JP2005316552A - Pattern identifying device - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a pattern identifying device for identifying an identification object pattern based on an identification object image acquired by an imaging means by using a coin or the like as the object of identification for improving identifying performance. <P>SOLUTION: This pattern identifying device is provided with an illuminating means for irradiating an identification object passing through a path with the rays of light, an imaging means for receiving reflected or transmitted rays of light from the identification object and a storage means for storing a reference image, and configured to identify the identification object pattern based on an image acquired by the imaging means and the reference image. A point (center 114) being the reference of the location of a coin 23 in the acquired image is verified and detected as a plurality of outer peripheral candidate points 116 so that the location of the coin 23 can be surely detected. Thus, it is possible to accurately identify the pattern. <P>COPYRIGHT: (C)2006,JPO&NCIPI

Description

  The present invention relates to a pattern identification device that reads a pattern such as a coin and performs determination or recognition of authenticity or type.

  In recent years, vending machines have become widespread, and coin recognition devices used for them are required to have high identification performance.

  Conventionally, this type of coin discriminating apparatus includes a magnetic sensor composed of a coil and a ferrite core, and identifies the coin by detecting the material, thickness, and outer diameter of the coin.

For example, Patent Document 1 is known as prior art document information related to the invention of this application.
JP-A-8-161574

  However, in such a conventional configuration, what is identified is the material, thickness, and outer diameter of the coin, and it is difficult to detect the pattern of the coin. For this reason, there are cases in which fake coins with different patterns are illegally used. For example, it is a fake coin that is made by cutting the thickness of a similar foreign coin whose material and outer diameter are almost equal.

  It is an object of the present invention to provide a pattern recognition device with high identification performance capable of accurately identifying a pattern that can prevent such illegal use of false coins.

  In order to achieve this object, the pattern identification device of the present invention stores illumination means for irradiating an identification target passing through a passage, imaging means for receiving reflected or transmitted light from the identification target, and a reference image. A pattern identification device that identifies a pattern to be identified based on an image acquired by the imaging unit and the reference image, and a plurality of points that serve as references for the position of the identification target in the image This is a pattern identification device that verifies and detects points.

  As a result, the pattern can be accurately identified, and the identification performance can be improved.

  As described above, according to the present invention, the illumination means for irradiating the identification target passing through the passage, the imaging means for receiving the reflected or transmitted light from the identification target, and the storage means for storing the reference image are provided. In the pattern identification device for identifying the pattern to be identified based on the image acquired by the imaging unit and the reference image, a plurality of candidate points are verified as points that serve as a reference for the position of the identification target in the image. Since the pattern identifying device is to be detected, the pattern can be accurately identified, and the identification performance can be improved.

(Embodiment)
Hereinafter, embodiments of the present invention will be described with reference to FIGS. Although the pattern identification device in the present embodiment is intended for identification of a coin stamp pattern, the present invention is also applicable to a printed pattern such as a banknote or a card, a stamp pattern such as a medal or token, etc. as an identification target. It is. The pattern can be applied not only to the front and back surfaces of coins and the like, but also to side patterns. Furthermore, the object to be identified is not limited to rolling using gravity as in the present embodiment, but during natural fall, during movement by a conveying means such as a belt, and further by using a stopping means. Identification can be performed even when stopped.

  In the embodiment of the present invention, the imaging unit and the illumination unit are arranged on the same side of the passage, and identification is performed by reflected light from the identification target. However, the imaging unit and the illumination unit are arranged on the opposite side of the passage. The identification can also be performed with the transmitted light from the identification target.

  FIG. 1 is a front view showing an outline of a coin identifying device according to an embodiment of the present invention, and identifies the authenticity and type of inserted coins. In FIG. 1, a coin insertion slot 12 is provided in the upper part of the coin identification device main body 11, and a coin passage 13 is connected downward from the insertion slot 12. A part of the side wall of the passage 13 is constituted by an optical transparent body 14, and an illumination means 15 and an imaging means 16 for detecting a coin pattern are arranged on the back of the optical transparent body 14. Further, a thickness / material sensor 17 is disposed downstream of the passage 13. Further, the passage 13 is connected to a coin outlet 18 located at the lower part of the coin identification device main body 11.

  FIG. 2 is a cross-sectional view of the vicinity of the imaging means 16. A part of one side wall 21 constituting the passage 13 forms a bottom surface 22 of the passage. The inserted coins 23 roll on the bottom surface 22. A part of the other side wall 24 of the passage 13 is composed of the optical transparent body 14, and the coin 23 is illuminated with illumination light from the illumination means 15 including a plurality of LEDs 25 and a flexible wiring board. The reflected light reflected by the coin 23 is detected by the imaging means 16 arranged on the side wall 24 side. The imaging unit 16 includes an image sensor 26, a light receiving surface 27 on the image sensor 26, and a lens 28 that forms an image of reflected light from the coin 23 on the light receiving surface 27.

  The bottom surface 22 of the passage 13 is provided on the side wall 21 opposite to the illumination unit 15 and the imaging unit 16, thereby preventing a shadow from being formed on the bottom surface 22 and lowering the identification performance. Further, the width 22a of the bottom surface 22 is made smaller than the minimum thickness of the coin 23 to be identified so as not to prevent the illumination light from the illumination means 15 from being applied to the edge of the coin 23, that is, not to be a shadow. The dimension is such that the coin 23 having the minimum thickness does not fall even if it passes along the side wall 24 side.

  Further, the passage 13 is inclined with respect to the vertical so that the coin 23 can stably pass along one of the side walls 21 and 24. The side wall 24 opposite to the inclined side is not always necessary. In the present embodiment, the optical transparent body 14, the illumination means 15, and the imaging means 16 are arranged on the side opposite to the inclined side to reduce the adhesion of dirt to them. The optical transparent body 14 is formed of glass, plastic, or the like, so that the passage 13 side and the imaging means 16 side can be separated, and dust or coins 23 can be prevented from entering the imaging means 16 side from the passage 13 side. The optical transparent body 14 may be air, that is, nothing may be used.

  The side wall 21 and the side wall 24 are black in order to block disturbance light and reduce reflected light from the illumination means 15 other than the coins 23. By using a non-reflective or low-reflective material, color, and surface state, not only black, but also disturbance light other than illumination light from the illumination means 15 and reflected light other than the coins 23 of illumination light from the illumination means 15 Can be prevented from being detected by the imaging means 16, and the identification accuracy can be improved.

  The illumination means 15 is configured as shown in FIG. That is, a range including all of the coin position 31 passing through the passage 13 at the assumed minimum speed to the coin position 32 passing through the assumed maximum speed is defined as the coin position 33 at the time of imaging, and the coin position 33 at the time of imaging is completely set. It is configured to cover the shape. The shape of the illuminating means 15 is a non-circular shape having a long side and a short side, for example, an oval shape or an elliptical shape. By coinciding the long side with the passing direction of the coin 23, the coin 23 is a light receiving surface of the image sensor 26. The tolerance for the accuracy of detecting the timing at which the position corresponding to the center of 27 is detected is expanded, and it becomes possible to discriminate even during free fall or rolling where the passing speed of the coin 23 is not constant. Moreover, illumination can be made uniform by making the center of the illumination means 15 substantially coincide with the center of the coin position 33 during imaging. Further, the center of the light receiving surface 27 on the image sensor 26 is also arranged at these centers.

  In FIG. 2, the regular reflection light 29 is the regular reflection of the illumination light from the illuminating means 15 on the plane portion near the outer peripheral edge of the coin 23 having the maximum outer diameter to be identified, that is, the incident angle and the reflection angle are equal. The reflected light component is shown. When this regular reflection light 29 is incident on the image pickup means 16, a very bright unevenness occurs in the input image, which prevents accurate identification. Therefore, the passage 13, the illumination unit 15, and the imaging are arranged so that the regular reflection light 29 does not enter the imaging unit 16, in other words, in such a positional relationship that the regular reflection position 34 does not fall within the range of the coin position 33 at the time of imaging in FIG. The means 16 is arranged to prevent unevenness in the image at the coin position 33 during imaging. By making the shape of the illumination means 15 a non-circular shape having a long side and a short side, the shape of the regular reflection position 34 can be a non-circular shape having a long side and a short side, and within the range of the coin position 33 at the time of imaging. It can be difficult to enter. Furthermore, by making the long side of the illumination means 15 coincide with the passing direction of the coin 23, the long side of the regular reflection position 34 in the imaging means 16 can be made substantially parallel to the passing direction of the coin 23. By making the center coincide with the center of the coin position 33 at the time of imaging in the imaging means 16, the center of the regular reflection position 34 can be substantially coincident with the center of the coin position 33 at the time of imaging. Alternatively, a missing portion is provided in the regular reflection position 34 by having a missing portion in which the LED 25 is not disposed in the portion 15a (long side portion) of the illumination means 15 having the regular reflection position 34a that falls within the range of the coin position 33 during imaging. Can do. In any case, there is an effect that the passage 13, the illumination unit 15, and the imaging unit 16 can be easily arranged so that the regular reflection light 29 from the coin 23 is incident outside the coin position 33 at the time of imaging in the imaging unit 16. The same effect can be obtained by matching the center of the illumination unit 15 with the center of the imaging unit 16. When identification is performed using transmitted light, a transmitted light component (referred to as regular transmitted light) having the same incident angle and emission angle corresponds to regular reflected light 29 when identification is performed using reflected light, and unevenness of an image. The same can be said about.

  In order to detect the marking pattern of the coin 23, the incident angle of the irradiation light is set to a low angle with respect to the coin 23, and dark field illumination is performed so that the marking is further raised. The plurality of LEDs 25 constituting the illuminating means 15 (first illuminating means) are provided in multiples of 8, and are divided into two groups of the second illuminating means 36 and the third illuminating means 37. The second illuminating means 36 and the third illuminating means 37 can emit light independently. The second illumination unit 36 includes four LED groups 36a, 36b, 36c, and 36d, and is closer to the outlet 18 than the third illumination unit 37. The third illumination unit 37 also includes four LED groups 37a and 37b. , 37c, 37d, and the side relatively close to the insertion port 12. All the LED groups 36a, 36b, 36c, 36d, 37a, 37b, 37c, and 37d are composed of the same number of LEDs 25. The second illumination means 36 and the third illumination means 37 are symmetrical with respect to a straight line 35 that passes through the center of the illumination means 15 and is perpendicular to the passage 13. Each of the second illumination means 36 and the third illumination means 37 is symmetrical with respect to a straight line that passes through the center of the illumination means 15 and is parallel to the passage 13. By dividing the illumination means 15 into two groups and causing each illumination means 36 and 37 to emit light independently, the degree of unevenness of the coin 23 can be detected by a method described later. By configuring each of the second illumination unit 36 and the third illumination unit 37 with a plurality of LED groups, the first image data and the second image data, which will be described later, are made uniform and high in image quality, and the degree of unevenness of the coin 23 Can be detected with high accuracy. In particular, the second image data and the third image data are made symmetrical with respect to the straight line 35 perpendicular to the passage 13 so that the second image data and the third image data are input to the inlet 12. The difference in brightness between the side and the outlet 18 is suppressed and homogenized. Further, each of the second illumination means 36 and the third illumination means 37 is symmetric with respect to a straight line parallel to the passage 13 so that the second image data and the third image data are in the passage 13. The difference in brightness between the side close to the bottom surface 22 and the side far from the bottom surface 22 is suppressed and homogenized. By constituting the second illumination means 36 and the third illumination means 37 with a plurality of light emitting elements (LEDs 25), it becomes easy to divide each, and the second illumination means 36 and the third illumination means. 37 is composed of an equal number of LEDs 25, and each divided group is the same number of LEDs 25, so that the difference in brightness can be suppressed and the second image data and the third image data can be homogenized, and the unevenness degree of the coin 23 can be accurately determined. It is possible to detect.

