JPH0211953B2 - - Google Patents

Description

[Detailed description of the invention]

[Summary] A paper sheet validation machine development system that collects data on paper sheets, including banknotes, and performs various processes when using a validation machine for the paper sheets. It has a function to create sample data after checking its validity, and is configured to be able to identify paper sheets by applying recognition logic, so that it can test and evaluate the identification machine to be tested. It is disclosed that the [Industrial Application Field] The present invention relates to a paper sheet classification machine development system, particularly,
This invention relates to a paper sheet validator development system that collects data, creates desired sample data, and uses recognition logic to test and evaluate the target validator. [Prior Art] Conventionally, recognition machines for paper sheets including banknotes have been developed. However, in the case of conventional technology, a large amount of data similar to that used by the classification machine under development is collected from the paper sheets to be classified, and the classification machine under development I was trying to find out how accurately I could identify paper sheets. In other words, by setting in advance a so-called preferable discrimination mode, and more specifically, by setting the sensor position in advance at a preferable position, it is possible to determine how accurately the discrimination mode in such a discrimination machine can perform discrimination. Many methods were used to find out. [Problems to be Solved by the Invention] In the conventional case described above, it has not been possible to develop a discriminator of the desired form from a comprehensive standpoint. For example, in a paper recognition machine that distinguishes paper sheets, data is not collected when the sensor position is changed, such as evaluating which position on the paper sheet is best for the sensor to sense. Therefore, it was extremely difficult and virtually impossible. [Means for solving the problems] The present invention solves the above problems,
It checks the validity of the collected data, eliminates undesired collected data, and creates sample data that corresponds to changes in the sensor device, for example, and has functions that respond to various changes. There is. FIG. 1 shows a basic configuration diagram of the present invention. In the figure, reference numeral 1 is a data processing device, 2 is a bill data collector, 3 is a data editing device, 4 is a floppy disk that holds edited information and supplies it to the data processing device 1, and 5 represents a banknote validating machine that is being tested. The banknote data collector 2 sets m×n grid areas on both the front and back sides of the banknote, and collects data for each grid area, such as color, amount of light reflection by color, amount of light transmission by color, etc. Collect. Furthermore, paper sheets are set so that data can be collected for each square area. The data editing device 3 adds additional data such as the denomination, setting direction, environmental conditions at the time of data collection, and banknote manufacturing lot number to the collected data, and writes the data onto the floppy disk 4. The data processing device 1 is a floppy disk 4
It has the function of reading the contents of the data into the database 6 and performing the following processing. That is, (1) Conveyance state evaluation unit 7...When a banknote was set in the banknote data collector and data about the banknote was collected, whether or not the banknote conveyance speed was extremely abnormal. Also, check the degree of skew during transportation. (2) Data base information evaluation unit 8...
Regarding the information group collected on the base 6, (i) For example, whether there are an extremely large number of banknotes of a particular denomination, or whether the data collected under a particular set state when banknotes are set is extremely (ii) Check the input data acquisition conditions, such as whether there are too many input data, and (ii) check the data acquisition conditions, such as when a 10,000 yen bill was set but it was mistakenly assumed that a 1,000 yen bill was set at the time of data collection. The reliability of the information population on the database 6 is evaluated by checking for abnormalities, checking for undesired deviations in the collected data and data abnormalities. (3) Banknote side data change monitoring unit 9...Although it cannot be detected by the human eye, the type of ink on banknotes may sometimes change. For this,
It is necessary to constantly monitor the presence or absence of such changes and to ensure that the discrimination function of the discrimination machine correctly follows the changes. Try to change it to something more favorable. (4) Sample data creation unit 10: Creates a preferred number of sample data from the collected information to accommodate sensor variations in the discrimination machine to be tested, and supplies the data to the recognition logic unit 12, which will be described later. (5) Discrimination data synthesis unit 11...When collecting data by the banknote data collector 2, for example, collecting a large amount of data when a banknote is skewed at a predetermined angle is as follows: It is extremely complicated. For this reason, it is desirable to synthesize data obtained when the vehicle is skewed at the predetermined angle from a group of data collected without skew. In addition, there may be times when you want to perform a test such as changing the placement position of the sensor in the banknote validator, and it is practically impossible to change the sensor position of the data collector 2 and collect data again. Can not. For this reason, it is desirable to appropriately synthesize data obtained when the sensor position is changed from the data on the data base 6. The discrimination data synthesis section 11 has such a function. (6) Recognition logic unit 12... When developing a banknote validator, it is necessary to test the degree of recognition function that the banknote validator has. For this,
Regarding the data collected by data collector 2,
It is necessary to apply and investigate the preferred form of epistemic logic. It is also necessary to apply recognition logic to examine the data created in the sample data creation section 10. The recognition logic section 12 has a function for this purpose. (7) Discrimination sensor evaluation unit 13... evaluates what kind of sensor is more preferable as a sensor to be used in the test object discrimination machine. The data processing device 1 has the above-mentioned processing functions, but as shown in the figure, (i) the database internal information evaluation section 8 has the input data acquisition condition checking section 8-
1, a data abnormality check section 8-2, etc.
(ii) The discrimination data synthesis unit 11 includes a data synthesis unit 11-1 for sensor position movement, a data synthesis unit 11-2 for skew movement, etc., and (iii) the recognition logic unit 12 performs discrimination processing based on distance. It has a processing section 12-1, a processing section 12-2 based on intra-group division, and the like. The illustrated banknote validating machine 5 is a valid validating machine to be tested,
This corresponds to the discriminating machines that are actually in use and in operation, and information from these discriminating machines 5 is guided to the data processing device 1 via the data editing device 3 as necessary. [Function] Data is collected from the banknote data collector 2 for each denomination of banknotes by changing the set state of the banknotes, passes through the data editing device 3, and is stored on a floppy disk.
It is held on disk 4. At this time, by changing the above-mentioned set state, data such as color is collected for each square area where the entire surface of the front and back of the banknote is divided into m x n square areas. be made to be The data held on the floppy disk 4 is stored on the database 6, and the validity of the collected data is evaluated by the conveyance condition evaluation section 7 and the database information evaluation section 8. . Then, the sample data creation section 10 generates the data.
