JP3359986B2 - Coin recognition device - Google Patents

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a coin recognizing device used for recognizing the type and authenticity of coins and the like.

[0002]

2. Description of the Related Art Conventionally, devices that accept and handle coins have been widely used. In particular, in financial institutions and the like, automated equipment such as an automatic transaction device (ATM) has been used in order to automate the handling of deposits and deposits and the transfer processing. Widely used. In such an automated device, when a coin is inserted by a customer, the type and authenticity of the coin are recognized.
This process is performed by a coin recognizing device which is a coin discriminating unit in the automated equipment, and the following is known to perform the recognition.

[0003] For example, as described in JP-B-63-67714, a device for recognizing coins based on the outer diameter and material of the coin, and as described in JP-B-3-63780, depending on the thickness of the coin. There are devices that perform recognition. As a device for detecting the outer diameter of a coin, there is, for example, a device described in Japanese Patent Publication No. 2-48951. Further, as a device for detecting the thickness of a coin, Japanese Patent Publication No. 4-12
No. 518.

[0004]

However, in the conventional coin recognition device as described above, when the outer diameters and materials of the coins are similar, for example, the 500-yen coin and the 500-yen coin of foreign coins have the same outer diameter. And the material is almost similar, and the thickness is 10
Since the difference is only about 0 μm, a thickness detection sensor is required to detect this difference, or a complicated determination circuit is required, which causes an increase in cost.

[0005] Further, since the detection characteristics of the material sensor change under the influence of the temperature, an auxiliary circuit for compensating the change is required, which also causes an increase in cost. Therefore, there has been a demand for a coin recognizing device that can accurately recognize coins at low cost.

[0006]

According to the present invention, there is provided a method for determining the hardness of an object to be determined.
By receiving the reflected light from the currency to convert the surface of its coins and reading unit for reading an analog image, the analog image of the coin taken into Dede digital image data, and the center point coordinates of the <br/> coin and an image capture unit that extracts, the de
From the digital image data to the coin surface based on the coordinates of the center point
The provided ring pattern is extracted and a one-dimensional array
And a conversion unit for converting the image data into digital image data.
Each pixel in one-dimensional array of digital image data
To determine the authenticity of the coin by the binarization unit represented by binary data, the binary data obtained in the pre-Symbol conversion unit analyzes and compares the number of the ring pattern and the reference data
Characterized in that a that the determination unit.

[0007]

The reading unit receives reflected light from a coin to be determined.
Light up, read the coin's face as an analog image,
The image capture unit captures the analog image of this coin
Convert to digital image data and the center point of the coin
Extract the target.

[0008] Then, the conversion unit is the digital image data
From the center provided on the coin surface based on the coordinates of the center point.
Extracts ring pattern is converted into digital image data of the one-dimensional array, a digital one dimensional array output from the converter unit
Each pixel in the image data is binarized by the binarization unit . This
The decision unit analyzes the binarized data of
Authenticity of Thus the coin to compare the number with the reference data
Is determined . You .

As described above, according to the present invention, the hard discrimination target is determined.
Extract the ring pattern provided on the surface of the coin
By comparing the ring pattern of
Judges the authenticity of the coin.

[0010] For this reason, the recognition of coins can be performed more accurately and promptly as compared with the conventional case, and the recognition of coins having similar outer diameters and thicknesses can be performed with high accuracy. Will be able to do it.

[0011]

An embodiment of the present invention will be described below with reference to the drawings. First Embodiment FIG. 1 is an explanatory diagram of a configuration of a first embodiment. FIG. 1 (a)
Indicates a state in which the coin 1 being transported is viewed from above,
(B) shows the coin 1 as viewed from the side.

In FIG. 1, reference numeral 2 denotes a transport path, which is provided with a slit-shaped window 3. The coin 1 is transported on the transport path 2 in the direction of arrow A in the figure, for example. Reference numeral 4 denotes a light source, for example, a line light source such as a fluorescent lamp or a line filament lamp. The light from the light source 4 is transmitted through a slit 5
Used through. Reference numeral 6 denotes a half mirror,
The light is radiated from the slit 5 in a direction perpendicular to the surface of the coin 1.

