U.S. patent application number 10/639368 was filed with the patent office on 2004-06-10 for coin discrimination method and device.
This patent application is currently assigned to Kabushiki Kaisha Nippon Conlux. Invention is credited to Onodera, Akira, Sugata, Masanori.
Application Number | 20040108183 10/639368 |
Document ID | / |
Family ID | 27343428 |
Filed Date | 2004-06-10 |
United States Patent
Application |
20040108183 |
Kind Code |
A1 |
Sugata, Masanori ; et
al. |
June 10, 2004 |
Coin discrimination method and device
Abstract
A coin discrimination method and device reliably acquires stable
two-dimensional images of the surfaces of coins, and using the
acquired two-dimensional images is able to perform discrimination,
reliably and at high speed, between genuine and counterfeit coins,
and between coin types. In a coin pathway configured so as to block
interfering light, sensors are positioned at an image-capture
position and at a position upstream from the image-capture
position; an image sensor is caused to begin image capture
simultaneously with the detection, by the sensor upstream of the
image-capture position, of a coin, and illumination is emitted for
a short time simultaneously with the detection, by the sensor at
the image-capture position, of the coin, to acquire an image of the
coin. Specific patterns are detected in a binary image obtained by
converting the acquired image to binary level, and coin
discrimination is performed based on the detected patterns.
Inventors: |
Sugata, Masanori; (Hiki-gun,
JP) ; Onodera, Akira; (Kawagoe-shi, JP) |
Correspondence
Address: |
WELSH & KATZ, LTD
120 S RIVERSIDE PLAZA
22ND FLOOR
CHICAGO
IL
60606
US
|
Assignee: |
Kabushiki Kaisha Nippon
Conlux
Tokyo
JP
|
Family ID: |
27343428 |
Appl. No.: |
10/639368 |
Filed: |
August 12, 2003 |
Related U.S. Patent Documents
|
|
|
|
|
|
Application
Number |
Filing Date |
Patent Number |
|
|
10639368 |
Aug 12, 2003 |
|
|
|
09859151 |
May 16, 2001 |
|
|
|
6685000 |
|
|
|
|
Current U.S.
Class: |
194/328 |
Current CPC
Class: |
G07D 5/005 20130101 |
Class at
Publication: |
194/328 |
International
Class: |
G07D 005/00 |
Foreign Application Data
Date |
Code |
Application Number |
May 19, 2000 |
JP |
148224/2000 |
May 19, 2000 |
JP |
148225/2000 |
May 31, 2000 |
JP |
163378/2000 |
Claims
What is claimed is:
1. A coin discrimination method for discriminating coins which roll
along a coin pathway, wherein, when the coin reaches a prescribed
position of the coin pathway, a surface or an edge of the coin is
illuminated with light, a still image of the illuminated surface or
edge is captured, and based on the captured still image,
discrimination of the coin is performed.
2. The coin discrimination method according to claim 1, wherein the
coin pathway is a light-blocking space.
3. The coin discrimination method according to claim 1, wherein the
still image is captured by a two-dimensional image sensor.
4. The coin discrimination method according to claim 3, wherein the
two-dimensional image sensor is a MOS-type image sensor.
5. The coin discrimination method according to claim 3, wherein the
image capture means begins the image capture operation in advance,
before the coin reaches the prescribed position.
6. A coin discrimination method in which image information
corresponding to a pattern on a top side or on a bottom side of a
coin to be discriminated, which rolls along a coin pathway, is
captured, and the coin to be discriminated is discriminated based
on the captured image information; wherein the image information
for the top side or the bottom side of the coin to be discriminated
is separated into areas set in advance, a specific pattern is
extracted from one of the separated areas, and based on the
extracted specific pattern, a judgment is made as to whether the
coin to be discriminated is a prescribed coin or not.
7. The coin discrimination method according to claim 6, wherein the
image information is a binary image, in which a pattern based on
the pattern of the top side or the bottom side of the coin to be
discriminated is drawn in white or in black, and the separation is
performed by drawing separation lines of a prescribed width, in a
color opposite the pattern color, in preset positions of an image
representing the image information.
8. The coin discrimination method according to claim 7, wherein the
separation lines are circles having the same center as the coin to
be discriminated.
9. The coin discrimination method according to claim 7, wherein the
image information corresponds to an image which has been corrected
for rotation such that the coin to be discriminated faces a
prescribed reference direction, and the separation lines are
straight lines.
10. A coin discrimination method in which image information
corresponding to a pattern of a top side or a bottom side of a coin
to be discriminated, rolling along a coin pathway, is captured, and
the coin to be discriminated is discriminated based on the captured
image information; wherein at least two specific patterns are
extracted from the image information of the top side or the bottom
side of the coin to be discriminated, and using a relative
positional relation between the extracted specific patterns as a
characteristic quantity, discrimination of the coin to be
discriminated is performed.
11. The coin discrimination method according to claim 10, wherein
the characteristic quantity includes a distance between centers of
gravity of the respective extracted specific patterns.
12. The coin discrimination method according to claim 10, wherein
the characteristic quantity includes angles formed by line segments
connecting a center of the coin to be discriminated, and centers of
gravity of each of the specific patterns.
13. The coin discrimination method according to claim 10, wherein
the specific patterns are extracted from binary images obtained by
conversion of the image information to binary level.
14. The coin discrimination method according to claim 10, wherein
the image information is separated into a plurality of patterns,
and the specific patterns are extracted based on areas of each of
the separated patterns.
15. The coin discrimination method according to claim 10, wherein
the image information is separated into a plurality of patterns,
and the specific patterns are extracted based on distances between
centers of gravity of each separated pattern and a center of the
coin to be discriminated in the image information.
16. The coin discrimination method according to claim 10, wherein a
distance between centers of gravity of the specific patterns is
normalized based on a radius of the coin to be discriminated in the
image information, and discrimination of the coin to be
discriminated is performed using this normalized distance as the
characteristic quantity.
17. A coin discrimination device for discriminating a coin rolling
along a coin pathway, comprising illumination means, placed at a
prescribed position on the coin pathway, for illuminating with
light for a short time a surface or an edge of the coin rolling
along the coin pathway; image-capture means for capturing an image
of the surface or edge of the coin, illuminated with light from the
illumination means; image-capture start indication means, for
indicating a start of image capture to the image-capture means in
advance, before the coin reaches a image-capture position of the
image-capture means; and, light emission indication means, for
indicating a start of illumination of light to the illumination
means when the coin reaches the image-capture position of the
image-capture means.
