JP2003162711A - Image reading device and method and fingerprint collating device and method - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To much more precisely match fingerprints with each other. <P>SOLUTION: When image data 2 are outputted, a capture control part 3a calculates a gradation index Y indicating the gradation of a captured image as the image quality evaluation of the image data 2, and compares the calculated gradation index Y with preliminarily set thresholds Y<SB>th1</SB>and Y<SB>th2</SB>, and changes a parameter set by a parameter setting part 1a in order to make the gradation index Y fall within the range of a threshold. <P>COPYRIGHT: (C)2003,JPO

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an image capturing device and an image capturing method for capturing the shape of a target object as image data, and a fingerprint for utilizing these to detect unevenness due to a fingerprint as image data and perform collation. The present invention relates to a matching device and a fingerprint matching method.

[0002]

2. Description of the Related Art When fingerprint collation is performed, in order to improve the collation accuracy, it is necessary to capture a fingerprint image so that the unevenness of the fingerprint becomes clear. As a fingerprint sensor used for capturing a fingerprint image in this type of fingerprint collation device, there are an optical fingerprint sensor, a capacitive fingerprint sensor, and the like. The fingerprint sensor detects unevenness of a fingerprint as a difference in optical refractive index or a difference in capacitance value and generates a grayscale image.

In the above fingerprint collation device, when a user is authenticated using a fingerprint, first, the fingerprint data of the user is registered in advance. In this state, the image of the user's fingerprint is acquired by the fingerprint sensor, fingerprint data is generated, the generated fingerprint data is compared with the registered fingerprint data, and if both match, it is confirmed that the user is the user himself. recognize.

[0004]

By the way, human fingertips have different skin conditions such as dry skin and oily skin. Even for the same person, the skin condition of the fingertip changes depending on the season and physical condition. The conventional fingerprint collation device has a problem that an accurate fingerprint image necessary for collation cannot be obtained because the fingerprint image that changes as described above is detected under the same conditions. In this way, if an image in a desired state cannot be obtained, accurate fingerprint matching is hindered.

The present invention has been made to solve the above problems, and an object thereof is to obtain an image in a desired state.

[0006]

An image capturing apparatus according to one aspect of the present invention converts the shape of an object into an electric quantity according to a parameter value set in a parameter setting section, and corresponds to the shape of the object. An image capturing unit that outputs image data representing an image and image data output from this image capturing unit are received, and an evaluation index for evaluating the image quality of the image is calculated from this image data, and this evaluation index is set in advance. If it is out of the range of the standard value, the parameter value set in the parameter setting unit is changed so that it is within the range of the standard value, and the evaluation index is received from the image capturing unit that is within the range of the standard value. And a capture controller for outputting image data. According to this image capturing device, the conversion state in the image capturing unit is changed according to the state of the image data output from the image capturing unit.

In the above-mentioned image capturing device, when the parameter value set in the parameter setting unit is changed, the image capturing unit outputs the image data converted again according to the changed parameter value. Further, in the above invention, the image capturing unit includes a detection element for converting the shape of the object into an analog signal, and an analog signal output from the detection element as a digital signal according to a parameter value set in the parameter setting unit. And an A / D conversion circuit that outputs the image data as image data,
The parameter values set in the parameter setting unit are the conversion range and the conversion resolution when converting an analog signal into a digital signal.

In the above-mentioned image capturing device, the evaluation index calculated by the capture control unit is, for example, a gray scale index indicating a gray level of image data output by the image capture unit,
The index may be any index indicating the spatial frequency component of the image data output by the image capturing unit. Further, the evaluation index calculated by the capture control unit is a combination of a gray scale index indicating the gray level of the image data output by the image capture unit and an index indicating the spatial frequency component of the image output by the image capture unit. Good.

Further, in the above-mentioned image capturing device, the evaluation index calculated by the capture controller may be, for example, a histogram index generated from a histogram expressing the shade of an image. In this case, the capture control unit determines, in the histogram, the maximum value on the gradation side where the image density is high, and the minimum value that is closest to the maximum value on the gradation side where the image density is lighter than the gradation value indicating this maximum value. The ratio may be calculated as a histogram index.

In the image capturing device, the evaluation index calculated by the capture controller may be, for example, a ridge number index generated based on the number of ridges in the image. In this case, the capturing control unit determines the average number of horizontal ridges per unit length in the horizontal direction of the image and the average number of ridges per unit length in the vertical direction of the image in the vertical direction. The number of ridges may be calculated, and the larger of the average number of horizontal ridges and the number of vertical ridges may be calculated as the ridge number index. It should be noted that the evaluation index may be a combination of a histogram index generated from a histogram expressing the shade of an image and a ridge number index generated based on the number of ridges in the image.

An image capturing method according to an aspect of the present invention converts the shape of an object into an electric signal according to a preset parameter value, and generates image data representing an image corresponding to the shape of the object, An evaluation index for evaluating the image quality of an image is calculated from this image data, and the parameter value is changed so that the evaluation index falls within a preset reference value range. According to this image capturing method, the conversion state into image data is changed depending on the state of the generated image data.

In the above image capturing method, the parameter value is a conversion range and conversion resolution when an analog signal is converted into a digital signal, the shape of an object is converted into an analog signal, and this analog signal is converted into a parameter value. Therefore, it is converted into a digital signal and output as image data. In the above-mentioned image capturing method, the evaluation index may be, for example, a density index indicating the gradation level of the image data or an index indicating the spatial frequency component of the image data. Also,
The evaluation index may be a combination of a density index indicating the gradation level of the image data and an index indicating the spatial frequency component of the image data.

