Currency identification apparatus, currency processing apparatus, and currency identification method

Abstract

To provide a currency identification apparatus, a currency processing apparatus, and a currency identification method for enabling performance of sensing an abnormal medium minutely changed in feature quantity to be improved while preventing erroneous sensing of a normal medium.SOLUTION: Provided is a currency identification apparatus including a control unit that executes processing of collecting first data obtained by detecting a first physical quantity of the whole surface of a currency, processing of collecting second data obtained by detecting a second physical quantity different from the first physical quantity, and first determination processing concerning a first identification item based on the first data. The first determination processing determines whether the first identification item is normal based on the first threshold value for each partial region of the currency, and when a partial region in which the first identification item is not normal is present, executes second determination processing concerning a second identification item based on the second data. The second identification item is an identification item which is identical or relevant to the first identification item. The second determination processing determines whether the second identification item is normal in a second partial region corresponding to the first partial region based on the second threshold value.SELECTED DRAWING: Figure 1

Description

Technical Field

[0001] The present disclosure relates to a currency identification device, a currency processing device, and a currency identification method.

Background Art

[0002] Conventionally, in processing devices that process paper materials such as banknotes (bills), gift certificates, checks, and securities, it has been required to detect abnormal paper materials such as pasted paper materials, torn paper materials, and paper materials with scribbles.

[0003] Pasted paper materials are paper materials created by pasting pieces of paper using tape, glue, adhesives, etc. from one or two or more pieces of paper materials. Hereinafter, paper materials with pieces of paper pasted together may be abbreviated as pasted vouchers.

[0004] Note that Patent Document 1 describes, regarding the classification of currencies or value items such as banknotes or coins, a support vector machine and a method of using a subset for forming a subset of threshold data for identification by selecting a threshold suitable for identification from a large amount of multivariate data stored in a memory by scanning using a plurality of sensors and a plurality of wavelengths for identifying and classifying and authenticating documents including banknotes.

Prior Art Documents

Patent Documents

[0005]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0006] There are substances among tape, glue, adhesives, etc. that fluoresce when irradiated with ultraviolet light. Therefore, it is conceivable to detect pasted vouchers by determining the presence or absence of tape or the like based on the fluorescence image of the paper material.

[0007] However, in the case of paper materials such as banknotes, the fluorescence emission amount of banknotes tends to increase depending on the degree of circulation. Specifically, during the process of circulating in the market, dirt such as human hand stains adheres, and the hand stain part fluoresces, and there are banknotes in which the whole banknote fluoresces due to the hand stains. In addition, the fluorescence emission amounts of tapes, glues, adhesives, etc. attached to the joints of cut-and-pasted coupons are sometimes very small, and there are many cut-and-pasted coupons that are difficult to detect. Such cut-and-pasted coupons can be detected by making the threshold value regarding the fluorescence emission amount strict, but in that case, the case of misdetecting normal paper materials that are not cut-and-pasted coupons will increase.

[0008] Also, in the case of detecting cut-and-pasted coupons based on infrared transmission data or ultrasonic transmission data of paper materials, in the case of detecting thickness anomalies of paper materials based on thickness data of paper materials, in the case of detecting tears in paper materials based on ultrasonic transmission data, etc., the same problems exist, and there may be cases where it becomes difficult to detect the abnormality while preventing misdetection of normal paper materials.

[0009] The present disclosure has been made in view of the above situation, and an object thereof is to provide a currency discrimination device, a currency processing device, and a currency discrimination method capable of improving the detection performance of abnormal media with minute feature quantity changes while suppressing misdetection of normal media.

Means for Solving the Problems

[0010] In order to solve the above-described problems and achieve the object, (1) a currency identification device according to a first aspect of the present disclosure is a currency identification device that identifies currency, and includes a control unit that executes a process of collecting first data obtained by detecting a first physical quantity of the entire surface of the currency, a process of collecting second data obtained by detecting a second physical quantity different from the first physical quantity of the entire surface of the currency, and a first determination process regarding a first identification item based on the first data. The first determination process determines whether the first identification item is normal based on a first threshold value for each partial area of the currency. When there is a first partial area where the first identification item is not normal as a result of the first determination process, the control unit further executes a second determination process regarding a second identification item based on the second data. The second identification item is the same identification item as the first identification item or an identification item related to the first identification item. The second determination process determines whether the second identification item is normal based on a second threshold value in a second partial area corresponding to the first partial area.

[0011] (2) In the currency identification device according to (1) above, the control unit may further execute a third determination process regarding the first identification item based on the first data. The third determination process may determine whether the first identification item is normal based on a third threshold value for each partial area of the currency. The third threshold value may be a criterion that is looser than the first threshold value. When there is no partial area where the first identification item is not normal as a result of the third determination process, the control unit may execute the first determination process.

[0012] (3) In the currency identification device according to the above (1) or (2), the control unit may further execute a fourth determination process regarding the second identification item based on the second data. The fourth determination process may determine whether the second identification item is normal based on a fourth threshold value for each partial area of the currency. The fourth threshold value may be a looser criterion than the second threshold value. When, as a result of the fourth determination process, there is no partial area where the second identification item is abnormal, and as a result of the first determination process, there is the first partial area where the first identification item is abnormal, the control unit may execute the second determination process.

[0013] (4) In the currency identification device according to any one of the above (1) to (3), the first data and the second data may be a combination of thickness data obtained by detecting the thickness of paper as the first physical quantity or the second physical quantity, and fluorescence data obtained by detecting the fluorescence emitted by the paper as the first physical quantity or the second physical quantity.

[0014] (5) In the currency identification device according to the above (4), the first identification item and the second identification item may be a combination of a thickness abnormality determination for determining whether there is an abnormality in the thickness of the paper, and a cut-and-paste ticket determination for determining whether the paper has been cut and pasted. The control unit may execute the thickness abnormality determination based on the thickness data and execute the cut-and-paste ticket determination based on the fluorescence data.

[0015] (6) In the currency identification device according to any one of the above (1) to (3), the first data and the second data may be a combination of thickness data obtained by detecting the thickness of paper as the first physical quantity or the second physical quantity, and infrared transmission data obtained by detecting the infrared light transmitted through the paper as the first physical quantity or the second physical quantity.

[0016] (7) In the currency discrimination device according to (6) above, the first discrimination item and the second discrimination item may be a combination of a thickness abnormality determination for determining whether there is an abnormality in the thickness of the paper sheet and a cut-and-paste ticket determination for determining whether the paper sheet has been cut and pasted. The control unit may execute the thickness abnormality determination based on the thickness data and execute the cut-and-paste ticket determination based on the infrared transmission data.

[0017] (8) In the currency discrimination device according to any one of (1) to (3) above, the first data and the second data may be a combination of thickness data obtained by detecting the thickness of the paper sheet as the first physical quantity or the second physical quantity and ultrasonic transmission data obtained by detecting ultrasonic waves transmitted through the paper sheet as the first physical quantity or the second physical quantity.

[0018] (9) In the currency discrimination device according to (8) above, the first discrimination item and the second discrimination item may both be thickness abnormality determinations for determining whether there is an abnormality in the thickness of the paper sheet. The control unit may execute a thickness abnormality determination based on the thickness data and a thickness abnormality determination based on the ultrasonic transmission data.

[0019] (10) In the currency discrimination device according to (8) above, the first discrimination item and the second discrimination item may be a combination of a thickness abnormality determination for determining whether there is an abnormality in the thickness of the paper sheet and a tear determination for determining whether there is a tear in the paper sheet. The control unit may execute the thickness abnormality determination based on the thickness data and execute the tear determination based on the ultrasonic transmission data.

[0020] (11) Further, a currency processing device according to a second aspect of the present disclosure includes the currency discrimination device according to any one of (1) to (10) above.

[0021] (12) Further, the currency identification method according to the third aspect of the present disclosure is a currency identification method for identifying currency, comprising: a step of collecting first data obtained by detecting a first physical quantity of the entire surface of the currency; a step of collecting second data obtained by detecting a second physical quantity different from the first physical quantity of the entire surface of the currency; and a first determination step of making a determination regarding a first identification item based on the first data, wherein the first determination step determines whether the first identification item is normal based on a first threshold value for each partial area of the currency, and as a result of the first determination step, if there is a first partial area where the first identification item is not normal, the method further comprises a second determination step of making a determination regarding a second identification item based on the second data, the second identification item being the same identification item as the first identification item or an identification item related to the first identification item, and the second determination step determines whether the second identification item is normal based on a second threshold value in a second partial area corresponding to the first partial area.

Advantages of the Invention

[0022] According to the present disclosure, it is possible to provide a currency identification device, a currency processing device, and a currency identification method capable of suppressing misdetection of normal media while improving the detection performance of abnormal media with minute changes in feature amounts.

Brief Description of the Drawings

[0023]

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Embodiments for Carrying Out the Invention

[0024] Hereinafter, with reference to the drawings, embodiments of a currency discrimination device, a currency processing device, and a currency discrimination method according to the present disclosure will be described in detail. The currencies targeted by the present disclosure mainly include paper money and coins. Here, as the paper money, various paper money such as banknotes, checks, gift certificates, bills of exchange, forms, securities, and card-shaped media are applicable. In the following, the present disclosure will be described by taking an apparatus for banknotes as an example.

[0025] In the following description, the same reference numerals are commonly and appropriately used for the same parts or parts having the same functions among different drawings, and the repeated description thereof will be omitted as appropriate.

