JP2012221183A - Receipt data recognition device and program therefor - Google Patents

Abstract

PROBLEM TO BE SOLVED: To correctly and efficiently collect sales management data from an individual tenant shop and improve a speed and efficiency in sales management work at the tenant.SOLUTION: For a recognition character read from a receipt image, a receipt data extraction part 141 extracts a recognition character from a character string of an item name that is registered in definition data different for each shop and is shown on a receipt and from positional data of a money-amount item shown at an intra-receipt position; an inclination detection part 142 detects an inclination of the recognition character from the positional data of the extracted recognition character; an inclination correction part 143 corrects, if an inclination of the recognition character is detected, the positional data of the applicable money-amount item in accordance with the detected inclination; a receipt data identification part 144 extracts a recognition character representing the money-amount item from the recognition character and the positional data using the corrected positional data; and a sales management data generation part 15 outputs, or stores, data of the recognition result based on a recognition character matching the item name and the recognition character representing the money-amount item.

Description

  The present invention relates to a receipt data recognition apparatus and a program thereof, and more particularly to a technique for accurately extracting necessary data from receipt data read by character recognition in order to manage sales at a plurality of stores such as a shopping mall. It is.

  The tenant management department that manages stores of tenants (such as companies that operate stores) that open stores in shopping centers, shopping malls, etc. collects daily sales for each store, and breakdowns of sales such as cash sales, coupon sales, etc. ( Sales management item). When creating the sales breakdown, payment receipts provided from each store are collected and the numerical value of the sales management item is calculated. However, since the format of the payment receipt provided from each store depends on the POS system installed in each store, it is currently created in various formats. Therefore, the payment receipt processed by the tenant management department has a wide variety of items, item names, print sizes, print fonts, and the like.

  For example, regarding the names of the items on the payment receipt, even though the total sales, total sales, total sales, total sales, etc. indicate the same contents, different names are printed depending on the POS system. In addition, since the tenant's store that opens a store is frequently replaced, a new payment receipt format must also be supported. For this reason, the tenant management department currently requires enormous labor for the work of totaling the payment receipts as unified sales data, and the human and time burden for that is enormous. is there.

  Note that Patent Document 1 discloses a document image recognition apparatus. In this document image recognition apparatus, a set of components constituting a character is extracted with reference to a document image, horizontal and vertical line candidates are extracted based on the set, and reliability is estimated for the line candidates. Thereafter, a set of lines with high accuracy is extracted based on the estimated line reliability, and the inclination is estimated using the arrangement of the character components of the set of lines with high accuracy based on the result. Then, a line set with a fixed line direction is extracted from the set of basic elements that make up the document image, and a line and a stage are extracted by associating the lines with each other and performing a line extraction with a stage as a constraint. To do.

  Patent Document 2 discloses a receipt processing apparatus. In this receipt processing apparatus, text data is generated by recognizing characters from the receipt image, a predetermined character string is selected from the text data, and a line position including the selected predetermined character string is detected. Then, line data in units of lines is sequentially selected from a predetermined line range on the text data determined based on the detected line position, and data relating to the item is extracted from the line data.

JP 11-219407 A JP 2004-164218 A

  In the tenant management department of a company (organization) that operates a shopping center or the like, the clerk has traditionally used to collect the payment receipts (hereinafter referred to as receipts) provided by each store such as a shopping center. The receipt was read visually, and the read data was manually input to the data processing device. The work amount of the sales totaling work is very heavy because the number of stores may reach 100 stores or more and must be performed every day.

  As a proposal for reducing this burden, it is conceivable to automatically collect sales data (receipt data) of each store from a terminal of each store via a network. However, in general, each store has a different corporate body, so it is necessary to obtain permission to open the network individually, and the type of network to be connected and the difficulty of adding / modifying applications differ depending on the installed system. There are difficult problems.

  Another way to reduce the above-mentioned work load by changing the existing system, especially information devices such as terminals in each store as much as possible, is to recognize character images instead of reading receipt data by humans. The reading method can be considered. That is, the receipt of each store is read by, for example, a reader or scanner having an OCR (Optical Character Recognition) function, and the necessary receipt items and their numerical data are extracted as sales management items, and the sales management data is extracted. This is a method to re-enter.

  However, even in this method, it is necessary to solve a problem that cannot be solved by the conventional recognition of character images. Next, this problem will be described.

  When a receipt is read by a reading device or the like having an OCR function, the reading device or the like needs to be read in a state where the receipt is fixed by being sandwiched between transparent sheets or attached to paper or the like.

  For example, a receipt sandwiched between transparent sheets or the like is in the form of an elongated slit, and when it is read, the settlement receipt (receipt) sandwiched may be inclined with respect to the sheet. In addition, a receipt sandwiched between sheets or the like may not be inclined at a constant angle, but may be inclined at a different angle from the middle. In addition, when printing, the printed item may have more space than the previous line item on the line in the middle of the receipt due to misalignment of the paper feed or improper adjustment. May have. In addition, the paper may be partially bent and fixed in the middle of the receipt.

  FIG. 15 is a diagram for explaining an example in which erroneous recognition occurs in the receipt OCR process. As shown in FIG. 15, for example, when the receipt 22u is a long sheet, the paper may be partially bent and inclined midway from the receipt upper part 221u to the receipt lower part 222u. In this state, when the receipt 22u sandwiched between the sheets is read by the reading device and subjected to OCR processing, the correspondence between the item name and the amount in the receipt item is not read in the line of the correct correspondence, and the item name and the amount May be read in different row relationships. As a result, the amount of the receipt item may be misrecognized as the amount of another receipt item, and sales may be aggregated.

  FIG. 16A shows an example when the amount of the receipt item is not erroneously recognized, and FIG. 16B shows an example when the amount of the receipt item is erroneously recognized.

  In FIG. 16A, the receipt lower part 222v inclined in the receipt 22v is shown. It is assumed that the inclination angle α1 (the angle with respect to the broken line in the figure) of the receipt 22v from the reference direction Lb is a range in which the amount of the receipt item is not erroneously recognized. For example, the amount item Dat # 101 corresponding to the receipt item name “total sales” (Str # 101 shown in the figure) in the receipt lower item 222v is “¥ 654,735”, and “total sales ¥ 654” is obtained by OCR processing. , 735 ".

  On the other hand, FIG. 16 (B) shows an inclined receipt lower portion 222w in the payment receipt 22w. It is assumed that the inclination angle α2 (angle with respect to the broken line in the figure) of the receipt 22w from the reference direction Lc is a range in which the amount of the receipt item is erroneously recognized. For example, the amount item Dat # 102 corresponding to the receipt item name “total sales” (Str # 102 shown in the figure) in the lower portion 222w of the receipt is correctly “¥ 654,735”. As a result, it is misrecognized as “total sales ¥ 623,603”.