Reference numeral 7 denotes a reading unit, which is constituted by, for example, a line image sensor such as a CCD, and receives regular reflection light from a coin surface through the half mirror 6.
It is set on the vertical axis of the coin plane. Note that the specularly reflected light is reflected light received by the reading sensor when the light source 4 and the reading unit 7 are installed symmetrically with respect to a vertical axis with respect to the surface of the coin 1.

Each of the above components is irradiated with light from the light source 4 through the slit 5, the irradiation direction of the light is in the direction of the vertical axis of the coin surface by the half mirror 6, and the reading unit 7 is positioned on this vertical axis. And is arranged to receive specularly reflected light from the coin surface. In addition, the above-mentioned components such as the window 3 and the reading unit 7 are set to have a length equal to or longer than the diameter of the coin having the largest diameter among the coins to be recognized, and can scan all the coin types to be recognized. There is.

Reference numeral 8 denotes an image capturing unit, and a reading unit 7
1 which is analog image data read by
The data of the reflected light intensity is taken in, and digital image data is created by A / D conversion, and the digital image data is written and stored in the image storage unit 9 composed of, for example, a frame memory. The image capturing unit 8 can also extract the outer diameter of the coin 1 and its center point.

Reference numeral 10 denotes a binarizing unit which sets a threshold value for performing binarization from the digital image data, and
By comparing the threshold value with the image data, binarized image data is output. 11 is a conversion unit,
The feature data is extracted from the image data output from the binarization unit 10, and the feature data is associated with another image space advantageous for rotation or reduction, and the feature data is extracted from the other image space. Is output after being converted into coordinate data.

Numeral 12 denotes a judging unit.
1 is compared with the registered pattern, which is reference data stored in the registered pattern storage unit 13, and the coin 1
Has a function of judging the denomination and authenticity. The registration pattern storage unit 13 is configured by a storage unit including, for example, a ROM, a RAM, or a magnetic disk device. Also, the registration pattern as the reference data is, for example, domestic coins of 500 yen, 100 yen, 50 yen, 10 yen,
When 5 yen and 1 yen are to be accepted, the coins are stored in the registration pattern storage unit 13 as data that has been subjected to space conversion and the like described below in advance for each coin. It should be noted that the type of coin is not limited to the case described above, and can correspond to the coin to be issued.

Next, the operation of the coin recognition device having the above configuration will be described. When the coin 1 is inserted into the coin recognition device, the light source 4 is turned on, and the light passing through the slit 5 is reflected by the half mirror 6 to irradiate the lower surface of the coin 1. Light specularly reflected from the coin surface passes through the half mirror 6 and enters the reading unit 7. Here, the uneven pattern on the surface forming the pattern of the coin 1 is clearly extracted as described below.

FIG. 2 is an explanatory view of the extraction of the concavo-convex pattern, showing the concavo-convex portions on the surface forming the pattern of the coin surface. In FIG. 1B, the light reflected by the half mirror 6 illuminates the lower surface of the coin so that the light is irradiated upward from below. However, in FIG. Is expressed. That is, in FIG. 2, the irradiation light 14 from the half mirror 6 is reflected on the surface of the coin 1 and is reflected as the reflected light 15 from the coin 1.

First, in FIG. 2A, the irradiation light 14 irradiates the flat portion of the coin 1, so that the reflected light 15a goes in the direction opposite to the direction of the irradiation light 14. As a result, the reflected light 15a passes through the half mirror 6 and enters the reading unit 7 as regular reflected light as shown in FIG. On the other hand, in the case shown in FIG. 2B, since the irradiation light 14 irradiates the upwardly raised portion in FIG. 2 of the convex portion on the coin surface, the reflected light 15b is directed in a direction different from the direction of the regular reflected light. Heading. Therefore, the reflected light 15b does not go to the half mirror 6, and does not enter the reading unit 7.

In FIG. 2C, since the irradiation light 14 irradiates a flat portion on the convex portion on the coin surface, the reflected light 15c is positive as in the case of FIG. The reflected light passes through the half mirror 6 and enters the reading unit 7. Further, in the case shown in FIG. 2D, the irradiation light 14 irradiates the lower left portion in FIG.
5d goes in a direction different from the direction of the specularly reflected light. Therefore, the reflected light 15d does not enter the reading section 7 as in the case of FIG. 2B.