[0026] (Embodiment 1) The configuration of the currency discrimination device according to the present embodiment will be described with reference to FIG. 1. FIG. 1 is a block diagram for explaining an example of the configuration of the currency discrimination device according to Embodiments 1 and 2.

[0027] As shown in FIG. 1, the currency discrimination device 1 according to the present embodiment is a device for discriminating banknotes as paper money, and includes a control unit 10.

[0028] In addition, the currency discrimination device 1 may further include a storage unit composed of a semiconductor memory (RAM or ROM), a hard disk, etc., and a plurality of types of sensors capable of detecting various physical quantities of banknotes, such as a thickness detection sensor, an optical line sensor, and an ultrasonic sensor.

[0029] As shown in FIG. 1, the control unit 10 has a data acquisition unit 11, a first discrimination processing unit 12, and a second discrimination processing unit 13.

[0030] The control unit 10 is a controller that controls each part of the currency discrimination device 1, and is configured as a computer system including a CPU (Central Processing Unit) and various hardware controlled by the CPU (for example, FPGA (Field Programmable Gate Array)). The control unit 10 realizes various processes by executing a predetermined software program in the CPU.

[0031] The data acquisition unit 11 performs a process of collecting (acquiring) first data which is data obtained by detecting a first physical quantity of the entire surface of the banknote to be identified, and a process of collecting (acquiring) second data which is data obtained by detecting a second physical quantity different from the first physical quantity of the entire surface of the banknote.

[0032] The first data and the second data are different types of data obtained by detecting different physical quantities for the entire front side of the same banknote to be identified.

[0033] Examples of the first data and the second data include a combination of thickness data and fluorescence data, a combination of thickness data and infrared transmission data, a combination of thickness data and ultrasonic transmission data, and the like.

[0034] More specifically, the first data may be thickness data and the second data may be fluorescence data, or the first data may be thickness data and the second data may be infrared transmission data, or the first data may be thickness data and the second data may be ultrasonic transmission data.

[0035] Here, the thickness data is data obtained by detecting the thickness of paper materials as a physical quantity. The fluorescence data is data obtained by detecting the fluorescence emitted by paper materials as a physical quantity. Note that fluorescence can be detected by irradiating the paper materials with excitation light such as ultraviolet light. The infrared transmission data is data obtained by detecting infrared light transmitted through the paper materials as a physical quantity. The ultrasonic transmission data is data obtained by detecting ultrasonic waves transmitted through the paper materials as a physical quantity.

[0036] The thickness data can be detected, for example, using a thickness detection sensor. The fluorescence data and the infrared transmission data can be detected, for example, using an optical line sensor. When acquiring the fluorescence data, an excitation light source such as ultraviolet light can be used for irradiation. When acquiring the infrared transmission data, an infrared light source can be used for irradiation. The ultrasonic transmission data can be detected, for example, using an ultrasonic sensor.

[0037] The first data and the second data may be an image (image data) composed of a plurality of pixels arranged in a matrix in the main scanning direction and the sub-scanning direction of the sensor. Here, the address of each pixel may be specified by the channel (column) of the detection element of the sensor corresponding to the position in the main scanning direction and the line (row) corresponding to the position in the sub-scanning direction. Note that the line (row) is a number assigned in order to the line data sequentially output by a plurality of detection elements of the sensor.

[0038] In that case, the thickness data may be thickness image data in which each pixel indicates the thickness of the paper sheet, the fluorescence data may be fluorescence image data in which each pixel indicates the intensity of fluorescence emitted from the paper sheet, the infrared transmission data may be infrared transmission image data in which each pixel indicates the intensity of infrared light transmitted through the paper sheet, and the ultrasonic transmission data may be ultrasonic transmission image data in which each pixel indicates the intensity of ultrasonic waves transmitted through the paper sheet.

[0039] The data acquisition unit 11 may directly acquire the first data and the second data from the same or different sensors that detected those data, or may acquire those data from an external storage device that stores those data via communication means.

[0040] The first identification processing unit 12 executes a first determination process regarding a first identification item based on the first data.

[0041] In this specification, the "identification item" represents specifically what kind of abnormality determination is to be made. For example, it includes sticker determination, thickness abnormality determination, tear determination, etc. Thus, the "identification item" may represent a determination corresponding to so-called positive / negative determination.

[0042] The sticker determination is to determine whether the paper sheets have been cut and pasted. That is, to determine whether the paper sheets are stickers. The thickness abnormality determination is to determine whether there is an abnormality in the thickness of the paper sheets. The thickness abnormality determination may include a tape coupon determination to determine whether it is a tape coupon which is a paper sheet with a tape attached. The tear determination is to determine whether there is a tear in the paper sheets. That is, to determine whether it is a torn coupon which is a paper sheet with a tear.

[0043] The first determination process by the first identification processing unit 12 determines whether the first identification item is normal based on the first threshold value for each partial area of the banknote. That is, it determines whether there is an abnormal part regarding the first identification item in the banknote using the first data and the first threshold value, determines whether such an abnormality exists for each partial area, and if it does not exist, determines that it is normal, and if it exists, determines that it is not normal (there is an abnormality).

[0044] More specifically, the first identification processing unit 12 may scan the image data as the first data for each partial area (for example, a rectangular area), calculate a feature amount (evaluation value) from the data constituting each partial area, compare the calculated feature amount with the first threshold value, and determine whether the first identification item is normal according to the comparison result. At this time, it may also be determined whether the first identification item is normal based on whether the calculated feature amount exceeds the first threshold value. If it does not exceed the first threshold value, it may be determined to be normal, and if it exceeds the first threshold value, it may be determined to be not normal.

[0045] In addition, in this specification, "a certain identification item is not normal" shall include not only the case where the identification item is not normal, but also the case where there is a suspicion that the identification item is not normal. Further, "a certain identification item is normal" shall include not only the case where the identification item is normal, but also the case where there is a possibility that the identification item is normal.

[0046] In addition, in this specification, "a certain identification item is normal" indicates that the identification item has been determined to be OK, and indicates that there is no (or there may be no) abnormality (defect) related to the identification item in the currency. On the contrary, "a certain identification item is not normal" indicates that the identification item has been determined to be NG, and indicates that there is (or there is a suspicion of) an abnormality (defect) related to the identification item in the currency.

[0047] The second identification processing unit 13 executes a second determination process regarding the second identification item based on the second data. That is, the types of data used in the first determination process and the second determination process are different.

[0048] In addition, the second determination process by the second identification processing unit 13 is executed when, as a result of the first determination process by the first identification processing unit 12, there is a first partial region where the first identification item is not normal. The second determination process is executed when at least one first partial region exists.

[0049] Note that when, as a result of the first determination process by the first identification processing unit 12, there is no partial region where the first identification item is not normal, the second determination process by the second identification processing unit 13 may not be executed.

[0050] Here, the second identification item is the same identification item as the first identification item or an identification item related to the first identification item. In the former case, it is determined whether the same type of abnormality exists using different data. In the latter case, it is determined whether there are different types of abnormalities that are related to each other using different data.

[0051] The "abnormalities that are of different types but related to each other" may refer to two different types of abnormalities where a certain correlation relationship (corresponding relationship) is recognized between the occurrence location of one abnormality and the occurrence location of the other abnormality. Examples include cases where the occurrence locations of these two types of abnormalities are substantially the same or correspond to each other.

[0052] Thus, "the second identification item is related to the first identification item" means that a certain correlation relationship (corresponding relationship) is recognized between the occurrence locations of the two types of abnormalities targeted by those items.

[0053] For example, the thickness abnormality determination is an identification item related to the sticker determination. However, the thickness abnormality of the paper sheet determined by the thickness abnormality determination may occur at the same location as the pasted portion of the paper sheet determined by the sticker determination. This is because when pasting paper pieces using tape, glue, adhesive, etc., the thickness of the pasted portion becomes larger than the normal thickness.

[0054] Then, the second determination process by the second identification processing unit 13 determines whether the second identification item is normal based on the second threshold value in the second partial region corresponding to the first partial region (the region where the first identification item is not normal). That is, using the second data and the second threshold value, it determines whether the abnormal portion related to the second identification item exists in the second partial region corresponding to the first partial region. As a result of the second determination process, if the abnormal portion related to the second identification item does not exist in the second partial region, it may be determined that the second identification item is normal, and if it exists in the second partial region, it may be determined that the second identification item is not normal (abnormal).

[0055] More specifically, the second identification processing unit 13 may calculate a feature amount (evaluation value) from the data constituting the second partial region of the image data as the second data, compare the calculated feature amount with a second threshold value, and determine whether the second identification item is normal according to the comparison result. Further, the second identification processing unit 13 may scan the data constituting the second partial region for each partial region smaller than the second partial region (for example, a rectangular region), calculate a feature amount (evaluation value) from the data constituting each partial region, compare the calculated feature amount with the second threshold value, and determine whether the second identification item is normal according to the comparison result. In any case, it may be determined whether the second identification item is normal based on whether the calculated feature amount exceeds the second threshold value. When the second threshold value is not exceeded, it may be determined to be normal, and when the second threshold value is exceeded, it may be determined to be abnormal.

[0056] Note that the second identification processing unit 13 may not execute the second determination process in other partial regions except the second partial region.

[0057] Next, with reference to FIG. 2, the operation of the currency identification device 1 according to the present embodiment will be described. FIG. 2 is a flowchart for explaining an example of the operation of the currency identification device according to Embodiment 1.

