JPH09282387A - Document processor - Google Patents

Abstract

PROBLEM TO BE SOLVED: To efficiently and surely sort bills and securities by integrating and handling all bills and securities. SOLUTION: An image reader 10 generates MICR(magnetic ink character recognition) character data and a surface image from an actual bill TG1 and generates OCR-processed character recognition data from the surface image and feature data after specific image processing, and sends them to an image file server IFS. A data determination part 20 corrects and additionally input recognition data by referring to the surface image, and performs confirmation processing. Then, an encoder 30 prints necessary MICR characters on the bill TG2 outputted from the image reader 10 according to data acquired from the image file server IFS. At this time, the surface image of the bill TG2 is read to generate its feature data, which are compared with the feature data generated by the image reader 10 to give a print to only the matching bill.

Description

Detailed Description of the Invention

[0001]

TECHNICAL FIELD The present invention relates to banks, credit unions,
The present invention relates to a form processing device capable of simplifying the processing of promissory notes / exchange bills brought in by a customer at a financial institution such as a credit union, and in particular, simplifying the journal processing to save labor.

[0002]

2. Description of the Related Art Conventionally, financial institutions visually check check writer prints and the like written on securities such as bills and checks received at counters, and read the written amount data,
Magnetic ink character recognition (MI
It was encoded and printed with the (CR) character.

However, since it is necessary to visually read the characters printed on the check writer each time, there is a problem that it takes time to process securities.

Therefore, for example, in the securities processing apparatus disclosed in Japanese Patent Laid-Open No. 3-102470, the financial institution number is read in the clear band to identify the financial institution, and the image data of securities is acquired. Then, by reading the check writer characters on the acquired image data at the optical reading slice level corresponding to the identified financial institution, the influence of the tint block on the securities is eliminated, and only the check writer printed characters are printed. It is surely recognized, and the recognized character contents are automatically printed as MICR characters at a predetermined position in the clear band.

As a result, the processing of securities received at the counter becomes efficient and the processing time is shortened.

[0006]

However, among the securities, when a check and a promissory note are to be drawn out, it is known in advance from which financial institution and which account the payment will be made. The financial institution number and account number written in MICR characters can be printed on the bill, but the bill of exchange is handled in advance by MICR characters because it is not known who pays the bill unless it is issued. The financial institution number of the financial institution cannot be printed.

For example, the promissory note shown in FIG.
The financial institution code is printed with CR characters.
MICR characters are not printed on the bill of exchange shown in.

Therefore, in the case of a bill of exchange, it is not possible to perform data retrieval based on MICR characters, and it is not possible to carry out journal processing based on data retrieval similar to checks and promissory notes. However, there was a problem that the journal entry processing could not be performed efficiently.

That is, since the processing contents differ depending on the type of bills, the bills cannot be processed in a unified manner, and as a first step, it is necessary to perform an extra journalizing process of classifying only the bills of exchange as other bills. There is.

In the case of the bill of exchange, the financial institution number and the like are not printed even in the case of Japanese Patent Application Laid-Open No. 3-102470.
After the CR printing, the duplicate processing of forcing the amount data to be MICR printed again on the bill of exchange is forced by the automatic processing similar to the promissory note.

Accordingly, the present invention eliminates such problems, and provides a form processing apparatus which can handle all bills in a unified manner and can perform journal processing of the bills efficiently and reliably. To aim.

[0012]

According to a first aspect of the present invention, a batch processing identifier is provided in a form processing apparatus that prints MICR characters necessary for accepted bills of bill and classifies the bills of bill by bill due date. The bill related to the bill is sent and stored, and the server means for correcting and adding the data online and a series of passage numbers are printed on the back of the bill. Number printing means, first reading means for reading image data of at least the surface of the bill of commerce, character recognition means for recognizing characters on the bill of commerce based on the image data, the passage number, image data, and characters First processing means connected to the server means, which has a control means for controlling transmission of a recognition result to the server means as data relating to the bill of exchange. , Obtaining data relating to the bill of exchange securities which has been processed by the first processing means from the server means, referring to image data of the data relating to the bill of exchange securities, correcting or additionally inputting data of the bill of exchange securities, and Processing by the first processing means and second processing means connected to the server means for performing confirmation processing, and sending to the server means data relating to the bill of securities for which the correction or addition and confirmation processing has been performed. Second bill reading means for reading at least the image data of the front side of the bill of commerce completed by the bill, and the bill of bill corresponding to at least the image data of the front side read by the second reading means, the bill being processed by the second processing means. Data acquisition means for acquiring data relating to the data from the server means, image data acquired by the data acquisition means, and the second Collating means for comparing and collating whether or not the image data read by the reading means is matched, and the bill-related securities obtained by the data acquisition means are printed in MICR characters on the bills of bill having the matching results of the matching means. MICR character printing means, third processing means connected to the server means, and bill information processed by the third processing means, MICR character information printed on the bill securities It is characterized by performing a classification process based on.

