からの書類の画像データを受信することでスタートする。 Here, with reference to FIG. 2, a flowchart showing the flow of the electronic data determination method of the document executed by the management server 3 is shown, and the electronic data determination method will be described in detail below with reference to the same flowchart. The electronic data determination method starts by receiving the image data of the document from the information terminal 2.
　まず、ステップＳ１として、管理サーバ３の画像判別部２０は、画像解析処理により当該画像データの読取方式を判別する。具体的には、画像判別部２０は、画像判別ＡＩを用いて画像データがスキャナによる読取方式であるか、カメラによる読取方式であるかを判別する。 First, as step S1, the image discrimination unit 20 of the management server 3 discriminates the reading method of the image data by the image analysis process. Specifically, the image discrimination unit 20 uses the image discrimination AI to determine whether the image data is a scanning method by a scanner or a reading method by a camera.
　ステップＳ２において、振分部２１は、画像判別部２０にて判別された結果、画像データがスキャナによる読取方式であるか否かを判定する。当該判定結果が真（Ｙｅｓ）である場合は、ステップＳ３に進む。 In step S2, the distribution unit 21 determines whether or not the image data is read by the scanner as a result of the determination by the image discrimination unit 20. If the determination result is true (Yes), the process proceeds to step S3.
　ステップＳ３において、画像要素抽出部２２は、画像解析処理により画像データから画像要素を抽出する。具体的には、画像要素抽出部２２は、画像要素抽出ＡＩを用いて、当該画像データにおける、書類を受領した日（受領日）、画像データの読取日、画像データの解像度や色の階調や画像の大きさ、等を抽出する。 In step S3, the image element extraction unit 22 extracts an image element from the image data by an image analysis process. Specifically, the image element extraction unit 22 uses the image element extraction AI to receive the document (receipt date), the image data reading date, the image data resolution, and the color gradation in the image data. And the size of the image, etc.
　そしてステップＳ４において、期間判定部２３は、画像データ内の書類の受領日から画像データの読取日までの期間（読取日－受領日）が、スキャナによる読取方式に定められた第１の所定期間（２カ月と７営業日）以下であるか否かを判定する。当該判定結果が真（Ｙｅｓ）である場合、ステップＳ５に進む。 Then, in step S4, the period determination unit 23 has a first predetermined period in which the period (reading date-receipt date) from the receiving date of the document in the image data to the reading date of the image data is defined by the scanning method by the scanner. (2 months and 7 business days) Determine if it is less than or equal to. If the determination result is true (Yes), the process proceeds to step S5.
　ステップＳ５において、画像要件判定部２４は、画像データの解像度が所定解像度（２００ｄｐｉ）以上であるか否かを判定する。当該判定結果が真（Ｙｅｓ）である場合はステップＳ６に進む。 In step S5, the image requirement determination unit 24 determines whether or not the resolution of the image data is equal to or higher than the predetermined resolution (200 dpi). If the determination result is true (Yes), the process proceeds to step S6.
　ステップＳ６において、画像要件判定部２４は、画像データの色の階調が所定階調（２５６階調）以上であるか否かを判定する。当該判定結果が真（Ｙｅｓ）である場合はステップＳ７に進む。 In step S6, the image requirement determination unit 24 determines whether or not the color gradation of the image data is equal to or higher than a predetermined gradation (256 gradations). If the determination result is true (Yes), the process proceeds to step S7.
　ステップＳ７において、画像要件判定部２４は、画像データの画像の大きさが所定の大きさ（Ａ４サイズ）以上であるか否かを判定する。当該判定結果が真（Ｙｅｓ）である場合はステップＳ８に進む。 In step S7, the image requirement determination unit 24 determines whether or not the size of the image of the image data is a predetermined size (A4 size) or more. If the determination result is true (Yes), the process proceeds to step S8.
　ステップＳ８において、画像要件判定部２４は、今回取得した書類の画像データは保存要件を満たした画像データとして、当該画像データの読取方式、画像要素、ステップＳ４～Ｓ７の判定結果、等の情報を書類ＤＢ２８に保存し、当該ルーチンを終了する。 In step S8, the image requirement determination unit 24 sets the image data of the document acquired this time as image data satisfying the storage requirement, and obtains information such as a reading method of the image data, an image element, and determination results of steps S4 to S7. It is saved in the document DB 28, and the routine is terminated.