In the above-mentioned image capturing method, the evaluation index is, for example, a histogram index generated from a histogram expressing the shade of an image or a ridge number index generated based on the number of ridges in the image. It may be. For example, in the histogram index, there are a maximum value on the gradation side where the shade of the image is dark in the histogram and a minimum value which is closest to the maximum value on the gradation side where the shade of the image is lighter than the gradation value indicating this maximum value. A ratio may be used. Further, for example, an average number of horizontal ridges per unit length in the horizontal direction of the image, and a number of vertical ridges per unit length in the vertical direction of the image, and Then, the larger one of the average number of horizontal ridges and the number of vertical ridges may be used as the ridge number index. It should be noted that the evaluation index may be a combination of a histogram index generated from a histogram expressing the shade of an image and a ridge number index generated based on the number of ridges in the image.

A fingerprint collation device according to one aspect of the present invention is
An image capturing unit that converts the unevenness of the fingerprint into an electric quantity according to the parameter value set in the parameter setting unit and outputs image data representing a fingerprint image corresponding to the unevenness of the fingerprint, and the image capturing unit outputs the image data. The image data is received, an evaluation index for evaluating the image quality of the fingerprint image is calculated from this image data, and if the evaluation index is outside the preset reference value range, it is set within the reference value range. A capture control unit that changes the parameter value set in the parameter setting unit and outputs the image data received from the image capture unit whose evaluation index is within the range of the reference value, and the image data output from this capture control unit. And a collating means for comparing and collating with registered image data prepared in advance. According to this fingerprint collation device, the conversion state in the image capturing unit is changed according to the state of the image data output from the image capturing unit.

In the fingerprint collation apparatus, when the parameter value set in the parameter setting section is changed, the image capturing section outputs the image data converted again according to the changed parameter value. Further, in the above fingerprint collation device, the image capturing unit digitally detects the detection element that converts the unevenness of the fingerprint into an analog signal and the analog signal output from this detection element according to the parameter value set in the parameter setting unit. The parameter value set in the parameter setting unit is composed of an A / D conversion circuit that converts the signal into a signal and outputs the image data, and a conversion range and a conversion resolution when converting an analog signal into a digital signal.

In the fingerprint collation device, the evaluation index calculated by the capture control unit is, for example, a gray scale index indicating the shade level of the image data output by the image capture unit,
The index may be any index indicating the spatial frequency component of the image data output by the image capturing unit. Further, the evaluation index calculated by the capture control unit is a combination of a gray scale index indicating the gray level of the image data output by the image capture unit and an index indicating the spatial frequency component of the image output by the image capture unit. Good.

Further, in the above fingerprint collation apparatus, the evaluation index calculated by the capture control unit may be, for example, a histogram index generated from a histogram expressing the shade of an image. In this case, the capture control unit determines, in the histogram, the maximum value on the gradation side where the image density is high, and the minimum value that is closest to the maximum value on the gradation side where the image density is lighter than the gradation value indicating this maximum value. The ratio may be calculated as a histogram index.

In the fingerprint collation device, the evaluation index calculated by the capture controller may be, for example, a ridge number index generated based on the number of ridges in the image.
In this case, the capturing control unit determines the average number of horizontal ridges per unit length in the horizontal direction of the image and the average number of ridges per unit length in the vertical direction of the image in the vertical direction. The number of ridges may be calculated, and the larger of the average number of horizontal ridges and the number of vertical ridges may be calculated as the ridge number index. It should be noted that the evaluation index may be a combination of a histogram index generated from a histogram expressing the shade of an image and a ridge number index generated based on the number of ridges in the image.

Further, in the above fingerprint collating apparatus, a finger placement detecting unit for detecting that a finger is placed on the image capturing unit is provided, and the image capturing unit and the finger placement detecting unit place the finger on the image capturing unit. When the fact is detected, the unevenness due to the fingerprint may be converted into an electric quantity according to the parameter value set in the parameter setting unit, and the image data representing the fingerprint image corresponding to the unevenness of the fingerprint may be output.

In the fingerprint collation method according to one aspect of the present invention, the unevenness due to the fingerprint is converted into an electric signal according to a preset parameter value to generate image data representing a fingerprint image corresponding to the unevenness of the fingerprint. , Calculating an evaluation index for evaluating the image quality from this image data, changing the parameter value so that this evaluation index is within the range of the preset reference value, and the evaluation index is within the range of the reference value. It is intended to compare and compare the image data that has become unregistered with the registered image data that is prepared in advance. According to this fingerprint matching method, depending on the state of the generated image data,
The conversion state to image data is changed.

In the above fingerprint collation method, the parameter value is a conversion range and conversion resolution when an analog signal is converted into a digital signal, unevenness due to fingerprints is converted into an analog signal, and this analog signal is converted into a parameter value according to the parameter value. It is intended to be converted into a digital signal and output as image data. Further, in the above fingerprint collation method, the evaluation index may be, for example, a density index indicating a gradation level of image data or an index indicating a spatial frequency component of image data. Further, the evaluation index may be a combination of a density index indicating the gradation level of the image data and an index indicating the spatial frequency component of the image data.