  FIG. 4 is a sectional view of a part of the passage 13. A discharge assisting means 41 is provided on the other side wall 24 located on the opposite side of the one side wall 21 having the bottom surface 22. When a deformed coin, a coin wet with rain or the like, or a coin with a sticky substance attached thereto is inserted and stopped in the passage 13, the distance between the one side wall 21 and the other side wall 24 is increased, whereby the coin 23 is Although it is dropped downward and returned from the outlet 18, the discharge assisting means 41 ensures the discharge of the coin 23 by holding the upper part of the coin 23 on the side wall 24 side.

  FIG. 5 is a sectional view of the vicinity of the thickness / material sensor 17. E-type cores 51 and 52 made of a ferrite material are attached to one side wall 21 and the other side wall 24 constituting the passage 13 so as to face each other. The E-type cores 51 and 52 have a length smaller than the outer diameter of the smallest coin 23 to be identified, and are arranged at a position where the center of the coin 23 passes near the center of the E-type cores 51 and 52. ing. The combined thickness / material sensor 17 includes an E-type core 51, two coils 53 and 54 wound inside the E-type core 51, and an E-type core 52 and two coils 55 and 56 wound therein. . The coil 53 and the coil 55 are connected in series opposite phase so that mutual inductance becomes negative. By arranging the two coils 53 and 55 opposite to the passage 13 and connecting them in reverse phase, the magnetic flux direction of the alternating magnetic field generated in the passage 13 is parallel to the surface of the coin as shown by the broken line in FIG. Thus, the thickness of the coin can be sensitively detected. Further, the coil 54 and the coil 56 are connected in series and in phase so that mutual inductance becomes positive. By arranging the two coils 54 and 56 facing the passage 13 and connecting them in phase, the magnetic flux direction of the alternating magnetic field generated in the passage 13 is changed to the surface of the coin as shown by a two-dot chain line in FIG. It becomes vertical and can detect the material of coins sensitively. The thickness sensor 71 and the material sensor 75 are used for the purpose of downsizing and cost reduction, but separate sensors may be used.

  FIG. 6 is a block diagram of the control circuit of the image sensor 26 forming the imaging means 16. In this embodiment, a MOS type two-dimensional (area) image sensor is used as the image sensor 26 to obtain a two-dimensional image at high speed. However, the present invention is not limited to this, and time series data of a CCD or a one-dimensional (line) sensor may be used. The image data detected by each pixel 61 composed of the light receiving element of the image sensor 26 selects the pixel 61 by a horizontal scanning line 64 and a vertical scanning line 65 controlled by a horizontal scanning circuit 62 and a vertical scanning circuit 63 which are a kind of shift register. Then, it is sequentially output 67 from the horizontal scanning circuit 62. At this time, it is possible to output only the image data of the specific area 66 by controlling only a part of the scanning lines by the horizontal scanning circuit 62 and the vertical scanning circuit 63. Output of partial image data can be realized by a MOS type image sensor, and by providing such an imaging means 16, it is possible to speed up reading by narrowing the output of image data to only a necessary portion. Is possible. In addition, each pixel 61 has a square shape, and uses the image sensor 26 in which the number of pixels in the horizontal direction is larger than the number of pixels in the vertical direction and the detection area is rectangular, and the longitudinal direction of the image sensor 26 in the passing direction of the coins 23. Are arranged so that they substantially coincide with each other to obtain rectangular image data. The reason why the longitudinal direction is made coincident with the passing direction is the tolerance for the accuracy of detecting the timing when the coin 23 comes to the position corresponding to the center of the light receiving surface 27 of the image sensor 26 by effectively using the pixels of the image sensor 26. The image sensor 26 performs scanning of the horizontal scanning circuit 62 to which the output 67 is connected in preference to scanning of the vertical scanning circuit 63 to which the output 67 is not connected (for horizontal scanning). This is because the horizontal pause period (horizontal blanking period) in the output signal is small to detect an image in a horizontally long region, and the image data can be read out in a shorter time.

  In the present embodiment, as shown in the block diagram of the control circuit in FIG. 7, the image sensor 26 in the imaging unit 16 includes a control circuit 68 that supplies a voltage for sensitivity control to a row of the pixel matrix, and a pixel matrix. And a neural network 69 for processing the current flowing from the row to the ground. Since the details of the control circuit 68 and the neural network 69 are described in Japanese Patent Laid-Open No. 6-139361 (Example 6), the description of the configuration and operation will be omitted. For example, a product-sum operation of a 3 × 3 filter matrix and an image can be executed and output. That is, the function of the edge detection means 84 and the edge enhancement function described later can be realized in the image sensor 26. Arithmetic operations based on neighboring surrounding pixel data can be executed particularly quickly. It is natural that the original image can be output as it is, instead of the edge image, by changing the filter setting. Since the image sensor 26 is provided with the control circuit 68 and the neural network 69 in this manner, the product-sum operation of the filter matrix and the image can be executed in the image sensor 26, so that the edge detection means 84 is not required and the edge detection is performed. Processing time can be shortened and data processing can be speeded up. Note that the image sensor 26 with a built-in edge detection function has both the functions of the imaging unit 16 and the edge detection unit 84, and the imaging unit 16 and the edge detection unit 84 may be separate. In the description, the imaging unit 16 and the edge detection unit 84 will be described separately.

  FIG. 8 is a block diagram showing the configuration of the control circuit. The thickness sensor 71 is connected to the oscillation circuit 72 and is input to the thickness detection means 74 through a rectifier circuit 73 that converts the oscillation waveform from a sine wave to a signal indicating the oscillation level. Has been. The material sensor 75 is connected to the oscillation circuit 76 and is input to the material detection means 78 via the rectifier circuit 77. The outputs of the rectifier circuits 73 and 77 are also input to the input detection means 79 for detecting that the coin 23 has been input. The input detection means 79 controls the illumination means 15 and the imaging means 16, detects the reflected light irradiated from the illumination means 15 and reflected by the coin 23, and detects the captured analog image data into a multi-value digital signal. It outputs to the A / D conversion means 80 to convert. The output of the A / D conversion means 80 is connected to a CDS means 70 for removing noise by a correlated double sampling method and an adjustment means 81 for controlling and adjusting the imaging means 16. The CDS means 70 reads out an image signal and a non-image signal consisting only of a bias component and a noise component for each pixel and outputs a difference between them. Noise due to such as can be removed. The output of the CDS means 70 is an input detection means 79, a dew condensation detection means 82 for detecting whether or not the passage 13 in the vicinity of the imaging means 16 is dewed, an unevenness detection means 83 for detecting the unevenness degree of the coin 23, and an edge of image data The edge detection means 84 for detecting the part and the center / outer diameter detection means 85 for detecting the center and outer diameter of the coin part in the image data are input. The center / outer diameter detection means 85 is connected to the edge detection means 84, the denomination temporary determination means 86, and the magnification correction means 87, and the denomination temporary determination means 86 detects the value of the outer diameter detected by the center / outer diameter detection means 85. Tentatively determine up to two types of denominations that are considered to be applicable. The output of the edge detection means 84 enters the coordinate conversion means 88 for converting the image data from orthogonal coordinates to polar coordinates, and the magnification correction means 87 is caused by the passage position of the coin 23 in the passage 13, the assembly error of the imaging means 16, and the like. The imaging magnification is corrected and the coordinate conversion means 88 is controlled. The output of the coordinate conversion means 88 is input to a threshold value setting means 89 for setting a threshold value for binarization and a binarization means 90 for converting image data from a multi-value digital value to a binary digital value. The output of the binarization means 90 is connected to the rotation angle detection means 91, detects the rotation angle of the image data of the inserted coin 23 with respect to the reference image data stored in the storage means 92, and The image data and the reference image data are output to the pattern matching means 93 for matching. The output of the denomination temporary determination means 86 is connected to the magnification correction means 87, the threshold setting means 89, the rotation angle detection means 91, and the pattern matching means 93, and the storage means 92 includes the rotation angle detection means 91, the pattern matching means 93, And it is connected to each comparison means 94-97. Each of the comparison means 94 to 97 receives the outputs of the thickness detection means 74, the material detection means 78, the unevenness detection means 83, and the pattern matching means 93. The comparison means 94 to 97 compare with the reference stored in the storage means 92. If they match within the allowable range, a signal indicating the type of the genuine coin is output, and if it does not match any type of reference value, a signal indicating that it is a false coin is output. The determination means 99 outputs a signal indicating the type of the genuine coin only when the signals from the comparison means 94 to 97 all indicate the same genuine coin type, and determines a signal indicating the false coin otherwise. Output as signal 100. The outputs of the dew condensation detection means 82 and the switching means 98 are also input to the determination means 99.

  The operation of the coin discriminating apparatus configured as described above will be described with reference to the block diagram of FIG. 8 using the flowcharts shown in FIGS. In steps S11 to S17, it is detected that the coin 23 has been inserted. Here, the insertion and detection of insertion of the coin 23 mean to include arrival of the coin 23 to the identification unit and detection of arrival. First, in order to detect coin insertion by the imaging unit 16, the insertion detection unit 79 sets the imaging unit 16 (S11). Specifically, in the imaging range 101 shown in the conceptual diagram of the imaging region in FIG. 11, the imaging unit 16 is set so that only a partial image of the first input detection region 102 is output, and each pixel of the image sensor 26 is set. Imaging is started after preparation for imaging such as initialization (reset) 61 is performed.

  Next, the illumination means 15 is caused to emit light for a short time at the timing when all the pixels 61 in the first input detection region 102 are in the light receiving state (S12). By emitting light for a short time with respect to the passing speed of the coin 23, an image close to a stationary state can be obtained without stopping the coin 23, and the identification accuracy can be improved. In addition, the LED 25 can be driven with a large current so that the illumination can be increased in illuminance or the life can be extended. Note that the illumination unit 15 causes both the second illumination unit 36 and the third illumination unit 37 to emit light. Unless otherwise specified, illuminating the illumination means 15 means that both the second illumination means 36 and the third illumination means 37 are caused to emit light.