Thus, the pattern on the surface of the coin 1 is
In a portion where the state of the coin surface is flat, the light is brightened by the specular reflection light. On the other hand, in a portion which is obliquely inclined, the coin becomes darker and appears darker.
The uneven pattern on the surface can be read. FIG. 3 is an explanatory diagram of image data, and conceptually shows digital image data obtained by the image capturing unit.

In the figure, reference numeral 16 denotes digital image data. A white portion of the image data 16 is a coin image 17, and the above-mentioned concavo-convex pattern for forming a pattern of a coin surface is present in the coin image 17 portion. From the image data 16, the outer diameter and the center point position of the coin 1 are extracted. The Figure has been shown x-axis and y-axis, the end point coordinates of the coin 1 corresponding to the x-axis x _s and x _e is determined, end point coordinates of the coin 1 corresponding to the y-axis y _s and y _e
Is required. Further, the coordinates of the center point (x
_c, y _c) are calculated. These outer diameter data and center point data are output to the determination unit 12 via the image capturing unit 8.

The calculation of the center point coordinates (x _c , y _c ) will be described below with reference to the drawings. FIG. 4 is an explanatory diagram illustrating extraction of the center point array in the x direction, and FIG. 5 is an explanatory diagram illustrating extraction of the center point array in the y direction. The reference numerals are the same as in FIG. In the x direction, as shown in FIG. 4, a line is drawn in the horizontal direction, and the left and right end points x _s (1) and x _e (1) of the image 17 of the coin 1 are detected. Similarly, for the second line, _xs (2) and _xe (2) are obtained, and the left and right end point arrays _xs (n) and _xe (n) of all n lines are obtained. After the left and right end point arrays are extracted in this way, a center point array x _c (n) is extracted from each of the left and right end point arrays. That is, for the first line, x _c (1) =
( _Xs (1) + _xe (1) / 2), and similarly extract the center point array _xc (n) for all n lines.

The center point of the image 17 of the coin 1 in the x direction
x_cCalculate from (n). That is, x _c(n) = (Σx
_c(n)) / n. For the y direction,
As shown in FIG. 5, a line is drawn in the vertical direction, and the coin 1
Top and bottom points y of image 17_s(1) and y_e(1) is detected.
Similarly for the second line, y_s(2) and y_e(2)
, And the upper and lower end point array y of all n lines_s(n) and
Y_eFind (n). In this way, the upper and lower end point arrays are extracted.
After output, the center point array y_c
Calculate from (n).

The coordinates (x _c , y _c ) of the center point of the image 17 of the coin 1 thus obtained are output to the conversion unit 12, and the image written in the image storage unit 9 is output to the binarization unit 10. I do. First, the binarizing unit 10 extracts the image data obtained by the image capturing unit 8 by, for example, reading it out from the image storage unit 9 and extracts the occurrence frequency distribution of the density representing the gray value.

In order to binarize the image of the coin 1, an appropriate threshold value is determined so as not to be affected by output fluctuations due to dirt, rust and the like of each coin 1 and fluctuations of the reading section 7 with time. Good to do. For example, the average value of the density distribution is calculated, and the optimum threshold value is determined based on the calculated average value.
FIG. 6 is an explanatory diagram of the threshold value determination. In the figure, the horizontal axis indicates the density of the target image, and the vertical axis indicates the frequency of occurrence of this density. The figure shows the case where the average value of the density is set as the threshold value 18. However, in addition to this, for example, when the distribution shape of the density occurrence frequency has two peaks, the valley of the peak is set as the threshold value. There is a method to determine. From these, it is preferable to select a method most suitable for the properties of the target coin and determine the threshold value. The binarized data binarized based on the threshold is output to the conversion unit 11.