　一方、ステップＳ４～Ｓ７の判定結果のいずれかが偽（Ｎｏ）であった場合、即ち書類の受領日から読取日までの期間（読取日－受領日）が第１の所定期間を超えていた場合、解像度が所定解像度未満であった場合、色の階調が所定階調未満であった場合、又は画像の大きさが所定の大きさより小さかった場合には、ステップＳ９に進む。 On the other hand, when any of the determination results in steps S4 to S7 is false (No), that is, the period from the receipt date of the document to the reading date (reading date-receipt date) exceeds the first predetermined period. In this case, if the resolution is less than the predetermined resolution, the color gradation is less than the predetermined gradation, or the size of the image is smaller than the predetermined size, the process proceeds to step S9.
　ステップＳ９において、アラート処理部２５は、今回取得した書類の画像データは保存要件を満たさなかった画像データとして、ステップＳ４～Ｓ７の判定結果に応じたアラート処理を行い、当該ルーチンを終了する。 In step S9, the alert processing unit 25 performs alert processing according to the determination results of steps S4 to S7, assuming that the image data of the document acquired this time is image data that does not satisfy the storage requirement, and ends the routine.
　また上記ステップＳ２の判定結果が偽（Ｎｏ）であった場合、即ち振分部２１により画像データがカメラによる読取方式と判定された場合には、ステップＳ１０に進む。 If the determination result in step S2 is false (No), that is, if the image data is determined by the distribution unit 21 to be a reading method by the camera, the process proceeds to step S10.
　ステップＳ１０では、ステップＳ３と同様に、画像要素抽出部２２が、画像解析処理により画像データから受領日等の画像要素を抽出する。 In step S10, as in step S3, the image element extraction unit 22 extracts an image element such as a receipt date from the image data by image analysis processing.
　そしてステップＳ１１において、期間判定部２３は画像データ内の書類の受領日から画像データの読取日までの期間（読取日－受領日）が、カメラによる読取方式に定められた第２の所定期間（７営業日）以下であるか否かを判定する。当該判定結果が真（Ｙｅｓ）である場合はステップＳ１２に進み、当該判定結果が偽（Ｎｏ）である場合は上述したステップＳＳ９に進む。 Then, in step S11, the period determination unit 23 has a second predetermined period (reading date-receipt date) defined in the reading method by the camera, from the receiving date of the document in the image data to the reading date of the image data. 7 business days) Determine if it is less than or equal to. If the determination result is true (Yes), the process proceeds to step S12, and if the determination result is false (No), the process proceeds to step SS9 described above.
　これ以降のステップＳ１２～Ｓ１５は、上述したステップＳ５～Ｓ８と同様である。 Subsequent steps S12 to S15 are the same as steps S5 to S8 described above.
　以上のように、本実施形態における電子データ判定システム１では、まず書類の画像データの読取方式を判別して、読取方式に応じて画像データを振り分ける。このように自動的に読取方式に応じて画像データの振り分けを行うことで、１つ１つ人手により画像データの読取方式を確認する手間を省くことができ、且つ人手によるチェックの精度のばらつきを防ぐことができる。 As described above, in the electronic data determination system 1 of the present embodiment, the reading method of the image data of the document is first determined, and the image data is distributed according to the reading method. By automatically sorting the image data according to the reading method in this way, it is possible to save the trouble of manually checking the image data reading method one by one, and to reduce the variation in the accuracy of the check by hand. Can be prevented.
　また、電子データ判定システム１では、書類の受領日から画像データの読取日までの期間が読取方式に応じて定められた所定期間内であるか否かを判定し、所定期間外であると判定された画像データに対してはアラート処理を行うことで、読取方式に応じた保存要件を自動的にチェックし、不備がある場合にはアラート処理されることで、人手によるチェックを最小限に抑えることができる。 Further, the electronic data determination system 1 determines whether or not the period from the date of receipt of the document to the date of reading the image data is within a predetermined period determined according to the reading method, and determines that the period is out of the predetermined period. By performing alert processing on the image data that has been created, the storage requirements according to the reading method are automatically checked, and if there are any deficiencies, alert processing is performed to minimize manual checks. be able to.
　特に、判別する読取方式として、本実施形態のようにスキャナによる読取方式と、カメラによる読取方式とが含まれることで、例えばスキャナによる読取方式とカメラによる読取方式とが同じデータ方式であり区別できない場合であっても、画像解析処理により読取方式を判別し振り分けることができる。 In particular, as the reading method for discrimination includes a reading method using a scanner and a reading method using a camera as in the present embodiment, for example, the reading method using a scanner and the reading method using a camera are the same data method and cannot be distinguished. Even in this case, the reading method can be determined and sorted by the image analysis process.