  Then, the image data of the first input detection area 102 is input (S13). Next, when the image pickup means 16 detects the input, the same input is performed in the second input detection area 103, the next input in the third input detection area 104, and then the process returns to the first input detection area 102. The reason why the insertion detection is performed in the three insertion detection areas 102 to 104 is to reliably detect the insertion of the coin 23 even when the coin 23 and the passage 13 are dirty. Further, as shown in FIG. 11, the three insertion detection areas 102 to 104 are calculated backward from the time required for the pattern input illumination (S40) described later and the passing speed of the coin 23 with respect to the coin position 33 at the time of imaging. By disposing at the position, the coin 23 having an average passing speed can be imaged at substantially the center of the light receiving surface 27 on the illumination means 15 and the image sensor 26. In addition, the input detection regions 102 to 104 are separated from each other as much as possible so that they are not easily affected by the dirt of the coins 23 and the passages 13, and the detection timing is not shifted by the outer diameter of the coins 23. The height is arranged near and above and below the center of the coin position 105 of the smallest coin to be identified, and the insertion detection areas 102 and 104 arranged above and below are the insertion detection areas arranged near the center of the coin position 105 of the smallest coin. It is arranged slightly closer to the inlet than 103.

  Based on the image data of the input detection areas 102 to 104 input in this way, dew condensation is detected in the passage 13 including the optical transparent body 14, the lens 28, the light receiving surface 27 of the image sensor 26, and the like (S14). The determination as to whether or not condensation is made is based on the fact that the input image is blurred by defocusing on the surface of the coin 23 due to dew adhering to the optical transparent body 14 or the lens 28. If the variation of the image data in the three input detection areas 102 to 104, that is, the state in which all three variances are smaller than a certain value, dew condensation is determined. Dispersion can be easily obtained, and a shift in focus of the image pickup means 16 due to dew condensation can be detected by determining with the small dispersion. Furthermore, if even one of the input detection areas 102 to 104 has a large variance, the condensation determination is not performed, thereby preventing erroneous determination and improving the reliability of the condensation determination. If it is determined that condensation has occurred, the control processing of the image sensor 26 is not performed, so that malfunction due to abnormal image data can be prevented, condensation prevention means (not shown) can be operated, and condensation can be prevented from occurring in the vending machine. It is also possible to communicate to the control unit and notify the operator of the vending machine by displaying. Condensation can be detected without using a dedicated sensor by using the image pickup means 16, and an image for detecting condensation can be obtained in a short time by using the image sensor 26 capable of outputting a partial image. Can do.

  The input detection (S15) by the image pickup means 16 utilizes the fact that the illumination light irradiated from the illumination means 15 is reflected by the inserted coin 23 and the image data detected by the image pickup means 16 changes. If even one of the averages or variances of the image data in the three insertion detection areas 102 to 104 has a certain change from the standby state value, it is determined that the coin 23 has been inserted. If at least one of the average and the variance changes, it is determined that the coin 23 has been inserted, so that it is possible to reliably detect the insertion even when there is no change in either the average or the variance. In addition, the average and variance are calculated in a plurality of areas, and if there is a change in any one of the areas, it is determined that the coins are inserted. Can do.

  In the case where an input detection sensor is provided separately, a space for providing this sensor is required, and if an optical sensor is used, interference with the illumination light of the illumination means 15 is prevented, or the input detection sensor and the imaging are taken. Assembling of the means 16 causes a variation in the distance between the two sensors, and an error occurs in the timing of image detection. On the other hand, as in the present embodiment, it is possible to easily detect the input at a plurality of locations by using the image pickup means 16 to detect the input and also serve as the input detection sensor, reduce the space, and interfere with the illumination light. And accurate image detection that is not affected by assembly variations. Furthermore, by using the image sensor 26 capable of outputting a partial image, an input detection image can be obtained in a short time, and the input detection can be performed at high speed.

  Since it is not possible to detect the insertion of the coin 23 during the condensation determination or due to dirt in the passage 13 even if it is not condensation, the insertion is also detected by the thickness sensor 71 and the material sensor 75 other than the imaging means 16 (S16, S17). When the coin 23 inserted from the insertion slot 12 approaches the thickness / material combination sensor 17, the impedances of the coils 53 to 56 change, and the oscillation levels of the oscillation circuits 72 and 76 change accordingly. If there is a certain change from the oscillation level during standby, it is determined that a coin 23 has been inserted, and thickness and material detection (S20) is performed.

  In the thickness and material detection (S20), the thickness and material are detected from the change in the oscillation level of the oscillation circuits 72 and 76 according to the impedance change of the coils 53 to 56 by the coin 23. As described above, the oscillation level of the thickness sensor 71 sensitive to the thickness of the coin 23 is connected to the thickness detecting means 74 via the rectifier circuit 73 that converts the oscillation waveform from a sine wave to a signal indicating the oscillation level. The maximum amount of change in the oscillation level during passage is detected and output to the comparison means 94. Similarly, the material detection means 78 detects the maximum amount of change of the oscillation level of the material sensor 75 sensitive to the material of the coin 23 when the coin passes and outputs it to the comparison means 95.

  When the imaging means 16 detects the insertion (S15), the unevenness and pattern detection (S21) and the thickness and material detection (S20) are performed in parallel. Image detection is first performed from the adjustment step (S22). The image quality of image data to be detected changes depending on the material and dirt of the inserted coin 23, dirt on the passage 13, deterioration and temperature characteristics of the illumination means 15, and the brightness and contrast increase and decrease. On the other hand, every time the coin 23 passes, before performing the unevenness input and pattern input to be described later, the same image pickup means 16 and illumination means 15 as those used for these inputs are used in advance. Get a partial image. Based on the acquired image, the input conditions of the imaging unit 16, specifically the sensitivity, that is, the gain of the amplification circuit included in the image sensor 26, so that the image quality of the image data detected by the imaging unit 16 is as constant as possible. Adjust the offset level. As shown in FIG. 11, the input condition setting area 106 is set to a position and size that are completely included in the coin position 105 of the minimum coin with the assumed minimum speed and the coin position 107 with the assumed maximum speed. . In FIG. 11, the coin 23 is actually moved by the time required from the input detection to the input condition setting input, but the coin position 105 of the minimum coin with the minimum speed is It is the same as when detecting input. At the beginning of the adjustment step (S22), in order to speed up the readout time, the output image area of the imaging means 16 is set only to the input condition setting area 106, and imaging is started after preparation for imaging (S31). Subsequently, the illumination unit 15 emits light for a short time (S32), and the image data of the input condition setting area 106 is input (S33). In the present embodiment, among the pixels included in the input condition setting region 106, the output of the pixel corresponding to 5% of the order from the brighter image signal (before noise removal including the non-image signal), and (the bias component) The gain or offset level of the amplification circuit included in the image sensor 26 is changed in accordance with the output of the pixel corresponding to the order of 5% from the dark side of the non-image signal. (S34) is performed. For this reason, the bright portion and the dark portion are prevented while the bright portion exceeds the upper limit of the A / D conversion range of the A / D conversion means 80, or the dark portion falls below the lower limit and falls outside the A / D conversion range. Appropriate adjustments can be made so that the difference between the parts is sufficient. It may be based on the output of the brightest and darkest pixels and can be easily adjusted. The reason why the output of pixels corresponding to 5% of the order from the brighter side and the order from the darker side is used is to prevent the adjustment of the image pickup means 16 when there is a defective pixel. is there. However, the present invention is not limited to this, and it may be based on the average value or variation of the image data, or even if the reference voltage of the A / D conversion means 80 is changed, the gain or offset level of the amplifier circuit included in the image sensor 26 is changed. Has the same effect as Thus, by acquiring the image of the coin 23 in advance by the imaging unit 16, the input conditions of the imaging unit 16 and the like can be adjusted based on the acquired image, and image data with a constant image quality can be obtained. Further, by storing the adjustment amount and correcting the adjustment amount every time the coin 23 is inserted, it is possible to reduce the influence of changes over time such as component deterioration and maintain the identification performance. By inputting at an assumed position of the coin 23, an image of the coin 23 can be reliably obtained and appropriate adjustment can be performed. Furthermore, by using the image sensor 26 capable of outputting a partial image, an adjustment image can be obtained in a short time and can be adjusted at high speed.

  Further, the same effect can be obtained by changing the illumination conditions such as the light emission intensity and the light emission time of the illumination means 15, but in the adjustment method of the present embodiment, when adjusting the illumination conditions, specifically, the illumination means 15 As compared with the case where the drive power supply (for example, the drive current of the LED 25) and the light emission time are changed, the adjustment can be performed without adding a power supply circuit or complicated control for changing the reading timing of the image sensor 26.

  A technique for providing a reflected light sensor different from the imaging unit 16 and performing adjustment according to the amount of light received by the reflected light sensor is disclosed in, for example, Japanese Patent Application Laid-Open No. 2000-33111. In this case, an image for adjustment is acquired by using the same image pickup means 16 used for unevenness input and pattern input, so that no adjustment dedicated sensor is provided and separate sensors are used for adjustment and identification. It is possible to adjust without being affected by the detection error.

  The subsequent process is an unevenness input process (S23). A fake coin (hereinafter referred to as a copy affixed fake coin) produced by pasting a copy of a true coin or a paper printed with a pattern of a true coin on a metal is sufficient with the true coin in the pattern verification (S51) described later. It is difficult to eliminate them without finding any significant difference. Therefore, in order to detect the degree of unevenness and eliminate copy-pasted fake coins, the illumination means 15 is replaced with the second illumination means 36 on the outlet 18 side and the third illumination means 37 on the insertion port 12 side as described above. The second illumination means 36 and the third illumination means 37 can emit light independently. Then, as shown in FIG. 12, the first image data can be obtained when illuminated only by the second illumination means 36 that is generated if there is unevenness (see the cross-sectional view in the vicinity of the coin in FIG. 12A). The shadow position (see the schematic diagram of the image data in FIG. 12B) and the second when illuminated only by the third illumination means 37 (see the cross-sectional view in the vicinity of the coin in FIG. 12C) The difference between the positions of the shadows that can be formed in the image data (see the schematic diagram of the image data in FIG. 12D), that is, the difference when illuminated from different directions is used. As shown by broken lines in FIG. 11, the three unevenness detection lines 108 to 110 are completely included in the assumed minimum coin position 105 of the minimum coin and the assumed minimum coin position 107 of the maximum speed. Since the position and length are set, an image of the coin 23 can be obtained with certainty and appropriate unevenness can be detected. In FIG. 11, the coin 23 is actually moved for the time required from the input detection to the input of the unevenness detection, but the coin position 105 of the minimum coin with the minimum speed is detected for the sake of simplicity. Same as time. At the beginning of the concavo-convex input step (S23), the output image area of the imaging means 16 is sequentially set to these concavo-convex detection lines 108 to 110, and imaging preparation is started (S35). Subsequently, the second illuminating means 36 or the third illuminating means 37 are alternately switched with respect to one unevenness detection line to emit light for a short time (S36), and image data is input (S37). It repeats until the 1st and 2nd image data of the unevenness | corrugation detection lines 108-110 are input (S38). By performing the interval between the first image input and the second image input in a short time of about 500 microseconds, the coin movement between them is an average passing speed equivalent to one pixel, which will be described later. In addition, when the difference between the first image data and the second image data is calculated, the influence of the coin movement can be suppressed by correcting the shift of one pixel. In the present embodiment, the second illumination means 36 and the third illumination means 37 are all constituted by the LEDs 25 having the same wavelength characteristics. Therefore, the unevenness can be detected in the monochrome image. In addition, as described with reference to FIG. 3, the second illumination means 36 and the third illumination means 37 for detecting unevenness are configured by dividing the illumination means 15 into two groups, that is, illumination for pattern detection. Since the means 15 is also used and the image pickup means 16 is also used as the same, the cost and space can be reduced, and the adjustment is not required for a dedicated adjustment process. By causing the second illuminating unit 36 and the third illuminating unit 37 to emit light at different timings, interference of illumination light by the second and third illuminating units can be prevented, and an image of each reflected light can be obtained reliably. . By using the image sensor 26 capable of outputting a partial image, it is possible to obtain an image of reflected light in a short time and to input unevenness at high speed.