18. The coin discrimination device according to claim 17, wherein
the image-capture start indication means comprises a first sensor,
positioned on an upstream side of the illumination means on the
coin pathway, and the light emission indication means comprises a
second sensor, positioned corresponding to the image-capture
means.
19. The coin discrimination device according to claim 17, wherein
the coin pathway constitutes a light-blocking space.
20. The coin discrimination device according to claim 17, wherein
the image-capture means is a two-dimensional image sensor.
21. The coin discrimination device according to claim 20, wherein
the two-dimensional image sensor is a MOS-type image sensor.
22. A coin discrimination device which acquires image information
corresponding to a pattern of a top side or a bottom side of a coin
to be discriminated which rolls along a coin pathway, and
discriminates the coin to be discriminated based on the acquired
image information, comprising: separation means for separating the
image information for the top side or the bottom side of the coin
to be discriminated into areas set in advance; specific pattern
extraction means for extracting specific patterns from among any of
areas separated by the separation means; and, judgment means for
comparing specific patterns extracted by the specific pattern
extraction means with reference values, and for judging whether or
not the coin to be discriminated is a prescribed coin.
23. The coin discrimination device according to claim 22, wherein
the image information is a binary image, in which a pattern based
on the pattern of the top side or the bottom side of the coin for
discrimination is drawn in white or in black, and the separation
means separates the pattern by drawing separation lines of a
prescribed width, in the color opposite the pattern color, in
preset positions in the binary image.
24. The coin discrimination device according to claim 22, wherein
the separation means draws, in the image, circles having the same
center as the coin for discrimination as the separation lines.
25. The coin discrimination device according to claim 22, wherein
the image information corresponds to an image subjected to rotation
correction such that the coin to be discriminated faces a
prescribed reference direction, and the separation means draws on
the image straight lines as separation lines.
26. A coin discrimination device, in which image information
corresponding to a pattern on a top side or a bottom side of a coin
to be discriminated, rolling along a coin pathway, is acquired, and
the coin to be discriminated is discriminated based on the acquired
image information, comprising: specific pattern extraction means
for extracting specific patterns from image information for the top
side or the bottom side of the coin for discrimination;
pattern-to-pattern distance computation means for computing a
distance between at least two specific patterns extracted by the
specific pattern extraction means; and, judgment means for judging
the coin for discrimination based on the distance calculated by the
pattern-to-pattern distance computation means.
27. The coin discrimination device according to claim 26, wherein
the pattern-to-pattern distance computation means computes the
distance between centers of gravity of the respective specific
patterns extracted by the specific pattern extraction means.
28. The coin discrimination device according to claim 26, further
comprising angle computation means for computing angles formed by a
plurality of line segments joining each of centers of gravity of at
least two specific patterns extracted by the specific pattern
extraction means with a center of the coin to be discriminated in
the image information, and wherein the judgment means judges the
coin to be discriminated based on the angles computed by the angle
computation means.
29. The coin discrimination device according to claim 26, wherein
the specific pattern extraction means comprises image conversion
means for converting to binary level the image information for the
top side or the bottom side of the coin to be discriminated, and
the image conversion means extracts the specific patterns from the
binary-level image.
30. The coin discrimination device according to claim 26, wherein
the specific pattern extraction means comprises pattern separation
means for separating the image information into a plurality of
patterns, and area computation means for computing an area of each
pattern separated by the pattern separation means; and patterns,
areas of which as computed by the area computation means are within
a range set in advance, are extracted as the specific patterns.
31. The coin discrimination device according to claim 26, wherein
the specific pattern extraction means comprises pattern separation
means for separating the image information into a plurality of
patterns, and position specification means for specifying positions
of patterns separated by the pattern separation means based on a
distance between center of gravity of the patterns and a center of
the coin to be discriminated in the image information; and
patterns, positions of which as specified by the position
specification means are within a range set in advance, are
extracted as the specific patterns.
32. The coin discrimination device according to claim 26, further
comprising normalization means for normalizing the distance between
the specific patterns based on a radius of the coin to be
discriminated in the image information, and wherein the judgment
means judges the coin to be discriminated based on comparison of
the distance normalized by the normalization means with a reference
value.
Description
BACKGROUND OF THE INVENTION
[0001] 1. Field of the Invention
[0002] This invention concerns a coin discrimination method and
device, and in particular concerns a coin discrimination method and
device to perform discrimination of genuine and counterfeit coins
and of coin types, based on the pattern of the surface and other
parts of the coin.
[0003] 2. Description of the Related Art
[0004] Coin discrimination devices used in automatic vending
machines and similar generally employ a sensor using a magnetic
coil to detect the material, outer diameter, surface pattern and
other parameters of a coin to discriminate among coins. The
detection signals output from this sensor are concentrated in a
basic pattern representing the characteristics of the coin; by
comparing this basic pattern with basic patterns established in
advance, the genuine or counterfeit nature of the coin, and the
coin type, are discriminated.
[0005] However, recently there have appeared altered coins which
are foreign coins, similar in material and shape, and machined such
that the magnetic pattern matches that obtained from genuine coins;
as the machining precision of these altered coins increases, it has
become more difficult to discriminate between genuine and
counterfeit coins by means of a magnetic sensor.
[0006] Consequently there is increasing demand for coin
discrimination devices which use optical sensors or similar to
capture a two-dimensional image of the coin surface, and perform
pattern matching of the captured two-dimensional image with known
coin patterns to perform coin discrimination.
[0007] However, when an image sensor captures the image of the
surface of a coin which moves by rolling at high speed along a coin
pathway, the image of the surface of the coin is blurred, and there
have been such problems as an inability to obtain a clear
two-dimensional image sufficient for coin discrimination, and
difficulties in clearly capturing, over the entire face of the
coin, a pattern formed only from slight protrusions and depressions
on the coin surface.
[0008] Further, the captured two-dimensional image of the coin
surface is a rotated image due to the rotation of the coin; when
performing pattern matching, the rotation angle of the acquired
two-dimensional image must be detected and corrected, and so there
is the problem that processing time is lengthened.