According to a second aspect of the present invention, in the first aspect, the first processing means generates the characteristic data indicating the characteristic of the image from the image data read by the first reading means. Means for transmitting the bill characteristic data including the generated characteristic data to the server means, and the third processing means extracts the characteristic of the image from the image data read by the second reading means. A second generation unit that generates the characteristic data shown, wherein the collation unit compares and collates the characteristic data generated by the first generation unit with the characteristic data generated by the second generation unit. Characterize.

In a third aspect based on the first or second aspect, each of the first processing means and the third processing means is a MICR character for reading a MICR character printed on a bill of commerce. The first processing means sends the data represented by the MICR character read by the MICR character reading means of the first processing means to the server means as data relating to the bill of lading, and The data acquiring means of the processing means of No. 3 acquires the data relating to the bill of exchange including the data indicated by the MICR character sent to the server means, and the collating means of the third processing means of the third processing means. The data indicated by the MICR character read by the MICR character reading means and the data indicated by the MICR character acquired by the data acquisition means match. And comparing the verification, including whether.

In a fourth aspect based on the first to third aspects, the first processing means includes a plurality of bill notes.
It is provided with a first hopper means for feeding out one by one and a first stacker means for outputting the bills that have been processed, and the third processing means is a plurality of bills output from the first stacker means. Second hopper means for paying out securities one by one, a first pocket for outputting bills of bill with matching results by the matching means, and a second pocket for outputting bills of bills with mismatching matching results by the matching means. And a second stacker unit having a.

[0016]

BEST MODE FOR CARRYING OUT THE INVENTION Embodiments of the present invention will be described below with reference to the drawings.

FIG. 1 is a diagram showing a configuration of a bill processing apparatus according to an embodiment of the present invention. In FIG. 1, the bill processing apparatus includes an image file server IFS that holds and manages various data, and two local area networks (LA) connected to the image file server IFS.
N) 1, 2, image reader 1 connected to LAN 1
0, an encoder 30 connected to LAN1, a reader sorter 40 connectable to LAN1, and a data determination unit 20 connected to LAN2.

The image reader 10 includes a hopper unit 11 and a hopper unit 1 that take in each of the bills TG1 with an attached slip.
MICR reader 12 that reads MICR characters on the bill captured by 1., front image sensor 13 that reads the entire front (front) image of the bill that has been captured and a predetermined partial image, back image that reads the back image of the captured bill The sensor 14, the endless printer 15 that prints a series of passage numbers (serial numbers) at predetermined positions on the back surface of the captured bill, the stacker unit 16 that outputs the processed bill, and the predetermined portion read by the front surface image sensor 13 A character recognition unit 17 that performs OCR (optical character recognition) processing from an image, and generates characteristic data by performing predetermined image processing on a predetermined portion of the entire surface image read by the surface image sensor 13. Image processing unit 18, temporary storage unit 19 for temporarily storing various data And a control unit C10 for controlling overall various processes including a communication process with the LAN1 like. The stacker unit 16 has an output port of one pocket, and all bills and the like input from the hopper 11 are output to this one pocket.

The encoder 30 includes a hopper unit 31 that takes in the bills TG2 processed by the image reader 10 one by one, and a MIC on the bill that is taken in by the hopper unit 31.
MICR reader 32 that reads the R character, surface image sensor 3 that reads the entire captured surface image of the handprint
3. MICR encoder 34 for printing MICR characters on a bill, endors printer 35 for printing a processed mark on the back of the bill with MICR characters printed, stacker unit 36 for outputting the processed bill, and front surface image sensor 33
An image processing unit 37 for generating characteristic data by performing image processing on a predetermined portion of the entire surface image read by the image reader 1.
0, the collation unit 38 that collates the characteristic data generated by the image processing unit 18 with the characteristic data generated by the image processing unit 37, the journal printer 39 that prints the processing result for the series of bills input from the hopper 31, and the LAN.
It has a control unit C30 that totally controls various processes including a communication process with the first and the like. It should be noted that the stacker unit 36 has two pockets for output, the collation unit 38 obtains a collation result such as matching of feature data, and the MICR encoder 34 outputs M.
It has a "processed" pocket for outputting a bill with ICR characters printed thereon, and a "reject" pocket for outputting a bill with a collation result such as feature data not matching in the collating unit 38.