Next, the operation of the converter 11 will be described. FIG.
FIG. 3 is a block diagram of a conversion unit. Reference numeral 19 denotes a boundary line component extraction unit for extracting a white / black boundary line of the binarized image 17. The boundary line component extraction unit 19 performs the extraction using a template. FIG. 8 is an explanatory diagram of a template for extracting a boundary line component. Here, a template 21 composed of 3 × 3 is exemplified as an example. The template 21 includes a white pixel 22 and a black pixel 2
3 so that the white / black border passes through the center of the template. If the data to be recognized matches any of the templates in the figure,
The boundary component image is obtained by determining that the pixel is a black boundary line and outputting a black pixel corresponding to the black boundary line.

Reference numeral 20 denotes a space conversion unit which converts the binary image xy space output from the boundary line component extraction unit 19 into a uv
It converts to space, and performs rotation and compression. Hereinafter, an example of space conversion will be described with reference to FIGS. 9 and 10. FIG. 9 is an explanatory diagram of an image of a coin in the xy space before conversion. In the figure, reference numeral 21 denotes an image whose radius from the center point coordinates (x _c , y _c ) is slightly larger than the radius of the circle of the image 17 of the coin 1, and P denotes the black of the coin 1 existing in the image 17. Pixel and coordinates P in xy space
(X, y).

FIG. 10 is an explanatory diagram of a coin image in the uv space after the conversion. In the figure, reference numeral 24 denotes an area corresponding to the area of the image 17 in the xy space, and Q denotes a point corresponding to the coordinates P, which is described as Q (u, v). Coordinate P in image 17 of coin 1 in xy space
When a black pixel exists at (x, y), the distance from the center point coordinates (x _c , y _c ) to P (x, y) is r,
The angle formed with the x-axis, that is, the angle in the counterclockwise direction from the horizontal point to the right from the center point is θ, and the radius of the slightly larger image 21 is R, for example, x−
Convert y space to uv space.

U = K · (θ / 2π) Equation (1) v = K · log _R (r) Equation (2) where log _R is a logarithm based on the radius R of the image 21. . The radius R is fixed as a diameter slightly larger than the coin having the largest diameter among the coins to be recognized, and the fixed value is used in the above equation (2) when recognizing all coins. The conversion from the xy space to the uv space was performed. For example, domestic circulation coin 500 yen, 10
In the case where coins of 0 yen, 10 yen, 50 yen, 5 yen, and 1 yen are to be recognized, the radius R is a value which is slightly larger than the diameter of the largest diameter 500 yen coin among the above coins. Fixed to. When the radius R is set in this manner, all the coins to be recognized (for example, 500 yen, 100 yen, 10 yen, 50 yen, 5 yen, 1 yen, including the largest diameter coin (for example, 500 yen))
It becomes possible to recognize the boundary of the image of (circle).

The value of K is a value less than 1. This makes it possible to reduce the resolution by lowering the values of u and v calculated by the above equation, to reduce the amount of image data from the image 17 in the xy space, and to simplify the coin recognition process. Will be able to do it. Note that the value of K is
It is preferable that the size is about 1/2 to about 1/4 of the radius R of the image 21 . When the size is about 1/2 to about 1/4 of the radius R, the point is appropriate as a harmony point between the viewpoint of the amount of image data necessary for coin recognition processing and the viewpoint of simplification of the processing, and This is because the image data amount required for the recognition processing becomes the minimum value. The setting of the harmony point is
That is, the value of K depends on the nature of the coin to be used and how much the minimum value is set and the amount of image data can be reduced, and is ultimately appropriately set by experience. By appropriately setting the value of K in this manner, coin recognition can be performed accurately and promptly in accordance with the target coin.

According to the above conversion, the object is recognized by converting the image data into the uv space having a smaller image data amount than the image data amount in the xy space. Can be achieved. According to the above two equations, the black pixel existing at the coordinates P (x, y) of the image 17 of the coin 1 is a binary image converted into the coordinates Q (u, v ) in the uv space. Are output to the determination unit 12. Hereinafter, the processing of the determination unit 12 will be described.

The judging unit 12 matches the binary image in the uv space output from the converting unit 11 with some reference images stored in advance in the registered pattern storage unit 13 and compares them. The authenticity of the target coin 1 is determined, and it is checked whether the coin 1 is a coin to be accepted. That it is intended to be compared with to determine the authenticity of the uneven pattern of the coin 1 surface by the translation based on the equation (3) in the horizontal direction between u-v empty FIG. Further, at the time of the determination, if the coin 1 is necessary to correct the turned angle is conveyed by rotating, a small amount of data as the images of the u-v space, simple does not require a complicated rotation process The insertion angle is corrected according to the insertion state of the coin 1 by the parallel movement process, and the coin is compared with the registered pattern.