  The cause of this misrecognition is that the output of the OCR processing result is only the character strings of each item and their coordinate information. The character item “at 623,603” of the amount item Dat # 102 corresponding to the item name “net sales” to be placed on the same line as the receipt item name “total sales” due to the inclination angle α2 This is because it is recognized as a column.

  When the entire receipt 22 has the same inclination angle with respect to the reference direction, as a solving means, the OCR process detects the inclination angle of the entire receipt 22 and corrects the inclination of the entire receipt line. Therefore, the correct amount can be extracted. However, in the case shown in FIG. 15, when the receipt upper portion 221u has a small inclination angle and the receipt lower portion 222u is inclined at a midway portion, the receipt angle of the entire receipt 22u is detected and corrected. , As shown in FIG. 15, it cannot be applied when some of the rows have different slopes.

  As described above, when such a receipt 22u is read by a reading device or the like and the receipt numerical data is subjected to OCR processing, a monetary item that does not correspond to the receipt item name may be processed. As a result, an aggregation error occurs in the sales management data. For this check, it is necessary to manually check the payment receipt, and the human burden is not reduced.

  In view of the above, the present invention collects sales management data accurately and efficiently from the receipts of each tenant's store without significantly changing the current system of each store's information device, etc. The purpose is to improve efficiency and efficiency.

  In the present invention, for example, in order to recalculate receipts printed for each store into a unified sales management item, recognition characters obtained by reading receipt images are registered in different definition data for each store that issued the receipt. The necessary recognition characters are extracted from the character string of the item name in the received receipt and the relative position data of the monetary item from the position in the receipt, and the inclination of the recognition character is detected from the extracted position data of the recognition character When the inclination of the recognized character is detected, the relative position data of the corresponding monetary item is corrected according to the detected inclination, and the amount of money is calculated from the recognized character and its position data using the corrected relative position data. A recognition character representing an item is extracted, and recognition result data is output or stored from a recognition character that matches the item name and a recognition character that represents a monetary item.

  In other words, when the receipt image is read by a reader, the receipt is in the form of a long and narrow slit. Therefore, even if the receipt is tilted or tilted from the middle of the receipt, the items and the amount in the receipt are accurate. Can be read, and only necessary items are accurately extracted from receipts printed in different formats, and the items and amounts in the receipts necessary for sales management are recognized data. Can be output or stored as. Specifically, the present invention includes the following means.

  (1) The present invention provides an image data storage unit for storing a recognized character obtained by character recognition of a receipt image and its position data, and a character string of an item name printed on the receipt. And a definition data storage unit for storing definition data defined for each item name to be read in the receipt, relative position data of the amount item corresponding to the item name from the position in the receipt of the item name , A receipt data extracting unit that extracts a recognized character that matches the character string of the item name defined in the definition data from the recognized character stored in the image data storage unit, and a recognition from the extracted recognized character position data Relative position data of the corresponding monetary item in the definition data when the inclination detector for detecting the inclination of the character and the inclination of the recognized character are detected , Using a tilt correction unit that corrects the detected tilt according to the detected tilt, and using the corrected relative position data, a recognition character stored in the image data storage unit and a recognition character representing the amount item are extracted from the position data. A receipt data specifying unit that generates a recognition result data from a recognition character that matches the item name and a recognition character that represents the amount item, and outputs or stores the recognition result data. It is characterized by.

  As a result, for the receipt item to be converted into the sales management item inputted in advance, the item name and the relative position of the corresponding money amount column are registered in the definition data, and the inclination of the recognized character read from the receipt image is detected. Therefore, even if there is a tilt of the recognized character, the relative position of the amount column corresponding to the item name can be corrected by correcting the tilt of the recognized character, and the receipt required for the sales management item accurately. You can read the amount of the item.

  (2) Further, according to the present invention, in the above invention, the receipt is a receipt printed in a format different for each store, and the definition data storage unit stores the definition data for each store. The receipt data extracting unit, the tilt detecting unit, the tilt correcting unit, the receipt data specifying unit, and the data generating unit are executed using different definition data for each store that issued Features.

  As a result, even if the item name and print position of the receipt printed at each store are different, the item name and the relative position of the corresponding amount field are registered in the definition data for each store. The necessary receipt data can be read from the receipt image regardless of the difference between the receipt item name and the position of the corresponding money amount column.

  (3) Further, according to the present invention, in the above invention, the definition data stored in the definition data storage unit corresponds to the character string of the item name printed on the receipt and is used for sales management of a plurality of stores. Including data on sales management item names used in common, and the data generation unit converts recognition character data that matches the item names into corresponding sales management item names defined in the definition data. It is characterized by generating.

  As a result, even if the item name and print position of the receipt printed at each store are different, the item name and the corresponding amount for each receipt item to be converted into the sales management item input in advance. Regardless of the difference between the receipt item name for each store and the position of the corresponding monetary amount column, the necessary receipt data is read from the receipt image and unified sales management data is generated to register the relative position of the column in the definition data. can do.

The effects of the present invention are as follows.
(1) By registering the receipt items necessary for sales management items from the receipt in advance in the definition data, the necessary receipt data can be automatically extracted using them. And speeding up can be achieved.
(2) Using the definition data registered and set in advance for each store, what kind of receipt it has, what item name it has, and information such as relative position with respect to the amount of money is used for image analysis Reading accuracy, including character recognition.
(3) Since the inclination of the character string can be detected for each of the recognized characters read from the receipt and the relative position with respect to the amount of the definition data can be corrected using them, the inclination of some lines of the receipt can be corrected. In some cases, it is possible to avoid erroneous recognition of receipt data extraction and to extract correct receipt data. For this reason, it is possible to further improve the reading accuracy including character recognition. In addition, since recognition errors can be reduced, labor saving and speeding up of the check work can be achieved.
(4) Further, basic data required by the sales management department can be uniformly collected from the receipt data of each store having different receipt items, and stored in a sales management database or the like.

It is a figure which shows the apparatus structural example of embodiment of this invention. It is a figure explaining the sheet | seat for receipt clamping. It is a figure which shows the example of the correspondence of a sales management item and a receipt item. It is a process flowchart of the receipt data recognition apparatus which concerns on embodiment of this invention. It is a figure which shows the example of a receipt image. It is a figure which shows an example of recognition character data. It is a figure which shows the example of a recognition character table. It is a figure explaining a definition data table. It is a flowchart of a receipt data process. It is a flowchart of an inclination correction process. It is a figure explaining an inclination detection process and an inclination correction process. It is a figure which shows an example of the specified receipt data. It is a flowchart of a sales management data generation process. It is a figure which shows the example of sales management DB. It is a figure explaining the subject of this invention. It is a figure explaining the subject of this invention.

  Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings. In the following, an example of an apparatus for totalizing store sales will be described. However, the present invention is not limited to sales totalization, and totals actual data printed on purchase total data or other slips. The present invention can be applied to a device for the same.

  FIG. 1 shows an apparatus configuration example for explaining the outline of the present invention. In FIG. 1, reference numeral 1 is composed of a CPU and a storage device such as a hard disk and a memory, etc., and a receipt data recognition device for executing processing relating to sales aggregation based on data read from a receipt, and 20 is associated with each store. This is a receipt holding sheet that is marked with the identification code 21 (shown in FIG. 2) and holds the receipt 22 (shown in FIG. 2) of each store. The receipt 22 is a receipt printed in a different format for each store.

  The receipt 22 is printed for each tenant's store, for example, the result of totaling the sales of the store in one day using a cash register provided in each store. Further, these receipts 22 are shown as an example related to sales aggregation, and may be related to purchase aggregation and other form processing in addition to sales aggregation.

  First, the receipt clamping sheet 20 will be described. FIG. 2 is a diagram showing a configuration of one embodiment of the receipt clamping sheet 20. 2A is a top view of the receipt sandwiching sheet 20 as viewed from the transparent film 231 side, and FIG. 2B is a receipt sandwiching sheet 20 in which the receipt 22 is sandwiched by the transparent sheet 23. FIG. It is a perspective view explaining the previous state.

  As shown in FIG. 2A, for example, the receipt holding sheet 20 holds a receipt 22 of each store on a transparent sheet 23 with a mount. In the upper right corner of the transparent sheet 23, an identification code 21 (two-dimensional code such as QR code (registered trademark)) corresponding to the store is printed or marked with a seal or the like.

  As shown in FIG. 2B, the transparent sheet 23 is, for example, a transparent film (sheet) 231 and a mount 232 connected (adhesive or the like) at one end 233, and in a state before the receipt 22 is sandwiched, 23 is in a half-opened state. The receipt 22 is placed on the mount 232 of the transparent sheet 23 in the semi-opened state, and the receipt 22 is sandwiched, for example, by adhering the mount 232 and the transparent film 231 having a slightly adhesive surface. The above-described identification code 21 is marked by printing, sticking, or the like within a range positioned at the upper right corner of the mount 232, for example.

  Next, the correspondence relationship between the receipt items in the receipt 22 for each store and the sales management items counted by the tenant management department, which is processed by the receipt data recognition apparatus 1, will be described.

  FIG. 3 is a diagram illustrating an example of a correspondence relationship between sales management items and receipt items. In the example of FIG. 3, the sales summary data actually required by the tenant management department for store sales management is “No. No. 1 cash sales 11 sales management items up to 11 customers. However, these sales management items are not printed as a one-to-one relationship as receipt items of the receipt 22 of each store. Therefore, processing for calculating each of the eleven sales management items from the receipt item of each store is performed using correspondence information 1022 (1022a) for each store.

  In the case of the receipt 22 a shown in FIG. 3, the “cash sales amount” of the 14th receipt item is “No. Correspondence information 1022 (1022a) indicates that it corresponds to “cash sales” of one sales management item. Other sales management items are also associated with each other by the correspondence information 1022. The correspondence information 1022 between the sales management item and the receipt item for each store as shown in FIG. 3 is registered and stored in advance in the definition data storage unit 102 (shown in FIG. 1).

  In FIG. 3, the receipt item shown in the receipt 22a is, for example, 14th “cash sales amount” or the like, but in actuality, the 14th (nth) row is fixed from the top position in the receipt. Is not in the position. Depending on the result of receipt collection on the day of the store, the number of print lines increases in the nth or earlier receipt items, or there are receipt items that are omitted during printing. For this reason, in the receipt data recognition device 1, definition data including the receipt item name in the receipt item and the relative position of the corresponding amount item (relative amount field position) is registered in advance and used together with the correspondence information 1022. In this way, the above problems are solved.

  The receipt data recognition apparatus 1 determines the “sales date” and the sales management item No. for each store code according to the definition data and the correspondence information 1022 as described above. 1 “Cash Sales”, No. 1 2 “Multiple sales”, No. 2 3 Amounts corresponding to items related to sales such as “credit sales”,... Are aggregated and stored in the sales management data storage unit 103. For this purpose, the receipt data recognition apparatus 1 executes processing described below.

  The receipt data recognition device 1 reads a receipt 22 from a receipt holding sheet 20. The receipt data recognition device 1 uses the definition data for the receipt 22 to extract receipt data including the item name and amount in the receipt item. The receipt data recognition apparatus 1 converts the extracted receipt data item into sales management data using the correspondence information 1022 between the sales management item and the receipt item. That is, receipt items necessary for the sales management data are extracted, and the amounts of the receipt items are aggregated as sales management data.

  As described above, the receipt data recognition device 1 executes the receipt data recognition process using the definition data for each store that issued the receipt 22.

  The configuration of the receipt data recognition apparatus 1 shown in FIG. 1 for executing the receipt data recognition process described above will be specifically described below.

  The image data storage unit 101 stores the image data of the receipt sandwiching sheet 20 read by the reader 10. The image data is data including a recognized character and its coordinates (position data) obtained by performing OCR processing on the image of the receipt 22. Furthermore, the image data may include an identification code 21. The image data storage unit 101 may store an image file of the receipt sandwiching sheet 20 such as a bitmap format file in association with the image data.

  The definition data storage unit 102 is a storage unit that stores definition data used in the receipt data recognition apparatus 1. The definition data includes information such as the receipt item of the receipt 22 and the position of the amount for each store.

  Specifically, in the definition data, sales management item names that are commonly used for sales management of a plurality of stores are registered corresponding to the character string of the receipt item name printed on the receipt 22. For example, the definition data includes a receipt item name character string printed on the receipt 22 and a relative position data of a monetary item corresponding to the receipt item name from the position in the receipt of the receipt item name. Defined for each receipt item name to be read. Such definition data is created in advance for each receipt 22 of the store to be tabulated and stored in the definition data storage unit 102. Details of the definition data will be described later with reference to FIG.