[0058] As shown in FIG. 2, first, the data acquisition unit 11 executes a process of acquiring first data, which is data obtained by detecting a first physical quantity of the entire surface of the banknote, and a process of acquiring second data, which is data obtained by detecting a second physical quantity different from the first physical quantity of the entire surface of the banknote (step S11).

[0059] Next, the first identification processing unit 12 executes a first determination process regarding the first identification item based on the first data (step S12). At this time, the first identification processing unit 12 determines whether the first identification item is normal based on the first threshold value for each partial region of the banknote.

[0060] In step S12, if there is no abnormal part regarding the first identification item in all partial areas (step S12, Yes), it may be determined that the first identification item is normal (step S13), and then the operation of the currency identification device 1 may end.

[0061] In step S12, if there is at least one first partial area where the first identification item is not normal (step S12, No), the second identification processing unit 13 executes a second determination process regarding the second identification item based on the second data (step S14). At this time, the second identification processing unit 13 determines whether the second identification item is normal based on the second threshold value in the second partial area corresponding to each first partial area.

[0062] In step S14, if there is no abnormal part regarding the second identification item in all second partial areas (step S14, Yes), it may be determined that the second identification item is normal (step S15), and then the operation of the currency identification device 1 may end.

[0063] In step S14, if there is an abnormal part regarding the second identification item in at least one second partial area (step S14, No), it may be determined that the second identification item is not normal (abnormal) (step S16), and then the operation of the currency identification device 1 may end.

[0064] According to the present embodiment, first, the first identification processing unit 12 executes a first determination process regarding a first identification item for each partial area of the banknote based on the first data and the first threshold value. As a result, when there is a first partial area where the first identification item is not normal, the second identification processing unit 13 executes a second determination process regarding a second identification item that is the same as or related to the first identification item based on second data different from the first data and a second threshold value. Therefore, by making the first and second threshold values stricter respectively, not only banknotes with a high possibility that the first and second identification items are not normal, but also banknotes with a low possibility (banknotes that may not be normal) can be determined to be abnormal in the first and second determination processes. Accordingly, even a slight abnormality regarding the first and / or second identification items can be detected. Further, since the second identification processing unit 13 executes the second determination process in a second partial area corresponding to the first partial area, it is possible to determine twice whether the first and second identification items that are the same or related to each other are normal for corresponding locations (for example, the same location) of the banknote (double check). Therefore, the probability of erroneously detecting a normal banknote for which those identification items are not abnormal can be reduced. From the above, it is possible to improve the detection performance of an abnormal medium with a minute change in feature amount while suppressing the erroneous detection of a normal medium.

[0065] Hereinafter, specific examples of the first and second data, specific examples of the first and second identification items, and specific examples of the first and second determination processes will be described.

[0066] When the first data and the second data are a combination of thickness data obtained by detecting the thickness of the banknote as the first physical quantity or the second physical quantity and fluorescence data obtained by detecting the fluorescence emitted by the banknote as the first physical quantity or the second physical quantity, the first identification item and the second identification item may be a combination of a thickness abnormality determination and a cut-and-paste ticket determination. The control unit 10 (one of the first identification processing unit 12 and the second identification processing unit 13) may execute a thickness abnormality determination based on the thickness data, and the control unit 10 (the other of the first identification processing unit 12 and the second identification processing unit 13) may execute a cut-and-paste ticket determination based on the fluorescence data.

[0067] Specific examples of paper sheets with abnormal thickness include, for example, tape tickets which are paper sheets with tape attached, and those with adhesives or glue attached, etc.

[0068] When the first data and the second data are a combination of thickness data obtained by detecting the thickness of the banknote as the first physical quantity or the second physical quantity, and infrared transmission data obtained by detecting infrared light transmitted through the banknote as the first physical quantity or the second physical quantity, the first identification item and the second identification item may be a combination of thickness abnormality determination and cut-and-pasted ticket determination. The control unit 10 (either the first identification processing unit 12 or the second identification processing unit 13) may execute thickness abnormality determination based on the thickness data, and the control unit 10 (the other of the first identification processing unit 12 and the second identification processing unit 13) may execute cut-and-pasted ticket determination based on the infrared transmission data.

[0069] According to the infrared transmission data, it is possible to detect cut-and-pasted tickets with a large overlap of paper pieces at the pasted portion, cut-and-pasted tickets with dust attached to the pasted portion, and cut-and-pasted tickets with a small overlap of paper pieces at the pasted portion. This is because at a portion where the overlap of paper pieces is large or dust is attached, the intensity of infrared light transmitted through the banknote decreases, and at a portion where the overlap of paper pieces is small (which may be a portion where a gap is formed), the intensity of infrared light transmitted through the banknote increases.

[0070] When the first data and the second data are a combination of thickness data obtained by detecting the thickness of the banknote as the first physical quantity or the second physical quantity, and ultrasonic transmission data obtained by detecting ultrasonic waves transmitted through the banknote as the first physical quantity or the second physical quantity, both the first identification item and the second identification item may be thickness abnormality determination. The control unit 10 (either the first identification processing unit 12 or the second identification processing unit 13) may execute thickness abnormality determination based on the thickness data, and the control unit 10 (the other of the first identification processing unit 12 and the second identification processing unit 13) may execute thickness abnormality determination based on the ultrasonic transmission data.

[0071] According to the ultrasonic transmission data, it is possible to detect paper materials with abnormal thickness, such as tape tickets and those with adhesives or glue attached. This is because the intensity of the ultrasonic waves transmitted through the banknote decreases at the parts where the tape or adhesive is attached. Also, by using the ultrasonic transmission data, it is possible to more effectively detect tape tickets with thin tapes attached compared to the case of using thickness data.

[0072] Also, when the first data and the second data are a combination of thickness data that detects the thickness of the banknote as the first physical quantity or the second physical quantity, and ultrasonic transmission data that detects ultrasonic waves transmitted through the banknote as the first physical quantity or the second physical quantity, the first identification item and the second identification item may be a combination of thickness abnormality determination and tear determination. The control unit 10 (one of the first identification processing unit 12 and the second identification processing unit 13) may execute thickness abnormality determination based on the thickness data, and the control unit 10 (the other of the first identification processing unit 12 and the second identification processing unit 13) may execute tear determination based on the ultrasonic transmission data.

[0073] According to the ultrasonic transmission data, it is possible to detect torn banknotes with tears. This is because the diffraction phenomenon of ultrasonic waves transmitted through the banknote occurs at the tear, and its intensity increases significantly.

[0074] Also, although the thickness abnormality determination is an identification item related to the tear determination, the thickness abnormality of the paper material determined by the thickness abnormality determination may occur at a location corresponding to or, for example, adjacent to the location where the tear of the paper material determined by the tear determination exists. For example, in a cut-and-paste ticket where pieces of paper are partially bonded together by tape, adhesive, or glue, the thickness increases at the location where the tape or adhesive exists, and the diffraction phenomenon of ultrasonic waves occurs at the location where the pieces of paper overlap adjacent to the tape or adhesive or at the location where a gap is formed between the pieces of paper, resulting in an increase in the amount of ultrasonic waves transmitted.

[0075] (Embodiment 2) As shown in FIG. 1, the currency discrimination device 2 according to this embodiment, like the currency discrimination device 1 according to Embodiment 1, has a control unit 10, a data acquisition unit 11, a first discrimination processing unit 12, and a second discrimination processing unit 13. However, it is different from the currency discrimination device 1 according to Embodiment 1 in that the first discrimination processing unit 12 further executes a third determination process, and the second discrimination processing unit 13 further executes a fourth determination process.

[0076] In this embodiment, before the first determination process, the first discrimination processing unit 12 executes a third determination process regarding the first discrimination item based on the first data. Similar to the first determination process, the third determination process by the first discrimination processing unit 12 determines whether the first discrimination item is normal based on a third threshold value for each partial area of the banknote. That is, it determines whether there is an abnormal portion regarding the first discrimination item in the banknote using the first data and the third threshold value, determines whether such an abnormality exists for each partial area, and if it does not exist, determines that it is normal, and if it exists, determines that it is not normal (abnormal).

[0077] More specifically, the first discrimination processing unit 12 may scan the image data as the first data for each partial area (for example, a rectangular area), calculate a feature amount (evaluation value) from the data constituting each partial area, compare the calculated feature amount with the third threshold value, and determine whether the first discrimination item is normal according to the comparison result. At this time, it may be determined whether the first discrimination item is normal based on whether the calculated feature amount exceeds the third threshold value. If it does not exceed the third threshold value, it is determined to be normal, and if it exceeds the third threshold value, it is determined to be not normal.

[0078] Here, the third threshold value is a looser standard than the first threshold value. Therefore, in the third determination process, only banknotes with a higher possibility of the first discrimination item being not normal (abnormal) are detected compared to the first determination process. In this way, the third determination process may be executed to detect banknotes with clearly abnormal first discrimination items.

[0079] Also, the first determination process and the third determination process may be the same determination process except that the threshold values used are different. That is, in the first determination process and the third determination process, the scanning mode of the partial area and the calculation method of the feature amount may be common.

[0080] Note that the fact that a certain threshold value A is a looser criterion than another threshold value B means that it is easier for threshold value A to pass (result in an OK determination) the said determination process than threshold value B. That is, when the same banknote group is determined by a common determination method using threshold value A and threshold value B, in the determination process using threshold value A, compared with the case of using threshold value B, the number of banknotes determined to be normal may be larger, and conversely, the number of banknotes determined to be not normal (with abnormality) may be smaller.

[0081] And in the present embodiment, when, as a result of the third determination process, there is no partial area where the first identification item is not normal, the first identification processing unit 12 executes the first determination process.