For example, as a coin, 500 yen in Japan, 1
In the case of accepting 00 yen, 50 yen, 10 yen, 5 yen, and 1 yen, it is determined which of these denominations corresponds, and if none of the denominations corresponds to the registered pattern, This is excluded. It should be noted that the correction of the throw angle can be performed by the process of performing parallel movement by the rotation angle, as described above, from the xy space as a uv
By converted into space, the center point coordinates (x _c, y _c) of the x-y space of the image 17 rotation based on the u-v spatial
This is because equivalent to move in parallel in the lateral axis direction by. That is, when the rotation angle and theta ', parallel movement amount k of images in u-v space shown in FIG. 10, is because it is given by the following equation.

K = K · (θ ′ / 2π) Equation (3) Accordingly, the rotation process only needs to be translated in the uv space, so that the speed of the process can be increased. According to the first embodiment, the xy of the binarized image
By converting from the space to the uv space, the image size can be reduced, the amount of processing can be reduced, and the processing time can be shortened. And the processing time can be shortened. In addition, a small amount of data is stored in the registration pattern storage unit.

Therefore, even with coins having similar outer diameters and thicknesses, the unevenness of the coin surface can be reduced by a small amount of data and simple horizontal movement as in the image 23 in the uv space. By comparing the data from the patterns, a highly accurate determination can be made. For example, even if foreign coins with similar outer diameters and thicknesses are inserted while accepting domestic coins, accurate judgment can be made and this can be eliminated. Become.

Further, since the image of the entire area of the coin surface requiring recognition of the coin 1 is read, a certain statistical amount is extracted from the image, and the binarization threshold value is determined. Is not affected by local dirt or rust on the coin surface, and stable recognition can be always performed. Furthermore, from the binarized image, the correction of the angle deviation from the registration pattern according to the coin insertion status is performed by parallel movement, so that the coin can be extracted regardless of the rotation angle of the coin. Regardless of the throwing angle and the transport condition, stable and highly accurate recognition can always be performed, and the correction processing and the processing time can be simplified as compared with the rotational movement.

The present invention is not limited to the apparatus having the above-described configuration, but may have any configuration as long as it can scan and analyze a coin surface. FIG. 11 is an explanatory diagram of another configuration example. In this example, an optical lens 24 is used instead of the slit 5 in FIG. The optical lens 24 is composed of, for example, an aspherical lens, a self-fog lens, or the like, and its focal position is on the coin surface and the light receiving surface of the reading unit 7. Accordingly, when the light from the light source 4 is converged by the optical lens 24, the light from the light source 4 is reflected by the half mirror 6, irradiates the surface of the coin 1, and then enters the reading unit 7, where the light is analyzed in the same manner as described above. -A determination is made.

Second Embodiment FIG. 12 is an explanatory view of the configuration of the second embodiment. FIG. 12A shows a state in which the coin 1 being transported is viewed from above, and FIG. 12B shows a state in which the coin 1 is viewed from the side. In the figure, reference numeral 2 denotes a conveyance path, which is a slit-shaped window 3.
Is provided. The coin 1 is transported on the transport path 2 in the direction of arrow A in the figure, for example.

Reference numeral 4 denotes a light source, which comprises a line light source such as a fluorescent lamp or a line filament lamp. This light source 4
Is used through the slit 5. Reference numeral 6 denotes a half mirror, which is installed so that the direction of light irradiation from the slit 5 is perpendicular to the surface of the coin 1.
Reference numeral 7 denotes a reading unit, which is constituted by, for example, a line image sensor such as a CCD, and is disposed on a vertical axis of the coin surface so as to receive specularly reflected light from the coin surface through the half mirror 6. For example, a grayscale image with 256 gradations can be output. Note that the specularly reflected light is reflected light received by the reading sensor when the light source 4 and the reading unit 7 are installed symmetrically with respect to a vertical axis with respect to the surface of the coin 1.