　また、本実施形態のように、読取方式に応じて定められた所定期間がスキャナによる読取方式に定められた第１の所定期間よりも、カメラによる読取方式に定められた第２の所定期間の方が短く設定されていることで、電子帳簿保存法等に沿った振り分けを行うことができる。 Further, as in the present embodiment, the predetermined period determined according to the reading method is a second predetermined period defined by the reading method by the camera rather than the first predetermined period defined by the reading method by the scanner. By setting the shorter one, it is possible to perform sorting according to the electronic book storage method or the like.
　さらに、画像要件判定部２４により、画像の解像度に基づく要件、画像の色の階調に基づく要件、画像の大きさに基づく要件、等の所定の画像要件を画像データが満たしているかの判定を行い、当該所定の画像要件を満たしていない場合にはアラート処理を行うことで、期間判定部２３による期間の判定だけでなく画像要件の判定も行うことができ、さらに人手によるチェックを削減することができる。 Further, the image requirement determination unit 24 determines whether the image data satisfies predetermined image requirements such as a requirement based on the resolution of the image, a requirement based on the gradation of the color of the image, and a requirement based on the size of the image. By performing alert processing when the predetermined image requirement is not satisfied, not only the period determination unit 23 can determine the period but also the image requirement can be determined, and the number of manual checks can be reduced. Can be done.
　以上のことから、本実施形態に係る電子データ判定システム１は、書類の電子データの保存に際して、書類の電子化の正確性及び作業効率を向上させることができる。 From the above, the electronic data determination system 1 according to the present embodiment can improve the accuracy and work efficiency of digitizing documents when storing electronic data of documents.
　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。 This concludes the description of the embodiment of the present invention, but the embodiment of the present invention is not limited to this embodiment.
　例えば、上記実施形態の電子データ判定システム１は情報端末２と管理サーバ３の２つのコンピュータにより構成されているが、例えば、１つのコンピュータ（例えばＰＣ）のみで構成してもよいし、３つ以上のコンピュータで機能を分割して構成してもよい。 For example, the electronic data determination system 1 of the above embodiment is composed of two computers, an information terminal 2 and a management server 3, but may be composed of only one computer (for example, a PC) or three computers, for example. The functions may be divided and configured by the above computers.
　また、上記実施形態では、電子データとして保存する書類を、電子帳簿保存法に定められる国税関係帳簿書類としているが、保存要件が定められている書類であればその他の書類にも本発明を適用可能である。 Further, in the above embodiment, the documents to be stored as electronic data are the national tax-related book documents stipulated in the Electronic Bookkeeping Law, but the present invention is also applied to other documents as long as the documents have storage requirements. It is possible.
　１　電子データ判定システム
　２　情報端末
　３　管理サーバ
　１０　読取部
　１１　表示部
　２０　画像判別部
　２１　振分部
　２２　画像要素抽出部（受領日抽出部）
　２３　期間判定部
　２４　画像要件判定部
　２５　アラート処理部
　２６　学習システム
　２７　要件ＤＢ
　２８　書類ＤＢ 1 Electronic data judgment system 2 Information terminal 3 Management server 10 Reading unit 11 Display unit 20 Image discrimination unit 21 Distribution unit 22 Image element extraction unit (receipt date extraction unit)
23 Period judgment unit 24 Image requirement judgment unit 25 Alert processing unit 26 Learning system 27 Requirements DB
28 Document DB

Claims (11)

  1. 　書類を読取した画像データから、画像解析処理により当該画像データの読取方式を判別する画像判別部と、
    　前記画像判別部により判別された読取方式に応じて前記画像データの振り分けを行う振分部と、
    を備える電子データ判定システム。     An image discrimination unit that determines the reading method of the image data by image analysis processing from the image data obtained by reading the document, and an image discrimination unit.
    A distribution unit that distributes the image data according to the reading method determined by the image discrimination unit, and a distribution unit.
    Electronic data judgment system equipped with.