Further, in the above fingerprint matching method, the evaluation index is, for example, a histogram index generated from a histogram expressing the shade of an image or a ridge number index generated based on the number of ridges in the image. It may be. For example,
In the histogram index, the ratio of the maximum value on the gradation side where the density of the image is dark in the histogram and the minimum value that is the closest to the maximum value on the gradation side where the density of the image is lighter than the gradation value indicating this maximum value. It should be used. Further, for example, an average number of horizontal ridges per unit length in the horizontal direction of the image, and a number of vertical ridges per unit length in the vertical direction of the image, and Then, the larger one of the average number of horizontal ridges and the number of vertical ridges may be used as the ridge number index.
In the fingerprint matching method described above, the evaluation index is a combination of a histogram index generated from a histogram expressing the shade of an image and a ridge number index generated based on the number of ridges in the image. May be.

[0023]

BEST MODE FOR CARRYING OUT THE INVENTION Embodiments of the present invention will be described below with reference to the drawings. <First Embodiment> FIG. 1 is a block diagram showing the arrangement of an image capturing apparatus according to the first embodiment of the present invention. In the present embodiment, the case where the image capturing device is applied to fingerprint collation is taken as an example, and hereinafter, a fingerprint collation device will be described. The fingerprint collation device is provided with an image capturing unit 1 that first converts a concavo-convex image of a fingerprint into image data that is an electric signal and outputs the image data. The image capturing unit 1 determines the conversion state into image data according to the parameters set in the parameter setting unit 1a.

Further, the apparatus of FIG. 1 instructs the storage unit 4 for storing the registered image data G _{1 to} G _N for fingerprint collation and the user performing collation to place the finger on the image capturing unit 1. A finger placement instruction unit 6, a finger placement detection unit 7 that detects that a finger is placed on the image capturing unit 1, and a control unit 3 that controls the entire apparatus are provided.

The control unit 3 is composed of a CPU that executes a predetermined arithmetic processing by a program, and first determines the image data output from the image capturing unit 1 and capture control means 3a for changing the parameters of the parameter setting unit 1a. I have it. The control unit 3 includes an image data 2 that took the image capture unit 1 collates the registered image data G ₁ ~G _N in the storage unit 4 are stored, and outputs the result as a comparison result 5 collated And means 3b. The acquisition control means 3a and the collation means 3b are realized by programs.

FIG. 2 is a perspective view showing the structure of the image capturing section 1. On the detection surface 12 of the image capturing unit 1, a large number of sensor cells 11 are arranged in a matrix in the vertical and horizontal directions. The sensor cell 11 is composed of an element that converts a minute unevenness of a target into an electric quantity, and when the finger 21 contacts the detection surface 12, each sensor cell 11 detects the unevenness of the fingerprint 22. As the detection result of all the sensor cells, one image data 2 representing the fingerprint image as shown in FIG. 3 is output from the image capturing unit 1.

FIG. 4 is a configuration diagram showing the configuration of the image capturing section 1. The sensor cell 11 is composed of a detection element 11a and a sensor circuit 11b. The detection element 11a is
For example, it is a capacitive sensor composed of electrodes having an insulating layer on the surface. Further, the detection element 11a is, for example,
It may be an optical sensor composed of a photodiode or the like.

The unevenness of the fingerprint is converted into an electric signal by the detecting element 11a, and the converted signal is amplified by the sensor circuit 11b. Sensor circuit 11b of each sensor cell 11
The output of is connected to the common data line 13. The sensor cell 11 is sequentially selected and outputs an analog signal corresponding to the unevenness of the fingerprint to the data line 13. A / D conversion circuit 1
4 sequentially converts an analog signal transmitted through the data line 13 into a digital signal of 256 gradations and outputs the analog signal according to the parameter set in the parameter setting unit 1a. When the digital signals of all the sensor cells 11 are arranged in a matrix by reflecting the arrangement of each sensor cell, the fingerprint image data in the state shown in FIG. 3 is obtained.

The A / D conversion circuit 14 converts an analog signal corresponding to the unevenness of the fingerprint into a digital signal. The analog value and the digital value according to the parameter value set in the parameter setting section 1a. The correspondence with and changes. FIG. 5 is an explanatory diagram showing an example of parameters set in the A / D conversion circuit 14 (FIG. 4). Each of the parameters A and B is a rational number of 0 or more. When the analog value input to the A / D conversion circuit 14 is at a level lower than the set parameter value (A + B), the fingerprint image data of gradation 0 is obtained from the A / D conversion circuit 14. Gradation 0
The fingerprint image data of is a black image.

If the analog value input to the A / D conversion circuit 14 is equal to or greater than the set parameter value (A + 255 × B), the A / D conversion circuit 14 can obtain fingerprint image data of gradation 255. Fingerprint image data of gradation 255 is
It will be a white image. Furthermore, the analog value input to the A / D conversion circuit 14 is the parameter value (A + n
× B) or more and the parameter value {A + (n + 1) ×
If the level is less than B}, image data of gradation n is obtained from the A / D conversion circuit 14.

As described above, if the parameter value A is set large, the fingerprint image obtained from the A / D conversion circuit 14 becomes black, and if the parameter value A is set small,
The fingerprint image obtained from the A / D conversion circuit 14 becomes white.
Further, when the parameter value B is set large, the resolution of the fingerprint image obtained from the A / D conversion circuit becomes coarse, and when the parameter value B is set small, the resolution of the fingerprint image obtained from the A / D conversion circuit 14 becomes fine. . The number of gradations is not limited to 256, but may be 64 or 128.