Each of the above-mentioned components is irradiated with light from the light source 4 through the slit 5, the irradiation direction of the light is in the direction of the vertical axis of the coin surface by the half mirror 6, and the reading unit 7 is positioned on this vertical axis. And is arranged to receive specularly reflected light from the coin surface. In addition, the above-mentioned components such as the window 3 and the reading unit 7 are set to have a length equal to or longer than the diameter of the coin having the largest diameter among the coins to be recognized, and can scan all the coin types to be recognized. There is.

Reference numeral 8 denotes an image capturing unit, and a reading unit 7
1 which is analog image data read by
The data of the reflected light intensity is taken in, and digital image data is created by A / D conversion, and the digital image data is written and stored in the image storage unit 9 composed of, for example, a frame memory. The image capturing unit 8 can also extract the outer diameter of the coin 1 and its center point. The operation of calculating the coordinates of the center point and the like of the image capturing unit 8 is the same as that described in the first embodiment with reference to FIGS. 3 to 5, and a description thereof will be omitted.

Reference numeral 25 denotes a conversion unit which extracts concentrically distributed ring patterns from the coin surface image data output from the reading unit 8 and stored in the image storage unit 9;
It outputs image data of a dimensional array. Reference numeral 26 denotes a binarization unit that sets a threshold value for performing binarization from the image data, and outputs binarized image data by comparing the threshold value with the image data. . The operation of the binarizing unit 26 for determining the threshold value and the extraction of the frequency distribution of the density are the same as those described in the first embodiment with reference to FIG.

Numeral 27 denotes a judging unit which detects the size and number of ring patterns on the coin surface from the binary image data output by the binarizing unit 26, and stores them in the registered pattern storing unit 28. It has a function of determining the denomination and authenticity of the coin 1 by comparing with the registered pattern. The registration pattern storage unit 28 is, for example, a ROM or an R
It is configured by storage means such as an AM or a magnetic disk device. In addition, for example, in the case of a domestic coin of 500 yen, a reference pattern as the reference data is obtained by extracting in advance a ring pattern arranged concentrically around the circumference of the coin surface from an appropriate 500 yen coin. It is to be registered. It should be noted that the type of coin is not limited to the above-described case, and it is possible to cope with a case where such an issued coin has such a ring pattern.

Next, the operation of the coin recognition device having the above configuration will be described. When the coin 1 is inserted into the coin recognition device, the light source 4 is turned on, and the light passing through the slit 5 is reflected by the half mirror 6 to irradiate the lower surface of the coin 1. Light specularly reflected from the coin surface passes through the half mirror 6 and enters the reading unit 7. Here, the concavo-convex pattern on the surface forming the pattern of the surface of the coin 1 is clearly extracted as described with reference to FIG. 2 and the like in the first embodiment, and the center is similar to that in the first embodiment. The point coordinates and the like are calculated, and the extracted image data of the coin 1 is stored in the image storage unit 9.

The conversion unit 25 operates in accordance with the operation of the boundary component extraction unit 19 described in the first embodiment to generate a ring pattern concentrically distributed from the image data of the coin 1 surface stored in the image storage unit 9. Is extracted. The following is a description with reference to the drawings. FIG. 13 is an explanatory diagram illustrating the operation of the conversion unit. In the figure, reference numeral 29 denotes a ring pattern which is concentrically distributed near the forehead in the image 30 of the coin 1 surface.

Reference numeral 31 denotes a center point, which is the coordinates (x _c , y _c ) of the center point of the image 30 of the coin 1 extracted by the image capturing unit 8. Ring patterns 29 are distributed on a concentric circle 32 having a radius r with the center point 31 as the center. That is, the distance r from the center point 31 is set so as to pass through the center of the ring pattern 29, and a point on the concentric circle 32 has an angle θ counterclockwise from the positive axis of the x-axis in the figure. When it is at the rotated position 33, it is obtained by the following equation.