The data confirming section 20 includes an image reader 10
An input processing unit that refers to the surface image of the handprint read by the computer and the surface image that reflects the recognition result, and additionally inputs the data that the operator lacks and corrects the misrecognized character or additionally inputs the unrecognizable data. 21 and a confirmation processing unit 22 for the operator to confirm whether the data of all the bills including the bills corrected or added by the input processing unit 21 are correct by referring to the entire front image and the entire back image. Have.
The input processing unit 21 has two terminals, a first input processing unit 21a and a second input processing unit 21b, and the first input processing unit 21
In a, mainly data that could not be read by the character recognition unit 17, for example, additional input or correction input of amount data is performed. The second input processing unit 21b mainly performs additional input of the payer name and the like. The first input processing unit 21
In the case of a small-scale store, a and the second input processing unit 21b can be shared by one terminal. Confirmation processing unit 22
Refers to the entire front and back images of the handprint and corrects this data if there is an error,
Output as confirmed data. Therefore, the data confirmation unit 20
Are usually manually input by three operators, and in small shops, two operators are manually input. The number of operators can be increased at any time according to the size of the store.

The image file server IFS has a data storage unit 3 and an image reader 10 via the LAN 1.
And storing / reading of data input / output to / from the encoder 30 or the reader / sorter 40, and the LAN 2
The data input / output to / from the data determination unit 20 via the memory is read and updated. The data storage unit 3 temporarily inputs the bill pass number, the front side image, the back side image, the feature data, the MICR data, the character recognition data, and the like input from the image reader 10 from the input processing unit 22 of the data determination unit 20. The confirmation data and the confirmation data input from the confirmation processing unit 22 of the data confirmation unit 20 are input and stored. In addition, the data storage unit 3 to the data determination unit 20
The encoder 30 outputs the entire surface image of the handprint to be processed, the image data reflecting the recognition result, and the print data.

The reader sorter 40 is connected to the LAN 1 or is off-line to classify the bills output from the “processed” pocket of the stacker unit 36 of the encoder 30. The reader sorter 40 includes a hopper unit 41 and a hopper unit 4 for inputting bills output from the "processed" pocket.
MI that reads the MICR character of the bill imported from 1.
It has a CR reader 42, a sorter / stacker unit 43 that sorts in order of collection section / payment date based on the read MICR characters, and a control unit C40 that controls the whole. Note that the sorter / stacker unit 43 has 11 pockets in this example, and in the case of classifying into 11 or more categories, the number of pockets can be increased, but it is also possible to repeatedly input rejected bills from the hopper unit 41. You can do it.

The bills sorted and output from the sorter / stacker unit 43 are stored by the staff according to the classification according to collection category / payment date.
It is taken out of this storage and processed.

The bill handling apparatus is mainly used in the centralized section of the center of a financial institution. Bills with due dates of two weeks or more are collected from each branch of this financial institution in the centralized section of this center. In the centralized section, the collected bills are sorted and stored according to date / type / store. I do.

Next, the data structure stored in the data storage unit 3 of the image file server IFS will be described with reference to FIG.

The data storage unit 3 has a batch management table TBATCH indicating each batch ID, a management table storage location of each batch ID, and a management table TB for each bill, and data acquired from each bill. Manage. That is, the batch management table TBATCH has a storage location of a management table TB that manages a group of bills of note by a batch ID (batch number) and manages the group of bills indicated by each batch ID. The management table TB indicated by this storage location includes a passage number N that has passed through the image reader 10, a pointer P1 indicating the storage location of a front surface image file F1 that stores the entire front surface image acquired by the front surface image sensor 13, and a back surface image sensor. Pointer P2 indicating the storage location of the back side image file F2 storing the entire back side image acquired by 14; Pointer P3 indicating the storage location of the characteristic data file F3 storing the characteristic data acquired by the image processing unit 18; A pointer P4 indicating a storage location of various bill data D such as a code, a bill type G, a processing flag FG1 indicating whether or not the processing by the first input processing unit 21a has been processed, and a processing by the second input processing unit 21b is processed. By the processing flag FG2 indicating whether or not it has been completed, the confirmation processing unit 22 Process consists of processing flag FG3 indicating whether processed. In distributed processing, parallel processing becomes possible by specifying the batch ID.