The parameter setting section 1a is set to
Although the parameter value A and the parameter value B described above are used as the parameters used for the conversion in the image capturing unit 1, the present invention is not limited to this. For example, the same applies when the minimum value and the maximum value of the signal conversion region are used as the parameter value A and the parameter value B, respectively, in order to control the brightness and the resolution.

As described above, the A / D conversion circuit 14
A / D conversion circuit 1 by changing the parameter value of
The brightness and resolution of the fingerprint image obtained from 4 can be changed. Therefore, when detecting a fingerprint image of a human fingertip whose state changes due to individual differences, seasons, and physical conditions such as dry fingers and oily skin, it is necessary to set appropriate parameter values and capture the image. Therefore, it is possible to obtain an accurate fingerprint image that is not affected by individual differences or state changes.

Next, using the flowchart of FIG.
The operation of the fingerprint collation device (image capturing device) according to the present embodiment will be described. First, the capture control unit 3a of the control unit 3 instructs the user who performs the collation from the finger placement instruction unit 6 to place a finger on the detection surface 12 (FIG. 2) of the image capture unit 1 (step S1). Specific examples of the finger placement instruction include a mode in which the instruction is displayed using a display device including a light emitting element such as an LED, and a mode in which a predetermined instruction is turned on or a voice message is output. After the finger placement detection unit 7 detects that the user placed the finger on the detection surface 12 according to the finger placement instruction (step S2), the image capturing unit 1 captures the fingerprint image and outputs the image data 2 (step S2).
3).

When the image data 2 is output, the capture control section 3a first calculates a shade index Y indicating the shade level of the captured image as an image quality evaluation of the image data 2 (step S4). Any shade index may be used as long as it indicates the shade balance of the image data to be evaluated. For example, the ratio of the number of pixels having a predetermined gradation value or less to all the pixels of the image data may be used as an index. Alternatively, a predetermined area, for example, an area provided near the center of the detection surface 12 may be set as the target area for the index calculation, instead of the total pixel number as the target for the index calculation. Compared to,
The shade index can be calculated in a short time.

At the next steps S5 to S15,
The capture controller 3a compares the grayscale index Y obtained as described above with the preset threshold _values Y _th1 and Y _th2 . First, in step S5, the capture controller 3a
It is determined whether the calculated shade index Y is greater than or _equal to the threshold value Y _th1 . When it is determined in step S5 that the lightness index Y is equal to or greater than the threshold value Y _th1 , the process proceeds to step S6, and this time, it is determined whether the _lightness index Y is equal to or less than the threshold value Y _th2 . Step S6
If it is determined that the density index Y is less than or equal to the threshold value Y _th2 , the process proceeds to step S7, and the capture control unit 3a outputs the captured image data to the matching unit 3b.

On the other hand, if it is determined in step S5 that the shade index Y is less than the threshold value Y _th1 , the process proceeds to step S8, and it is first determined whether the parameter value B set in the parameter setting unit 1a is the maximum value. to decide. Step S
If it is determined in step 8 that the set parameter value B is not the maximum value, the process proceeds to step S9, and the capture control unit 3
a increases the parameter value B in the parameter setting unit 1a by a predetermined value, and returns to step S3. When it is determined in step S8 that the parameter value B set in the parameter setting unit 1a is the maximum value, the process proceeds to step S10, and the parameter value A set in the parameter setting unit 1a is the maximum value. Determine if

When it is determined in step S10 that the set parameter value A is not the maximum value, step S1
1, the import control unit 3a determines the parameter setting unit 1
The parameter value A in a is increased by a predetermined value, and the process returns to step S3. If it is determined in step S10 that it is the maximum value, the process proceeds to step S7, and the capture control unit 3a
Outputs the captured image data to the matching unit 3b.
When Y <Y _th1 , the captured image is in a slightly thin state. Therefore, the parameter values A and B are increased and the fingerprint image is captured again by the above process.

If it is determined in step S6 that the lightness index Y exceeds the threshold value Y _th2 , the process proceeds to step S12, in which the parameter value A set in the parameter setting unit 1a is the minimum value, for example, Judge whether it is 0 or not. When it is determined that the set parameter value A is not 0, the process proceeds to step S13, and the capture control unit 3a determines the parameter value A in the parameter setting unit 1a.
Is decreased by a predetermined value, and the process returns to step S3. Also,
When it is determined in step S12 that the parameter value A set in the parameter setting unit 1a is 0, the process proceeds to step S14, and it is determined whether the parameter value B set in the parameter setting unit 1a is the minimum value. to decide.

When it is determined in step S14 that the set parameter value B is not the minimum value, step S1
5, the import control unit 3a determines that the parameter setting unit 1
The parameter value B in a is decreased by a predetermined value, and the process returns to step S3. If it is determined in step S14 that the value is the minimum value, the process proceeds to step S7, and the capture control unit 3a
Outputs the captured image data to the matching unit 3b.
In the case of Y _th2 <Y, the captured image is in a slightly dark state, and thus the parameter values A and B are reduced and the fingerprint image is captured again.

The capture control section 3a repeats the above series of operations until the image quality of the image data satisfies a predetermined condition, and when the condition is satisfied, outputs the image data to the matching means 3b as an image suitable for authentication. To do. As described above, according to the present embodiment, it is possible to obtain an image in a desired state within the set parameter range.
Thereafter, the collation means 3b has received the image data, received an authentication process by comparing the image data with the registered image data G ₁ ~G _N in the storage unit 4 are stored performed.