[0082] Note that when, as a result of the third determination process, there is at least one partial area where the first identification item is not normal, the first identification processing unit 12 usually does not execute the first determination process, but in that case, the first determination process may also be executed.

[0083] Also, in the present embodiment, before the second determination process, the second identification processing unit 13 executes a fourth determination process regarding the second identification item based on the second data. The fourth determination process by the second identification processing unit 13, similar to the first determination process, determines whether the second identification item is normal based on a fourth threshold value for each partial area of the banknote. That is, it determines whether there is an abnormal part regarding the second identification item in the banknote using the second data and the fourth threshold value, determines whether such an abnormality exists for each partial area, and determines that it is normal if it does not exist, and determines that it is not normal (with abnormality) if it exists.

[0084] More specifically, the second identification processing unit 13 may scan the image data as the second data for each partial area (for example, a rectangular area), calculate a feature amount (evaluation value) from the data constituting each partial area, compare the calculated feature amount with a fourth threshold value, and determine whether the second identification item is normal according to the comparison result. At this time, it may be determined whether the second identification item is normal based on whether the calculated feature amount exceeds the fourth threshold value. When the fourth threshold value is not exceeded, it may be determined to be normal, and when the fourth threshold value is exceeded, it may be determined to be abnormal.

[0085] Here, the fourth threshold value is a looser criterion than the second threshold value. Therefore, in the fourth determination process, only banknotes with a higher possibility that the second identification item is abnormal are detected as compared with the second determination process. In this way, the fourth determination process may be executed to detect banknotes in which the second identification item is clearly abnormal.

[0086] In addition, the second determination process and the fourth determination process may be the same determination process except that the threshold values used and the determination target areas are different. That is, the method for calculating the feature amount may be common in the second determination process and the fourth determination process.

[0087] In this embodiment, when, as a result of the fourth determination process, there is no partial area where the second identification item is abnormal, and as a result of the first determination process by the first identification processing unit 12, there is a first partial area where the first identification item is abnormal, the second determination process is executed.

[0088] Note that when, as a result of the fourth determination process, there is at least one partial area where the second identification item is abnormal, the second identification processing unit 13 usually does not execute the second determination process, but the second determination process may also be executed in that case.

[0089] Next, with reference to FIG. 3, the operation of the currency identification device 2 according to the present embodiment will be described. FIG. 3 is a flowchart for explaining an example of the operation of the currency identification device according to Embodiment 2.

[0090] As shown in FIG. 3, first, the data acquisition unit 11 executes a process of acquiring first data (step S21) and a process of acquiring second data (step S22).

[0091] Next, the first identification processing unit 12 executes a third determination process regarding the first identification item based on the first data (step S23). At this time, the first identification processing unit 12 determines whether the first identification item is normal based on a third threshold value for each partial area of the banknote.

[0092] In step S23, if there is at least one partial area where the first identification item is not normal (step S23, No), it may be determined that the first identification item is not normal (there is an abnormality) (step S24), and then step S25 described later may not be executed.

[0093] In step S23, if there is no partial area where the first identification item is not normal (step S23, Yes), the first identification processing unit 12 executes a first determination process regarding the first identification item based on the first data (step S25). At this time, the first identification processing unit 12 determines whether the first identification item is normal based on a first threshold value, which is a stricter standard than the third threshold value, for each partial area of the banknote.

[0094] In step S25, if there is no abnormal part regarding the first identification item in all partial areas (step S25, Yes), it may be determined that the first identification item is normal (step S26).

[0095] Also, the second identification processing unit 13 executes a fourth determination process regarding the second identification item based on the second data (step S27). At this time, the second identification processing unit 13 determines whether the second identification item is normal based on a fourth threshold value for each partial area of the banknote.

[0096] In step S27, when there is at least one partial region where the second identification item is not normal (step S27, No), it may be determined that the second identification item is not normal (there is an abnormality) (step S28), and then, step S29 described later may not be executed.

[0097] In step S27, when there is no partial region where the second identification item is not normal (step S27, Yes), and in step S25, when there is a first partial region where the first identification item is not normal (step S25, No), the second identification processing unit 13 executes a second determination process (step S29). At this time, the second identification processing unit 13 determines whether the second identification item is normal based on a second threshold value, which is a stricter criterion than the fourth threshold value, in the second partial region corresponding to each first partial region.

[0098] In step S29, when there is no abnormal part regarding the second identification item in all the second partial regions (step S29, Yes), it may be determined that the second identification item is normal (step S30), and then, the operation of the currency identification device 1 may end.

[0099] In step S29, when there is an abnormal part regarding the second identification item in at least one second partial region (step S29, No), it may be determined that the second identification item is not normal (there is an abnormality) (step S31), and then, the operation of the currency identification device 1 may end.

[0100] According to the present embodiment, for each of the first and second identification items, by changing (tightening) the threshold value to perform two-stage determination, the detection performance for abnormalities with minute changes in the feature amounts regarding the first and second identification items can be further improved.

[0101] Note that in the present embodiment, an example of performing two-stage determination using two types of threshold values for each of the first and second identification items has been described, but two-stage determination using two types of threshold values may be performed for only one of the first and second identification items.

[0102] (Embodiment 3) The configuration of the currency processing apparatus according to this embodiment will be described with reference to FIGS. 4 and 5. FIG. 4 is a perspective schematic view showing an example of the appearance of the currency processing apparatus according to Embodiment 3. FIG. 5 is a block diagram for explaining an example of the configuration of the currency processing apparatus according to Embodiment 3.

[0103] The currency processing apparatus according to this embodiment may have, for example, the configuration shown in FIG. 4. The currency processing apparatus 300 shown in FIG. 4 incorporates a currency identification device 200 (see FIG. 5) that performs identification processing of banknotes, a hopper 301 on which a plurality of banknotes to be processed are placed in a stacked state, two reject units 302 from which rejected banknotes are discharged, an operation unit 303 for inputting instructions from an operator, four stacking units 306a to 306d for classifying and stacking banknotes whose denomination, authenticity, and integrity have been identified within the housing 304, and a display unit 305 for displaying information such as the identification and counting results of banknotes and the stacking status of each of the stacking units 306a to 306d.

[0104] Also, as shown in FIG. 5, the currency processing apparatus 300 further includes a transport unit 310, a main body storage unit 330, and a main body control unit 320.

[0105] The transport unit 310 is configured to include a transport roller for transporting banknotes, a drive mechanism (a drive source and a driving force transmission mechanism) for driving the transport roller, and the like.

[0106] The main body storage unit 330 is composed of a storage device such as a semiconductor memory (RAM or ROM) and a hard disk, and stores various programs and information (data) for controlling the currency processing apparatus 300.

[0107] The main control unit 320 is a controller that controls each part of the currency processing apparatus 300, and is configured as a computer system including a CPU and various hardware (e.g., FPGA) controlled by the CPU. The main control unit 320 realizes various processes by executing a predetermined software program stored in the main storage unit 330 (which may be a storage unit provided separately from the main storage unit 330) in its CPU.

[0108] FIG. 6 is a block diagram for explaining an example of the configuration of the currency identification apparatus according to Embodiment 3.

[0109] As shown in FIG. 6, the currency identification apparatus 200 according to the present embodiment includes a detection unit 210, a control unit 220, and a storage unit 230.

[0110] The detection unit 210 detects various physical quantities (physical characteristics) of the banknote being conveyed, and may include a thickness detection sensor 211 and an optical line sensor 212 along the conveyance path of the banknote.

[0111] The thickness detection sensor 211 detects the thickness of the banknote by detecting the displacement amount when the banknote passes through one of the rollers facing each other across the conveyance path of the banknote, and outputs it as thickness data. Further, a plurality of these pairs of rollers are arranged in the width direction of the conveyance path, whereby the banknote can be divided into regions corresponding to each pair of rollers, and the thickness can be detected in each region.

[0112] The optical line sensor 212 is a close contact image sensor including a linear light source capable of irradiating light such as visible light, infrared light, and ultraviolet light, and a one-dimensional image sensor (linear image sensor) of a CCD type or a CMOS type. For example, ultraviolet light is irradiated as excitation light onto the banknote being conveyed along the conveyance path, and the fluorescence emitted from the banknote is received by each detection element (imaging element) of the image sensor and output as image data. The optical line sensor 212 can also irradiate light such as infrared light or visible light onto the banknote being conveyed along the conveyance path, and receive the light reflected or transmitted by the banknote by each detection element of the image sensor and output it as image data.

[0113] The memory unit 230 is composed of a storage device such as a semiconductor memory (RAM or ROM) or a hard disk, and stores various programs and information (data) for controlling the currency identification device 200.

[0114] The control unit 220 is a controller that controls each part of the currency identification device 200, and is configured as a computer system including a CPU and various hardware (for example, FPGA) controlled by the CPU. The control unit 220 realizes various processes by executing a predetermined software program stored in the memory unit 230 in its CPU.

[0115] In addition, the control unit 220 performs an identification process using various data (signals) related to the banknote acquired from the detection unit 210. The control unit 220 identifies the denomination and authenticity of the banknote. Further, the control unit 220 determines the integrity of the banknote. Specifically, for example, the control unit 220 detects stains, folds, tears, etc. of the banknote, and also detects tapes or the like attached to the banknote from the thickness of the banknote, thereby determining whether to process the banknote as a valid note that can be reused in the market or a damaged note that is not suitable for market circulation.