Sample data is created in a desired form from the contents of the base 6. Also, by the discrimination data synthesis unit 11,
Data for the case where the sensor position is moved are synthesized, and the synthesized data is used as necessary. The recognition logic unit 12 performs predetermined recognition logic,
Perform various tests. Also, the discrimination sensor evaluation section 13
performs evaluations such as selecting preferred types of sensors. [Example] Fig. 2 shows the configuration of an embodiment of the banknote data collector, in which Fig. 2A is a side view, Fig. 2B is a plan view, and Fig. 2B is a plan view.
Figure C shows a configuration diagram of the roller. Reference numeral 14 in the figure is a feeding section, which supplies the banknote 18 to the data collection section 15 when the banknote 18 is inserted. The data collection unit 15 includes a roller 19 as shown in FIGS. 2B and 2C.
is generated, and the banknote 18' is conveyed on the conveyance path 20 as shown by the arrow. The conveyance path 20 is shown in FIG. 2B.
As shown, it has a width that is sufficiently large compared to the distance in the longitudinal direction of the banknote 18'. On the conveyance path 20, banknote entry detection sensors S ₁ , S ₂ , 21 and passage detection sensor 22 are provided, and data collection sensors 23 are arranged symmetrically with respect to the vertical center line shown in FIG. 2B. has been done. A track detection sensor 24 is also provided as shown. As described above, since the width of the conveyance path 20 is sufficiently large compared to the longitudinal length of the banknote 18', the upper end of the banknote 18' is at the upper end of the conveyance path 20 shown in FIG. 2B. The banknotes 18' can be placed in any position from a state where the banknotes 18' are set and transported so that they touch each other to a state where the banknotes 18' are set and transported so that the lower end of the banknotes 18' touches the lower end of the transport path 20 shown in FIG. 2B. It is possible to set Corresponding to these set positions, which position on the banknote 18' is sensed by the data collection sensor 23 is determined. As shown in FIG. 3, the top of the banknote 18' is divided into m×n grid areas 25, and the grid areas arranged in the horizontal direction as shown in _FIG . If the grid area groups arranged in the vertical direction shown in FIG. 3 are defined as zones Z ₁ , Z ₂ , Z ₃ . , while the banknotes 18' are being conveyed, the data collection sensor 23 collects data on the grid areas on the two upper and lower tracks. By changing the position at which the banknote 18' is set on the conveyance path 20, data for each of the square areas 25 within a predetermined range on the banknote 18' is collected. can do. Also the third
The data in the hatched square area 25 is extracted at the transport timing corresponding to zone _Z2 while one of the sensors 23 is collecting data along the track T _i+1 . At this time, sensor 2
Which track 3 corresponds to can be determined by which position of the track detection sensor 24 the end of the banknote 18' passes through. The banknotes that have been conveyed through the data collection unit 15 are stored in the illustrated storage unit 16 as shown in the illustrated banknotes 18″.The data collected during the above-mentioned conveyance is sent from the control unit 17 to the banknotes shown in FIG. The data is transferred to the data editing device 3. Fig. 4 shows the configuration of an embodiment of the data editing device. Reference numeral 26 in the figure indicates a control unit (processor);
27 represents a data transmission means that receives data from the data collector. Reference numeral 28 denotes a data input section, which, in correspondence with each data transferred from the data collector 2, inputs (i) what kind of denomination the banknote 18' corresponds to;
(ii) Which direction does the data correspond to when the banknote 18' is set (there are two orientations for the front side and two orientations for the back side)? (iii) What environmental conditions were there at the time of data collection? and (iv) which banknote production lot the banknote 18' corresponds to.
It is input from 8. 29 is a data display section, 30 is a ROM writer, 3
1 is the data store section (floppy disk 4
). Data 32 transferred from data collector 2
As shown in the upper part of FIG. v) Has a data format with sense data. Then, as described above, additional data,
, , are added, and the entire information 33 is stored on the floppy disk 4 and supplied to the data processing device 1. A data base 6 is prepared in the data processing device 1, and from the floppy disk 4,
A group of information 33 collected as described above is stored. The data processing device 1 includes functional units 7, 8, 9, 10, 1 as described with reference to FIG.
1, 12, 13, etc. exist. The processing mode in each functional unit will be briefly described below. ☆ Conveying state evaluation unit 7 The histogram corresponding to each conveying speed and the amount of skew (bills 18' being conveyed diagonally) are taken to collect data in extreme cases. Delete it. ☆ Data base information evaluation section 8 Create histograms for each denomination, set direction, etc., and check for extreme deviations. ☆ Bill side data change monitoring unit 9 The bill discrimination results applied to the bill validating machine 5 in operation and the data collected during discrimination are sent to the data processing device 1, for example, periodically or at any time, and based on this information, Discrepancies with the information held on the database 6 are determined. ☆ Sample data creation unit 10 From the information collected on the database 6,
Taking into account variations in the sensors of banknote validators, a predetermined number of sample data that can be applied to all sensors is extracted without changing the characteristics of the population, and a simulation of correct discrimination or false discrimination is performed. Make sure to do the following. ☆ Discrimination data synthesis unit 11 Since the banknotes are conveyed diagonally in the test target discriminator, for example, the arrow A shown in FIG.
As shown, the data from the square area on arrow A is
It may be extracted as a grid area on track T _i+2 . In such a case, the data that would be collected by the test target classification machine is synthesized. That is, the data for each square area on the arrow A shown in FIG. do. Additionally, data corresponding to the case where the sensor placement position is changed is also synthesized as necessary. ☆ Recognition logic unit 12 When identifying banknotes, for example, a 10,000 yen bill, a 5
It is sufficient to identify either a 1,000 yen bill, a 1,000 yen bill, or a 500 yen bill. However, there are also banknote analogues that can be passed through a banknote validator. From this, for example, if the object to be identified is worth 10,000 yen, just because the distance from the standard feature of a 10,000 yen bill is within a predetermined threshold, the object to be identified is worth 10,000 yen. The distance from the standard features of other 5,000 yen bills, the distance from the standard features of 1,000 yen bills, the distance from the standard features of 500 yen bills, and even completely blank or completely The distance from the standard feature amount of the black paper is checked, and if the object to be classified is worth 10,000 yen, it is classified as 10,000 yen. ☆ Discrimination Sensor Evaluation Unit 13 In the discrimination machine to be tested, there may be a problem as to whether a sensor of a certain model #A or a sensor of another model #B should be used. In such a case, check the Euclidean distance (or Mahalanobis distance) when a 90% discrimination rate can be obtained, and use the sensor that can obtain the above 90% discrimination rate at a smaller distance. It is desirable to do so. The discrimination sensor evaluation unit 13
Such a test will be carried out. [Effects of the Invention] As explained above, according to the present invention, it is possible to collect a finite amount of data, create preferable sample data, and perform various tests, thereby developing a paper sheet identification machine. In doing so, from a comprehensive standpoint, it becomes possible to test, for example, what kind of sensor should be placed at what position.