X = x _c + r · cos θ formula (4) y = y _c −r · sin θ formula (5) In consideration of the above-mentioned properties of the ring pattern 29, formula (4)
In (5), the angle θ is from about 0.5 to about 1 from 0 to 360 degrees.
The image data of the ring pattern 29 distributed on the concentric circle 32 of the radius r existing in the image 30 is extracted while being changed every degree. When extracting a ring pattern of a 500 yen coin, there are 101 ring patterns.
The number of detection angles θ is preferably an integral multiple of 101, or 4 times. By setting it to an integral multiple, periodic data of the ring pattern can be obtained.

FIG. 14 is a one-dimensional array of the image data of the ring pattern 29 obtained by the conversion unit 25. The horizontal axis 34 is the rotation angle θ, and the vertical axis 35 is the image level.
Here, reference numeral 18 denotes an optimum threshold, which is obtained in the same manner as in the first embodiment. In the figure, the rotation angle θ is 0
When the angle is changed from degrees to 360 degrees, the image level appears as a waveform 36 corresponding to the change. This waveform 3
6 is extracted by the conversion unit 25 and output to the binarization unit 26.

The binarizing section 26 reads out one-dimensional image data of the waveform 36 and extracts a density occurrence frequency distribution representing the gray scale value. Then, in order to binarize the image 5 of the coin, output fluctuation due to dirt, rust, etc. of each coin,
It is desirable to determine an appropriate threshold value so as not to be affected by a change such as a temporal change of the reading sensor. Therefore, in the second embodiment, the average value of the density distribution is calculated to determine the threshold, and this is determined as the optimum threshold. The determination of the optimum threshold value is the same as that described with reference to FIG. 6 in the first embodiment, so that the description thereof will be omitted, and the density occurrence frequency distribution will be extracted using the optimum threshold value 18 shown in FIG. The density occurrence frequency distribution in consideration of the optimal threshold is, as shown in FIG.
The binary image 37 appears as a pulse wave periodically generated in the angle θ direction on the horizontal axis. The binarizing unit 26 converts this pulse wave into
Output to the determination unit 27.

The determination unit 27 compares the number of ring patterns and the width of each black image between the pulse wave output from the binarization tool 26 and the registered patterns stored in the registered pattern storage unit 28. To determine the authenticity of the target coin. That is,
In the case of a 500 yen coin, the number of ring patterns is 101, and if any other number is detected, it is excluded.

In the second embodiment described above, the ring pattern distributed on the outer periphery of the 500-yen coin is extracted and discriminated. However, the present invention is not limited to the 500-yen coin. For other coins, if there is concentrically distributed image data, the radius r and the number of detection angles θ are determined so that the feature can be extracted, and one-dimensional image data can be extracted in the same manner.

The present invention is not limited to the ring pattern, but may detect a characteristic pattern of each coin and make a determination based on the pattern. According to the second embodiment, an image of the entire surface of a coin requiring recognition of a coin is read, and concentrically distributed images having a constant radius are extracted from the image based on the center point of the coin. As a result, it is possible to extract discrimination data independent of the position and rotation of the coin.

Therefore, even coins having similar outer diameters and thicknesses can be determined with high accuracy. For example, if you are accepting domestic coins,
Even when foreign coins with similar outer diameters and thicknesses are inserted, accurate judgment can be made and this can be eliminated. In addition, since the image of the characteristic portion of the coin surface requiring recognition of the coin 1 is read, a certain statistic is extracted from the image, and the binarization threshold is determined. Is not affected by local dirt or rust on the coin surface, and can always be stably recognized.

The present invention is not limited to the apparatus having the above-described configuration, but may have any configuration as long as it can scan and analyze a coin surface. Further, similarly to the first embodiment, an optical lens 24 may be used instead of the slit 5. Further, the conversion unit described in the first embodiment is provided in the second embodiment, that is, a conversion unit is provided separately from the conversion unit 25 between the binarization unit 26 and the determination unit 27, and the image of the ring pattern is provided. X-y
The space may be converted into the uv space, and the binarized data may be compared with ring pattern data registered in the registration pattern storage unit in advance to make the determination. By doing so, the time required for comparing ring patterns is shortened, and less data needs to be stored in the registered pattern storage unit.