  In addition, although the technique which determines the unevenness | corrugation of a coin by irradiating with a different wavelength characteristic from a different direction is disclosed by Unexamined-Japanese-Patent No. 2002-183791, for example, since it irradiates with the same wavelength characteristic in this Embodiment. Unevenness can be detected without using illumination means and color image sensors or filters having different emission wavelengths. In addition, the degree of unevenness can be detected without being affected by variations in sensor sensitivity and filter transmission characteristics that change depending on the wavelength and ambient temperature.

  Further, a technique for determining the pattern of a coin by irradiating separately from different directions and performing binarization based on each reflected light intensity is disclosed in, for example, Japanese Patent Laid-Open No. 7-210720. In the embodiment, as will be described later in the unevenness calculation (S44), since the detection is based on the difference between the reflected light intensities, the unevenness degree can be detected with multiple values and can be accurately determined.

  The next step is a pattern input step (S24). The output image area of the imaging means 16 is set to a position and size that completely include the maximum coin with the assumed minimum speed and the maximum coin with the assumed maximum speed, and imaging is started after preparation for imaging is performed. (S39). Subsequently, the illumination unit 15 emits light for a short time (S40), and the third image data is input (S41). In the pattern input, the coin input position in the image data differs due to variations in the assembly dimensions generated for each product and the characteristics of the lens 28, etc. Therefore, it is necessary to set a larger pattern input area accordingly. In contrast, in this embodiment, the position of the bottom surface 22 in the image data, that is, the lower end position of the coin 23 and the imaging magnification are variably stored, and the upper end position in the image data of the largest coin is calculated. By reducing the pattern input area, the input time of image data, the capacity of a storage circuit for storing data, and the processing time of data can be reduced. Further, the stored lower end position of the coin 23 and the imaging magnification can be reliably corrected by performing correction every time a genuine coin is inserted, and the performance deteriorates even with a change with time. Can be prevented, and the initial identification performance can be maintained. The lower end position of the coin 23 and the imaging magnification are stored and corrected, the center position of the minimum coin is calculated from these, and the insertion detection areas 102 to 104, the input condition setting area 106, based on any one or more of the three, By setting the unevenness detection lines 108 to 110, the pattern input region, and detection lines 111 and 112 for detecting the center and outer diameter described later, the position of the coin 23 in the imaging means can be accurately captured, It is possible to accurately detect each of the assembling error of the image pickup means 16 and the dimensional / characteristic change with time and regardless of the size of the inserted coin 23, that is, the denomination. For example, Japanese Patent Application Laid-Open No. 10-105765 discloses a technique for storing the position of the coin 23 in the adjustment mode. However, the coin is inserted by variably storing it as in the present embodiment. It is possible to correct each time, and the identification performance can be maintained following the change with time.

  In the subsequent unevenness detection step (S25), the unevenness degree is calculated from the first and second image data input in the unevenness input step (S23), but before that, the center and outer diameter are calculated from the third image data. , And tentatively determine which denomination is close to the inserted coin 23 based on the detected outer diameter.

  In the center / outer diameter detection (S42), in order to detect the position of the image corresponding to the coin 23 in the third image data, the outer diameter is obtained together with the center as the reference point. For an identification target having a shape other than a circle such as a rectangle, the position including not only the center but also the orientation can be detected by obtaining the outer periphery of the identification target from candidate points corresponding to the outer periphery. Although the detection accuracy can be improved by verifying with the distance from the center, the position of the coin 23 in the image data can be easily detected by obtaining the center and the outer diameter, particularly when the identification target is a circular coin 23. . Therefore, a plurality of candidate points corresponding to the outer periphery are selected, the distance between each outer periphery candidate point and the temporary center is verified, the center is obtained from the candidate points determined to correspond to the outer periphery, and the position of the coin 23 Is detected. As shown in FIG. 13, with respect to the third image data, first, the detection line 111 parallel to the passing direction (that is, the coordinate in the long side direction of the third image) and the direction perpendicular to the passing direction (that is, the third image) A plurality of detection lines 112 (parallel to the coordinates in the short side direction) are set. Since one coordinate of the center can be obtained for each detection line in one direction, it is possible to determine the coordinate of the center by performing detection with at least two straight lines having different directions. In particular, by using an orthogonal straight line and making it a straight line parallel to the coordinates of the third image, the handling of the coordinates is very easy and the error is reduced. In the present embodiment, each of the four detection lines 111 and 112 is always based on the lower end position of the stored coin 23 and the outer circumference of the minimum coin with the assumed minimum speed and the minimum coin with the assumed maximum speed. The layout and length are such that they intersect. By using the stored lower end position of the coin 23 and performing correction each time a correct coin is inserted, it is possible to reliably detect the position and to perform performance against changes over time. Deterioration can be prevented.

  First, smoothing and edge detection are performed on the image data on the detection lines 111 and 112. Specifically, for the data of 9 pixels including 8 pixels around the pixel of interest, the horizontal detection line 111 uses the array data in (Table 1) and the absolute value of the sum of the 9 elements integrated for each array element. Data after pixel smoothing and edge detection. In the detection line 112 in the vertical direction, the absolute value of the sum of the array data in (Table 2) and the nine elements integrated for each array element is used as data after smoothing and edge detection. By integrating with the array data according to the direction of the detection line (changing the calculation method between the detection line 111 in the horizontal direction and the detection line 112 in the vertical direction), it is possible to detect only the change in the direction matching each line, Calculation is speeded up. For the detection line 111 in the horizontal direction and the detection line 112 in the vertical direction, the absolute value of the sum of the array data of (Table 1) and the nine elements integrated for each array element, and the array data and array elements of (Table 2) It is also possible to obtain the sum of the 9 elements summed up every time and the absolute value of the sum to obtain the data after smoothing and detecting the edge of the pixel of interest.

  The point after the smoothing / edge detection is divided into two at the center of the detection lines 111 and 112, and the point having the maximum value in the first half and the second half is set as the outer peripheral candidate point 113. At this time, by taking a product with a value proportional to the distance from the center of the line and correcting it to obtain the maximum value up to the third, the outside of the image where the outer periphery of the coin 23 is likely to be copied, That is, a point away from the center of the line can be selected preferentially, and the position of the coin can be detected with high accuracy even when the illuminance of the illuminating means 15 is uneven and the outer periphery of the coin 23 appears dark. Further, by obtaining the peripheral candidate point 113 not by the maximum value but by the local maximum value, it is possible to select the peripheral candidate point 113 without concentrating on a specific portion even when the image is not clear and the local maximum is smooth. A part of the outer periphery candidate points 113 is indicated by white and black dots in FIG.

  Next, the center candidate point 114 to be identified is detected using the midpoint position between the outer periphery candidate points 113. For a point-symmetric shape identification target, the midpoint position of the intersection of the outer circumference and the straight line matches the position where the center of the identification target is projected onto this straight line, so use the midpoint position of the outer peripheral point detected on the straight line. By doing so, it is possible to accurately detect the center. For each of the detection lines 111 and 112, a total of nine midpoint positions are determined between the two outer peripheral candidate points 113 selected one by one from the former candidate point and the latter candidate point. Two maximum points with the highest frequency are obtained from the frequency distribution of a total of 36 middle point positions for four lines, and set as the coordinates of the center candidate point 114. When calculating the frequency distribution of the midpoint position between the first half candidate point and the second half candidate point, if the interval between the first half candidate point and the second half candidate point is not within a certain range (range A), this The midpoint position is not used for the frequency distribution. The upper limit is a value obtained by adding an allowable range to the diameter of the maximum coin to be identified, the lower limit is a value obtained by subtracting the allowable range from the diameter of the minimum coin to be identified, and the lower limit allowable range is the detection lines 111 and 112 and the coin center. By setting the value in consideration of the distance in the case of the farthest distance, the combination of intervals that cannot be the original outer peripheral point can be excluded, and the center can be accurately detected. This is obtained in the direction parallel to the passing direction (X coordinate) and the vertical direction (Y coordinate), and is set as the coordinates of the center candidate point 114 as indicated by x1, x2, y1, and y2 in FIG. .

  Subsequently, for each coordinate of the center candidate point 114, two diameter candidates are obtained from the interval between the outer periphery candidate points 113. In the case of a circular identification target, the fact that the interval between the outer periphery candidate points is a value close to the diameter is used. For example, as shown in FIG. 14 with respect to the X coordinate x1 of the center candidate point 114, the midpoint position coincides with x1 within an allowable range, and the interval is within a certain range (for example, range A). The frequency distribution of the intervals is obtained for the combination of the front and rear half of the outer periphery candidate points 113 on the detection line 111, the maximum positions up to the second are obtained, and the diameter candidates Rx11, Rx12 with respect to the X coordinate x1 of the center candidate point 114 To do. The frequencies in these diameter candidates are assumed to be Hx11 and Hx12, respectively. Similarly, the diameter candidates Rx21 and Rx22 and the frequencies Hx21 and Hx22 are obtained for the X coordinate x2 of the center candidate point 114, and for the Y coordinates y1 and y2 of the center candidate point 114, the outer peripheral candidate point 113 on the detection line 112 in the Y direction. Are used to find diameter candidates Ry11, Ry12, Ry21, Ry22 and frequencies Hy11, Hy12, Hy21, Hy22. Then, of the four combinations of the X and Y coordinates of the center candidate point 114, the following selection is made to narrow down the center candidate point 114 to two points. The narrowing down is performed by selecting from combinations having a high frequency among combinations in which the difference between the diameter candidate on the X coordinate side and the diameter candidate on the Y coordinate side is equal to or less than a certain value (value B). For example, in the case of the combination of the X coordinate x1 and the Y coordinate y1 of the center candidate point 114, | Rx12-Ry11 | of | Rx11-Ry11 |, | Rx12-Ry11 |, | Rx11-Ry12 | If is less than or equal to the value B, the frequency is Hx12 + Hy11. In particular, when the identification target is a circle, the interval between the outer peripheral points on the straight line passing through the center is constant regardless of the direction of the straight line. Since the interval is a value within a predetermined range, the accuracy of center detection can be improved by determining the difference between the diameter candidates.