[0009] As technology to resolve such problems, the "coin
discrimination device" described in Japanese Patent Application
Laid-open No. 8-180235, and the "currency discrimination device"
described in Japanese Patent Application Laid-open No. 6-27473 6,
and similar have been proposed.
[0010] An object of the present invention is to provide a coin
discrimination method and device which enable the stable and
reliable capture of the image of a coin surface, and which are
capable of competent discrimination processing of the coin using a
two-dimensional image of the coin surface.
[0011] In order to achieve the above object, the invention of claim
1 is a coin discrimination method for discriminating coins which
roll along a coin pathway, wherein, when the coin reaches a
prescribed position of the coin pathway, a surface or an edge of
the coin is illuminated with light, a still image of the
illuminated surface or edge is captured, and based on the captured
still image, discrimination of the coin is performed.
[0012] The invention of claim 2 is the invention of claim 1,
wherein the coin pathway is a light-blocking space.
[0013] The invention of claim 3 is the invention of claim 1,
wherein the still image is captured by a two-dimensional image
sensor.
[0014] The invention of claim 4 is the invention of claim 3,
wherein the two-dimensional image sensor is a MOS-type image
sensor.
[0015] The invention of claim 5 is the invention of claim 3,
wherein the image capture means begins the image capture operation
in advance, before the coin reaches the prescribed position.
[0016] The invention of claim 6 is a coin discrimination method in
which image information corresponding to a pattern on a top side or
on a bottom side of a coin to be discriminated, which rolls along a
coin pathway, is captured, and the coin to be discriminated is
discriminated based on the captured image information; wherein the
image information for the top side or the bottom side of the coin
to be discriminated is separated into areas set in advance, a
specific pattern is extracted from one of the separated areas, and
based on the extracted specific pattern, a judgment is made as to
whether the coin to be discriminated is a prescribed coin or
not.
[0017] The invention of claim 7 is the invention of claim 6,
wherein the image information is a binary image, in which a pattern
based on the pattern of the top side or the bottom side of the coin
to be discriminated is drawn in white or in black, and the
separation is performed by drawing separation lines of a prescribed
width, in a color opposite the pattern color, in preset positions
of an image representing the image information.
[0018] The invention of claim 8 is the invention of claim 7,
wherein the separation lines are circles having the same center as
the coin to be discriminated.
[0019] The invention of claim 9 is the invention of claim 7,
wherein the image information corresponds to an image which has
been corrected for rotation such that the coin to be discriminated
faces a prescribed reference direction, and the separation lines
are straight lines.
[0020] The invention of claim 10 is a coin discrimination method in
which image information corresponding to a pattern of a top side or
a bottom side of a coin to be discriminated, rolling along a coin
pathway, is captured, and the coin to be discriminated is
discriminated based on the captured image information; wherein at
least two specific patterns are extracted from the image
information of the top side or the bottom side of the coin to be
discriminated, and using a relative positional relation between the
extracted specific patterns as a characteristic quantity,
discrimination of the coin to be discriminated is performed.
[0021] The invention of claim 11 is the invention of claim 10,
wherein the characteristic quantity includes a distance between
centers of gravity of the respective extracted specific
patterns.
[0022] The invention of claim 12 is the invention of claim 10,
wherein the characteristic quantity includes angles formed by line
segments connecting a center of the coin to be discriminated, and
centers of gravity of each of the specific patterns.
[0023] The invention of claim 13 is the invention of claim 10,
wherein the specific patterns are extracted from binary images
obtained by conversion of the image information to binary
level.
[0024] The invention of claim 14 is the invention of claim 10,
wherein the image information is separated into a plurality of
patterns, and the specific patterns are extracted based on areas of
each of the separated patterns.
[0025] The invention of claim 15 is the invention of claim 10,
wherein the image information is separated into a plurality of
patterns, and the specific patterns are extracted based on
distances between centers of gravity of each separated pattern and
a center of the coin to be discriminated in the image
information.
[0026] The invention of claim 16 is the invention of claim 10,
wherein a distance between centers of gravity of the specific
patterns is normalized based on a radius of the coin to be
discriminated in the image information, and discrimination of the
coin to be discriminated is performed using this normalized
distance as the characteristic quantity.
[0027] The invention of claim 17 is a coin discrimination device
for discriminating a coin rolling along a coin pathway, comprising
illumination means, placed at a prescribed position on the coin
pathway, for illuminating with light for a short time a surface or
an edge of the coin rolling along the coin pathway; image-capture
means for capturing an image of the surface or edge of the coin,
illuminated with light from the illumination means; image-capture
start indication means, for indicating a start of image capture to
the image-capture means in advance, before the coin reaches a
image-capture position of the image-capture means; and, light
emission indication means, for indicating a start of illumination
of light to the illumination means when the coin reaches the
image-capture position of the image-capture means.
[0028] The invention of claim 18 is the invention of claim 17,
wherein the image-capture start indication means comprises a first
sensor, positioned on an upstream side of the illumination means on
the coin pathway, and the light emission indication means comprises
a second sensor, positioned corresponding to the image-capture
means.
[0029] The invention of claim 19 is the invention of claim 17,
wherein the coin pathway constitutes a light-blocking space.
[0030] The invention of claim 20 is the invention of claim 17,
wherein the image-capture means is a two-dimensional image
sensor.
[0031] The invention of claim 21 is the invention of claim 20,
wherein the two-dimensional image sensor is a MOS-type image
sensor.
[0032] The invention of claim 22 is a coin discrimination device
which acquires image information corresponding to a pattern of a
top side or a bottom side of a coin to be discriminated which rolls
along a coin pathway, and discriminates the coin to be
discriminated based on the acquired image information, comprising:
separation means for separating the image information for the top
side or the bottom side of the coin to be discriminated into areas
set in advance; specific pattern extraction means for extracting
specific patterns from among any of areas separated by the
separation means; and judgment means for comparing specific
patterns extracted by the specific pattern extraction means with
reference values, and for judging whether or not the coin to be
discriminated is a prescribed coin.
[0033] The invention of claim 23 is the invention of claim 22,
wherein the image information is a binary image, in which a pattern
based on the pattern of the top side or the bottom side of the coin
for discrimination is drawn in white or in black, and the
separation means separates the pattern by drawing separation lines
of a prescribed width, in the color opposite the pattern color, in
preset positions in the binary image.
[0034] The invention of claim 24 is the invention of claim 22,
wherein the separation means draws, in the image, circles having
the same center as the coin for discrimination as the separation
lines.