[0057]

As described in detail above, coins are determined by comparing the concavo-convex pattern of the target coin surface with reference data, so that coins having similar outer diameters and thicknesses are determined. However, there is an effect that highly accurate recognition can be performed. In addition, since accurate determination can be made without using a material sensor, a thickness detection sensor, and other complicated circuits, there is an effect that a low-cost and high-precision device can be provided.

[Brief description of the drawings]

FIG. 1 is a diagram illustrating the configuration of a first embodiment.

FIG. 2 is an explanatory diagram of extraction of a concavo-convex pattern

FIG. 3 is an explanatory diagram of image data.

FIG. 4 is an explanatory diagram illustrating extraction of a center point array in the x direction.

FIG. 5 is an explanatory diagram illustrating extraction of a center point array in the y direction.

FIG. 6 is an explanatory diagram of threshold determination.

FIG. 7 is a block diagram of a conversion unit.

FIG. 8 is an explanatory diagram of a template for extracting a boundary line component.

FIG. 9 is an explanatory diagram of an image of a coin in an xy space before conversion.

FIG. 10 is an explanatory diagram of a coin image in a uv space after conversion.

FIG. 11 is an explanatory diagram of another configuration example.

FIG. 12 is a configuration explanatory view of a second embodiment.

FIG. 13 is an explanatory diagram illustrating an operation of a conversion unit.

FIG. 14 is an explanatory diagram of a density occurrence frequency distribution of a ring pattern.

FIG. 15 is an explanatory diagram of a pulse wave of a ring pattern.

[Explanation of symbols]

 REFERENCE SIGNS LIST 1 coin 4 light source 7 reading section 8 image capturing section 9 image storage section 10 binarization section 11 conversion section 12 determination section 13 registration pattern storage section 25 conversion section 26 binarization section 27 determination section 28 registration pattern storage section

──────────────────────────────────────────────────続 き Continued on front page (58) Field surveyed (Int.Cl. ⁷ , DB name) G07D 5/02

Claims (6)

(57) [Claims] 1. A method of receiving reflected light from a coin to be determined.
Te, a reading unit for reading the surface of the coin as an analog image, the converted coin analog image taken in Dede digital image data, and an image capture unit which extracts the center point coordinates of the coin, the digital image data Coin based on the coordinates of the center point from
Ring pattern concentric with the outer periphery provided on the surface
And convert it to a one-dimensional array of digital image data
A converter, and a one-dimensional array of digital image data output by the converter.
Each pixel is analyzed and the binarization unit represented by binary data, the binary data obtained in the pre-Symbol conversion units on the phosphorus
A coin recognizing device comprising: a determination unit that determines the authenticity of the coin by comparing the number of gpatterns with reference data. 2. A method for receiving reflected light from a coin to be determined.
Read the coin surface as an analog image
And an analog image of the coin to obtain a digital image data.
Image to convert to coins and extract the center point coordinates of the coin
A coin based on the coordinates of the center point from the capturing unit and the digital image data.
Ring pattern concentric with the outer periphery provided on the surface
And convert it to a one-dimensional array of digital image data
A converter, and a one-dimensional array of digital image data output by the converter.
Analyzing the binarized data representing each pixel in the binarized data and the binarized data obtained by the conversion unit;
By comparing the width of the pattern with the reference data,
A coin recognizing device, comprising: a determination unit that determines whether the coin is authentic . 3. The coin reading area according to claim 1 or 2, wherein a coin reading area to be read by the reading unit is an object to be determined.
Greater than or equal to the diameter of the coin with the largest diameter
A coin recognition device characterized by being an area . 4. The method according to claim 1, wherein the registration pattern is stored in a registration pattern storage unit in advance according to a plurality of rotation angles of the coin.
A coin recognition device characterized in that registered reference data is registered . 5. An image capturing unit according to claim 1, wherein the image capturing unit extracts outer diameter data of the coin, and the determining unit determines the type of the coin based on the outer diameter data.
Separately, the reference data in the registration pattern storage
Coins that use only the reference data corresponding to the type for comparison
A coin recognizing device for determining the authenticity of a coin. 6. A was claim 1 or in claim 2, binarization unit, a threshold value so as to correspond to the reflected light intensity of the surface of the coin
A coin recognizing device , which determines and binarizes based on the threshold value .