  For each of the two center candidate points 114 thus narrowed down, the distance between the center candidate point 114 and each of the outer peripheral candidate points 113 is calculated to obtain a frequency distribution with respect to the distance (ie, representing the radius). However, the midpoint position of the outer half candidate point 113 in the first half and the second half is within the allowable range of the coordinates of the center candidate point 114 (X coordinate on the detection line 111 in the X direction and Y coordinate on the detection line 112 in the Y direction). It is obtained only from the outer peripheral candidate points 113 of the combination that match and the interval is within the range a. Further, as shown in FIG. 15, the frequency distribution is separately obtained for the outer periphery candidate point 113 on the detection line 111 in the X direction and the outer periphery candidate point 113 on the detection line 112 in the Y direction. Tie the one with the lower frequency. By calculating the frequency (the number of pairs of outer peripheral candidate points 113 whose midpoint position and interval satisfy both predetermined conditions) with respect to the distance (radius) and connecting the lower frequency in the X direction and the Y direction, It is possible to avoid misjudgment about the center candidate point 114 having high accuracy but low accuracy in the Y direction. Among the maximums of the frequency distribution, the maximum radius is obtained when the frequency is equal to or greater than a certain value (value c), and is set as a temporary radius. Among the outer peripheral candidate points 113 within a certain allowable range with respect to the provisional radius obtained by the distance to the center candidate point 114, two points that belong to only one point each in the first half and the second half of the same detection line. A set is selected and set as an outer peripheral point 115 indicated by a black dot in FIG. For example, the outer peripheral candidate point 116 is not the outer peripheral point 115 because the distance from the central candidate point 114 is within the allowable range, but there is no outer peripheral candidate point 113 within the allowable range on the same detection line 112. The center candidate point 114 having the largest provisional radius and the number of sets of outer peripheral points selected in this way is greater than or equal to a certain number in both the X and Y directions. The outer periphery candidate point 113 selected for the center candidate point 114 determined as the temporary center is set as the final outer periphery point 115. By detecting and verifying a plurality of candidate points with respect to the center of the identification target, it is possible to prevent erroneous detection due to the internal pattern of the identification target and external noise. Further, by verifying the center candidate point based on the distance from the outer peripheral point and giving priority to the one having a larger distance (radius), an error such as recognizing the pattern inside the identification target as the outer periphery can be avoided.

  Finally, the average X coordinate of the outer peripheral point 115 on the detection line 111 in the X direction and the average Y coordinate of the outer peripheral point 115 on the detection line 112 in the Y direction are obtained and set as the center. Further, the average of the distance between the center and the outer peripheral point 115 is obtained and doubled to obtain the outer diameter. In this embodiment, a plurality of candidate points corresponding to the outer periphery and a plurality of candidate points corresponding to the temporary center are selected, and verification is performed based on the distance between the outer periphery candidate point and the temporary center candidate point, and candidates corresponding to the outer periphery and the temporary center. By determining the point and obtaining the center and radius, the position of the coin 23 can be reliably detected, so that the pattern can be accurately identified. By setting a plurality of detection lines 111 and 112 and performing smoothing and edge detection to select a plurality of outer peripheral candidate points 113 on the detection lines 111 and 112 while correcting so that the outside of the image is given priority. Thus, it is possible to reliably detect the center / outer diameter, which is not easily affected by dirt on the coin 23 / passage 13 or unevenness of the illumination means 15. Similar effects can be obtained by edge enhancement instead of edge detection. In addition, when the identification target is other than a circle, for example, for a rectangular bill, the long side and the short side dimension may be obtained together with the center and the outer periphery. It is also possible to detect the position of the identification target by detecting it as a reference point.

  In addition, although the technique which detects an outer periphery point with a some detection line is disclosed by Unexamined-Japanese-Patent No. 9-17821 or Unexamined-Japanese-Patent No. 10-63852, for example, in this Embodiment, several candidate points of an outer periphery are selected, Since the outer peripheral point is obtained by performing verification based on the distance from the temporary center, the outer diameter point is not erroneously selected even when the bottom surface 22 is reflected or there is noise as shown in FIG. The center and outer diameter can be detected.

  In the denomination temporary determination (S43), it is temporarily determined which denomination is close to the inserted coin 23 from the outer diameter output from the center / outer diameter detection means 85. Two denominations close to the detected outer diameter are selected and output from a predetermined outer diameter reference value for each denomination and the stored imaging magnification. However, if the corresponding denomination is less than or equal to 1 denomination within a predetermined allowable range, that denomination is selected. Based on the outer diameter, the denomination can be easily tentatively determined. By using two denominations instead of narrowing down to one denomination, it is possible to misdetermine the denomination due to the influence of the passing position such as whether the coin 23 passes near or far away from the imaging means 16 in the passage 13. It is possible to improve the identification accuracy. For example, a Japanese one hundred yen coin (22.6 mm) and a ten yen coin (23.5 mm) have an outer diameter of about 4%. Especially when a wide-angle lens is used, the influence of the passing position is large. Since the outer diameter on the image data changes by ± 2% due to a change in the passing position of 5 mm, there is a risk of erroneous determination. Further, if it is tentatively determined to be more than 3 denominations, it takes a lot of time for the subsequent data processing, especially the rotation angle detection (S50) in the pattern matching step (S26) described later, and therefore the data processing time is constant for a maximum of 2 denominations. Although the upper limit time is not exceeded, three or more denominations may be used.

  A technique for determining a denomination as one denomination and performing processing according to the denomination is disclosed in, for example, Japanese Patent Application Laid-Open No. 10-63852. By doing so, it is possible to prevent the wrong determination of the denomination due to the influence of the passing position of the coin 23 or the like.

  In the subsequent concavo-convex calculation (S44), the concavo-convex degree of the coin 23 is detected by the concavo-convex detection means 83 from the first and second image data input in the concavo-convex input step (S23). For each unevenness detection line 108 to 110, the absolute value of the difference between the first image data and the second image data for each pixel is added over all the pixels on the unevenness detection line. By using the sum of absolute values of differences for each pixel, the comparison in the comparison unit 96 is simplified. The second illumination means 36 and the third illumination means 37 are configured as described with reference to FIG. 3 so that the first image data and the second image data are uniform. However, in the first image data and the second image data, it is difficult to completely suppress the difference in brightness between the inlet 12 side and the outlet 18 side, and the brightness of each pixel depends on the position of the pixel (the inlet 12 And the correlation is reversed between the first image and the second image. Therefore, before obtaining the pixel-by-pixel difference between the first image data and the second image data, each of the first image data and the second image data is corrected according to the position of the pixel. The difference in brightness between the 12 side and the outlet 18 side is further suppressed. For example, each image data can be homogenized by subtracting a value proportional to the distance from the insertion port 12 in the first image data and adding in the second image data. Further, by performing the correction so that the average values of the first image data and the second image data match each other, the accuracy of the difference obtained thereafter is further improved. By these corrections, errors in the first image data and the second image data are reduced, and the unevenness degree of the coin 23 is more accurately represented. After these corrections, the difference is obtained. When calculating the difference for each pixel, in order to cancel the influence of the movement of the coin 23 described above, the pixel of the first image data to be input first is one pixel behind the second image data (exit 18 side). ) To obtain the difference from the pixel data. The difference thus obtained is large for coins 23 with unevenness and small for copy-pasted fake coins without unevenness, but noise or the like occurs in some pixels, and an excessive difference occurs in these pixels. In such a case, even a copy-pasted fake coin has a large value. In order to prevent this and reduce the influence of noise, the difference per pixel is limited by providing an upper limit. In this way, the calculation is performed for the three unevenness detection lines 108 to 110, and the maximum value of the three is output. By setting a plurality of concavo-convex detection lines 108 to 110, the degree of concavo-convex can be reliably detected even with the coin 23 having a small concavo-convex pattern that is not easily affected by the dirt of the coin 23 and the passage 13.

  Further, a pattern matching step (S26) is performed. In the pattern matching step (S26), edge detection (S45) of multi-valued digital image data is performed, and then coordinate conversion from orthogonal coordinates to polar coordinates (S47) is performed while correcting imaging magnification (S46), and binarization is performed. After (S49), the rotation angle of the image data of the inserted coin 23 with respect to the reference image is detected (S50), and collation with the reference image is performed in consideration of the detected rotation angle (S51). These steps are performed on the two front and back surfaces of the two denominations that were provisionally determined in the denomination denomination (S43). If they are different, processing for a total of 16 planes may be performed.

  Each operation | movement of a pattern collation process (S26) is demonstrated in detail from edge detection (S45). In the edge detection means 84, edge detection that also serves as smoothing is performed on each pixel data of the third image data in the same manner as the center / outer diameter detection (S42), and the image data after edge detection is used as the fourth image data. Output as data. Specifically, for 9 pixel data including 8 pixels around the pixel of interest, the array data in (Table 1) and the absolute value of the sum of 9 elements integrated for each array element, and the array data in (Table 2) The sum with the absolute value of the sum of the nine elements integrated for each array element is obtained and used as data after edge detection of the pixel of interest. Note that it is sufficient that the edge detection (S45) is performed on pixels located within the outer diameter range of the maximum outer diameter coin to be identified with reference to the center detected by the center / outer diameter detection (S42). By performing edge detection (S45) on the image data, it is possible to determine not only the brightness (brightness) of the reflected light but also the brightness difference with the adjacent portion, so that the overall brightness of the image data is determined. It is difficult to be affected by various changes and local unevenness, and accurate identification becomes possible. Similar effects can be obtained by performing edge enhancement instead of edge detection. Here, the overall change in brightness of the image data and local unevenness are caused by the material and color of the coin 23, the entire passage 13 or the local contamination of the coin 23, and the like. These effects can be reduced.