Next, the relationship between the bill data D stored in the data storage unit 3 and the image reader 10, the data determination unit 20, and the encoder 30 will be described with reference to FIG.

First, in the image reader 10, the MICR reader 12 reads MICR characters from the input bill TG1 and stores the read code line 52 in the data storage unit 3 as the bill data DA. Also,
The surface image sensor 13 takes in the character recognition image 54 and the entire surface image 55, the character recognition image 54 is OCR processed 57 by the character recognition unit 17, and is stored in the data storage unit 3 as the bill data DA.
The entire front image 55 and the entire back image 56 captured by the back image sensor 14 are the front image file F1 and the back image file F2, respectively.
Is stored in the data storage unit 3. Further, the entire surface image 55 is subjected to the feature extraction processing 58 of the image of a predetermined portion by the image processing unit 18, and the feature data as the processing result is stored in the data storage unit 3 as the feature data file F3.

On the other hand, the first input processing unit 21a of the data confirmation unit 20 refers to the image indicated by the front image file F1 and inputs the bill data rejected by the OCR process as the first input, and the temporary confirmation data DB To generate.
Further, the second input processing unit 21b refers to the image indicated by the surface image file F1 and inputs the bill number, payer name, etc., which are not OCR processed, as the second input, and outputs the temporary confirmation data DB or the confirmation data DC. Produce a copy.
Further, the confirmation processing unit 22 uses the front surface image file F1.
Is checked to see if the temporary confirmation data DB is correct, and if it is not correct, corrected or added confirmation data DC is generated.

In the encoder 30, the input bill TG is input.
A process 72 for reading the MICR character No. 2 by the MICR reader 32 is performed to compare the read MICR character with the code line 73 and the code line in the bill data DA, and from the entire surface image 76 captured by the surface image sensor 33. Image matching (matching process) 77 between the generated feature data and the feature data indicated by the feature data file F3 is performed, and MI is matched only when at least one of the MICR character and the match process 77 matches.
Confirm data D on the bill TG2 by the CR encoder 34
Print C with MICR characters.

It should be noted that the processing by the image reader 10, the processing by the data confirming unit 20, and the processing by the encoder 30 can be executed by distributing the image in batch units via the file server IFS. However, it is assumed that the processing target by the data confirmation unit 20 is the bill data that has been processed by the image reader 10, and the processing target by the encoder 30 is the bill data that has been processed by the data confirmation unit 20. There is.

Next, a bill processing procedure of the bill processing apparatus will be described with reference to the flowcharts of FIGS. As described above, the processes of the image reader 10, the data determination unit 20, and the encoder 30 are distributed and executed.

FIG. 4 is an overall flowchart showing a bill processing procedure relating to bill classification. First, the ID of this batch process defined by a financial institution is input from a terminal unit (not shown) of the image reader 10. Then, the actual bill TG1 is placed on the hopper unit 11 of the image reader 10 to start the input of the bill TG1 (step 1
01). The bill TG1 is input in a unit of several hundred bills, and a bill is attached. After that, the image reader 10 performs an initial data acquisition process (step 102). The data acquired by this process is
The bill data DA, the front side image, the back side image, the characteristic data and the like shown in FIG. Thereafter, these acquired data are transmitted to the image file server I via the LAN 1.
It is stored in the data storage unit 3 of the FS.

After that, the data confirming unit 20 refers to the surface image stored in the data storage unit 3 to correct and add the bill data DA stored in the data storage unit 3 and to perform confirmation processing. Perform (step 104). As a result, the finalized data DC is generated via the temporary finalized data DB.

After that, the actual bill TG2 output from the stacker unit 16 of the image reader 10 is transferred to the encoder 30.
Again (step 105). At this time, batch I
Input D to the encoder 30. The file stored in the image file server IFS is specified by this batch ID. This re-entered bill TG2
The encoder 30 re-reads the MICR character and the characteristic data, compares them with the MICR character and the characteristic data stored in the data storage unit 3 of the image file server IFS, and encodes the matched bill data with the MICR character. And end the processed mark on the back side.

Thereafter, the physical bills TG3 output from the encoder 30 are classified by the reader / sorter 40 (step 108), and the classified physical bills are stored in the storage box 4 according to the classification.

Now, the process of acquiring the initial data in step 102 will be described with reference to the detailed flowchart of FIG.