[0116] At this time, the control unit 220 uses the image (image data) of the banknote acquired by the thickness detection sensor 211 and the optical line sensor 212 to identify the denomination, authenticity, integrity, etc. In addition, the control unit 220 performs a thickness abnormality determination process, which will be described later, as a determination process regarding the integrity of the banknote. Further, the control unit 220 performs a fluorescence abnormality determination process, which will be described later, as a determination process regarding the authenticity and integrity of the banknote.

[0117] As shown in FIG. 6, the control unit 220 includes a data acquisition unit 221, a thickness abnormality determination processing unit 222, and a fluorescence abnormality determination processing unit 223.

[0118] The data acquisition unit 221 performs a process of acquiring the thickness image data as the first data and a process of acquiring the fluorescence image data as the second data.

[0119] The thickness abnormality determination processing unit 222 performs (1) pre-determination processing, (2) two-note determination processing, (3) full-tape note determination processing, and (4) partial-tape note determination processing.

[0120] (1) In the pre-determination processing, pre-processing such as edge detection is performed on the thickness image data.

[0121] (2) In the two-note determination processing, based on the pre-processed thickness image data and a predetermined threshold value, it is determined whether the banknote to be identified is a two-note. Note that a two-note indicates a medium in which two sheets of paper are being conveyed while overlapping.

[0122] (3) In the full-tape note determination processing, based on the pre-processed thickness image data and a predetermined threshold value, it is determined whether the banknote to be identified is a full-tape note. Note that a full-tape note indicates a sheet of paper that is not as thick as a two-note and has a relatively thick area in a relatively large area.

[0123] (4) In the partial-tape note determination processing, based on the pre-processed thickness image data and a predetermined threshold value, it is determined whether the banknote to be identified is a partial-tape note. Note that a partial-tape note indicates a sheet of paper that is not as thick as a two-note and has a relatively thick area in a relatively small area compared to a full-tape note.

[0124] As the (4) partial-tape note determination processing, the thickness abnormality determination processing unit 222 executes (4a) partial-tape note determination processing (standard mode) corresponding to the above-described third determination processing and (4b) partial-tape note determination processing (strict mode) corresponding to the above-described first determination processing.

[0125] (4a) The difference between the partial-tape note determination processing (standard mode) and (4b) the partial-tape note determination processing (strict mode) is only that the threshold values used are different. The standard threshold value used in the partial-tape note determination processing (standard mode) corresponds to the above-described third threshold value, and the strict threshold value used in the partial-tape note determination processing (strict mode) corresponds to the above-described first threshold value. The standard threshold value is a looser criterion than the strict threshold value.

[0126] In Embodiments 3 to 5, the threshold is set to 256 levels (the loosest = 0 to the strictest = 255) as a relative threshold, the standard threshold is 128, and the strict threshold is 255. However, the specific value of each threshold can be arbitrarily set. For example, the strict threshold may be 224.

[0127] The fluorescence abnormality determination processing unit 223 performs (1) pre-determination processing, (2) fluorescence abnormality determination processing, and (3) cut-and-pasted note determination processing.

[0128] (1) In the pre-determination processing, pre-processing such as rotation correction is performed on the fluorescence image data.

[0129] (2) In the fluorescence abnormality determination processing, based on the pre-processed fluorescence image data and a predetermined threshold, two-mode determination processing of a washed note determination processing and a counterfeit note determination processing is performed. In the washed note determination processing, it is determined whether the banknote to be identified is a washed note. Note that a washed note refers to a banknote with high fluorescence intensity over the entire main surface of the paper. In the counterfeit note determination processing, it is determined whether the banknote to be identified can emit the fluorescence that it should originally emit. For example, a banknote with low fluorescence intensity in the thread part where fluorescence should be emitted is determined as a counterfeit note.

[0130] (3) In the cut-and-pasted note determination processing, based on the pre-processed fluorescence image data and a predetermined threshold, it is determined whether the banknote to be identified is a cut-and-pasted note. Note that a cut-and-pasted note based on fluorescence data refers to paper with high fluorescence intensity in a linear partial region.

[0131] As the (3) cut-and-pasted note determination processing, the fluorescence abnormality determination processing unit 223 executes (3a) a cut-and-pasted note determination processing (standard mode) corresponding to the fourth determination processing above and (3b) a cut-and-pasted note determination processing (strict mode) corresponding to the second determination processing above.

[0132] (3a) The difference between the sticker coupon determination process (standard mode) and (3b) the sticker coupon determination process (strict mode) is only that the threshold value used and the determination target area are different. The standard threshold value used in the sticker coupon determination process (standard mode) corresponds to the fourth threshold value above, and the strict threshold value used in the sticker coupon determination process (strict mode) corresponds to the second threshold value above. The standard threshold value is a looser criterion than the strict threshold value.

[0133] Next, with reference to FIGS. 7A and 7B, the operation of the currency identification device 200 according to the present embodiment will be described. FIGS. 7A and 7B are flowcharts for explaining an example of the operation of the currency identification device according to Embodiment 3. FIG. 7A shows an example of the operation of the thickness abnormality determination processing unit, and FIG. 7B shows an example of the operation of the fluorescence abnormality determination processing unit.

[0134] As shown in FIG. 7A, first, the data acquisition unit 221 executes a process of acquiring thickness image data as first data (step S41). The thickness image data is based on the output of the thickness detection sensor 211.

[0135] Next, the thickness abnormality determination processing unit 222 performs pre-determination processing on the thickness image data (step S42).

[0136] Next, the thickness abnormality determination processing unit 222 performs a two-sheet coupon determination process (step S43). Specifically, a feature amount (evaluation value) is calculated from the data constituting the entire medium area of the thickness image data after pre-processing, and the calculated feature amount is compared with a predetermined threshold value. If the calculated feature amount exceeds the threshold value (step S43, No), it is determined that the banknote to be identified is a two-sheet coupon (step S44), and the process proceeds to step S45. Even if the calculated feature amount does not exceed the threshold value (step S43, Yes), the process proceeds to step S45.

[0137] In step S45, the thickness abnormality determination processing unit 222 performs an overall tape ticket determination process. Specifically, a feature amount (evaluation value) is calculated from data that constitutes a relatively large area within the medium area of the thickness image data after preprocessing, the calculated feature amount is compared with a predetermined threshold value, and if the calculated feature amount exceeds the threshold value (step S45, No), it is determined that the banknote to be identified is an overall tape ticket (step S46), and the process proceeds to step S47. Even if the calculated feature amount does not exceed the threshold value (step S45, Yes), the process proceeds to step S47.

[0138] The overall tape ticket determination process may perform three-mode determination processes that respectively target (1) a partial area that is long in the main scanning direction (for example, a rectangular area), (2) a partial area that is long in the sub-scanning direction (for example, a rectangular area), and (3) the entire medium area. In the cases of (1) and (2), the above determination process may be performed while shifting the partial area by, for example, one pixel at a time.

[0139] In step S47, the thickness abnormality determination processing unit 222 performs a partial tape ticket determination process (standard mode). Specifically, the medium area of the thickness image data after preprocessing is scanned for each relatively small partial area (for example, a rectangular area), a feature amount (evaluation value) is calculated from the data that constitutes each partial area, and each calculated feature amount is compared with a standard threshold value. Then, if at least one feature amount exceeds the standard threshold value (step S47, No), it is determined that the banknote to be identified is a partial tape ticket (step S48), and thereafter, step S49 described later may not be executed. If all the feature amounts do not exceed the standard threshold value (step S47, Yes), the process proceeds to step S49.

[0140] In step S49, the thickness abnormality determination unit 222 performs the partial tape ticket determination process (severe mode). Specifically, it scans the media area of the thickness image data after preprocessing for relatively small partial areas (for example, rectangular areas) one by one, calculates feature amounts (evaluation values) respectively from the data constituting each partial area, and compares each calculated feature amount with a strict threshold value. Then, when at least one feature amount exceeds the strict threshold value (step S49, No), a flag indicating this is set to on, and when all feature amounts do not exceed the strict threshold value (step S49, Yes), it is determined that the banknote to be identified is a normal-thickness ticket (step S50).

[0141] Also, as shown in FIG. 7B, the data collection unit 221 executes a process of collecting fluorescence image data as the second data (step S51). The fluorescence image data is based on the output of the optical line sensor 212.

[0142] Next, the fluorescence abnormality determination unit 223 performs pre-determination processing on the fluorescence image data (step S52).

[0143] Next, the fluorescence abnormality determination unit 223 performs two-mode fluorescence abnormality determination processes, that is, the washed ticket determination process and the counterfeit banknote determination process respectively (step S53). Specifically, in the washed ticket determination process, a feature amount (evaluation value) is calculated from the data constituting the entire media area of the fluorescence image data after preprocessing, the calculated feature amount is compared with a predetermined threshold value, and when the calculated feature amount exceeds the threshold value (step S53, No), it is determined that the banknote to be identified is a washed ticket (step S54). In the counterfeit banknote determination process, a feature amount (evaluation value) is calculated from the data constituting the thread part of the fluorescence image data after preprocessing, the calculated feature amount is compared with a predetermined threshold value, and when the calculated feature amount exceeds the threshold value (step S53, No), it is determined that the banknote to be identified is a counterfeit banknote (step S54). After step S54, it proceeds to step S55. Also, when the feature amount calculated in the washed ticket determination process does not exceed the threshold value and the feature amount calculated in the counterfeit banknote determination process does not exceed the threshold value (step S53, Yes), it proceeds to step S55.