  Next, coordinate conversion (S47) will be described before magnification correction (S46). The coordinate conversion means 88 converts the fourth image data from orthogonal coordinates to polar coordinates, and outputs the image data after the coordinate conversion as fifth image data. In the present embodiment, an optical design is performed in which a Japanese coin is an identification target, and a 500-yen coin having a maximum outer diameter becomes N × N pixels (for example, 100 × 100 pixels). In addition, the imaging magnification is assumed to be 0.9 to 1.1 depending on the passing position of coins, assembly dimensions, and variations in the component characteristics such as the lens 28. That is, a 500-yen coin may be imaged from a minimum of 0.9 N × 0.9 N to a maximum of 1.1 N × 1.1 N pixels (for example, 90 × 90 to 110 × 110 pixels) for each product or coin insertion. However, for simplification, the coordinate conversion (S47) and the magnification correction (S46) will be described with a maximum of 7 × 7 pixels. FIG. 16A schematically shows the fourth image data. The X coordinate 122 (direction parallel to the passing direction of the coin 23) and the Y coordinate of the center 121 detected by the center / outer diameter detection (S42). 123 (direction perpendicular to the passing direction of the coin 23) is (0, 0), and 49 pixels from orthogonal coordinates (-3, -3) to (3, 3) are shown. FIG. 16B schematically shows the fifth image data after the coordinate conversion. The fifth image data is divided into four at non-uniform intervals in the radial direction of the polar coordinates (R coordinate 124), and the circumferential direction (S The polar coordinates (0, 0) to (3, 7) are illustrated by dividing the coordinate 125) into 8 at equal intervals to 0-7. This coordinate conversion is performed using the conversion tables shown in (Table 3) and (Table 4).

  (Table 3) represents the S coordinate of the polar coordinate corresponding to the X coordinate and the Y coordinate of the orthogonal coordinate, and (Table 4) represents the R coordinate of the polar coordinate corresponding to the X coordinate of the orthogonal coordinate and the Y coordinate. For example, a pixel at orthogonal coordinates (0, 0) is converted to polar coordinates (0, 0), and a pixel at orthogonal coordinates (-1, -3) is converted to polar coordinates (3, 7). In this way, all the pixels of the orthogonal coordinates are converted, and when a plurality of orthogonal coordinates correspond to the same polar coordinates, the average value of these pixels is used, and the polar coordinates having no corresponding orthogonal coordinates are adjacent polar coordinate data. Set based on adjacent data, such as copying. By converting the coordinates to polar coordinates, the rotation angle detection (S50) and collation (S51) described later can be facilitated, the data amount can be reduced, and the processing speed can be increased. In the radial table for polar coordinate conversion (Table 4), there is a coordinate where the R coordinate of the radial coordinate is 4 which is larger than the maximum value of 3, but this is outside the outer diameter range of the coin 23 and will be used thereafter. It is necessary to perform conversion while determining whether the R coordinate is 3 or less at the time of coordinate conversion by preparing up to 4 R coordinates in the array for storing the image data after coordinate conversion, indicating that the pixel is not to be converted Therefore, all pixels can be handled in common and converted at high speed. Further, by performing coordinate conversion (S47) after the edge detection (S45), the edge can be detected faithfully to the pattern of the coin 23 and the identification accuracy can be improved. This is because if the edge detection (S45) is performed after the coordinate conversion (S47) because the distance to the adjacent surrounding pixels (coordinates) is changed by the polar coordinate conversion, the surrounding neighboring used for edge detection or enhancement of the target pixel. This is because the distance to the pixel differs depending on the coordinates of the pixel of interest and the coordinates of adjacent pixels, and is not constant.

  The magnification correction (S46) corrects the imaging magnification caused by the passage position of the coin 23 in the passage 13, the assembly error of the imaging means 16, and the like. This correction is based on the values in the radial direction table (Table 4) for polar coordinate conversion based on the outer diameter detected in the center / outer diameter detection (S42) and the money type temporarily determined in the money type temporary determination (S43). Do by updating. The radial direction table is obtained from a distance table indicating the distance between each pixel and the center as shown in (Table 5) and an upper limit distance table indicating the upper limit of the distance for each radial coordinate as shown in (Table 6).

  For example, if the X coordinate is x, the Y coordinate is y, and the distance table value is represented by R ′ (x, y), R ′ (0, 0) is 0.00 and less than 1.75. R (0,0) is set to 0, and R ′ (3,1) is 3.16, which is 3.03 or more and less than 3.50, so R (3,1) is set to 3. Note that the distance table of the portion of X coordinate <0 and Y coordinate <0 is omitted by using objectivity to reduce data storage capacity and processing time, and when x <0 and y ≧ 0, R (x, y) = R (−x, y), when x ≧ 0 and y <0, R (x, y) = R (x, −y), when x <0 and y <0, R (x, y) The radial coordinate R is obtained by the following equation: y) = R (−x, −y).

  In the magnification correction (S46), for example, one of the denominations temporarily determined in the denomination temporary determination (S43) is 500 yen, and the outer diameter (eg, 90) detected in the center / outer diameter detection (S42) is 500 yen. Since the imaging magnification is 0.9 times when the standard outer diameter (for example, 100) is 0.9 times, the upper limit distance value in the upper limit distance table is 0.9 times the standard as shown in (Table 7). Update to the value of.

  Then, when the value of the radial direction table for polar coordinate conversion is updated from this upper limit distance table and the distance table (Table 5), it becomes (Table 8).

  By performing coordinate conversion based on this conversion table, coordinate conversion can be realized simultaneously while enlarging the image data by 1.11 times in the radial direction, and the imaging magnification is easily corrected. By performing the magnification correction, accurate identification can be performed without being affected by variations in the passing position of the coin 23, assembly dimensions, and component characteristics. In addition, it is possible to suppress the variation in the identification performance for each product by storing the reference image in common without storing different reference images for each product, and to increase the allowable range of assembly and component characteristics.

  In the present embodiment, the value of the upper limit distance in the upper limit distance table is set to an unequal interval, with the interval being wider as the radius is smaller and the interval being larger as the radius is larger. As shown in (Table 9), they may be set at equal intervals.

  However, there is a large difference in the area of each polar coordinate, and the number of orthogonal coordinate pixels that are converted to the same polar coordinate at the time of coordinate conversion becomes non-uniform, resulting in a bias in the weight of each polar coordinate at the time of collation. In particular, if the upper limit distance is set so that each polar coordinate has the same area, the weight of each polar coordinate becomes equal, and the identification performance can be improved by setting the radial direction coordinate at unequal intervals.

  Japanese Patent Laid-Open No. 9-245213 discloses a technique for acquiring an image of a reference object, obtaining a magnification error, correcting the image, and cutting out the image. However, the reference object is a fixed denomination. There is no problem when only the denomination is input in the adjustment mode, but application is difficult when a plurality of denominations are input. On the other hand, this embodiment can be applied to a case where a plurality of denominations are input by provisionally determining a plurality of denominations.

  Subsequently, threshold setting (S48) for binarization (S49) is performed. The binarizing means 90 converts each pixel (coordinate) of the fifth image data after coordinate conversion, which is a multi-valued digital value, into a binary digital value of 1 or 0 depending on whether or not it is greater than or equal to a threshold value. The binarized image data is output as sixth image data. By performing binarization (S49), the influence of noise in the image data can be reduced, and the amount of image data can be reduced to speed up the processing. In addition, by performing edge detection (S45) or edge enhancement and coordinate transformation (S47) before binarization (S49), accurate edge detection or enhancement and coordinate transformation using multi-valued data can be performed and identified. Accuracy can be improved.

  The threshold setting unit 89 sets a threshold for binarization (S49), and outputs a threshold set based on the fifth image data and the denomination temporarily determined by the denomination temporary determination unit 86. . Specifically, in the sixth image data after binarization, the ratio of the number of pixels having a value of 1 to the total number of pixels is a ratio determined for each denomination and surface (front surface or back surface). In other words, the threshold is set so that the frequency distribution after binarization becomes constant. As a result, the image quality of the sixth image data after binarization is made uniform, and a reference image used for pattern matching (S51), which will be described later, is also created at a similar ratio, whereby the sixth image and the reference image are generated. Homogenization is possible and identification performance can be improved. In this embodiment, this ratio is set to 50% for all denominations and faces. However, it is possible to optimize the binarization according to each denomination and face pattern by changing it for each denomination and face. Based on the experiment, the pattern was clearly readable at a rate of 30 to 70%, and high discrimination performance was achieved. For example, a threshold value may be obtained by creating a frequency distribution (histogram) of data values and the number of pixels from the fifth image data and obtaining a value at which the cumulative frequency from the larger data is 50%. In addition, the fifth image data used for setting the threshold value should naturally be limited to the inside of the coin portion, that is, the outer diameter, and the radius of the denomination whose radial coordinate is predetermined by performing magnification correction and polar coordinate conversion. This is easily possible if only the following parts are used. Further, in the present embodiment, the outer periphery / hole edge that differs for each coin 23 depending on the state of the coin 23 and the issue year, the inside of the hole that is the background instead of the coin 23, and the same coin 23 depending on the rotation angle and position. Also, different latent image / thin line patterns are excluded from use for threshold setting. FIG. 17 is a schematic diagram in which a reference image (to be described later) of a new 500-yen coin is overwritten with an excluded portion in gray and inversely converted into orthogonal coordinates. The outer peripheral edge 131, the latent image pattern portion 132, and the fine line pattern portion 133 Indicates. Wear and burrs are likely to occur on the outer periphery and edge of the hole, the background can be seen inside the hole, and the latent image and fine line pattern part have moire depending on the angle between the pixel arrangement direction of the image sensor 26 and the coin pattern. Appearance changes remarkably, and when used for threshold setting, it is affected by these partial images and hinders accurate binarization of the whole. For the same reason, the year part which is different for each coin may be excluded. Which part of the fifth image data is used for threshold setting can be determined by storing a binary digital value table in polar coordinate format for each denomination / surface in advance. Stable binarization suitable for the pattern can be performed. Further, when the portion used for setting the threshold value is not rotationally symmetric with respect to the center of the coin, the threshold value changes for each rotation angle of the coin. Therefore, the threshold value is set each time image data is rotated in the rotation angle detection (S50) described later. It requires a great deal of processing. In the present embodiment, the portion used for threshold setting is set so as not to include the excluded portion and to be rotationally symmetrical, that is, concentric with respect to the center of the coin. Therefore, every time image data is rotated in the rotation angle detection (S50). There is no need to re-determine the threshold value, and the table for storing the portion used for setting the threshold value may be one-dimensional data (hereinafter referred to as threshold setting area data) for the coordinates in the radial direction. In this way, the threshold value is set so that the ratio of the number of pixels having a value of 1 to the total number of pixels in the sixth image data becomes a predetermined ratio, that is, the frequency distribution after binarization is constant. By doing so, stable identification is possible without being influenced by the material of the coin 23, the state of the edge or surface, the rotation angle, and the difference in illuminance due to variations in the illumination means 15 and assembly dimensions.

  In addition, although the technique which sets the threshold value of binarization in a specific threshold value calculation area is disclosed by Unexamined-Japanese-Patent No. 2002-109596, for example, the specific part in the coin (state of the coin 23 which interferes with binarization) In addition, there is no mention of a technique for removing outer peripheries and hole edges that differ for each coin 23 depending on the issue year, and a latent image or thin line pattern that differs for each coin 23 depending on the rotation angle or position. In the present embodiment, stable threshold setting and binarization can be performed by setting threshold values in regions other than these regions.