[Brief explanation of drawings]

Fig. 1 is a diagram of the principle configuration of the present invention, Fig. 2 is an example of the structure of a banknote data collector, Fig. 3 is an explanatory diagram for explaining the collection of banknote data, Fig. 4 is the structure of a data editing device, and Fig. 5 shows an example data format of collected information. In the figure, 1 is a data processing device, 2 is a banknote data collector, 3 is a data editing device, 4 is a floppy disk, 6 is a database, 8 is an information evaluation unit in the database, and 10 is a sample data creation unit. , 11
12 represents a discrimination data synthesis section, and 12 represents a recognition logic section.

Claims (1)

[Scope of Claims] 1. A data collector 2 that reads information about set paper sheets 18 including banknotes using a plurality of sensors 23; An information processing function unit that includes a data editing device 3 that adds additional data related to data, and a database 6 that holds information edited by the data editing device 3, and processes information in the database 6. In the paper sheet recognition machine development system having at least a data processing device 1 equipped with a conveyance state evaluation section 7 that performs checks on the data collected by the data collector 2; a database internal information evaluation section 8 that performs checks on the data collected by the data collector 2, including checking for data acquisition conditions and checking for abnormal data; a specimen data creation unit 10 that creates specimen data to be used for paper leaf identification using information on the database 6; It is equipped with a discrimination data synthesis section 11 that synthesizes data, and a recognition logic section 12 that performs processing based on the recognition logic used for the above-mentioned paper sheet discrimination. A feature is that sample data used for type discrimination is created, and the results recognized by the recognition logic section 12 are used to test and evaluate the paper sheet discrimination machine that is the test object. A paper sheet identification machine development system.