[0035] The invention of claim 25 is the invention of claim 22,
wherein the image information corresponds to an image subjected to
rotation correction such that the coin to be discriminated faces a
prescribed reference direction, and the separation means draws on
the image straight lines as separation lines.
[0036] The invention of claim 26 is a coin discrimination device,
in which image information corresponding to a pattern on a top side
or a bottom side of a coin to be discriminated, rolling along a
coin pathway, is acquired, and the coin to be discriminated is
discriminated based on the acquired image information, comprising:
specific pattern extraction means for extracting specific patterns
from image information for the top side or the bottom side of the
coin for discrimination; pattern-to-pattern distance computation
means for computing a distance between at least two specific
patterns extracted by the specific pattern extraction means; and
judgment means for judging the coin for discrimination based on the
distance calculated by the pattern-to-pattern distance computation
means.
[0037] The invention of claim 27 is the invention of claim 26,
wherein the pattern-to-pattern distance computation means computes
the distance between centers of gravity of the respective specific
patterns extracted by the specific pattern extraction means.
[0038] The invention of claim 28 is the invention of claim 26,
further comprising angle computation means for computing angles
formed by a plurality of line segments joining each of centers of
gravity of at least two specific patterns extracted by the specific
pattern extraction means with a center of the coin to be
discriminated in the image information, and wherein the judgment
means judges the coin to be discriminated based on the angles
computed by the angle computation means.
[0039] The invention of claim 29 is the invention of claim 26,
wherein the specific pattern extraction means comprises image
conversion means for converting to binary level the image
information for the top side or the bottom side of the coin to be
discriminated, and the image conversion means extracts the specific
patterns from the binary-level image.
[0040] The invention of claim 30 is the invention of claim 26,
wherein the specific pattern extraction means comprises pattern
separation means for separating the image information into a
plurality of patterns, and area computation means for computing an
area of each pattern separated by the pattern separation means; and
patterns, areas of which as computed by the area computation means
are within a range set in advance, are extracted as the specific
patterns.
[0041] The invention of claim 31 is the invention of claim 26,
wherein the specific pattern extraction means comprises pattern
separation means for separating the image information into a
plurality of patterns, and position specification means for
specifying positions of patterns separated by the pattern
separation means based on a distance between center of gravity of
the patterns and a center of the coin to be discriminated in the
image information; and patterns, positions of which as specified by
the position specification means are within a range set in advance,
are extracted as the specific patterns.
[0042] The invention of claim 32 is the invention of claim 26,
further comprising normalization means for normalizing the distance
between the specific patterns based on a radius of the coin to be
discriminated in the image information, and wherein the judgment
means judges the coin to be discriminated based on comparison of
the distance normalized by the normalization means with a reference
value.
[0043] By means of this invention, the coin pathway is configured
such that light is blocked and there is illumination by light for a
short time when the coin reaches the image-capture position, and in
addition, the image sensor is caused to begin image capture in
advance before the coin reaches the image-capture position. Hence
the image of the surface of the coin rolling at high speed can be
captured in a manner close to the stationary state, and an image
free of omissions can be captured.
[0044] Separation lines set in advance are drawn on a binary image
acquired from the top side or from the bottom side of the coin,
arranged so as to separate the pattern; hence linking of patterns
by various factors can be prevented, without changing the
conditions for binary-level conversion.
[0045] Further, the device is configured such that a plurality of
prescribed patterns are detected from the image of the top side or
of the bottom side of the coin, and the coin is discriminated based
on the distance between the centers of gravity of each of the
detected patterns, so that discrimination of the coin can be
performed without correcting for the rotation angle of the image of
the rolling coin.
BRIEF DESCRIPTION OF THE DRAWINGS
[0046] FIG. 1 is a block diagram showing the schematic
configuration of a coin discrimination device to which this
invention is applied;
[0047] FIG. 2 is a figure showing the configuration of the image
input unit 2;
[0048] FIG. 3 is a figure showing the schematic configuration of a
MOS-type image sensor;
[0049] FIG. 4 is a figure showing the detailed circuitry of a unit
pixel comprised by the pixel array 24 in FIG. 3;
[0050] FIG. 5 is a figure showing one example of the installation
position of the illumination 22;
[0051] FIG. 6 is a figure showing the operation timing of each
constituent component of the image input unit 2;
[0052] FIG. 7 is a block diagram showing the configuration of the
image processing unit 3 and discrimination unit 4;
[0053] FIG. 8 is a figure showing the bottom side of a 500 yen
coin;
[0054] FIG. 9 is a figure showing an example of an image converted
to binary level with a comparatively low threshold;
[0055] FIG. 10 is a figure showing an example of an image converted
to binary level with a comparatively high threshold;
[0056] FIG. 11 is a flow chart showing the flow of pattern
separation processing and discrimination processing;
[0057] FIG. 12 is a figure showing an example of the drawing of
separation lines;
[0058] FIG. 13 is a figure showing the results of drawing of
separation lines;
[0059] FIG. 14 is a figure showing an example of the drawing of
separation lines on the surface image of a 500 yen coin;
[0060] FIG. 15 is a figure (1) used to explain discrimination for
the case in which a leaf-shape pattern and a character pattern are
taken as specific patterns;
[0061] FIG. 16 is a figure (2) used to explain discrimination for
the case in which a leaf-shape pattern and a character pattern are
taken as specific patterns;
[0062] FIG. 17 is a figure showing an example of the drawing of
straight-line separation lines;
[0063] FIG. 18 is a block diagram showing a configuration of the
discrimination unit 4, separate from that of FIG. 7;
[0064] FIG. 19 is a figure showing a binary image of the bottom
side of a 500 yen coin;
[0065] FIG. 20 is a figure showing a quadrilateral shape formed by
connecting patterns on the bottom side of a 500 yen coin;
[0066] FIG. 21 is a figure showing a binary image of the top side
of a 500 yen coin;
[0067] FIG. 22 is a figure showing a quadrilateral shape formed by
connecting patterns on the top side of a 500 yen coin;
[0068] FIG. 23 is a figure (1) used to explain the relation between
patterns in cases in which an image is enlarged or reduced;
[0069] FIG. 24 is a figure (2) used to explain the relation between
patterns in cases in which an image is enlarged or reduced;
[0070] FIG. 25 is a flow chart (1) showing the flow of processing
of each unit.