In the above description, the gray scale index is used as the image quality evaluation index of the captured image data.
It is not limited to this. For example, saturation, brightness, contrast, etc. may be used as an index. Alternatively, the spatial frequency component may be extracted from the captured image data by performing processing such as Fourier transform, and this may be used as an index. In this case, it is possible to evaluate whether not only the light and shade but also the response of the fingerprint is properly acquired as an image. Further, the image may be evaluated by combining it with a gradation index.

Second Embodiment Next, another embodiment of the present invention will be described. By the way, in the above-described embodiment, the gray scale index is used as the image quality evaluation index, but since the thickness and interval of the ridges of the fingerprint pattern differ depending on the target person, the image data of the image quality optimized by the gray scale index is used. However, it may not be said that the image data has the optimum image quality for authentication. In the following embodiment, for example, a histogram index is used for image quality evaluation to solve the above.
The ridge is a line indicating a pattern obtained by the convex portion of the fingerprint.

As shown in FIG. 7, from the captured image data, a histogram index generated from a histogram expressing the shade of the image represented by this image data can be calculated. In FIG. 7, the horizontal axis represents the gradation value and the vertical axis represents the frequency. The gradation value indicates the degree of gradation of black and white in 256 steps (gradation), with gradation 0 being black and gradation 255 being white. A histogram index is calculated as shown in FIG. 7 (b) from the image data captured as shown in FIG. 7 (a), and a histogram index is calculated as shown in FIG. 7 (c). A histogram index is obtained as shown in 7 (d).

By the way, normally, when the image data is taken in as shown in FIG. 8A, two convex portions showing the density of ridges, noise, etc. are displayed in a histogram as shown in FIG. 8B. Appear inside. However, as described below, by providing a calibration circuit in the image capturing unit 1 (FIG. 1) to suppress / reduce noise and the like, FIG.
As shown in (b) and (d), it is possible to make only one convex portion showing the density of the ridge appear in the histogram.

In the present embodiment, the frequency of the maximum value on the lower gradation value side indicated by the histogram index and on the higher gradation side of the image is used as the peak value, and the peak value is higher than the gradation value indicating this peak value. Also, on the gradation side where the light and shade of the image is light, the frequency of the minimum value closest to the peak value is used as the tail value, and the histogram index H is
Define H = peak value / tail value. In the present embodiment, since the gradation value 255 is white, the tail value exists on the right side of the peak value in the histogram of FIG. Note that, in FIG. 8, the convex portion indicating the density of the ridge exists in the histogram on the side where the gradation value of the image is dark, so the minimum value between the two convex portions is the tail value. The maximum value of the convex part on the left side of is the peak value.

When the histogram index H defined as described above has a small value, the contrast of the image becomes small,
The higher the value, the higher the contrast. In the present embodiment, the parameters A and B are set based on such a histogram index H. Figure 7
In the case of black and white unclear image data as shown in (a),
As shown in FIG. 7B, the histogram index H (= peak value / tail value) is small.

In such a case, the values of the parameters A and B are set so that the histogram index H becomes large so that the result as shown in FIG. 7D is obtained. As a result, the contrast of the fingerprint image is increased as shown in FIG. 7C, and a clear fingerprint image can be obtained. As described above, by setting the parameters A and B so that the histogram index H falls within a preset reference value range, that is, an appropriate range, fingerprint authentication is performed without being affected by the density of the fingerprint. An appropriate fingerprint image can be acquired.

Next, using the flowchart of FIG.
The operation of the fingerprint matching device (image capturing device) using the histogram index as the evaluation index will be described. First, the capture control unit 3a of the control unit 3 instructs the detection surface 12 of the image capture unit 1 from the finger placement instructing unit 6 to the user who performs collation.
An instruction to place the finger on (FIG. 2) is given (step S1). Specific examples of the finger placement instruction include a mode in which the instruction is displayed using a display device including a light emitting element such as an LED, or a predetermined instruction is turned on.
And voice messages are output. After the finger placement detection unit 7 detects that the user placed the finger on the detection surface 12 according to the finger placement instruction (step S2), the image capturing unit 1 captures the fingerprint image and outputs the image data 2 (step S3). ). These are the same as the embodiment shown in FIG.

In this embodiment, when the image data 2 is output, the capture controller 3a uses the histogram index H from the image data 2 as the image quality evaluation index of the captured image.
Is calculated (step S101). The histogram index H may be calculated not only from all the pixels of the captured image, but also from a predetermined region of the captured image, for example, a region provided near the center of the detection surface 12. In this case, the histogram index H can be calculated in a shorter time than when all pixels are targeted.

Next steps S102 to S11
2, the capture control unit 3a uses the histogram index H obtained as described above and the preset threshold value H.
Compare _th1 and H _th2 . First, the capture controller 3a
Is the histogram index H calculated in step S102.
Is greater than or _equal to the threshold value H _th1 . Step S1
If the histogram index H is determined to be equal to or greater than the threshold value H _{th1 in} 02, the process proceeds to step S103 to determine whether the histogram index H is equal to or less than the threshold value H _th2 . When it is determined in step S103 that the histogram index H is less than or equal to the threshold value H _th2 , the process proceeds to step S104, and the capture control unit 3a outputs the captured image data to the matching unit 3b.