[0144] In step S55, the fluorescence abnormality determination unit 223 performs the cut-and-pasted ticket determination process (standard mode). Specifically, it scans the medium area of the fluorescence image data after preprocessing for relatively small partial areas (e.g., rectangular areas) one by one, calculates feature amounts (evaluation values) from the data constituting each partial area, and compares each calculated feature amount with a standard threshold value. And when at least one feature amount exceeds the standard threshold value (step S55, No), it is determined that the banknote to be identified is a cut-and-pasted ticket (step S56), and thereafter, step S57 described later does not need to be executed. When all feature amounts do not exceed the standard threshold value (step S55, Yes), it proceeds to step S57.

[0145] The cut-and-pasted ticket determination process may perform a four-mode determination process in both the standard mode and the strict mode, where each of (1) a partial area long in the main scanning direction (e.g., a rectangular area), (2) a partial area long in the sub-scanning direction (e.g., a rectangular area), (3) a partial area long in the first diagonal direction (e.g., +45° direction) with respect to the main scanning direction or the sub-scanning direction (e.g., a rectangular area), and (4) a partial area long in the second diagonal direction (e.g., -45° direction) with respect to the main scanning direction or the sub-scanning direction (e.g., a rectangular area) is the determination target. In the cases of (1) to (4), the above determination process may be performed while shifting the partial area by, for example, one pixel at a time.

[0146] In step S57, the above flag is checked. When the flag is off, that is, when all the feature amounts calculated in the partial tape ticket determination process (strict mode) by the thickness abnormality determination unit 222 do not exceed the strict threshold value (step S57, Yes), it is determined that the banknote to be identified is a fluorescence normal ticket (step S58). When the flag is on, that is, when at least one of the feature amounts calculated in the partial tape ticket determination process (strict mode) by the thickness abnormality determination unit 222 exceeds the strict threshold value (step S57, No), it proceeds to step S59.

[0147] In step S59, the fluorescence abnormality determination unit 223 performs the cut-and-pasted ticket determination process (severe mode). Specifically, among the medium regions of the fluorescence image data after preprocessing, each relatively small partial region (for example, a rectangular region) within the target region is scanned, feature amounts (evaluation values) are respectively calculated from the data constituting each partial region, and each calculated feature amount is compared with a strict threshold value. Here, the "target region" is a region (second partial region) corresponding to a partial region (first partial region) in which the feature amount exceeds the strict threshold value in the partial tape ticket determination process (severe mode) by the thickness abnormality determination unit 222. And when at least one feature amount exceeds the strict threshold value (step S59, No), it is determined that the banknote to be identified is a cut-and-pasted ticket (step S60), and when all feature amounts do not exceed the strict threshold value (step S59, Yes), it is determined that the banknote to be identified is a fluorescence normal ticket (step S61), and then the operation of the currency identification device 200 ends.

[0148] According to the present embodiment, it is possible to effectively detect thick abnormal tickets and fluorescence abnormal tickets with minute feature amount changes while suppressing misdetection of normal media.

[0149] In the present embodiment, basically, cut-and-pasted tickets are detected based only on fluorescence image data. However, for cut-and-pasted tickets with minute changes in fluorescence amount, if the result of strict threshold determination using thickness image data is an NG determination, such cut-and-pasted tickets can be detected as fluorescence abnormalities by performing strict threshold determination also on the fluorescence image data.

[0150] Note that in the present embodiment, an example in which strict threshold determination is first performed using thickness data and then strict threshold determination using fluorescence data is performed according to the result has been described. However, two-stage determination may be performed in the reverse order. That is, strict threshold determination may be first performed using fluorescence data and then strict threshold determination using thickness data may be performed according to the result.

[0151] (Embodiment 4) The configuration of the currency processing device according to the present embodiment will be described with reference to FIG. 8. FIG. 8 is a block diagram for explaining an example of the configuration of the currency identification device according to Embodiment 4.

[0152] As shown in FIG. 8, the currency processing apparatus according to the present embodiment is substantially the same as the currency processing apparatus according to Embodiment 3, except that the control unit 220 of the currency identification device 200 has an infrared cut-and-paste determination processing unit 224 instead of the fluorescence abnormality determination processing unit 223.

[0153] The infrared cut-and-paste determination processing unit 224 performs (1) seam enhancement filter processing, (2) edge detection / rotation correction processing, and (3) cut-and-paste ticket determination processing.

[0154] (1) In the seam enhancement filter processing, processing is performed to enhance black lines (dark lines) or white lines (bright lines) in the infrared transmission image data. Black lines may occur in portions where the overlapping of paper pieces is large in the cut-and-paste ticket or in portions where dust adheres in the bonding portion, and white lines may occur in portions where the overlapping of paper pieces is small in the cut-and-paste ticket.

[0155] (2) In the edge detection / rotation correction processing, edge detection processing is performed on the infrared transmission image data after the seam enhancement filter processing, and the inclination of the image is corrected. By the edge detection processing, the infrared transmission image data is binarized, and edges including black lines and white lines are detected as bright lines (white).

[0156] (3) In the cut-and-paste ticket determination processing, based on the infrared transmission image data after the edge detection / rotation correction processing and a predetermined threshold value, it is determined whether the banknote to be identified is a cut-and-paste ticket.

[0157] Note that, for a cut-and-paste ticket with a large overlap of paper pieces in the bonding portion or a cut-and-paste ticket with dust adhering to the bonding portion, portions with a large overlap or portions with dust adhering can be detected as black lines in the infrared transmission image data. Also, for a cut-and-paste ticket with a small overlap of paper pieces in the bonding portion (which may have a gap), portions with a small overlap (or a gap) can be detected as white lines in the infrared transmission image data.

[0158] The infrared pasting determination processing unit 224 executes, as the (3) pasting ticket determination processing, (3a) a pasting ticket determination processing (standard mode) corresponding to the above-described fourth determination processing and (3b) a pasting ticket determination processing (strict mode) corresponding to the above-described second determination processing.

[0159] (3a) The difference between the pasting ticket determination processing (standard mode) and (3b) the pasting ticket determination processing (strict mode) is only that the threshold value used and the determination target area are different. The standard threshold value used in the pasting ticket determination processing (standard mode) corresponds to the above-described fourth threshold value, and the strict threshold value used in the pasting ticket determination processing (strict mode) corresponds to the above-described second threshold value. The standard threshold value is a looser standard than the strict threshold value.

[0160] Next, with reference to FIGS. 9A and 9B, the operation of the currency discrimination device 200 according to the present embodiment will be described. FIGS. 9A and 9B are flowcharts for explaining an example of the operation of the currency discrimination device according to Embodiment 4. FIG. 9A shows an example of the operation of the thickness abnormality determination processing unit, and FIG. 9B shows an example of the operation of the infrared pasting determination processing unit.

[0161] As shown in FIG. 9A, first, the data collection unit 221 executes a process (step S41) of collecting thickness image data as first data. The thickness image data is based on the output of the thickness detection sensor 211.

[0162] Thereafter, the thickness abnormality determination processing unit 222 executes the processes of steps S42 to S50 in the same manner as in the case of Embodiment 3.

[0163] For example, in step S49, when at least one feature amount calculated by the thickness abnormality determination processing unit 222 exceeds a strict threshold value (step S49, No), a flag indicating that fact is set to on.

[0164] Also, as shown in FIG. 9B, the data collection unit 221 executes a process (step S71) of collecting infrared transmission image data as second data. The infrared transmission image data is based on the output of the optical line sensor 212.

[0165] Next, the infrared splicing determination processing unit 224 performs seam enhancement filter processing on the infrared transmission image data (step S72).

[0166] Next, the infrared splicing determination processing unit 224 performs edge detection / rotation correction processing on the infrared transmission image data after the seam enhancement filter processing (step S73).

[0167] Next, the infrared splicing determination processing unit 224 performs a splicing ticket determination process (standard mode) (step S74). Specifically, a relatively small partial area (for example, a rectangular area) within the medium area of the infrared transmission image data after the edge detection / rotation correction process is scanned for each, and a feature amount (evaluation value) is calculated from the data constituting each partial area, and each calculated feature amount is compared with a standard threshold value. And when at least one feature amount exceeds the standard threshold value (step S74, No), it is determined that the banknote to be identified is a splicing ticket (step S75), and then, step S76 described later does not need to be executed. When all the feature amounts do not exceed the standard threshold value (step S74, Yes), the process proceeds to step S76.

[0168] The splicing ticket determination process may perform a determination process in four modes, each of which targets (1) a partial area (for example, a rectangular area) long in the main scanning direction, (2) a partial area (for example, a rectangular area) long in the sub-scanning direction, (3) a partial area (for example, a rectangular area) long in the first diagonal direction (for example, +45° direction) with respect to the main scanning direction or the sub-scanning direction, and (4) a partial area (for example, a rectangular area) long in the second diagonal direction (for example, -45° direction) with respect to the main scanning direction or the sub-scanning direction, in both the standard mode and the strict mode. In the cases of (1) to (4), the above determination process may be performed while shifting the partial area by, for example, one pixel at a time.

[0169] In step S76, the above flag is checked. If the flag is off, that is, if all the feature amounts calculated in the partial tape ticket determination process (severe mode) by the thickness abnormality determination processing unit 222 do not exceed the severe threshold value (step S76, Yes), it is determined that the banknote to be identified is a normal infrared banknote (step S77). If the flag is on, that is, if at least one of the feature amounts calculated in the partial tape ticket determination process (severe mode) by the thickness abnormality determination processing unit 222 exceeds the severe threshold value (step S76, No), the process proceeds to step S78.