In FIG. 5, first, one bill is fed out from the hopper unit 11, and a pass number is given to this bill (step 201). Then, the MICR reader 12 reads the MICR character of this handprint (step 202). This MICR character is, for example, the MICR character in the area ER of the promissory note shown in FIG.
Codes such as an exchange code, a financial institution code, a branch code, and an account number are read from the CR character. Thereafter, the surface image sensor 13 captures the surface image of the handprint and the OCR recognition image, and
The back image is captured by the back image sensor 14 (step 203). The character recognition unit 17 performs character recognition by OCR on the OCR recognition image of the captured images (step 20).
4). The area of this OCR recognition image is, for example, as shown in FIG.
In the promissory note shown in 3, there are areas CR1 to CR3, and
By the character recognition of CR, the exchange code, the financial institution code, and the branch code can be obtained from the area CR1.
The amount is obtained from 2, and the payment due date is obtained from the region CR3. Further, with respect to the front surface image captured in step 203, the image processing section 18 further performs predetermined image processing to generate characteristic data (step 205).

After that, the passage number given in step 201, the MICR data read in step 202,
The front side image data, the back side image data captured in step 203, the character recognition data recognized in step 204, and the feature data generated in step 205 are stored in the temporary storage unit 19 (step 20).
6) The pass number is printed on the back surface of the bill being processed and output to the stacker unit 16 (step 207). afterwards,
It is determined whether or not the next bill has been input (step 20).
8) If the next bill is input, step 201
When the next bill is not input, the process returns to step 102. The initial data obtained in this way is transferred to the data storage unit 3, stored and managed.

Next, the encoding process of step 106 will be described with reference to the detailed flowchart of FIG.

First, the encoder 30 takes out one bill from the hopper unit 31 and acquires the bill data corresponding to the pass number of this bill from the data storage unit 3 of the image file server IFS via the LAN 1 (step 3).
01). The MICR reader 32 uses the M
The ICR character is read (step 302). Further, the surface image sensor 33 captures the surface image of the handprint (step 303). After that, the read MICR data and the MIC acquired from the image file server IFS
It is determined whether or not the R data matches (step 30
4) If they do not match, further image processing unit 37
Generates the feature data by subjecting the captured surface image to predetermined image processing (step 305). Then, the collating unit 38 collates and collates the generated characteristic data with the characteristic data acquired from the image file server IFS (step 306), and based on the comparison and collation result, whether or not the characteristic data match. It is determined whether or not (step 307).

If the characteristic data match in step 307 or the MICR data match in step 304, the MICR encoder 34 uses the KNO.
MICR characters not printed on the bill are printed (step 308), and a processed mark is printed on the back surface of the bill (step 309). Then, the bill on which the processed mark is printed is output to the "processed" pocket of the stacker unit 36 (step 310). On the other hand, if it is determined in step 307 that the feature data do not match, this bill is output to the "reject" pocket of the stacker unit 36 (step 311).

Step 310 or Step 311
After the bill is output to the "processed" pocket or the "reject" pocket, it is determined whether or not there is another bill (step 312), and if the next bill is input, step 301 When the next bill is not input, the journal printer 39 prints out the processing result in a predetermined format and returns to step 106.

Next, step 205 and step 305
In the image processing section 18 and the image processing section 37,
The characteristic data generated by will be described. There are two methods for generating the characteristic data, for example, the first method and the second method. Therefore, the first method will be described first.
Of course, when the image processing unit 18 adopts the first method, the image processing unit 37 also adopts the first method,
The collating unit 38 also performs the collating process according to the first method, and the same applies when the second method is adopted.

First, the first method will be described with reference to FIGS. 7 to 9.

FIG. 7 is a detailed flowchart showing the first generation processing procedure of the characteristic data in steps 205 and 305, and FIG. 8 is a diagram for explaining the generation process.

First, the image processing units 18 and 37 obtain images I11 to I13 obtained by cutting out predetermined regions E11 to E13 of the surface image I10 captured by the surface image sensors 13 and 33 (step 40).
1). The area E1 is an area in which the name and amount of the payer are described, the area E12 is an area in which the name and address of the sender are described, and the area E13 is the name and address of the underwriter. Is the area in which is written. Then, histograms H11 to H13 of the density distribution for the respective images I11 to I13 are generated (step 402), predetermined threshold values are determined from the distribution of the histograms, and the respective images I11 to I13 are determined by the respective threshold values. Is binarized (step 403). Further, the ratio of black pixels to the respective regions of the binarized binarized images I21 to I23 is set as the characteristic values D1 to D3 (step 404). Then, the binarized image I21 ...
I23 and feature values D1 to D3 are paired to generate feature data (step 405), and the process returns to step 205 or step 305.