[0071] FIG. 26 is a flow chart (2) showing the flow of processing
of each unit.
[0072] FIG. 27 is an image example (1) used to explain the
processing of each part.
[0073] FIG. 28 is an image example (2) used to explain the
processing of each part.
[0074] FIG. 29 is an image example (3) used to explain the
processing of each part.
[0075] FIG. 30 is an image example (4) used to explain the
processing of each part.
[0076] FIG. 31 is an image example (5) used to explain the
processing of each part.
[0077] FIG. 32 is an image example (6) used to explain the
processing of each part.
[0078] FIG. 33 is an image example (7) used to explain the
processing of each part.
[0079] FIG. 34 is a figure showing an example of a characteristic
quantity in cases in which a partial image of the coin is used to
judge the genuine or counterfeit nature.
DESCRIPTION OF THE PREFERRED EMBODIMENTS
[0080] Below, one aspect of the coin discrimination method and
device of this invention is explained in detail, referring to the
attached drawings.
[0081] FIG. 1 is a block diagram showing the schematic
configuration of a coin discrimination device to which this
invention is applied.
[0082] As shown in the figure, the coin discrimination device 1
comprises an image input unit 2, image processing unit 3, and
discrimination unit 4. The image input unit 2 captures an image of
the coin rolling in the coin pathway, and acquires a stationary
image of the coin surface or similar. The image processing unit 3
executes image processing, including conversion to binary level of
the still image acquired by the image input unit 2. The
discrimination unit 4 discriminates between genuine and counterfeit
coins and between coin types for the coin the image of which is
captured, based on the still image resulting from image processing
by the image processing unit 3.
[0083] Next, the image input unit 2 is explained in detail,
referring to FIG. 2. FIG. 2 is a figure showing the configuration
of the image input unit 2.
[0084] As this figure indicates, the image input unit 2 comprises a
coin detection sensor 20 and coin detection sensor 21, illumination
22, and image sensor 23. These components are positioned at the
coin pathway 5. The coin pathway 5 is constructed using
light-blocking material such that interfering light is blocked.
[0085] The coin detection sensor 20 detects a coin rolling along
the coin pathway 5 as it passes a prescribed position upstream of
the image-capture position; the coin detection sensor 21 detects
the arrival of this coin at the image-capture position. As these
coin detection sensors 20, 21, magnetic excitation sensors can for
example be employed.
[0086] The illumination 22 illuminates the surface of the coin with
light uniformly from all directions for a short time when the coin
detection sensor 21 detects the coin.
[0087] As the image sensor 23, a MOS-type image sensor or other
two-dimensional image sensor is used; the image sensor starts image
capture when the coin detection sensor 20 detects a coin. The image
captured by the image sensor 23 is output to the later-stage image
processing unit 3.
[0088] Here, the operation of a two-dimensional image sensor
adopted as the image sensor 23 is briefly explained.
[0089] FIG. 3 is a figure showing the schematic configuration of a
MOS-type image sensor; FIG. 4 is a figure showing the detailed
circuitry of a unit pixel comprised by the pixel array 24 in FIG.
3.
[0090] In FIG. 3, the MOS-type image sensor performs operations to
prepare for image capture of the individual pixels comprised by the
pixel array 24 by selecting the pixel 24x (one of the pixels
comprised by the pixel array 24) by means of the orthogonal
X-address line 27 and Y-address line 28 (cf. FIG. 4), controlled by
the horizontal scan circuit 25 and vertical scan circuit 26, which
are one type of shift register.
[0091] Hence operations to prepare for image capture for each pixel
are not begun simultaneously for all pixels, but are begun for each
pixel selected in succession by the X-address 27 and Y-address 28;
in FIG. 3, operations to prepare for image capture are begun in
succession from the first pixel 24s.
[0092] For this reason, the time from the start of preparatory
operations for image capture for the first pixel 24s to the
completion of preparatory operations for image capture for the last
pixel 24e (the image capture preparation time) is determined by the
operation clock (accumulation clock) of the horizontal scan circuit
25 and vertical scan circuit 26 and by the total number of pixels
in the pixel array 24.
[0093] The image input unit 2 emits light for a short time only
when the coin, rolling at high speed, reaches the image-capture
position in the coin pathway 5, which is configured such that
incident interfering light is blocked; during the interval of
illumination, an image of the coin surface is captured, enabling
the acquisition of an image of the coin surface close to the
stationary state.
[0094] However, due to the characteristics of operation of the
above-described image sensor 23, if image capture is begun when the
coin reaches the image-capture position and is illuminated with
light, the image capture will be too late. That is, the
illumination with light takes place before image-capture
preparations are completed for all the pixels of the image sensor
23, and so the part of the image data corresponding to pixels for
which image-capture preparations are not complete is lacking.
[0095] Consequently, image-capture operations for the image sensor
23 are begun in advance, before the coin for discrimination reaches
the image-capture position, based on the output signal of a coin
detection sensor 20 provided upstream of the image-capture
position.
[0096] Because the coin pathway 5 is in a darkened state, with
interfering light blocked, no image can be incident on the image
sensor 23 while the illumination 22 is extinguished.
[0097] The coin detection sensor 20 is positioned on the coin
pathway 5 such that, when a coin rolls along the coin pathway at
the maximum anticipated velocity, the time from detection of the
coin by the coin detection sensor 20 to the arrival of the coin at
the image-capture position is longer than the time for
image-capture preparation by the image sensor 23. That is, it is
prepared such that image-capture preparations are completed for the
last pixel of the image sensor 23 before the coin reaches the
image-capture position in what is anticipated to be the shortest
time required from detection by the coin detection sensor 20 to
arrival at the image-capture position.
[0098] The accumulation time for each pixel after the completion of
image-capture preparations for the last pixel 24e of the image
sensor 23 is set by subtracting the time for image-capture
preparations from the time between detection of the coin by the
coin detection sensor 20 and arrival at the image-capture position,
when the coin rolls in the coin pathway 5 at the lowest anticipated
velocity, with the emission time of the-illumination 22 added. That
is, the accumulation time for each pixel is set such that the image
of a coin which takes the maximum amount of time, from detection by
the coin detection sensor 20, to arrive at the image-capture
position, can be reliably stored.