[0170] In step S78, the infrared sticking determination processing unit 224 performs a sticking ticket determination process (severe mode). Specifically, among the medium regions of the infrared transmission image data after the edge detection / rotation correction process, each relatively small partial region (for example, a rectangular region) within the target region is scanned, feature amounts (evaluation values) are respectively calculated from the data constituting each partial region, and each calculated feature amount is compared with a severe threshold value. Here, the "target region" is a region (second partial region) corresponding to a partial region (first partial region) in which the feature amount exceeds the severe threshold value in the partial tape ticket determination process (severe mode) by the thickness abnormality determination processing unit 222. If at least one of the feature amounts exceeds the severe threshold value (step S78, No), it is determined that the banknote to be identified is a sticking ticket (step S79). If all the feature amounts do not exceed the severe threshold value (step S78, Yes), it is determined that the banknote to be identified is a normal infrared banknote (step S80), and then the operation of the currency identification device 200 ends.

[0171] According to the present embodiment, it is possible to effectively detect a thickness abnormality ticket and an infrared abnormality ticket with a minute change in feature amount while suppressing misdetection of a normal medium.

[0172] In the present embodiment, basically, a sticking ticket is detected based only on infrared transmission image data. For a sticking ticket with a minute change in the transmitted light amount, if the result of the severe threshold determination using the thickness image data is an NG determination, such a sticking ticket can be detected as an infrared abnormality by performing a severe threshold determination also on the infrared transmission image data.

[0173] In this embodiment, an example has been described in which strict threshold determination is first performed using thickness data and then strict threshold determination using infrared transmission data is performed according to the result. However, the two-stage determination may be performed in the reverse order. That is, strict threshold determination may be first performed using infrared transmission data and then strict threshold determination using thickness data may be performed according to the result.

[0174] (Embodiment 5) The configuration of the currency processing apparatus according to this embodiment will be described with reference to FIG. 10. FIG. 10 is a block diagram for explaining an example of the configuration of the currency discrimination apparatus according to Embodiment 5.

[0175] As shown in FIG. 10, the currency processing apparatus according to this embodiment is substantially the same as the currency processing apparatus according to Embodiment 3, except that the detection unit 210 of the currency discrimination apparatus 200 has an ultrasonic sensor 213 instead of the optical line sensor 212, and the control unit 220 of the currency discrimination apparatus 200 has an ultrasonic thickness / tear determination processing unit 225 instead of the fluorescence abnormality determination processing unit 223.

[0176] Note that, also in this embodiment, the detection unit 210 may have an optical line sensor 212.

[0177] The ultrasonic sensor 213 includes an ultrasonic transmission element and an ultrasonic reception element that face each other across the paper currency conveyance path, transmits ultrasonic waves from the ultrasonic transmission element to the paper currency conveyed through the conveyance path, and receives the ultrasonic waves transmitted through the paper currency by the ultrasonic reception element and outputs them as ultrasonic transmission data. Further, a plurality of these pairs of elements are arranged in the width direction of the conveyance path, whereby the paper currency can be divided into regions corresponding to each pair of elements, and the ultrasonic waves transmitted through the paper currency in each region can be detected.

[0178] The ultrasonic thickness / tear determination processing unit 225 performs (1) two-sheet note determination processing, (2) full-surface tape note determination processing, (3) partial tape note determination processing, and (4) tear determination processing.

[0179] (1) In the two-bill determination process, based on the ultrasonic transmission image data and a predetermined threshold value, it is determined whether the bill to be identified is a two-bill.

[0180] (2) In the full-tape bill determination process, based on the ultrasonic transmission image data and a predetermined threshold value, it is determined whether the bill to be identified is a full-tape bill.

[0181] (3) In the partial-tape bill determination process, based on the ultrasonic transmission image data and a predetermined threshold value, it is determined whether the bill to be identified is a partial-tape bill.

[0182] The ultrasonic thickness / tear determination processing unit 225 executes, as the (3) partial-tape bill determination process, (3a) a partial-tape bill determination process (standard mode) corresponding to the above-described fourth determination process, and (3b) a partial-tape bill determination process (strict mode) corresponding to the above-described second determination process.

[0183] (3a) The difference between the partial-tape bill determination process (standard mode) and (3b) the partial-tape bill determination process (strict mode) is only that the threshold value used and the determination target area are different. The standard threshold value used in the partial-tape bill determination process (standard mode) corresponds to the above-described fourth threshold value, and the strict threshold value used in the partial-tape bill determination process (strict mode) corresponds to the above-described second threshold value. The standard threshold value is a looser criterion than the strict threshold value.

[0184] (4) In the tear determination process, based on the ultrasonic transmission image data and a predetermined threshold value, it is determined whether the bill to be identified is a torn bill.

[0185] The ultrasonic thickness / tear determination processing unit 225 executes, as the (4) tear determination process, (4a) a tear determination process (standard mode) corresponding to the above-described fourth determination process, and (4b) a tear determination process (strict mode) corresponding to the above-described second determination process.

[0186] (4a) Tear determination process (standard mode) and (4b) tear determination process (severe mode) differ only in the threshold value used and the determination target area. The standard threshold value used in the tear determination process (standard mode) corresponds to the fourth threshold value above, and the strict threshold value used in the tear determination process (severe mode) corresponds to the second threshold value above. The standard threshold value is a looser criterion than the strict threshold value.

[0187] Next, with reference to FIGS. 11A, 11B, and 11C, the operation of the currency discrimination device 200 according to the present embodiment will be described. FIGS. 11A, 11B, and 11C are flowcharts for explaining an example of the operation of the currency discrimination device according to Embodiment 5. FIG. 11A shows an example of the operation of the thickness abnormality determination processing unit, FIG. 11B shows an example of the first half of the operation of the ultrasonic thickness / tear determination processing unit, and FIG. 11C shows an example of the second half of the operation of the ultrasonic thickness / tear determination processing unit.

[0188] As shown in FIG. 11A, first, the data collection unit 221 executes a process of collecting thickness image data as the first data (step S41). The thickness image data is based on the output of the thickness detection sensor 211.

[0189] Thereafter, the thickness abnormality determination processing unit 222 executes the processes of steps S42 to S50 in the same manner as in the case of Embodiment 3.

[0190] For example, in step S49, when at least one feature amount calculated by the thickness abnormality determination processing unit 222 exceeds the strict threshold value (step S49, No), a flag indicating that is set to on.

[0191] Also, as shown in FIG. 11B, the data collection unit 221 executes a process of collecting ultrasonic transmission image data as the second data (step S91). The ultrasonic transmission image data is based on the output of the ultrasonic sensor 213.

[0192] Next, the ultrasonic thickness / tear determination processing unit 225 performs a two-note determination process (step S92). Specifically, a feature amount (evaluation value) is calculated from the data constituting the entire medium region of the ultrasonic transmission image data, the calculated feature amount is compared with a predetermined threshold value, and when the calculated feature amount exceeds the threshold value (step S92, No), it is determined that the banknote to be identified is a two-note (step S93), and the process proceeds to step S94. Even when the calculated feature amount does not exceed the threshold value (step S92, Yes), the process proceeds to step S94.

[0193] Note that in the present embodiment, since the two-note determination process, the full-tape note determination process, and the partial-tape note determination process are executed by both the thickness abnormality determination processing unit 222 and the ultrasonic thickness / tear determination processing unit 225, the final determination may be made by comprehensively combining the determination results of both. For example, when the determination result of at least one of the thickness abnormality determination processing unit 222 and the ultrasonic thickness / tear determination processing unit 225 is abnormal, it may be finally determined that it is abnormal, that is, a two-note, a full-tape note, or a partial-tape note.

[0194] In step S94, the ultrasonic thickness / tear determination processing unit 225 performs a full-tape note determination process. Specifically, a feature amount (evaluation value) is calculated from the data constituting a relatively large region within the medium region of the ultrasonic transmission image data, the calculated feature amount is compared with a predetermined threshold value, and when the calculated feature amount exceeds the threshold value (step S94, No), it is determined that the banknote to be identified is a full-tape note (step S95), and the process proceeds to step S96. Even when the calculated feature amount does not exceed the threshold value (step S94, Yes), the process proceeds to step S96.

[0195] The full-tape note determination process may perform three-mode determination processes for (1) a partial region long in the main scanning direction (for example, a rectangular region), (2) a partial region long in the sub-scanning direction (for example, a rectangular region), and (3) the entire medium region as determination targets. In the cases of (1) and (2), the above determination process may be performed while shifting the partial region by, for example, one pixel at a time.

[0196] In step S96, the ultrasonic thickness / tear determination processing unit 225 performs a partial tape ticket determination process (standard mode). Specifically, it scans the medium area of the ultrasonic transmission image data for relatively small partial areas (for example, rectangular areas) one by one, calculates feature amounts (evaluation values) from the data constituting each partial area respectively, and compares each calculated feature amount with a standard threshold value. Then, when at least one feature amount exceeds the standard threshold value (step S96, No), it is determined that the banknote to be identified is a partial tape ticket (step S97), and thereafter, step S98 described later does not need to be executed. When all feature amounts do not exceed the standard threshold value (step S96, Yes), the process proceeds to step S98.

[0197] In step S98, the ultrasonic thickness / tear determination processing unit 225 performs a tear determination process (standard mode). Specifically, it scans the medium area of the ultrasonic transmission image data for relatively small partial areas (for example, rectangular areas) one by one, calculates feature amounts (evaluation values) from the data constituting each partial area respectively, and compares each calculated feature amount with a standard threshold value. Then, when at least one feature amount exceeds the standard threshold value (step S98, No), it is determined that the banknote to be identified is a torn ticket (or a cut-and-pasted ticket) (step S99), and thereafter, step S100 described later does not need to be executed. When all feature amounts do not exceed the standard threshold value (step S98, Yes), the process proceeds to step S100.