  The sales management data storage unit 103 is a storage unit that stores sales management data generated by the receipt data recognition apparatus 1. The sales management data is data obtained as a result of collecting the amounts of the receipt items of each store in association with the sales management items in which the receipt items different for each store are unified. Details of the sales management data will be described later with reference to FIG.

  The reader 10 is an apparatus that reads an image on the receipt sandwiching sheet 20 by using an optical method or the like for image scanning. When the receipt holding sheet 20 is input, the reader 10 converts the receipt holding sheet 20 into image data. The image data includes, for example, an image file and character data recognized by OCR. The reader 10 stores the converted image data in the image data storage unit 101. For example, the reader 10 is based on a known technique such as a scanner or an OCR processing device.

  The image data reading unit 11 reads the image data stored in the image data storage unit 101. Note that the image data reading unit 11 may input image data from an input device external to the receipt data recognition device 1. The external input device is a reading device, a network device, or the like. In this case, an input device (not shown) inputs the image data of the receipt sandwiching sheet 20 input by a reading device installed at a location other than the installation location of the receipt data recognition device 1 via a network or the like. And stored in the image data storage unit 101.

  The store specifying unit 12 specifies the store code (or store) by identifying the identification code 21 of the receipt sandwiching sheet 20. In the configuration example of FIG. 1, the identification code 21 for the store code is formed as a recognition mark on the receipt sandwiching sheet 20, but the method of reading the store code is not limited to this embodiment. For example, when reading the receipt 22, the user may input the store code via an external input device such as a numeric keypad or a card reader. In that case, the store specifying unit 12 receives a store code input from an external input device. Alternatively, the reader 10 may read the identification code 21 of the receipt holding sheet 20 and the store specifying unit 12 may specify the store code from the read identification code 21.

  When the definition data reading unit 13 receives the store code specified by the store specifying unit 12, the definition data reading unit 13 searches the definition data storage unit 102 for definition data associated with the store code. The definition data reading unit 13 reads the definition data retrieved from the definition data storage unit 102 and sends the read definition data to the receipt data processing unit 14.

  The receipt data processing unit 14 uses the definition data for each store code to extract receipt data including the receipt item name and its amount from the image data, and specifies the receipt data required for the sales management item from the extracted receipt data. To do. For this purpose, the receipt data processing unit 14 includes the following functional units as shown in FIG.

  The receipt data extraction unit 141 searches the recognized character data of the image data stored in the image data storage unit 101 for a recognized character that matches the character string of the receipt item name defined in the definition data, and uses the recognized character data. Extract. The recognized character data includes a value indicating a difference between a candidate character by a dictionary (not shown) provided in the receipt data recognition device 1 in advance and a recognized character by OCR processing, and a relative coordinate position (relative position) indicating a character range. )including. The recognized character data will be described later with reference to FIG.

  The inclination detecting unit 142 detects the inclination of the recognized character using the relative position of the recognized character in the extracted recognized character data. For example, in order to detect the inclination of the recognized character, the inclination detecting unit 142 detects the deviation of the relative position with respect to the reference direction in advance for one or more recognized characters that match the character string of the receipt item name. Ask. The inclination detection unit 142 obtains an angle formed by the direction of the relative position shift with respect to a reference direction in advance as an inclination angle. A method for detecting the inclination will be described later with reference to FIG.

  When the inclination of the recognized character is detected, the inclination correction unit 143 refers to the definition data, and determines the relative position of the amount item corresponding to the recognized character that matches the character string of the receipt item name. Correct according to the angle. On the other hand, when the inclination of the recognized character is not detected, the inclination correction unit 143 does not correct the relative position of the amount item corresponding to the recognized character that matches the character string of the receipt item name.

  When receiving the relative position of the amount item corresponding to the receipt item name from the inclination correcting unit 143, the receipt data specifying unit 144 corresponds to the relative position of the amount item from the recognized characters stored in the image data storage unit 101. The recognition character to be extracted is extracted. Accordingly, the receipt data specifying unit 144 can accurately specify the amount item corresponding to the receipt item name.

  The sales management data generation unit 15 generates sales management data using the receipt data specified by the receipt data processing unit 14. Specifically, the sales management data generation unit 15 recognizes using the recognition character that matches the receipt item name and the correspondence information 1022 that is associated with the corresponding sales management item name defined in the definition data. Calculate (convert) the numerical data of the monetary item in the result to generate sales management data. The sales management data includes a store code, a sales management item, and an amount corresponding to the sales management item.

  For example, the sales management data generation unit 15 sets the “sales date”, the sales management item No., for each store code in accordance with the correspondence information 1022 between the sales management item and the receipt item. 1 “Cash Sales”, No. 1 2 “Multiple sales”, No. 2 3 Converts the amount corresponding to the item related to sales such as “credit sales”,... And stores them in the sales management data storage unit 103.

  In the following, the detailed functions of the receipt data recognition apparatus 1 shown in FIG. 1 will be described with reference to the processing flowcharts of FIGS. 4, 9, 10 and 13 while also using other figures.

  FIG. 4 is a process flowchart of the receipt data recognition apparatus 1 according to the embodiment of the present invention. The processing executed by the receipt data recognition apparatus 1 will be specifically described with reference to FIG.

  The receipt data recognition apparatus 1 is activated and this process is started. When the receipt holding sheet 20 is input to the reader 10, the reader 10 reads the receipt holding sheet 20, and stores the read image data of the receipt holding sheet 20 in the image data storage unit 101 (step S11). ).

  For specific description, a character string that is OCR processed from receipt image data will be described with reference to FIGS.

  FIG. 5 shows an example of an image of the receipt 22b read by the reader 10. The image data generated by the reader 10 includes recognized character data by OCR processing. When the image of the receipt 22 (22b) is OCR processed, the reader 10 generates recognized character data and stores it in the image data reading unit 11. The recognized character data includes the number of characters of the character string composed of the recognized characters and the coordinates of the character string, the coordinates of the characters constituting the character string, and a recognized character list that is a candidate character from the dictionary. Recognized characters by the OCR process are character string # 1, character string # 2,..., Character string # 14,. For example, the character string # 14 is “total sales”.

  FIG. 6 is a diagram showing an example of recognized character data by OCR processing. In particular, FIG. 6 shows the recognized character data 110 of the character string # 14 “total sales” shown in FIG.