[0099] The illumination 22 is positioned such that a coin for image
capture arriving at the image-capture position is illuminated with
light uniformly from all directions, so that shadows do not occur
on the surface of the coin for image capture at the time of image
capture. For example, as shown in FIG. 5, a plurality of emission
elements 29 may be installed in a ring shape, surrounding the image
sensor 23, as seen from the image-capture surface, and the
illumination 22 and image sensor 23 integrated as an image-capture
device.
[0100] The illumination 22 emits light in response to a detection
signal from the coin detection sensor 21, and is extinguished in a
sufficiently short length of time.
[0101] Next, the operation timing for each constituent component of
the image input unit 2 is explained. FIG. 6 is a figure showing the
operation timing of each constituent component of the image input
unit 2.
[0102] When the coin detection sensor 20 detects a coin passing
through the coin pathway 5, image-capture preparations for the
first pixel of the image sensor 23 are begun, in sync with this
detection signal.
[0103] When the coin detection sensor 21 detects a coin which has
arrived at the image-capture position, the illumination 22 emits
light for a short length of time, in sync with this detection
signal, and in this state, the image of the coin for image capture
is stored in the pixels of the image sensor 23.
[0104] By sequentially reading, one horizontal line of the pixel
array 24 at a time, this image of the coin for capture stored in
the pixels of the image sensor 23, two-dimensional image data of
the coin surface can be obtained.
[0105] Until now, the case of image capture of the surface of the
coin has been explained; but by changing the positions of the image
sensor 23 and illumination 22, an image of the edge of the coin can
also be captured.
[0106] By means of the configuration described above, image-capture
preparations for the image sensor 23 are always completed before
arrival of the coin at the image-capture position, regardless of
the coin type or of the inclination angle of the coin pathway 5;
hence a two-dimensional image of the coin surface can be obtained
reliably, without omissions of image data.
[0107] By maintaining the coin pathway 5 in a darkened state with
interfering light blocked, and by illuminating with light for a
short time when the coin arrives at the image-capture position, an
image of the coin surface can be obtained as a stationary
image.
[0108] Next, details of the image processing unit 3 and
discrimination unit 4 are explained. FIG. 7 is a block diagram
showing the configuration of the image processing unit 3 and
discrimination unit 4.
[0109] As shown in this figure, the image processing unit 3
comprises an A/D conversion unit 30, image memory unit 31, and
binary conversion unit 32; the discrimination unit 4 comprises a
pattern division unit 40, characteristic extraction unit 41, and
judgment unit 42.
[0110] The A/D conversion unit 30 converts the analog image signals
output by the image input unit 2 into digital multilevel image
signals. The image memory unit 31 temporarily stores the digitally
converted image signals and transfers these signals to the binary
conversion unit 32; the binary conversion unit 32 converts the
multilevel image signals into binary-level image signals. In the
binary conversion unit 32, processing is performed as necessary to
enhance outlines, in order to prevent the separation of patterns
which should be a single group.
[0111] By performing the processing described below, the pattern
separation unit 40 separates patterns which are connected but
should be separated. The characteristic extraction unit 41 performs
labeling processing and extracts patterns, determines the area,
center of gravity and other characteristic quantities for each
pattern, and stores the characteristic quantities thus determined.
The judgment unit 42 compares the characteristic quantities
extracted by the characteristic extraction unit 41 with reference
values, and discriminates between genuine and counterfeit coins and
between coin types.
[0112] Here, pattern connection due to binary level conversion of
images is explained.
[0113] When for example using the leaf-shape patterns 101, 102,
103, 104 on the bottom side of the 500 yen coin shown in FIG. 8 to
perform discrimination, when the image is converted to binary level
using a certain threshold, the leaf-shape patterns 101, 102, 103
are connected with the pattern of the coin perimeter, as shown in
FIG. 9. In order to avoid this, on performing binary level
conversion of the image using a higher threshold, the leaf-shape
pattern 104 and surrounding pattern are lost, as shown in FIG.
10.
[0114] When a pattern is completely lost as in FIG. 10, it is
conceivable that discrimination may become impossible; but when
patterns are connected as in FIG. 9, by separating these patterns,
discrimination becomes possible. For this reason, the pattern
separation unit 40 performs processing to separate connected
patterns.
[0115] Here the pattern separation processing in the pattern
separation unit 40 is explained.
[0116] FIG. 11 is a flow chart showing the flow of pattern
separation processing and discrimination processing.
[0117] The pattern separation unit 40 first specifies the position
of the coin image in the binary image (step 202). Prior to
specifying the position, there are cases in which rotation
correction of the binary image is performed; here however it is
assumed that no rotation correction is performed (an explanation of
cases in which rotation correction is performed is given
below).
[0118] Next, the pattern separation unit 40 draws the separation
line 111 and separation line 112, as shown in FIG. 12 (step 203).
The separation lines 111 and 112 are each circles which are
concentric with the coin image, and of width one pixel. The
separation lines 111 and 112 are drawn in the background color (the
color opposite the pattern color). For example, in the case of the
separation lines 111 and 1 12 drawn on the binary image shown in
FIG. 9, the lines are drawn in black (because the pattern is
white), as in FIG. 13; as a result, the leaf-shape patterns can be
separated from the perimeter. In the case shown in FIG. 13, the
separation line 112 is not necessary; but depending on the binary
image, a leaf-shape pattern and the character pattern "500" may be
connected, and in such cases, drawing of the separation line 112 is
useful.
[0119] When the pattern separation unit 40 draws the separation
lines 111 and 112, the characteristic extraction unit 41 performs
labeling processing and extracts patterns (step 204), and from
these patterns, leaf-shape patterns which are specific patterns are
extracted (step 205). Then, the judgment unit 42 compares the
positional relation of the leaf-shape patterns with reference
values and performs other processing, and judges whether or not the
coin image is of the bottom side of a 500 yen coin (step 206).
[0120] When, as shown in FIG. 14, the separation lines 111, 112 are
drawn on an image of the top side of a 500 yen coin, the character
patterns for each of the characters inscribed in the coin can be
separated, so that when using these character patterns as specific
patterns for the top side of a 500 yen coin, the same separation
lines 111, 112 can be used for both the top side and the bottom
side to perform pattern separation processing.
[0121] Here, discrimination is explained for the case in which a
leaf-shape pattern and character pattern are used as specific
patterns.