  In the rotation angle detection (S50), based on the sixth image data by the rotation angle detection means 91 and the reference image stored for each denomination / surface in the storage means 92, the coins 23 inserted into the reference image, that is, the first The rotation angle of the image data 6 is detected and output. Conversely, the rotation angle of the reference image with respect to the sixth image data may be detected. The reference image data is stored in advance as a binary digital value table in the polar coordinate format, like the sixth image data. The sixth image data is compared with the reference image data while rotating, and the most coincident angle is detected. Since the sixth image data is expressed in polar coordinates, in order to rotate it, it can be easily rotated by shifting in the circumferential direction, that is, by changing the circumferential coordinate. The sixth image data is B (r, s) (r is the radial direction of polar coordinates, s is the circumferential direction), the reference image data is R (r, s), and the remainder obtained by dividing a by b is mod (a, b) When the number of divisions in the circumferential direction in polar coordinates is represented by Ns, B (r, mod (s + Δs, Ns)) and R (r, s) are compared by changing Δs by 2 from 0 to Ns−1. I will do it. The degree of matching is determined by the number of pixels (coordinates) at which the values of the sixth image data and the reference image data match. Since the sixth image data and the reference image data are both binary digital values, they can be easily determined by taking the exclusive OR of these values and the number of pixels having a result of zero. The reason why Δs is changed by two is to shorten the detection time, and Δs having the highest degree of coincidence is obtained by changing by two. Then, the rotation angle adjacent to Δs, that is, the degree of coincidence between mod (Δs−1, Ns) and mod (Δs + 1, Ns) is also obtained, and the rotation angle with the highest degree of coincidence is selected from the three rotation angles. Thus, the rotation angle can be detected with high accuracy even if the rotation angle is thinned out. Not only the method of changing by two, but the accuracy is maintained by calculating the degree of coincidence by thinning the rotation angle, such as increasing the amount of change if the degree of coincidence is low and decreasing the amount of change if the degree of coincidence is high. The speed of rotation angle detection can be increased. Further, in the present embodiment, the degree of coincidence is calculated for the same reason as when the threshold value is set for the outer periphery / edge of the coin, the inside of the hole, and the latent image / thin line pattern portion excluded from use in the threshold setting (S48) ( This is also excluded in the rotation angle detection and verification). Specifically, data indicating pixels (regions) used for rotation angle detection (S50) and collation (S51) (hereinafter referred to as collation region data) is expressed in a polar coordinate format similar to the reference image data and the sixth image data. The binary digital values are stored in advance as a table. Then, an exclusive logical sum of the sixth image data and the reference image data and a logical product of the collation area data are calculated, and it can be determined that the degree of matching is higher as the number of mismatched pixels whose result is 1 is smaller. In order to represent the degree of coincidence, not relative, in this embodiment, the number of pixels whose value in the collation area data is 1 is used as the collation pixel number, and the number of mismatch pixels is subtracted from the collation pixel number. Is divided by the number of matching pixels to obtain the degree of matching. Thereby, even if the number of matching pixels is different, the degree of matching can be easily compared.

  In the pattern matching (S51), the sixth image data and the reference data at the rotation angle detected by the rotation angle detecting means 91 are checked. First, the sixth image data is shifted in the circumferential direction by the rotation angle detected by the rotation angle detecting means 91, that is, the rotation angle is corrected by changing the circumferential coordinate to obtain seventh image data. Then, an exclusive OR of the seventh image data and the reference image data is obtained, and a logical product with the collation area data used in the rotation angle collation is obtained as collation result data. The value of the pixel (coordinate) where the seventh image data and the reference image data do not match has an exclusive logical sum of 1, and if it is within the collation area, the logical product with the collation area data is 1, so the result is 1 The number of pixels represents the number of mismatched pixels. In addition, since the number of pixels having a value of 1 in the matching area data represents the number of matching pixels, the quotient obtained by dividing the difference between the number of matching pixels and the number of mismatched pixels by the number of matching pixels is the seventh image data and the reference image. Indicates the degree of match.

  In this embodiment, instead of obtaining the degree of coincidence of the entire coin, the coin area is divided into a plurality of areas, and the number of areas in which the degree of coincidence for each area is equal to or greater than a certain value, that is, the number of coincidence areas is obtained. . By comparing the degree of coincidence with a constant value, the number of coincidence areas can be easily obtained. Specifically, referring to FIG. 18, the example in which the number of pixels in the radial direction is 32 and the number of pixels in the circumferential direction is 16 will be described. This is a schematic diagram showing the region division in FIG. 18B for the image data shown in FIG. As shown in the figure, the radial direction 141 in polar coordinates is divided by a divisor of the number of pixels in the radial direction (the division number in this example is 8), and the circumferential direction 142 is similarly divided by a divisor of the number of pixels in the circumferential direction (this The number of divisions in the example is 4), and a plurality of (in this example, 32) regions 143 are obtained. By being based on polar coordinates, it is possible to easily divide the region, and if it is divided at equal intervals, the weight of each region 143 becomes equal. Then, for each region, the degree of matching is obtained with the pixels belonging to that region. Further, the pattern matching means 93 outputs this value as the matching area ratio, which is the ratio between the number of areas whose degree of matching for each area is equal to or greater than a predetermined lower limit value and the total number of areas. Note that it is difficult to accurately determine the degree of coincidence in the region 143 in which the amount of information used for calculating the degree of coincidence of each region is insufficient (the collation region is narrow, that is, the number of collation pixels is small). The region 143 in which the number of matching pixels is less than a certain value is excluded, and the matching region is accurately determined. In this way, instead of obtaining the degree of coincidence of the pattern of the entire coin, the coin area is divided into a plurality of areas 143 and collation is performed based on the degree of coincidence of each area. Even if it exists locally, it is not easily affected and accurate identification is possible. In addition, by simply changing the lower limit value of the degree of coincidence for each area determined to be a coincidence area and the allowable range of the coincidence area ratio in the comparison unit 97, it is possible to easily change the priority level of resistance to dirt and the anti-fouling performance. . For example, in order to be able to discriminate even if a 1/3 portion of a coin cannot be accurately read due to dirt or the like, the allowable range of the matching area ratio may be set to 2/3 or more.

  Furthermore, the number of coincidence areas is the number of areas where the degree of coincidence for each area is equal to or greater than a predetermined lower limit value. 23 and the influence of dirt on the passage 13 can be reduced and accurate identification can be performed. This is because if the coins 23 and the passage 13 are dirty, the degree of coincidence decreases, the number of coincidence areas decreases, and the possibility that the coins are not determined as genuine coins increases. This is because the matching degree of the entire collation region is almost uniformly reduced at any rotation angle in the rotation angle detection. On the other hand, for example, the matching degree at the rotation angle at which the matching degree of the entire collation region is the minimum. By using the difference between the maximum matching degree and the minimum matching degree, or by adding a certain value to the minimum matching degree, the improvement can be made. In this example, when the contamination is so severe that accurate identification is difficult, the maximum matching degree becomes a very low value and there is a risk of erroneous identification. However, if the absolute value of the maximum degree of matching is low, a lower limit value is determined not to be determined as a genuine coin, or the lower limit value calculated by adding a certain value to the minimum degree of matching is less than a predetermined constant value. For example, by setting the lower limit value to this constant value, it is possible to avoid erroneous identification.

  The pattern matching (S51) is first performed on the surface of the first denomination that is temporarily determined to be approximate in the denomination temporary determination (S43) based on the reference data and the matching area data. Next, since the threshold setting area data is different for each surface, the threshold setting (S48) to the pattern matching (S51) are repeated in the same manner for the back surface. Furthermore, since the magnification correction differs for each denomination, the second denomination that has been provisionally determined that the magnification correction (S46) to the end of two surfaces (S52) are approximated by the denomination temporary determination (S43). Do. Therefore, the pattern matching means 93 outputs the matching area ratio of 2 denominations × 2 planes.

  In the comparison (S61), the outputs of the thickness detection means 74, material detection means 78, unevenness detection means 83, and pattern matching means 93 input to each of the comparison means 94 to 97 are compared with the reference stored in the storage means 92. A comparison is made. If the values match within the allowable range, a signal indicating the type of the genuine coin is output, and if the reference value does not match any type, a signal indicating that it is a false coin is output. The determination (S62) outputs a signal indicating the type of the true coin only when the signals from the comparison means 94 to 97 input to the determination unit 99 all indicate the same type of the correct coin, and in other cases Outputs a signal indicating a false coin as the determination signal 100.

  A comparison (S71) between the case where the thickness sensor detects the insertion (YES in S16) and the case where the material sensor detects the insertion (YES in S17), that is, the case where dew condensation is being detected (S71) The outputs of the thickness detecting means 74 and the material detecting means 78 input to each of the comparing means 94 and 95, excluding the comparing means 96 and 97 to which the pattern matching means 93 is connected, are used as the reference stored in the storage means 92. A comparison is made. If the values match within the allowable range, a signal indicating the type of the genuine coin is output, and if the reference value does not match any type, a signal indicating that it is a false coin is output. Similarly in the determination (S72), the comparison means 96 and 97 related to the image pickup means 16 are excluded, and only when the signals from the comparison means 94 and 95 inputted to the determination means 99 all indicate the same genuine coin type. A signal indicating the type of coin is output, and a signal indicating a false coin is output as the determination signal 100 in other cases.

  In order to determine which of the determinations S62 and S72 is to be performed by the determination unit 99, the output of the dew condensation detection unit 82 is connected to the determination unit 99. The output of the switching means 98 such as a switch is also input to the determination means 99, and the identification items (thickness and material) excluding the identification items (unevenness and pattern) related to the imaging means 16 for the determination during the dew condensation detection. To avoid accepting sales opportunities as a vending machine, etc. during dew condensation, or forcing the inserted coins during dew condensation because it is difficult to identify with the imaging means 16 Although not shown in FIG. 9, it is possible to select whether to give priority to the counterfeit coin rejection performance without accepting it by the switching means 98. Thus, by providing the switching means 98, it is possible to select whether to give priority to accepting coins or give priority to fake coin elimination performance, and to easily change the selection even at the installation site of a vending machine or the like. In addition, although not shown, a dew condensation prevention unit using a heat generation unit is provided, and by operating this dew condensation prevention unit when dew condensation is detected, it is possible to always perform identification related to the imaging unit 16 while saving power consumption. . As the heat generating means, an electronic component having a large heat generation amount can be used in the vicinity of the passage 13 without using a dedicated component, or an inexpensive heater can be used.

  In the determination (S62), although not shown in FIG. 9, the identification items not related to the imaging means 16 (thickness and material in the present embodiment) are the same type of true coins, and the identification items related to the imaging means 16 ( In the case of unevenness and pattern), if it continues to be a fake coin or a different kind of genuine coin, it is determined that the image quality has deteriorated due to dirt on the passage 13 or the like. If all the identification items continue to be the same type of genuine coins, it is possible to detect the degree of deterioration in image quality by determining that there is no problem in image quality. When a drop in image quality is detected, it is possible to communicate with the control unit of the vending machine and display it to the operator of the vending machine to inform the user that the image quality has deteriorated and to encourage cleaning. It is.