  In FIG. 6, the recognized character data 110 includes the number of characters 3 and the coordinates (x, y) − (x ′, y ′) of the character string # 14 “total sales”. The recognized character data 110 also includes the coordinates of the three characters of character # 141 “total”, # 142 “sell”, and # 143 “upper” that constitute character string # 14. For example, the coordinates of the character # 141 “total” are (x1, y1) − (x′1, y′1), and the other characters are as illustrated. Note that (x, y) − (x ′, y ′) and the like represent the coordinates of the illustrated rectangular frame, and (x, y) is the upper left as viewed from the paper, and (x ′, y ′). Is the coordinate corresponding to the lower right. For example, the upper left is the direction toward the coordinate origin, and the lower right is the direction away from the origin coordinates. The coordinate origin is, for example, a specific position of the image on the receipt holding sheet 20.

  Further, the recognized character data 110 includes a recognized character list of three characters of character # 141 “total”, # 142 “sell”, and # 143 “upper”. The recognized character list stores the recognized characters that are candidates and the degree of difference (or degree of coincidence) between the recognized characters and the read characters in accordance with the recognition order that is the candidate character from the dictionary. For example, in the recognized character list of the character # 141 “total”, the rank “1” is the recognized character “total” and the dissimilarity “1311”, the rank “2” is “fragile”, and the dissimilarity is “1581”. Yes, other rankings are shown in the same way. The degree of difference indicates that, for example, a numerical value closer to 0 indicates a higher degree of matching with a candidate character (not shown) provided in advance, and a higher value indicates a higher degree of difference from the dictionary candidate character. The recognized character lists of the characters # 142 “Sell” and # 143 “Up” are also as shown in FIG.

  FIG. 7 is a diagram illustrating an example of the recognized character table 1011 stored in the image data storage unit 101. The recognized character table 1011 is a table that stores recognized character data for each read image data. Further, the recognized character table 1011 includes recognized character data for each recognized character string of the receipt 22. The recognized character data is as described above.

  The recognized character table 1011 shown in FIG. 7 stores recognized character data such as character strings # 1 to # 14,... Shown in FIG. For example, the character string # 14 “total sales” and the characters # 141 “total”, # 142 “sell”, and # 143 “upper” constituting the character string # 14 are stored in the recognized character table 1011. Other character strings are stored in the same manner. Note that the definitions of items, settings, etc. in the recognized character table 1011 shown in FIG. 7 are the same as those of the recognized character data in FIG.

  Next, when the image data reading unit 11 reads the image data from the image data storage unit 101, the store specifying unit 12 determines the identification code 21 of the receipt sandwiching sheet 20 from the image data, and from the determined identification code 21. The store code is read (step S12).

  Specifically, the store specifying unit 12 decodes a QR code or the like, for example, and specifies a store code or an identification number associated with the store code from the decoded data. The QR code may be decoded by the reader 10 and the store code may be specified from the data decoded by the store specifying unit 12, and the specifying method is not limited.

  Next, upon receiving the store code specified by the store specifying unit 12, the definition data reading unit 13 acquires definition data associated with the store code from the definition data storage unit 102 (step S13).

  Specifically, FIG. 8 is a diagram illustrating the definition data table 1021. Hereinafter, an example of the definition data acquired by the definition data reading unit 13 will be described with reference to FIG.

  A receipt 22t shown in FIG. 8 is a part of an image of a receipt 22 (referred to as a reference receipt) prepared for creating definition data of a certain store. In FIG. 8, a definition data table 1021 stores definition data created in advance and is stored in the definition data storage unit 102. The receipt 22t displays the line number, receipt item name, and amount. From this receipt 22t, it is assumed that “cash sales amount” on the 14th line (BX14) and “other voucher amount” on the 18th line (BX18) are the receipt items to be extracted.

  In the definition data table 1021, receipt items to be extracted are registered as definition data. In order to create the definition data in advance, a reference receipt (receipt 22t) used as a reference for each store is used, and definition data for the receipt 22 for each store is created based on the reference receipt.

  The definition data table 1021 stores “read item”, “item attribute”, “read character”, and “read position of the money amount column” for each target store code and receipt item to be extracted. “Store code” is an identification number for each store corresponding to the store of the target receipt. “Read item” is the name of a sales management item. “Item attribute” is an attribute of a receipt item name to be read. The attribute is, for example, a value of “1”, “2”, or “3”. “1” indicates that the receipt item name corresponding to the sales management item is not duplicated in the standard receipt (ordinary item), “2” indicates that there is an identical duplicate name and an anchor character is set, and “3” "" Is an attribute when there are duplicate names and multiple keywords are set. “Reading character” is a receipt item name printed on the reference receipt corresponding to the sales management item. The “reading position in the amount field” is a relative position of the amount (including numerical characters, currency symbols, etc.) of the receipt item from the reading character.

  In the receipt 22t that is the reference receipt shown in FIG. 8, the image position BX14 includes character strings Str # 1 and Dat # 1 that are “cash sales amount” and “¥ 139,639”. The relative distance between the character string Str # 1 and the character string Dat # 1 is set to Dis # 1. In the image position BX18, there are character strings Str # 2 and Dat # 2 that are “other money voucher amount” and “¥ 8,000”. The relative distance between the character string Str # 2 and the character Dat # 2 is set to Dis # 2.

  The definition data table 1021 shown in FIG. 8 stores definition data created from the receipt 22t shown in FIG. As shown in FIG. 8, “store code”: “100001” is set in the definition data table 1021 as a store code that is a target of the reference receipt. “Read item # 1”: “cash sales” is a result of setting the item name “cash sales” in the sales management items. “Item attribute # 1”: “1” is a result of setting the above-described normal item. “Reading character # 1”: “cash sales amount” is a result of setting the character string Str # 1 at the image position BX14 of the receipt 22t. “Money amount reading position # 1”: “(x11, y11) − (x′11, y′11)” is a character as a relative distance Dis # 1 between the character string Str # 1 and the character string Dat # 1. This is a result of setting the relative position of the position of the character string Dat # 1 from the position of the string Str # 1. As relative positions, the upper left coordinates (x11, y11) and the lower right coordinates (x'11, y'11) of the rectangular frame of the illustrated character string Dat # 1 are stored. These coordinates are relative coordinates. Other definition data is stored in the same manner. Note that #n in the definition data table 1021 shown in FIG. 8 is an identifier for distinguishing the setting items of a plurality of definition data, and n is an integer such as 1, 2.

  The definition data table 1021 described above is referred to via the definition data reading unit 13 when the receipt data extraction unit 141 extracts receipt data. The receipt data extraction unit 141 extracts receipt items for the read image data (recognized characters of the receipt 22) based on the definition data stored in the definition data table 1021. That is, the receipt data extraction unit 141 can determine the receipt item to be extracted based on the definition data of the reference receipt.