On the other hand, if it is determined in step S102 that the histogram index H is less than the threshold value H _th1 , step S1
In step 05, it is determined whether the parameter value B set in the parameter setting unit 1a is the maximum value. When it is determined in step S105 that the set parameter value B is not the maximum value, the process proceeds to step S106, the capture control unit 3a increases the parameter value B in the parameter setting unit 1a by a predetermined value, and then the process proceeds to step S3. Return. When it is determined in step S105 that the parameter value B set in the parameter setting unit 1a is the maximum value, the process proceeds to step S107, and the parameter value A set in the parameter setting unit 1a is the maximum value. Determine if

If it is determined in step S107 that the set parameter value A is not the maximum value, step S107
In step 108, the capture control unit 3a increases the parameter value A in the parameter setting unit 1a by a predetermined value, and the process returns to step S3. If it is determined in step S107 that it is the maximum value, the process proceeds to step S104, and the capture control unit 3a compares the captured image data with the collation unit 3b.
Output to. When H <H _th1 , the contrast of the captured image is slightly small, and thus the parameter values A and B are increased and the fingerprint image is captured again.

If it is determined in step S103 that the histogram index H exceeds the threshold value H _th2 , the process proceeds to step S109, where the parameter setting unit 1a is set.
It is determined whether or not the parameter value A set to is a minimum value, for example, 0. When it is determined that the set parameter value A is not 0, the process proceeds to step S110, the capture control unit 3a decreases the parameter value A in the parameter setting unit 1a by a predetermined value, and the process returns to step S3. When it is determined in step S109 that the parameter value A set in the parameter setting unit 1a is 0, the process proceeds to step S111, and the parameter value B set in the parameter setting unit 1a is the minimum value. Determine whether

When it is determined in step S111 that the set parameter value B is not the minimum value, step S111
In step 112, the capture control unit 3a decreases the parameter value B in the parameter setting unit 1a by a predetermined value, and the process returns to step S3. When it is determined in step S111 that the value is the minimum value, the process proceeds to step S104, and the capture control unit 3a compares the captured image data with the collation unit 3b.
Output to. When H _th2 <H, the captured image has a slightly high contrast, and thus the parameter values A and B are reduced and the fingerprint image is captured again.

The capture controller 3a repeats the above series of operations until the image quality of the image data satisfies a predetermined condition, and when the condition is satisfied, outputs the image data to the collating means 3b as an image suitable for authentication. To do. As described above, according to the present embodiment, it is possible to obtain a fingerprint image with a sharp contrast without being affected by the light and shade of the fingerprint pattern, individual differences, and state changes.

As exception processing, parameters A and B are used.
If the condition is not satisfied even if the value of becomes the maximum value or the minimum value, the captured image at this time is output. After that, the collating means 3b having received the image data receives the received image data and the registered image data G stored in the storage unit 4.
Performs authentication processing by comparing the ₁ ~G _N. Further, in the present embodiment, the above operation can be performed after smoothing the histogram of the captured fingerprint image. By doing so, it is possible to reduce the influence of the fluctuation of the histogram due to the noise or the variation.

Hereinafter, a configuration example of the fingerprint collation device (image capturing device) according to the present embodiment, the operation example of which has been described with reference to the flowchart of FIG. 9, will be described. After that,
In order to suppress / reduce noise, etc., the image capturing unit 1
A configuration in which the calibration circuit is provided in (FIG. 1) will be described. FIG. 10 shows the calibration circuit 101.
It is a block diagram which shows the structure of the image acquisition part 1 provided with.
Note that in FIG. 10, one sensor cell is shown as a representative in consideration of the fact that many sensor cells have the same configuration.

As shown in FIG. 10, the sensor cell 11 is composed of a detection element 11a, a sensor circuit 11b, and an output signal level correction circuit 101. The output signal level correction circuit 101 takes in the output of the sensor circuit 11b and outputs the sensor signal. The output of the circuit 11b is supplied to one of the inputs of the comparison circuit 102. The comparison circuit 102 includes the sensor circuit 11b.
Output and calibration reference signal generation circuit 103
The calibration reference value (signal) that is the output of the above is compared. The calibration circuit 105 is the comparison circuit 1
The output level of the sensor circuit 11b is adjusted (corrected) by controlling the input side of the sensor circuit 11b or the gain control of the sensor circuit 11b so that the difference between the two output by 02 is eliminated.
To do.

Calibration reference signal generation circuit 1
03 is preferably configured to generate the same level of calibration reference signal for each sensor cell. The output signal level correction circuit 101 has a function of eliminating variations in the output of each sensor cell 11 as much as possible, and various known configurations can be applied as long as they perform such an operation. By doing this, the output of each sensor circuit, that is, each sensor cell 1
The output level of 1 can be adjusted to the same level, noise due to sensitivity variations can be suppressed, and peaks due to noise in the histogram index as shown in FIG. 8 can be eliminated.

The details will be described below. FIG. 11 is a configuration diagram showing a partial configuration of the image capturing unit 1 by the sensor cell 11 including the calibration circuit 105.
Each of the sensor cells 11 has the same configuration and is composed of a detection element 11a, a sensor circuit 11b, and a calibration circuit (sensitivity adjustment circuit) 105, and the detection sensitivity of each sensor cell 11 is adjusted using the calibration circuit 105. . In addition, the calibration circuit 10
5, a signal processing circuit 5 and a control line L _C.

The sensor cell 11 is composed of a detection element 11a, a sensor circuit 11b and a calibration circuit 105. The detection element 11a is an element for converting the surface shape into an electric signal. The sensor circuit 11b is a circuit that measures the amount of electricity of the detection element 11a that changes depending on the surface shape. When correcting the output level of each sensor cell 11, that is, performing calibration, the sensor cell 11 detects a reference sample having no unevenness as an object to be measured, or performs detection without placing anything on the sensor cell, so that each sensor cell 11 can be detected. Detect the same measured value. The signal output from the sensor cell 11 is input to the A / D conversion circuit 4 via the data line L _D and output as a digital output signal 4A.