[0122] First, in a circular image of a coin or other object, if the
distance between point A and point B shown in FIG. 15 is 1, and the
angle formed by the line segments connecting these points to the
center of the circle is .theta., then when the entire image is
rotated as shown in FIG. 16, the distance 1' between point A' and
point B' is 1'=1, and the angle .theta.' formed by the line
segments connecting point A' and point B' to the circle center is
.theta.'=.theta.. Hence when a leaf-shape pattern and character
pattern are used as specific patterns, rotation of the coin image
due to rolling of the coin does not affect discrimination, and so
the processing of step 201 in FIG. 11 can be omitted.
[0123] When the rotation correction processing of step 201 is
performed and the coin image is positioned upright, by drawing the
separation lines 121 through 126 as shown in FIG. 17, the character
patterns "5", "0" and "0" can be separated.
[0124] Hence when rotation correction is performed for the coin
image, the separation lines can be straight lines, and the
separation lines can be associated with various specific
patterns.
[0125] In the above explanation, the example of a 500 yen coin is
used; but this invention can be applied to any kind of coin, and
specific patterns can be freely established.
[0126] Next, an example of another configuration of the
discrimination unit 4 is explained. FIG. 18 is a block diagram
showing a configuration of the discrimination unit 4, separate from
that of FIG. 7.
[0127] As shown in the figure, the discrimination unit 4 comprises
a labeling unit 45 and characteristic extraction unit 46, shape
recognition unit 47, and judgment unit 48.
[0128] The labeling unit 45 performs labeling processing for image
signals output by the binary conversion unit 32; for example, when
protrusions in the coin surface are represented by white pixels, an
area in which white pixels are connected is regarded as one area,
and is distinguished from other separated white pixel areas. The
characteristic extraction unit 46 determines the area, center of
gravity, and other characteristic quantities for each area
subjected to labeling processing by the labeling unit 45, and
stores the characteristic quantities thus determined. The shape
recognition unit 47 determines the distances and angles between
pluralities of centers of gravity and the ratios of areas of
pluralities of areas, based on the characteristic quantities
extracted by the characteristic extraction unit 46. The judgment
unit 48 compares each of the values recognized by the shape
recognition unit 47 with reference values, and discriminates
between genuine and counterfeit coins and between coin types.
[0129] Next, processing by the labeling unit 45, characteristic
extraction unit 46, shape recognition unit 47, and judgment unit 48
is explained. First, an overview is given.
[0130] Using a 500 yen coin as an example in the explanation, a
binary image of the bottom side of a 500 yen coin is as shown in
FIG. 19.
[0131] On the bottom side of a 500 yen coin, leaf-shape patterns
(areas) are positioned in four places near the outer perimeter; the
quadrilateral formed by connecting the centers of gravity of these
patterns is a square, as shown in FIG. 20. The centers of gravity
(Xc,Yc) of each of the patterns can be represented by eq. 1, taking
for example the number of pixels comprised by the pattern to be n,
and the coordinates of each pixel to be (Xi,Yi) (i=0, . . . ,n-1).
1 ( X c , Y c ) = ( i = 0 n - 1 X i / n , i = 0 n - 1 Y i / n ) (
Eq . 1 )
[0132] The binary image of the top side of a 500 yen coin is as
shown in FIG. 21, with character patterns located in six places
near the outer perimeter. These character patterns are positioned
at places located a distance from the coin center which is
approximately equal to that of the leaf-shape patterns on the
bottom side; however, the quadrilateral formed by connecting any
four of the centers of gravity of the character patterns is not a
square, as indicated in FIG. 22.
[0133] In this way, the shape of the quadrilaterals formed on the
top side and on the bottom side of a 500 yen coin are different;
this is used as a characteristic to perform discrimination. This
characteristic is, in actuality, specified by the distances
between, and the angles from the coin center of, the centers of
gravity of the patterns; but this is not affected by the rotation
angle of the image or by the enlargement or reduction factor.
[0134] For example, if the coordinates of point A are (X1,Y1) and
the coordinates of point B are (X2,Y2) in FIG. 15, then the
distance 1 between A and B is expressed by eq. 2. 2 l = ( X1 - X2 )
2 + ( Y1 - Y2 ) 2 ( Eq . 2 )
[0135] If the coordinates of the center of the coin (circle) are
(X0,Y0), then the angle .theta.1 made with the X-axis by the line
segment connecting point A with the center is expressed by eq. 3,
and the angle .theta.2 made with the X-axis by the line segment
connecting point B with the center is expressed by eq. 4. Hence eq.
5 can be used to compute the angle .theta. made by the line segment
connecting point A with the center and the line segment connecting
point B with the center. 3 1 = tan - 1 ( Y1 - Y0 X1 - X0 ) ( Eq . 3
) 2 = tan - 1 ( Y2 - Y0 X2 - X0 ) ( Eq . 4 ) = 1 - 2 ( Eq . 5 )
.theta.=.vertline..theta.1-.theta.2.vertline. (Eq. 5)
[0136] Point A' and point B' in the image shown in FIG. 16,
obtained by rotating the image of FIG. 15 through an arbitrary
angle, correspond to point A and point B respectively. In this
case, the distance 1' between the points A' and B' computed from
eq. 2 is such that 1=1', and the angle .theta.' made by the line
segment connecting point A' and the center with the line segment
connecting point B' and the center, computed from eq. 5, is such
that .theta.=.theta.'.
[0137] If, as in the image shown in FIG. 23, the radius of the coin
(circle) is r, and the radius of the coin (circle) in the image
shown in FIG. 24 which is enlarged or reduced from the image of
FIG. 23 is r", then from eq. 2, the relation between the distance 1
between A and B and the distance 1" between A" and B" is as
indicated in eq. 6. 4 l " = l .times. r " r ( Eq . 6 )
[0138] Hence the distance between centers of gravity is constant
regardless of the rotation angle of the image (coin), and even if
the enlargement or reduction ratio is different, the ratio is
constant. Because the angle made by the line segments connecting
the two centers of gravity with the coin center is constant
regardless of the image rotation angle and enlargement or reduction
ratio, the above-described characteristic quantities are not
affected by image rotation or similar.
[0139] Next, the details of processing by the labeling unit 45,
characteristic extraction unit 46, shape recognition unit 47, and
judgment unit 48 are explained, referring to FIG. 25 through FIG.
33.