  Actually, even when the payment receipt (receipt 22) is printed by the same POS system, some receipt items in the middle may be skipped (dropped) depending on the output at that time. . Accordingly, if the “reading position of the amount column” in the definition data table 1021 is created with fixed coordinates, it is not possible to cope with a case where such a part of receipt item is skipped and printed. Therefore, as in the definition data table 1021 shown in FIG. 8, by using the coordinate position of the relative position from the character string position of the receipt item name as the definition data, printing such a part of the receipt items is skipped. It can correspond to. In FIG. 8, the receipt item name and the corresponding amount of money are printed on the same line. However, the receipt item name and the corresponding amount of money may be on different lines. In that case, the relative position of the amount of money in the different rows is registered in the definition data.

  Next, when the receipt data processing unit 14 receives the definition data associated with the store code from the definition data reading unit 13, the receipt data processing unit 14 executes receipt data processing (step S14). A detailed flow of the receipt data processing will be described later with reference to FIG.

  After receipt data processing is performed by the receipt data processing unit 14, the sales management data generating unit 15 generates sales management data from the processed receipt data. The sales management data generation unit 15 stores the generated sales management data in the sales management data storage unit 103 (step S15). After storing the sales management data, the receipt data recognition apparatus 1 ends this processing. The detailed processing flow of step S15 will be described later with reference to FIG.

  The processing flow described above is the overall processing flow executed by the receipt data recognition apparatus 1.

  FIG. 9 is a detailed process flowchart of the receipt data process in step S14 shown in FIG. The receipt data processing executed by the receipt data processing unit 14 will be specifically described with reference to FIG.

  The receipt data extraction unit 141 extracts only the item name of the line targeted for the receipt 22 from the image data (step S21).

  Specifically, upon receipt of image data (recognized character data) from the image data reading unit 11, the receipt data extraction unit 141 extracts only the item name from the first line of the receipt 22. For example, in the case of the image data of FIG. 5, the character string # 1 “October 10, 2010 (Sunday) 22:30 No: 0002” of the receipt 22b is extracted. Character string # 2 “**”,..., Character string # 7 “sales”, character string # 8 “297 points”, character string # 9 “¥ 226,701”,. Not extracted. In step S21, the item name including the receipt item name, amount, symbol (for example, “**”) is extracted.

  Next, the receipt data extraction unit 141 refers to the definition data stored in the definition data table 1021 (step S22).

  Specifically, the definition data reading unit 13 reads definition data corresponding to the store code from the definition data table 1021 stored in the definition data storage unit 102. The definition data reading unit 13 sends the read definition data to the receipt data extraction unit 141. The receipt data extraction unit 141 uses the definition data sent from the definition data reading unit 13 in the processing from step S23. The receipt data extraction unit 141 stores the definition data sent from the definition data reading unit 13 in a work memory (not shown), and refers to the definition data on the work memory.

  Next, the receipt data extraction unit 141 checks whether or not the extracted item name is set in the definition data (step S23).

  Specifically, the receipt data extraction unit 141 determines whether there is a match among the read characters #n (n is an integer) in the definition data table 1021 for the character string # 14 “total sales” shown in FIG. To check.

  Next, when it is set in the definition data (step S23: Yes), the inclination detection unit 142 calculates an inclination for the recognized character that matches the read character of the definition data (step S24). On the other hand, if it is not set in the definition data (step S23: No), the process proceeds to step S28.

  Specifically, the inclination detecting unit 142 detects the inclination from the y coordinate of the recognized character that matches the read character of the definition data.

  FIG. 11 is a diagram for explaining the inclination detection process and the inclination correction process. In particular, FIG. 11A is a diagram showing an example of the arrangement of receipt items in the receipt 22d, and FIG. 11B is a diagram for explaining the operation of detecting and correcting the inclination of the recognized character.

  As shown in FIGS. 11A and 11B, the character string Str # 20 “total sales” is obtained from the recognized characters Str # 21 “total”, Str # 22 “sell”, and Str # 23 “above”. It is assumed that these characters form an inclination angle α with respect to a reference direction on the image data.

  For the recognized character sent from the image data reading unit 11, the receipt data extraction unit 141 refers to the read character #n in the definition data table 1021 to check whether there is a match. For example, it is assumed that the character string Str # 20 “total sales”, which is a recognized character, is in the read character #n “total sales” of the definition data table 1021.

  The receipt data extraction unit 141 refers to the recognized character table 1011 on the work memory for the character string Str # 20 “total sales” sent from the image data reading unit 11. The receipt data extraction unit 141 acquires the image data (recognized character data) of the recognized characters Str # 21 “Total”, Str # 22 “Sell”, and Str # 23 “Up” searched on the recognized character table 1011. That is, the receipt data extraction unit 141 extracts the character string Str # 20 “total sales” as the receipt item name.

  The inclination detection unit 142 uses the recognized character data acquired by the receipt data extraction unit 141 to determine the inclination of the recognized character as follows.

  For example, the image data acquired by the receipt data extraction unit 141 is the coordinate position (x1, y1) − (x′1, y′1), Str # of Str # 21 “total” as shown in the example of FIG. 22 “Sell” coordinate position (x2, y2) − (x′2, y′2), Str # 23 “Up” coordinate position (x3, y3) − (x′3, y′3), etc. . The coordinate position (x1, y1) − (x′1, y′1) and the like indicate the upper left and lower right coordinates of the rectangular frame. Also, coordinates (black circles in the figure) Pt1 = (x′1, y′1), coordinates Pt2 = (x′2, y′2), coordinates Pt3 = (x′3, y ′) shown in FIG. This will be described as 3).

The inclination detection unit 142 calculates the inclination angle α as shown below by using the coordinates Pt1 to Pt3 for the x-coordinate distance k1 and the y-coordinate distance k2 shown in FIG. When k1, k2, and tan (α) are obtained,
k1 = x'3-x'1
k2 = y'3-y'1
tan (α) = k2 / k1
α = arctan (k2 / k1)
It becomes.

  Next, the inclination correction unit 143 determines whether it is necessary to correct the inclination of the recognized character from the calculated inclination (step S25). If it is not necessary to correct the inclination (step S25: No), the process proceeds to step S27. On the other hand, when it is necessary to correct the inclination (step S25: Yes), the inclination correction unit 143 executes an inclination correction process (step S26).