The digital output signal 4A output from the A / D conversion circuit 4 is also input to the signal processing circuit 5. The signal processing circuit 5 adjusts the detection sensitivity of the sensor circuit 11b by comparing the digital output signal 4A output from the A / D conversion circuit 4 with the digital output signal that should be originally output (hereinafter, referred to as an expected value). The adjustment parameter for calculating is calculated.
Then, based on the calculated adjustment parameter, the control line L _C
Is used to control the calibration circuit 105.

The data line L _D and the control line L _C are shared by the respective sensor cells 11, the sensor cells 11 are sequentially selected, and the output signal 2A of the sensor cells 11 is sequentially A / A.
The signal is input to the D conversion circuit 4, and the signal processing circuit 5 controls the calibration circuit 105 in the sensor cell 11. By repeating this operation once or plural times for each sensor cell 11, the sensitivity of each sensor circuit 11b is adjusted, and the performance of each sensor cell 11 is made uniform.

In this case, the signal processing circuit 5 has the comparison circuit 102 described in FIG. 10 and the calibration reference signal generation circuit 103 as another signal processing circuit 110. In the example of FIG. 11, the input signal is digital, and thus the comparison circuit 102 remains the digital signal.
In the case of inputting to, a known digital comparison circuit can be used as the comparison circuit 104. If the comparison circuit 104 is a normal analog comparison circuit, it is once D / A converted and supplied to the comparison circuit 104. Of course, the same applies to the calibration reference signal generation circuit 103.

Further, as shown in FIG. 12, the image capturing section 1 may be constructed by the sensor cell 11 provided with the calibration circuit 105. The image capturing unit 1 shown in FIG. 12 includes a sensor circuit 11b ′ with a voltage-time conversion function.
And a time signal comparison circuit 106 is used. The sensor circuit 11b ′ with a voltage-time conversion function is a sensor circuit that converts an output signal corresponding to the amount of electricity from the corresponding detection element 11a into a signal that changes in the time axis direction. Further, the time signal comparison circuit 106 compares the voltage-time conversion signal output from the sensor circuit 11b ′ with a voltage-time conversion function with the calibration reference signal, and the calibration circuit 105 uses the signal difference as a control signal. Output to. When calibrating each sensor cell 11 of the image capturing unit 1 configured as described above, the sensor cell 11 detects a reference sample having no unevenness as an object to be measured, and causes each sensor cell 11 to detect the same measurement value.

As a result, the sensor circuit with voltage-time conversion function 11b 'converts a signal having analog information as a voltage value into a signal having analog information in the time axis direction, and outputs the signal as shown in FIG. It is output as the signal 2B (see FIG. 14: t _S is the output time, and this t _S changes). The output signal 2B is input to the A / D conversion circuit 4 via the data line L _D and output as a digital output signal. At the same time, this output signal 2B is transmitted to the sensor cell 11
It is internally supplied to the calibration circuit 105 via the time signal comparison circuit 106. Time signal comparison circuit 106
Corresponds to the comparison circuit 102 of FIG.
Digital output 2 of sensor circuit 11b 'with time conversion function
The time difference between B and the reference pulse signal having the reference time t _R from the calibration reference signal generating circuit is obtained.

The time signal comparison circuit 106 compares the signal voltage-time converted by the sensor circuit 11b 'with the voltage-time conversion function with the reference pulse signal, and the comparison pulse signal representing the time difference between them is calibrated by the calibration circuit 105.
Send to. As a result, the calibration circuit 105
The control operation is performed so that there is no time difference between the reference pulse signal and the output from the sensor circuit voltage-time converting function-equipped sensor circuit 11b '. The data line L _D is shared by the plurality of sensor cells 11, and the sensor cells 11 are sequentially selected to perform the above operation.

By repeating the above-mentioned operation once or plural times for each sensor cell 11, the sensitivity of each sensor circuit 11b 'with a voltage-time conversion function is adjusted, and the performance of each sensor cell 11 is made uniform. Also, the sensor cell 1
Even if a plurality of 1s are selected at the same time, the calibration can be performed in parallel for each sensor cell, and the calibration can be performed at high speed.

FIG. 13 shows a concrete configuration example of a sensor cell having a sensor circuit with a voltage-time conversion function. The sensor circuit 11b ′ with a voltage-time conversion function includes, for example, a voltage-time conversion circuit 121, and the voltage-time conversion circuit 1
A general-purpose device may be used as the device 21, and it may be composed of a constant current circuit, a capacitor, and a threshold circuit 121a (see, for example, Japanese Patent Application No. 11-157755).

Sensor circuit 11 with voltage-time conversion function
The operating principle of the calibration circuit when b'is used will be briefly described with reference to FIG. First, the time signal comparison circuit 106 is typically configured by an AND circuit, and outputs the output signal 2B of the sensor circuit 11b ′ with a voltage-time conversion function and the reference pulse signal from the reference pulse signal generation circuit (not shown). The logical product is calculated and the result is output to the counter circuit 154 as a comparison pulse signal.