  2. 　前記画像データから画像解析処理により書類の受領日を抽出する受領日抽出部と、
    　前記受領日抽出部により抽出された受領日から前記画像データの読取日までの期間が前記読取方式に応じて定められた所定期間内であるか否かを判定する期間判定部と、
    　前記期間判定部により前記所定期間外であると判定された前記画像データに対してアラート処理を行うアラート処理部と、
    をさらに備える請求項１記載の電子データ判定システム。     A receipt date extraction unit that extracts the receipt date of documents from the image data by image analysis processing,
    A period determination unit for determining whether or not the period from the receipt date extracted by the receipt date extraction unit to the reading date of the image data is within a predetermined period determined according to the reading method.
    An alert processing unit that performs alert processing on the image data determined to be outside the predetermined period by the period determination unit, and
    The electronic data determination system according to claim 1.
  3. 　画像判別部により判別する読取方式には、スキャナによる読取方式と、カメラによる読取方式とが含まれる請求項１又は２に記載の電子データ判定システム。 The electronic data determination system according to claim 1 or 2, wherein the reading method for discrimination by the image discrimination unit includes a scanning method using a scanner and a reading method using a camera.
  4. 　前記読取方式に応じて定められた所定期間は、前記スキャナによる読取方式に定められた第１の所定期間よりも、前記カメラによる読取方式に定められた第２の所定期間の方が短い、請求項３に記載の電子データ判定システム。 The predetermined period determined according to the reading method is shorter in the second predetermined period defined in the reading method by the camera than in the first predetermined period defined in the reading method by the scanner. Item 3. The electronic data determination system according to item 3.
  5. 　前記画像データが所定の画像要件を満たしているか否かを判定する画像要件判定部をさらに備え、
    　前記アラート処理部は、前記画像要件判定部により前記所定の画像要件を満たしていないと判定された前記画像データに対してアラート処理を行う、請求項２から４のいずれか一項に記載の電子データ判定システム。     Further, an image requirement determination unit for determining whether or not the image data satisfies a predetermined image requirement is provided.
    The electron according to any one of claims 2 to 4, wherein the alert processing unit performs alert processing on the image data determined by the image requirement determination unit to not satisfy the predetermined image requirement. Data judgment system.
  6. 　前記所定の画像要件は、画像の解像度に基づき定められている請求項５に記載の電子データ判定システム。 The electronic data determination system according to claim 5, wherein the predetermined image requirement is defined based on the resolution of the image.
  7. 　前記所定の画像要件は、画像の色の階調に基づき定められている請求項５又は６に記載の電子データ判定システム。 The electronic data determination system according to claim 5 or 6, wherein the predetermined image requirement is defined based on the color gradation of the image.
  8. 　前記所定の画像要件は、画像の大きさに基づき定められている請求項５から７のいずれか一項に記載の電子データ判定システム。 The electronic data determination system according to any one of claims 5 to 7, wherein the predetermined image requirement is defined based on the size of the image.
  9. 　書類を読み取りした画像データから、画像解析処理により当該画像データの読取方式を判別する画像判別部と、
    　前記画像判別部により判別された読取方式に応じて前記画像データを振り分けて保存する振分部と、
    を備える電子データ判定装置。     An image discrimination unit that determines the reading method of the image data by image analysis processing from the image data obtained by reading the document, and an image discrimination unit.
    A distribution unit that distributes and stores the image data according to the reading method determined by the image discrimination unit, and a distribution unit.
    An electronic data determination device comprising.
  10. 　書類を読取した画像データから、画像解析処理により当該画像データの読取方式を判別する画像判別ステップと、
    　前記画像判別部により判別された読取方式に応じて前記画像データを振り分けて保存する振分ステップと、
    　をコンピュータが実行する電子データ判定方法。     An image discrimination step for discriminating the reading method of the image data by image analysis processing from the image data obtained by reading the document, and an image discrimination step.
    A distribution step of distributing and storing the image data according to the reading method determined by the image discrimination unit, and
    An electronic data determination method performed by a computer.
  11. 　書類を読取した画像データから、画像解析処理により当該画像データの読取方式を判別する画像判別ステップと、
    　前記画像判別部により判別された読取方式に応じて前記画像データを振り分けて保存する振分ステップと、
    　をコンピュータに実行させる電子データ判定プログラム。

          An image discrimination step for discriminating the reading method of the image data by image analysis processing from the image data obtained by reading the document, and an image discrimination step.
    A distribution step of distributing and storing the image data according to the reading method determined by the image discrimination unit, and
    An electronic data judgment program that causes a computer to execute.
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