The verification processing procedure by the verification unit 38 in step 306 for the characteristic data generated by the first method will be described with reference to the detailed flowchart of FIG.

First, the collating unit 38 is the image processing unit 1.
The degree of non-coincidence of the characteristic values of the area E11 generated by each of Nos. 8 and 37 is calculated (step 501), and it is determined whether or not the characteristic values coincide with each other based on the degree of non-coincidence (step 502). That is, if the degree of non-coincidence of the ratio of black pixels is within the allowable range, it is determined that they match, and if it is outside the allowable range, it is determined that they do not match. If it is determined that they do not match, the input bill is set as “non-match” (step 514) and the process returns to step 306. If it is determined that they match, the degree of mismatch of the feature values of the area E12 is calculated in the same manner (step 503), and it is determined whether the feature values match based on this degree of mismatch ( (Step 504) If they do not match, the process moves to Step 514 and is set as "mismatch". If it is determined in step 504 that they match, the degree of mismatch of the feature values of the area E13 is calculated in the same manner (step 505), and whether the feature values match based on this degree of mismatch is determined. Is determined (step 506), and if they do not match, the process proceeds to step 514 and is set as “mismatch”.

On the other hand, if it is determined in step 506 that the feature values of the area E13 match each other, the binarized image collation processing is further performed. First, the image processing unit 18,
The degree of coincidence of the binarized image I21 of the area E11 generated by each of 37 is calculated (step 507). This 2
In the calculation processing of the degree of coincidence of the binarized image, an image of a predetermined area in the binarized image of the area E11 generated by the image processing unit 37 of the encoder 30 is extracted, and the extracted image is processed by the image processing unit of the image reader 10. 1
8, the matching calculation is performed while shifting by 1 pixel for every area of the binarized image of the area E11 generated,
The value at the time of the best match is the match degree. After that, if the calculated degree of coincidence is equal to or greater than a predetermined value, a process of determining a match is performed (step 508), and if it is determined that they do not match, the process proceeds to step 514 and is set as “mismatch”. . On the other hand, if it is determined that they match each other, the degree of coincidence of the binarized image of the area E12 is calculated in the same manner as in step 507 (step 509).
Based on this degree of coincidence, it is determined whether or not the binarized images of the area E12 coincide (step 510). If it is determined that they do not match, the process proceeds to step 514 and is set as “mismatch”. On the other hand, if it is determined that they match each other, the same process is performed for the area E13 2
The degree of coincidence of the binarized images is calculated (step 511), and it is determined based on the degree of coincidence whether or not the binarized images of the area E13 are coincident (step 512). If it is determined that they do not match, the process proceeds to step 514 and “mismatch” is set, and the process returns to step 306. If it is determined that they match, “match” is set ( Step 513) and the process returns to step 306.

As described above, in the first method, the characteristic data having the characteristic value is generated, and the template matching (here, the residual sequential test method) is performed on the generated characteristic data.

Next, the second method will be described with reference to FIGS. In the second method, the density image itself is generated without obtaining the characteristic value, and in the matching process, template matching by cross-correlation is performed.

FIG. 10 is a detailed flowchart showing the second generation processing procedure of the characteristic data in steps 205 and 305, and FIG. 11 is a diagram for explaining the generation process.

First, the image processing units 18 and 37 obtain images (density images) I31 to I33 obtained by cutting out predetermined regions E31 to E33 of the surface image I30 taken in by the surface image sensors 13 and 33 (steps). 601). Thereafter, the acquired density images I31 to I33 are generated as characteristic data (step 602), and the process returns to step 205 or step 305.

The verification processing procedure by the verification unit 38 in step 306 for the characteristic data generated by the second method will be described with reference to the detailed flowchart of FIG.