[0140] FIG. 25 and FIG. 26 are flow charts showing processing by
individual units; FIG. 27 through FIG. 33 are examples of images
used in explaining the processing of individual units.
[0141] The binary conversion unit 32 converts to binary level a
multilevel image of the bottom side of the coin as shown in FIG.
27, to obtain the binary image shown in FIG. 28 (step 301). Next,
the labeling unit 45 removes the outer perimeter of the binary
image as shown in FIG. 29 (step 302), performs labeling, and
obtains patterns 401 through 408 as shown in FIG. 30 (step 303).
Here, the labeling unit 45 acquires characteristic quantities such
as the centers of gravity and areas for the patterns 401 through
408, as well as the coin center, radius, and similar.
[0142] Next, candidates for the four leaf-shape patterns are
selected by the characteristic extraction unit 46 from the labeled
patterns 401 through 408 (step 304). Selection of candidates is
performed by ranking in terms of distances from the center of the
center of gravity of each pattern; for example, the top five
candidates (patterns 404, 403, 401, 408, 406) may be selected as
shown in Table 1.
1TABLE 1 Coordinates of center of gravity Pattern Distance from
(taking coin Leaf-shaped number by coin center to center as origin)
pattern labeling center of gravity X Y Area candidate rank 1 (404)
35.0 -35 -1 177 3 2 (403) 1.4 1 1 2630 5 3 (401) 27.0 -1 37 179 4 4
(408) 37.3 5 -37 84 1 5 (406) 36.1 36 3 183 2
[0143] Next, the shape recognition unit 47 eliminates patterns with
areas that are too large or too small from the selected candidates,
to reduce the number of candidates to four (step 305). For example,
pattern 403 (cf. Table 1), with too large an area, may be
eliminated, to obtain the results shown in Table 2.
2TABLE 2 Pattern number Distance from coin Coordinates of center of
gravity assigned by center to center (taking coin center as origin)
Leaf-shape pattern labeling of gravity X Y candidate rank 1 (404)
35.0 -35 -1 3 2 (403) Not calculated 1 1 5 3 (401) 27.0 -1 37 4 4
(408) 37.3 5 -37 1 5 (406) 36.1 36 3 2
[0144] In cases where there are fewer than four candidates for
leaf-shape patterns (YES in step 306), the coin is judged to be
other than a 500 yen coin (step 307), and processing is halted.
[0145] Next, the shape recognition unit 47 names one of the four
remaining leaf-shape pattern candidates "Pat 1" (step 308), and
calculates the distance between the centers of gravity of Pat1 and
the other three patterns (step 309). For example, the pattern 408
which is ranked first as a leaf-shape pattern candidate may be
named Pat 1, as shown in Table 3 and FIG. 31, and the distances
between the centers of gravity of Pat 1 and the other patterns 401,
404, and 406 are computed.
3TABLE 3 Pattern number Distance from Coordinates of center of
gravity assigned by pat1 to center (taking coin center as origin)
Leaf-shape pattern labeling of gravity X Y candidate rank 1 (404)
53.8 -35 -1 3 2 (403) Not calculated 1 1 5 3 (401) 74.2 -1 37 4 4
<--Pat1 0 5 -37 1 5 (406) 50.6 36 3 2
[0146] Next, the shape recognition unit 47 assigns to the three
patterns other than Pat 1 the names "Pat2", "Pat3" and "Pat4" in
the counter-clockwise direction from Pat 1 (step 310). For example,
as shown in FIG. 32, pattern 406 is named Pat2, pattern 401 is
named Pat3, and pattern 404 is named Pat4.
[0147] Then, the shape recognition unit 47 computes the distance L1
between the centers of gravity of Pat 1 and Pat2 (step 311), the
distance L2 between the centers of gravity of Pat2 and Pat3 (step
312), the distance L3 between the centers of gravity of Pat3 and
Pat4 (step 313), and the distance L4 between the centers of gravity
of Pat4 and Pat1 (step 314). The distances L1, L2, L3, L4 are then
each normalized by dividing by the radius of the coin (the image
radius) (step 315). The results of normalization may for example be
as shown in Table 4.
4TABLE 4 Error with respect Normalized length to standard value
Side Length (ratio to coin radius) (%) L1 50.6 1.01 1.7 L2 50.2
1.00 2.5 L3 51.0 1.02 1.0 L4 53.8 1.08 4.5 Standard value -- 1.03 0
Coin radius 50.0 1.00 --
[0148] The judgment unit 48 judges whether the coin image is the
image of the bottom side of a 500 yen coin, based on the normalized
values L1, L2, L3, L4 (step 316); if it is judged to be an image of
the bottom side (YES in step 317), checks of the area and other
parameters for each pattern are performed (step 318).
[0149] Area checks are performed by, for example, computing the
ratios of the areas of each normalized pattern to the total area of
all patterns, as in Table 5, and if the error is greater than or
equal to a fixed value, the image is judged not to be an image of
the bottom side of a 500 yen coin.
5TABLE 5 Normalized area Error with respect (ratio to total to
standard value Pattern number Area for all patterns) (%) Pat1 84
0.026 50.6 Pat2 183 0.056 7.6 Pat3 179 0.055 5.3 Pat4 177 0.054 4.1
Standard value -- 0.052 0 Total for entire coin 3253 1.00 --
[0150] As a result of the judgment of step 316, if the image is
judged not to be an image of the bottom side of a 500 yen coin (NO
in step 317), similar procedures are used (cf. FIG. 33) to check
whether the image is an image of the top side of a 500 yen coin
(step 319).
[0151] In the above explanation, the case in which leaf-shaped
patterns on the bottom side and character patterns on the top side
of a 500 yen coin are used as characteristic quantities is
described; but other patterns can also be used as characteristic
quantities.
[0152] In the image input unit 2, there is no need to use an
optical sensor in order to obtain a two-dimensional image of the
protrusions and depressions of a coin surface; a magnetic sensor or
other means may be used to obtain two-dimensional information.
[0153] The two-dimensional image of the coin surface need not
necessarily cover the entire surface; a partial image of a coin,
indicated by the frame 500 shown in FIG. 34, can also be used to
discriminate between genuine and counterfeit coins. In this case,
judgment of the genuine or counterfeit nature can be performed
using, as characteristic quantities, the protrusions 501, 502, and
similar positioned at constant intervals near the outer perimeter
of the coin.
* * * * *