  In addition to the switching means 98, it is possible to select whether or not to perform identification (hereinafter referred to as image identification) itself by the imaging means 16 by a second switching means (not shown). By providing the second switching means, it is possible to select a method in which image identification is not performed when the imaging means 16 or the optical transparent body 14 has a failure, a serious scratch or dirt, and the dew condensation detection (S14) and the imaging means. By not performing the input detection (S15) and the unevenness and pattern detection (S21) in FIG. 16 (not shown in FIG. 9), it is possible to prevent the product from being stopped due to a malfunction or the identification performance from being deteriorated.

  Note that the coin-insertion detection method, the passage configuration described with reference to FIGS. 2 and 4, and the dew condensation detection, dew condensation prevention, and image quality detection can be applied to a pattern identification device having a conventional configuration. Reliable input detection, reliable identification that is not easily affected by dirt, and accurate identification with reduced effects of condensation, dirt, and the like are possible.

  As described above, according to the present embodiment, it is possible to prevent occurrence of unevenness in an image by performing identification at a non-incident portion of the regular reflection light 29 from the coin 23. Further, by providing the imaging unit 16 vertically above the passage 13, adhesion of dirt to the imaging unit 16 can be reduced. Since the imaging unit 16 includes the image sensor 26 that can output a partial image, the image data of the specific area 66 can be read out in a short time. The imaging means 16 includes an array of light receiving elements arranged in a matrix, a control circuit 68 for supplying a voltage for sensitivity control to the rows of the array, and a neural network for processing a current flowing from a column of the array to the ground. 69, the product-sum operation of the filter matrix and the image can be executed in the image sensor 26. By providing the condensation detection means 82 for detecting whether or not the passage 13 in the vicinity of the imaging means 16 is condensed, it is possible to detect whether or not the passage 13 is condensed. Then, by omitting the control process of the image pickup means 16, it is possible to prevent malfunction due to abnormal image data, to operate the condensation prevention means, or to notify the occurrence of condensation. By detecting that the coin 23 has been inserted using the image pickup means 16, it is possible to reliably detect that the coin 23 has been inserted. Image data with a constant image quality can be obtained by adjusting the reading conditions based on the image read in advance by the imaging means 16. A second illumination unit 36 and a third illumination unit 37 that irradiate light to the coin 23 from different directions having substantially the same wavelength characteristics, and reflection from the coin 23 when irradiated by the second illumination unit 36. By identifying the coin 23 based on the difference between the light and the reflected light from the coin 23 when irradiated by the third illumination means 37, the unevenness of the coin 23 can be detected. The position of the coin 23 can be reliably detected by verifying and detecting a point serving as a reference for the position of the coin 23 in the third image, that is, the center by verifying the plurality of outer peripheral candidate points 116. By tentatively determining and identifying one or more denominations, it is possible to prevent misdetermination of denominations due to the influence of the passing position of the coin 23. By providing the image pickup means 16 on the vertically upper side of the passage 13, the adhesion of dirt to the image pickup means 16 and the like can be reduced. The edge can be detected faithfully to the pattern of the coin 23 by performing coordinate conversion and identifying after the edge detection enhancement of the third image. By setting a threshold value based on an image excluding a specific portion of the coin 23 and performing binarization with this threshold value, stable binarization can be performed. By performing collation with the reference image based on an image excluding a specific portion of the coin 23, stable collation can be performed. By detecting the rotation angle by thinning out the rotation angle, the rotation angle can be detected at high speed while maintaining accuracy. Since the image of the coin 23 is divided into a plurality of regions 143 and identification is performed based on the degree of coincidence of each region with the reference image, the influence of dirt on the coins 23 and the passage 13 is reduced.

  Therefore, since the pattern of the coin can be accurately identified, it is possible to realize a pattern identification device with high identification performance that can prevent the illegal use of the false coin.

  As described above, according to the present invention, the illumination means for irradiating the identification target passing through the passage, the imaging means for receiving the reflected or transmitted light from the identification target, and the storage means for storing the reference image are provided. In the pattern identification device for identifying the pattern to be identified based on the image acquired by the imaging unit and the reference image, a plurality of candidate points are verified as points that serve as a reference for the position of the identification target in the image. Since the pattern identifying device is to be detected, the pattern can be accurately identified, and the identification performance can be improved.

The front view which showed the outline | summary of the coin identification device in one embodiment of this invention Sectional view of the vicinity of the imaging means Same as above, front view of illumination means Cross section of the passage Sectional view of the vicinity of the sensor for both thickness and material Same configuration diagram of control circuit of image sensor Same configuration diagram of control circuit of image sensor The same block diagram showing the configuration of the control circuit Same as above, flowchart explaining operation Same as above, flowchart for explaining the operation of irregularities and patterns Same as above, conceptual diagram of imaging area of imaging means (A) The cross-sectional view of the vicinity of the coin when illuminated with only the second illumination means, (b) The schematic diagram of the image data when illuminated with only the second illumination means, (c) Sectional drawing of the coin vicinity at the time of illuminating only with 3 illumination means, (d) The schematic diagram of the image data at the time of illuminating only with the 3rd illumination means Schematic diagram of third image data explaining center / outer diameter detection Same frequency distribution diagram explaining diameter detection for center / outer diameter detection (A) Frequency distribution diagram explaining radius detection in X direction for center / outer diameter detection, (b) Frequency distribution diagram explaining radius detection in Y direction for center / outer diameter detection, (c) , Frequency distribution diagram explaining radius detection for center and outer diameter (A) Schematic diagram of fourth image data explaining coordinate transformation and magnification correction, (b) Schematic diagram of fifth image data explaining coordinate transformation and magnification correction. Schematic of reverse conversion of reference image of new 500-yen coin to Cartesian coordinates, explaining threshold setting (A) Schematic diagram of sixth image data explaining pattern matching, (b) Schematic diagram of sixth image data explaining area division of pattern matching.

Explanation of symbols

DESCRIPTION OF SYMBOLS 11 Coin identification apparatus main body 12 Insertion slot 13 Passage 14 Optical transparent body 15 Illumination means (1st illumination means)
16 Imaging means 17 Thickness / material combined use sensor 18 Exit 21 Side wall 22 Bottom surface 23 Coin 24 Side wall 25 LED
26 Image sensor 27 Light receiving surface 28 Lens 29 Regular reflection light 31 Coin position 32 Coin position 33 Coin position during imaging 34 Regular reflection position 35 Straight line 36 Second illumination means 37 Third illumination means 41 Discharge auxiliary means 51 Core 52 Core 53 Coil 54 Coil 55 Coil 56 Coil 61 Pixel 62 Horizontal scanning circuit 63 Vertical scanning circuit 64 Horizontal scanning line 65 Vertical scanning line 66 Specific area 67 Output 68 Control circuit 69 Neural network 70 CDS means 71 Thickness sensor 72 Oscillation circuit 73 Rectification circuit 74 Thickness Detection means 75 Material sensor 76 Oscillation circuit 77 Rectifier circuit 78 Material detection means 79 Input detection means 80 A / D conversion means 81 Adjustment means 82 Condensation detection means 83 Concavity and convexity detection means 84 Edge detection means 85 Center / outer diameter detection means 86 Denomination Temporary judgment means 87 Means 88 Coordinate conversion means 89 Threshold setting means 90 Binarization means 91 Rotation angle detection means 92 Storage means 93 Pattern matching means 94 Comparison means 95 Comparison means 96 Comparison means 97 Comparison means 98 Switching means 99 Determination means 100 Determination signal 101 Imaging range DESCRIPTION OF SYMBOLS 102 1st insertion detection area 103 2nd insertion detection area 104 3rd insertion detection area 105 Coin position 106 Input condition setting area 107 Coin position 108 Concavity and convexity detection line 109 Concavity and convexity detection line 110 Concavity and convexity detection line 111 Detection line 112 Detection line 113 Peripheral Candidate Point 114 Center Candidate Point 115 Peripheral Point 116 Peripheral Candidate Point 121 Center 122 X Coordinate 123 Y Coordinate 124 R Coordinate 125 S Coordinate 131 Peripheral Edge 132 Latent Image Pattern 133 Thin Line Pattern 141 Radial Direction 142 Circumferential Direction 143 Pass

Claims (18)

Acquired by the imaging means, comprising a passage, an illuminating means for irradiating light to the identification target passing through the passage, an imaging means for receiving reflected or transmitted light from the identification target, and a storage means for storing a reference image A pattern identification apparatus for identifying a pattern to be identified on the basis of an obtained image and the reference image, wherein a point serving as a reference for the position of the identification target in the image is verified by detecting a plurality of candidate points. The pattern identification apparatus according to claim 1, wherein the reference point is the center of the identification target. The pattern identification apparatus according to claim 2, wherein the candidate point is an outer periphery of the identification target, and a center is obtained from a midpoint position between these outer periphery candidate points. The pattern identification device according to claim 3, wherein outer periphery candidate points are detected on a plurality of straight lines in different directions. The pattern identification device according to claim 4, wherein the outer periphery candidate points are detected on a straight line including straight lines whose directions are orthogonal to each other. The pattern identification apparatus according to claim 4, wherein the outer periphery candidate points are detected on a straight line including a straight line parallel to the coordinates of the image acquired by the imaging means. The pattern identification device according to claim 3, wherein a distance between the outer periphery candidate points is determined to obtain a center position between the outer periphery candidate points. The pattern identification apparatus according to claim 7, wherein outer periphery candidate points are detected on a plurality of straight lines in different directions, and a difference in interval between the outer periphery candidate points in each of these directions is determined. The pattern identification apparatus according to claim 3, wherein the verification is performed with the number of sets of outer peripheral candidate points whose midpoint positions and intervals satisfy a predetermined condition. The pattern identification device according to claim 2, wherein the center of the identification target is verified based on a distance from the outer periphery candidate point. The pattern identification apparatus according to claim 10, wherein priority is given to a larger distance from the outer periphery candidate point. The pattern identification apparatus according to claim 2, wherein a plurality of candidate points with respect to the center of the identification target are detected and the candidate points are verified. The pattern identification apparatus according to claim 1, wherein the candidate point is an outer periphery of the identification target. The pattern identification device according to claim 13, wherein an edge is detected in the direction of a straight line, and an outer periphery candidate point is detected on the straight line. The pattern identification device according to claim 13, wherein priority is given to a larger distance from the center of the straight line, and outer periphery candidate points are detected on the straight line. The pattern identification apparatus according to claim 15, wherein a product of a distance from the center of a straight line is obtained and an outer periphery candidate point is detected on the straight line. The pattern identification device according to claim 13, wherein the outer peripheral candidate points are verified at a distance from the center of the identification target. The pattern identification apparatus according to claim 1, wherein a candidate point is detected by obtaining a local maximum point.

Images