First, the collating unit 38 is the image processing unit 1.
The degree of coincidence of the density images of the area E31 generated by each of No. 8 and 37 is calculated (step 701). For example, the area E3 generated by the image processing unit 18 of the encoder 30
The cross-correlation coefficient is obtained by shifting the density image of a predetermined area in the density image I31 of 1 and the density image I31 of the area E31 generated by the image processing unit 18 of the image reader 10 by one pixel. When the maximum value of 1 is the highest, the maximum value of the cross-correlation coefficient is calculated as the degree of matching. Then, depending on whether or not the degree of coincidence is a predetermined value or more, each density image I
It is determined whether 31 matches (step 702).
When it is determined that they do not match, the process proceeds to step 708, the setting is made as “mismatch”, and the process returns to step 306. On the other hand, if it is determined that they match, the area E3 is further processed in the same manner as in step 701.
The degree of coincidence of the second density image I32 is calculated (step 7
03), it is determined based on this degree of coincidence whether or not the density images of the area E32 match (step 704).
If it is determined that they do not match, it is set as "mismatch" (step 708). On the other hand, if it is determined that they coincide with each other, the degree of coincidence of the density image I33 of the area E33 is calculated similarly to step 701 (step 705), and the density image of the area E33 is calculated based on this degree of coincidence. It is determined whether or not match (step 706). If it is determined that they do not match, it is set as "mismatch" (step 708), and step 3
If it returns to 06 and it is judged that they match,
It is set as "match" (step 707), and the process returns to step 306.

As described above, in the second method, the density image as it is is generated as the characteristic data, and the template matching (here, the method using the cross-correlation coefficient) is performed on the generated characteristic data.

The template matching based on the images generated by the above-mentioned first method and second method is not limited, and the image matching may be performed by another template matching method. Further, the matching process may be performed by structure matching. In short, the image reader 10
Image of handprint read by and encoder 30
It suffices to be able to perform matching processing with the image of the handprint read by.

As described above, in the above-described embodiment of the present invention, since the image file server IFS manages the processing results of the image reader 10, the data determination unit 20, and the encoder 30, the image reader 10,
The processing by the data determination unit 20 and the encoder 30 can be distributed and performed. Further, since the automatic processing by the image reader 10 and the encoder 30 and the manual input processing by the data confirming unit 20 are separated, it is possible to perform efficient billing journal processing. Furthermore, image reader 1
Since the bills are compared using the image during the processing by 0 and the processing by the encoder 30, it is possible to automatically process the bills in which MICR characters are not printed at the time of drawing such as a bill of exchange. Become.

[0060]

As described in detail above, in the first invention, the server means sequentially holds and manages the data relating to the bill of commerce, and the first processing means, the second processing means, and the third processing means. Since each processing of the processing means can be distributed and performed based on the image data, there is an advantage that efficient classification processing can be performed, and at the same time, an M-like bill of exchange can be used.
Since the collation processing of the image data is performed even for the bill of affairs on which the ICR character is not printed, the necessary MICR character is printed on the bill of denomination that surely matches, despite the distributed processing. It has the advantage of being able to.

Further, in the second aspect of the invention, since the characteristic data for the image data is subjected to the predetermined image processing, it is possible to perform the collation processing of the bill of commerce efficiently, and the overall efficient processing is possible. It has an advantage that a classification process can be performed.

Further, according to the third aspect of the invention, since the MICR character is read in the case where a predetermined MICR character is printed at the time of drawing such as a promissory note, efficient classification processing is performed. It has the advantage that Further, the MICR character is also used to perform the collation process of the bill of commerce, so that there is an advantage that the collation process of the bill of commerce can be performed more reliably.

In the fourth invention, the first processing means and the second
Since each of the processing means of 1 has a hopper and a stacker, it has an advantage that bill processing can be automatically performed. Further, since the second processing means has a first pocket for outputting bills of bill with matching matching results and a second pocket for outputting bills of bill with unmatched matching results, the bills are output from the first pocket. There is an advantage that it is possible to perform a reliable classification process for bills of credit by making only the bills of note that have been classified into bills of interest for classification processing.

[Brief description of drawings]

FIG. 1 is a diagram showing a configuration of a bill processing apparatus according to an embodiment of the present invention.

FIG. 2 is a diagram showing a configuration of data stored in a data storage unit 3 of an image file server IFS.

FIG. 3 is a bill data D stored in a data storage unit 3, an image reader 10, a data determination unit 20, and an encoder 30.
The figure explaining the relationship between and.

FIG. 4 is an overall flowchart showing a bill processing procedure related to bill classification.

FIG. 5 is a detailed flowchart showing an initial data acquisition processing procedure in step 102.

FIG. 6 is a detailed flowchart showing the encoding processing procedure of step 106.

FIG. 7 is a detailed flowchart showing a first generation processing procedure of characteristic data in steps 205 and 305.

FIG. 8 is a diagram illustrating a first generation process of characteristic data in steps 205 and 305.

FIG. 9 is a detailed flowchart showing the verification processing procedure by the verification unit in step 306 for the characteristic data generated by the first method.