[0198] In step S100, the above flag is checked. When the flag is off, that is, when all feature amounts calculated in the partial tape ticket determination process (strict mode) by the thickness abnormality determination processing unit 222 do not exceed the strict threshold value (step S100, Yes), it is determined that the banknote to be identified is a banknote with normal thickness (step S101). When the flag is on, that is, when at least one feature amount calculated in the partial tape ticket determination process (strict mode) by the thickness abnormality determination processing unit 222 exceeds the strict threshold value (step S100, No), the process proceeds to steps S102 and S105.

[0199] As shown in FIG. 11C, in step S102, the ultrasonic thickness / tear determination processing unit 225 performs a partial tape ticket determination process (severe mode). Specifically, in the medium region of the ultrasonic transmission image data, scanning is performed for each relatively small partial region (for example, a rectangular region) within the target region, and feature amounts (evaluation values) are respectively calculated from the data constituting each partial region, and each calculated feature amount is compared with a strict threshold value. Here, the "target region" is a region (second partial region) corresponding to a partial region (first partial region) in which the feature amount exceeds the strict threshold value in the partial tape ticket determination process (severe mode) by the thickness abnormality determination processing unit 222. And when at least one feature amount exceeds the strict threshold value (step S102, No), it is determined that the banknote to be identified is a partial tape ticket (step S103), and when all feature amounts do not exceed the strict threshold value (step S102, Yes), it is determined that the banknote to be identified is a normal thickness ticket (step S104).

[0200] In step S105, the ultrasonic thickness / tear determination processing unit 225 performs a tear determination process (severe mode). Specifically, in the medium region of the ultrasonic transmission image data, scanning is performed for each relatively small partial region (for example, a rectangular region) within the target region, and feature amounts (evaluation values) are respectively calculated from the data constituting each partial region, and each calculated feature amount is compared with a strict threshold value. Here, the "target region" is a region (second partial region) corresponding to a partial region (first partial region) in which the feature amount exceeds the strict threshold value in the partial tape ticket determination process (severe mode) by the thickness abnormality determination processing unit 222. And when at least one feature amount exceeds the strict threshold value (step S105, No), it is determined that the banknote to be identified is a torn ticket (it may also be a cut-and-pasted ticket) (step S106), and when all feature amounts do not exceed the strict threshold value (step S105, Yes), it is determined that the banknote to be identified is a normal tear ticket (step S107), and then the operation of the currency identification device 200 ends.

[0201] Note that steps S102 and S105 may be processed in parallel or concurrently as shown in FIG. 11C, or may be processed serially in either order.

[0202] According to this embodiment, it is possible to effectively detect a thickness-abnormal ticket and a torn ticket with minute feature amount changes while suppressing misdetection of normal media.

[0203] In this embodiment, basically, torn tickets are detected based only on ultrasonic transmission image data. For pasted tickets with minute changes in the transmission amount, if the result of strict threshold determination using thickness image data is an NG determination, such torn tickets can be detected as ultrasonic abnormalities by performing strict threshold determination also on the ultrasonic transmission image data.

[0204] Note that, in this embodiment, an example has been described in which strict threshold determination is first performed using thickness data and then strict threshold determination using ultrasonic transmission data is performed according to the result. However, two-stage determination may be performed in the reverse order. That is, strict threshold determination may be first performed using ultrasonic transmission data and then strict threshold determination using thickness data may be performed according to the result.

[0205] As described above, the embodiments have been described with reference to the drawings. However, the present disclosure is not limited to the above-described embodiments. Also, the configurations of the respective embodiments may be appropriately combined or changed without departing from the gist of the present disclosure.

Industrial Applicability

[0206] As described above, the present disclosure is a technique useful for detecting abnormal media with minute feature amount changes while suppressing misdetection of normal media.

Explanation of Signs

[0207] 1, 2, 200: Currency identification device 10, 220: Control unit 11, 221: Data collection unit 12: First identification processing unit 13: Second identification processing unit 210: Detection unit 211: Thickness detection sensor 212: Optical line sensor 213: Ultrasonic sensor 222: Thickness Abnormality Judgment Processing Unit 223: Fluorescence Abnormality Judgment Processing Unit 224: Infrared Sticking Judgment Processing Unit 225: Ultrasonic Thickness / Crack Judgment Processing Unit 230: Memory Unit 300: Currency Processing Device 301: Hopper 302: Reject Unit 303: Operation Unit 304: Housing 305: Display Unit 306a~306d: Integration Unit 310: Conveyor Unit 320: Main Body Control Unit 330: Main Body Memory Unit

Claims

1. A currency identification device for identifying currency, a process of collecting first data detecting a first physical quantity of the entire surface of the currency, a process of collecting second data detecting a second physical quantity different from the first physical quantity of the entire surface of the currency, and a control unit that executes a first determination process regarding a first identification item based on the first data, the first determination process determines whether the first identification item is normal based on a first threshold value for each partial area of the currency, when a first partial area where the first identification item is not normal exists as a result of the first determination process, the control unit further executes a second determination process regarding a second identification item based on the second data, the second identification item is the same identification item as the first identification item or an identification item related to the first identification item, the second determination process determines whether the second identification item is normal based on a second threshold value in a second partial area corresponding to the first partial area, A currency identification device characterized by the above.

2. the control unit further executes a third determination process regarding the first identification item based on the first data, the third determination process determines whether the first identification item is normal based on a third threshold value for each partial area of the currency, the third threshold value is a looser standard than the first threshold value, when no partial area where the first identification item is not normal exists as a result of the third determination process, the control unit executes the first determination process, The currency identification device according to claim 1, characterized by the above.

3. the control unit further executes a fourth determination process regarding the second identification item based on the second data, The fourth determination process determines whether the second identification item is normal based on a fourth threshold value for each partial area of the currency, The fourth threshold value is a criterion that is looser than the second threshold value, When, as a result of the fourth determination process, there is no partial area where the second identification item is abnormal, and as a result of the first determination process, there is the first partial area where the first identification item is abnormal, the control unit executes the second determination process The currency identification device according to claim 1, characterized in that.

4. The first data and the second data are a combination of thickness data obtained by detecting the thickness of paper sheets as the first physical quantity or the second physical quantity, and fluorescence data obtained by detecting the fluorescence emitted by the paper sheets as the first physical quantity or the second physical quantity. The currency identification device according to claim 1, characterized in that.

5. The first identification item and the second identification item are a combination of a thickness abnormality determination for determining whether there is an abnormality in the thickness of the paper sheets, and a cut-and-paste ticket determination for determining whether the paper sheets have been cut and pasted, The control unit executes the thickness abnormality determination based on the thickness data and executes the cut-and-paste ticket determination based on the fluorescence data. The currency identification device according to claim 4, characterized in that.

6. The first data and the second data are a combination of thickness data obtained by detecting the thickness of paper sheets as the first physical quantity or the second physical quantity, and infrared transmission data obtained by detecting infrared light transmitted through the paper sheets as the first physical quantity or the second physical quantity. The currency identification device according to claim 1, characterized in that.

7. The first identification item and the second identification item are a combination of a thickness abnormality determination for determining whether there is an abnormality in the thickness of the paper sheets, and a cut-and-paste ticket determination for determining whether the paper sheets have been cut and pasted, The control unit executes the thickness abnormality determination based on the thickness data and executes the sticking label determination based on the infrared transmission data. The currency discrimination device according to claim 6, characterized in that.

8. The first data and the second data are a combination of thickness data obtained by detecting the thickness of paper sheets as the first physical quantity or the second physical quantity, and ultrasonic transmission data obtained by detecting ultrasonic waves transmitted through the paper sheets as the first physical quantity or the second physical quantity. The currency discrimination device according to claim 1, characterized in that.

9. Both the first identification item and the second identification item are thickness abnormality determinations for determining whether or not there is an abnormality in the thickness of paper sheets. The control unit executes a thickness abnormality determination based on the thickness data and a thickness abnormality determination based on the ultrasonic transmission data. The currency discrimination device according to claim 8, characterized in that.

10. The first identification item and the second identification item are a combination of a thickness abnormality determination for determining whether or not there is an abnormality in the thickness of paper sheets and a tear determination for determining whether or not there is a tear in the paper sheets. The control unit executes the thickness abnormality determination based on the thickness data and executes the tear determination based on the ultrasonic transmission data. The currency discrimination device according to claim 8, characterized in that.

11. A currency processing device, characterized by comprising the currency discrimination device according to any one of claims 1 to 10.

12. A currency discrimination method for discriminating currency, comprising: A step of collecting first data obtained by detecting a first physical quantity of the entire surface of the currency; A step of collecting second data obtained by detecting a second physical quantity different from the first physical quantity of the entire surface of the currency; A first determination step of making a determination regarding a first identification item based on the first data, and the first determination step determines whether the first identification item is normal based on a first threshold value for each partial area of the currency, if, as a result of the first determination step, there is a first partial area where the first identification item is not normal, further comprising a second determination step of making a determination regarding a second identification item based on the second data, the second identification item is the same identification item as the first identification item or an identification item related to the first identification item, and the second determination step determines whether the second identification item is normal based on a second threshold value in a second partial area corresponding to the first partial area. A currency identification method characterized by the above.

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