  More specifically, the inclination correction unit 143 compares the calculated inclination angle α with a predetermined allowable angle, and when the inclination angle α is smaller than the allowable angle, the inclination correction unit 143 sets the amount item Dat # 30 shown in FIG. On the other hand, it is determined that there is no need to correct the Y coordinate. On the other hand, when the calculated inclination angle α is equal to or larger than the allowable angle, the inclination correction unit 143 determines that the Y coordinate needs to be corrected for the monetary item Dat # 30 shown in FIG. . In the example of FIG. 11B, the calculated inclination angle α is greater than or equal to the allowable angle.

  FIG. 12 is a diagram illustrating an example of the specified receipt data. In particular, in FIG. 12, a character string on a different line in the receipt 22 will be described as an example for comparison.

(1) When the inclination detection is not performed The receipt data extraction unit 141 uses the result of the OCR process and the definition data table 1021 to calculate the amount item corresponding to the character string Str # 10 “cash balance” of the receipt item name. , Dat # 10 is recognized as “¥ 335,275”. Further, it is recognized that the amount item corresponding to the character string Str # 20 “total sales” of the receipt item name is “¥ 623,603” of Dat # 30. This is not the correct result. By detecting this, the correct amount item is extracted and resolved as follows.
(2) When inclination detection is performed For the character string Str # 10 “cash balance” shown in FIG. 12, the inclination detection unit 142 detects an inclination angle α1. The inclination correction unit 143 compares the inclination angle α1 with a predetermined allowable angle, determines that it is smaller than the allowable angle, and does not perform the correction process.

  For the character string Str # 20 “total sales” shown in FIG. 12, the inclination detector 142 detects the inclination angle α2. The inclination correction unit 143 compares the inclination angle α2 with a predetermined allowable angle, determines that the angle is equal to or larger than the allowable angle, and performs correction processing.

  FIG. 10 is a detailed process flowchart of the inclination correction process in step S26. Hereinafter, the inclination correction process executed by the receipt data processing unit 14 will be described in detail with reference to FIG.

  The receipt data extraction unit 141 acquires the position information (position of the amount column) of the amount item corresponding to the receipt item name from the definition data (step S261).

  For specific description, FIG. 11A shows a receipt 22d from which receipt data is extracted. In FIG. 11A, the receipt 22d includes character strings Str # 10 to # 30 recognized as receipt item names, and monetary items (monetary character strings) Dat # 10 to # 30 corresponding thereto. is there. For example, the character strings Str # 10 “cash balance”, Str # 20 “total sales”, and Str # 30 “net sales” recognized as receipt item names are used, and the corresponding monetary item Dat # 10 “¥ 335”. , 275 ”, Dat # 20“ ¥ 654,735 ”and Dat # 30“ ¥ 623,603 ”.

  The receipt data extraction unit 141 uses the store code definition data table 1021 (for example, FIG. 8) corresponding to the receipt 22d to acquire the receipt item name character string Str # 10 from “reading character # 10”. The position information of the corresponding monetary item Dat # 10 (the position of the monetary column) is acquired from the column reading position # 10. Similarly, the position information of the monetary items Dat # 20 and Dat # 30 is also acquired for the character strings Str # 20 and Str # 30.

  Next, the inclination correction unit 143 calculates the correction amount of the Y coordinate at the position of the money amount column from the detected inclination angle (step S262). Subsequently, the inclination correction unit 143 corrects the Y coordinate of the position of the money amount column from the calculated correction amount (step S263).

  Specifically, the inclination correction unit 143 corrects the Y coordinate of the position of the money amount column as described below for the money amount item Dat # 30.

The position of the amount column before correction is the position information (x21, y21) − (x′21, y ′) acquired from “amount column reading position # 20” as indicated by the solid-line rectangular frame in FIG. 21). The inclination correction unit 143 calculates the correction amount Δy of the y coordinate in the acquired position information using the detected inclination angle α. here,
Δy = x21 · tan (α)
It is said. Note that the calculation method of the tilt angle and the correction amount described above is an example, and other calculation methods may be used. For example,
Δy = {(x21 + x′21) / 2} · tan (α)
In this way, the calculation may be performed using the average value of the left and right x coordinates at the reading position # 20 in the amount column.

  As a result, as shown in the broken-line rectangular frame in FIG. 11B, the inclination correction unit 143 corrects the position of the corrected money amount column to (x21, y21 + Δy) − (x′21, y′21 + Δy). Since there is a money amount item Dat # 20 “¥ 654,735” in the broken-line rectangular frame in FIG. 11B, the inclination correction unit 143 determines that the money amount item corresponding to the character string Str # 20 is Dat # 20. to decide.

  Step S26 (S261-S263) is complete | finished after the correction process demonstrated above. Here, it returns to step S27 of the process flowchart of FIG. 9, and demonstrates according to FIG.

  Next, the receipt data specifying unit 144 acquires the amount item using the position information of the amount set in the definition data or the position information of the corrected amount (step S27).

  Specifically, the receipt data specifying unit 144 reads the character of the coordinates of the “read item #n” of the definition data that is close to the coordinates of the corrected position information or the position information of the amount of money left uncorrected. Get the column.

  For example, for the monetary item of the character string Str # 10 “cash balance” shown in FIG. 12, the inclination correction unit 143 does not execute the inclination correction process because the inclination angle α1 is smaller than the allowable angle. As a result, the receipt data specifying unit 144 recognizes the monetary item Dat # 10 “¥ 335,275” corresponding to the character string Str # 10 “cash balance”. That is, the receipt data having the receipt item name “cash balance” and the amount item “¥ 335,275” is specified.

  On the other hand, in FIG. 12, for the amount item of the character string Str # 20 “total sales”, since the inclination angle α2 detected by the inclination detection unit 142 is equal to or larger than the allowable angle, the inclination correction unit 143 executes the inclination correction processing. To do. After executing the inclination correction process, the inclination correction unit 143 sets the amount item Dat # 20 “¥ 654,735” at the distance Dis # 21 in the direction L # 21 for the amount item of the character string Str # 20 “total sales”. To do. Accordingly, the receipt data specifying unit 144 recognizes the monetary item Dat # 20 “¥ 654,735” corresponding to the character string Str # 20 “total sales”. That is, the receipt data having the receipt item name “total sales” and the amount item “654,735” is specified.

  Next, it is determined whether the processing of the last line of the receipt item is completed (step S28). When the process of the last line of the receipt item is not completed (step S28: No), the process returns to step S21, and the processes of steps S21 to S27 from the line of the next receipt item are repeated. On the other hand, when the process on the last line of the receipt item is completed (step S28: Yes), this process is terminated.

  11A, the receipt data specifying unit 144 specifies the amount item Dat # 20 “¥ 654,735” corresponding to the receipt item name Str # 20 “total sales”, for example. can do.