FIG. 10 is a detailed flowchart showing a second generation processing procedure of characteristic data in steps 205 and 305.

FIG. 11 is a diagram illustrating a second generation process of characteristic data in steps 205 and 305.

FIG. 12 is a detailed flowchart showing the verification processing procedure by the verification unit in step 306 for the characteristic data generated by the second method.

FIG. 13 is a diagram showing an example of the surface of a promissory note at the time of drawing out.

FIG. 14 is a diagram showing an example of the surface of a bill of exchange at the time of drawing.

[Explanation of symbols]

10 ... Image reader 20 ... Data determination unit 30 ... Encoder 40 ... Reader sorter IFS ... Image file server 1, 2 ... LAN 4 ... Storage box TG1 to TG3 ... Physical bill 3 ... Data storage unit C10 to C40 ... Control unit 11, 31 , 41 ... Hopper unit 12, 32, 42 ... MICR reader 12, 33 ... Front image sensor 14 ... Back image sensor 15, 35 ... End printer 16, 36 ... Stacker unit 17 ... Character recognition unit 18, 3
7 ... Image processing unit 19 ... Temporary storage unit 34 ... MICR encoder 38 ...
Collating unit 39 ... Journal printer 43 ... Sorter / stacker unit 21 ... Input processing unit 21a ... First input processing unit 21b ... Second input processing unit 2
2 ... Confirmation processing unit

Claims (4)

[Claims] 1. A form processing apparatus which prints MICR characters necessary for accepted bills of securities and classifies the bills of securities according to payment dates, etc., wherein said bills sent based on an identifier of batch processing. Server means for receiving and storing data relating to securities and enabling correction and addition of the data online, number printing means for printing a series of passage numbers on the back surface of the bill securities, at least the front surface of the bill securities A first reading means for reading image data of the bill, a character recognition means for recognizing a character on the bill of commerce based on the image data, the passage number, the image data, and a character recognition result as data relating to the bill of lading. A first processing means connected to the server means and having a control means for controlling transmission to the server means; The data relating to the bill of exchange that has been processed is acquired from the server means, the image data of the data relating to the bill of exchange is referred to, and the data relating to the bill of exchange is corrected or additionally input and confirmed, and the correction or Second processing means connected to the server means for sending to the server means data relating to the bill of securities for which addition and confirmation processing has been performed, and at least the surface of the bill of securities for which processing by the first processing means has been completed. Second reading means for reading the image data of
Data acquisition means for acquiring from the server means data corresponding to at least the surface image data read by the second reading means and relating to the bill of securities for which the processing by the second processing means has been completed, and the data acquisition means. Collation means for comparing and collating whether the image data read by the second reading means and the image data read by the second reading means match, and the bill of exchange securities acquired by the data obtaining means for the bill of securities whose matching result by the collating means matches. And a third processing means connected to the server means, the third processing means being connected to the server means.
A form processing apparatus, which performs a process of classifying bills processed by the processing means according to the information of MICR characters printed on the bills. 2. The first processing means comprises first generation means for generating characteristic data indicating characteristics of the image from the image data read by the first reading means, and the generated characteristic data And a second generation means for generating characteristic data indicating the characteristic of the image from the image data read by the second reading means. 2. The form processing according to claim 1, further comprising means, wherein the collating means compares and collates the characteristic data generated by the first generating means with the characteristic data generated by the second generating means. apparatus. 3. The first processing means and the third processing means each include MICR character reading means for reading MICR characters printed on a bill of lading, and the first processing means comprises: The data indicated by the MICR character read by the MICR character reading means of the first processing means is sent to the server means as data relating to the bill of lading, and the data acquisition means of the third processing means is sent to the server means. The data relating to the bill of lading including the data indicated by the MICR character is obtained, and the collating means of the third processing means and the data indicated by the MICR character read by the MICR character reading means of the third processing means and the data described above. 7. The comparison and collation including whether or not the data indicated by the MICR character acquired by the data acquisition unit matches. The form processing apparatus according to 1 or 2. 4. The first processing means comprises a first hopper means for feeding out a plurality of bills of note one by one, and a first stacker means for outputting the bills of bills which have been processed. The processing means of No. 3 is a second hopper means for feeding out a plurality of bills of bills outputted from the first stacker means one by one, and a first pocket for outputting bills of bills whose matching results by the matching means match. 4. The form processing apparatus according to claim 1, further comprising: a second stacker unit having a second pocket that outputs bills of bills whose matching results by the matching unit do not match.