  As described above, the receipt data processing unit 14 detects the inclination of each recognized character of the receipt item read from the receipt image using the definition data, and executes the correction process according to the detected inclination. , Necessary receipt data can be extracted.

  The receipt data processing unit 14 can extract the receipt data necessary for the sales management data, and the receipt item name and the amount of the extracted receipt data are converted into the sales management data of the sales management item in a predetermined correspondence relationship. Can be converted (aggregated).

  With the receipt data recognition process described above, it is possible to detect the inclination and correct the inclination of each recognized character in the receipt line, so that the receipt paper is bent halfway, printing misalignment, etc. Thus, the receipt item name and the corresponding monetary item can be accurately extracted. Thereby, sales management data can be correctly totaled.

  FIG. 13 shows a detailed process flowchart of the sales management data generation process in step S15. The sales management data generation process executed by the sales management data generation unit 15 will be specifically described with reference to FIG.

  The sales management data generation unit 15 acquires receipt data necessary for sales aggregation from the receipt data specifying unit 144 (step S31).

  Specifically, the sales management data generating unit 15 receives receipt data including a store code, data including a receipt item name and its amount specified from the recognized character data, and correspondence information 1022 shown in FIG. Obtained from the data identification unit 144.

  Next, the sales management data generation unit 15 aggregates the sales management data as sales management data using the correspondence relationship information 1022 (step S32).

  Specifically, the sales management data generation unit 15 aggregates the amount corresponding to the receipt item name as sales management data of the sales management item based on the correspondence relationship between the sales management item and the receipt item from the correspondence relationship information 1022. . As described above, the amount (numerical data) of the receipt item is converted into the numerical data of the sales management item.

  Next, the sales management data generation unit 15 stores the sales management data of the store code to be stored in the sales management DB 1031 of the sales management data storage unit 103 (step S33).

  For example, FIG. 14 shows an example of a sales management DB (database) 1031. In the sales management DB 1031, as shown in FIG. 14, “sales date”, sales management item No. 1 “Cash Sales”, No. 1 2 “Multiple sales”, No. 2 3 A numerical value (amount) corresponding to a settlement item relating to sales such as “credit sales”,... Is stored.

  As described above, in the sales management DB 1031, the receipt items of the receipt 22, which have a completely different format (sheet format) for each store, are unified, and the receipt item, name, Numerical values can be automatically collected without any manual input as sales management data based on unified sales management items. As a result, the person in charge of the tenant management department can automatically count the sales for each store, so that the store sales management business can be performed efficiently and speedily.

  In addition, since there is no need to change a receipt output device such as a cash register provided in each store, an extra expense can be suppressed for the tenant.

  The processing performed by the above receipt data recognition apparatus can be realized by a computer and a software program, and the program can be recorded on a computer-readable recording medium or provided through a network.

DESCRIPTION OF SYMBOLS 1 Receipt data recognition apparatus 10 Reader 11 Image data reading part 12 Store identification part 13 Definition data reading part 14 Receipt data processing part 15 Sales management data generation part 20 Receipt clamping sheet 101 Image data storage part 102 Definition data storage part 103 Sales Management data storage unit 141 Receipt data extraction unit 142 Inclination detection unit 143 Inclination correction unit 144 Receipt data identification unit

Claims (6)

An image data storage unit for storing a recognized character obtained by character recognition of the receipt image and its position data;
The character string of the item name printed on the receipt and the relative position data of the amount item corresponding to the item name from the position in the receipt of the item name are defined for each item name to be read in the receipt. A definition data storage unit for storing definition data;
A receipt data extracting unit that extracts a recognized character that matches the character string of the item name defined in the definition data from the recognized character stored in the image data storage unit;
An inclination detection unit for detecting the inclination of the recognized character from the extracted position data of the recognized character;
An inclination correction unit that corrects relative position data of the corresponding monetary item in the definition data according to the detected inclination when the inclination of the recognized character is detected;
Using the corrected relative position data, a recognized character stored in the image data storage unit and a receipt data specifying unit for extracting a recognized character representing the amount item from the position data;
A receipt data recognition device comprising: a data generation unit that generates recognition result data from a recognition character that matches the item name and a recognition character that represents the amount item, and outputs or stores the data of the recognition result . The receipt data recognition apparatus according to claim 1,
The receipt is a receipt printed in a different format for each store,
The definition data storage unit stores the definition data for each store,
Executing processing by the receipt data extracting unit, the tilt detecting unit, the tilt correcting unit, the receipt data specifying unit, and the data generating unit using different definition data for each store that issued the receipt. Receipt data recognition device characterized by this. In the receipt data recognition device according to claim 2,
The definition data stored in the definition data storage unit includes sales management item name data commonly used for sales management of a plurality of stores, corresponding to the character string of the item name printed on the receipt,
The receipt data recognition apparatus, wherein the data generation unit generates recognition result data obtained by converting a recognition character matching the item name into a corresponding sales management item name defined in the definition data. Computer
Image data storage means for storing a recognized character obtained by character recognition of a receipt image and its position data;
The character string of the item name printed on the receipt and the relative position data of the amount item corresponding to the item name from the position in the receipt of the item name are defined for each item name to be read in the receipt. Definition data storage means for storing definition data;
Receipt data extracting means for extracting a recognized character that matches the character string of the item name defined in the definition data from the recognized character stored in the image data storage means;
Inclination detecting means for detecting the inclination of the recognized character from the extracted position data of the recognized character;
Inclination detecting means for correcting the relative position data of the corresponding monetary item in the definition data according to the detected inclination when the inclination of the recognized character is detected;
Using the corrected relative position data, a recognized character stored in the image data storage means and a receipt data specifying means for extracting a recognized character representing the amount item from the position data;
A receipt data recognition program for generating recognition result data from a recognition character matching the item name and a recognition character representing the monetary item, and functioning as data generation means for outputting or storing the recognition result data. In the receipt data recognition program according to claim 4,
The receipt is a receipt printed in a different format for each store,
The definition data storage means stores the definition data for each store,
In the computer,
Using the definition data different for each store that issued the receipt, and executing the processing by the receipt data extracting means, the inclination detecting means, the inclination correcting means, the receipt data specifying means, and the data generating means. Receipt data recognition program characterized by In the receipt data recognition program according to claim 5,
The definition data stored in the definition data storage means includes data of sales management item names commonly used for sales management of a plurality of stores, corresponding to the character strings of the item names printed on the receipts,
The receipt data recognition program characterized in that the data generation means generates recognition result data obtained by converting a recognition character matching the item name into a corresponding sales management item name defined in the definition data.

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