The value of the counter circuit 154 is the value of the load circuit 15
1 is preset to an initial set value for controlling all the load elements Z _{1 to} Z _N that make up 1 and the output signal 2B of the sensor circuit 11b ′ with a voltage-time conversion function is also set to an initial set value. Set it. In the first sensing operation, when the output signal 2B changes earlier than a predetermined time (for example, the sensing operation is performed without placing the object such as the finger 21 on the detection surface 12 of the image capturing unit 1 during the sensing time). When the output signal of the sensor cell changes), the counter circuit 154 increments by 1 based on the output of the time signal comparison circuit 106. As a result, the counter circuit 154
Data changes so as to activate _one of the load elements Z _{1 to} Z _N. In addition, the sensor circuit 1 with a voltage-time conversion function
The output signal 2B of 1b 'is also reset to the initial setting value.

If the output signal changes faster than a predetermined time even in the second sensing operation (for example, the sensing operation is performed without placing the finger 13 and the output signal of the sensor cell changes during the sensing time), The counter circuit 154 is further incremented by one. Here, the load element Z ₁ ~
If the value of Z _N is set to twice each in accordance with the digit of the counter, as a result, twice the number of load elements will be activated. For example, Z ₁ = Z, Z ₂ = 2Z, Z ₃ = 4Z,
…, Z _N = 2 ^(N-1) Z is set, and the counter circuit 15
If Z _{1 to} Z _N are controlled in order from the lower bit of 4, the values of the load elements Z _{1 to} Z _N connected to the sensor circuit 11 b ′ with the voltage-time conversion function are increased by Z for each count up. Will be.

This operation is performed until the output signal of the sensor circuit 11b 'having the voltage-time conversion function does not change within a predetermined time (for example, the sensing operation is performed without placing the finger 13 and the sensor cell is operated during the sensing time). Repeat until the output signal of does not change). When the output signal does not change within the predetermined time, the counter circuit 154 is not counted up and the load element is not connected to the sensor circuit 11b ′ with the voltage-time conversion function any more.

As described above, since the direct current does not flow through the output level correction system including the calibration by performing the voltage-time conversion, the power consumption of the entire apparatus can be reduced as compared with the other embodiments. . As described above, by adding the calibration circuit 105 to the sensor circuit 11b and connecting an appropriate number of load elements Z _{1 to} Z _N inside the calibration circuit 105 to the sensor circuit 11b, a sensor cell due to process variations or the like can be obtained. The performance variation of 1 is not visible, and as a result, the performance of each sensor cell can be made uniform.

<Third Embodiment> Next, an image capturing method according to another embodiment of the present invention will be described. In the present embodiment, the ridge number index is used as the image quality evaluation index. First, the ridge number index will be described with reference to FIG. The ridges of the fingerprint appear as low-gradation (black) lines in the fingerprint image. The ridge number index N counts the average number of ridges of fingerprints in the horizontal and vertical directions within the fingerprint determination area (n × m pixels) shown in FIG. The line number index N is used.

The method of counting the number of ridges will be described. For example, when counting the number of ridges in the horizontal direction, pixels are scanned in the vertical direction, and the ridges that intersect at this time are counted. Assuming that the number of ridges when one row of pixels is scanned in the vertical direction is Ni, the determination area has n rows, and therefore the average number of ridges for n rows is represented by the following equation 1.

[0078]

[Equation 1]

Since the length of one line in the vertical direction is m pixels, P / P is standardized to the number of ridges per P pixel.
By multiplying m by Formula 1, the average number of horizontal ridges Nv per pixel P is calculated as shown in Formula 2 below.

[0080]

[Equation 2]

When the vertical direction is also obtained in the same manner, the average number of ridges Nh in the vertical direction per pixel number P is expressed by the following expression 3.

[0082]

[Equation 3]

Therefore, the ridge number index N is N = MAX
It is represented by (Nv, Nh), and the larger one of Nv and Nh is used as the ridge number index N.

FIG. 16 is a diagram for explaining ridge determination conditions. In FIG. 16, the vertical axis represents the gradation value of each pixel, and the horizontal axis represents the vertical or horizontal pixels of the determination area. The gradation value of each pixel is wavy due to the unevenness of the fingerprint image, and the number of this wave is the number of ridges. The method of counting ridges is, for example, using two thresholds HVTH and LVTH,
There is one ridge when the line crosses from HVTH to LVTH. Here, the reason why two threshold values are used is to prevent pixels due to noise or the like from being counted as a ridge line, but it is also possible to set one threshold value by setting HVTH = LVTH.

It is also possible to smooth the gradation values of the fingerprint image and then count the ridges. By doing so, it is possible to reduce the influence of fluctuations in the fingerprint image due to noise, device variations, and the like.

When the ridge number index N is extremely small, the fingerprint image is in a collapsed state. On the contrary, when the value of the ridge number index N is large, the fingerprint image is faint and the ridge is broken. Therefore, when the ridge number index N is extremely small, the image quality is thinned so that the image does not collapse, and conversely, when the ridge number index N is extremely large, the image is darkened. ,
Adjust parameters A and B. By doing so, it is possible to obtain an appropriate fingerprint image that is not affected by the contrast of the fingerprint pattern.

The ridge number index can be calculated from the valley line (white line in the fingerprint image of FIG. 15) instead of the ridge line (black line in the fingerprint image of FIG. 15). Also in this case, the evaluation index is equivalent to the ridge number index. The way of counting the valley lines can be counted, for example, with reference to FIG. 16, when there are two thresholds HVTH and LVTH when one valley line extends from LVTH to HVTH. Also in this case, the threshold value can be set to one.

Also in this embodiment, the configuration of the apparatus is
This is the same as the image capturing device (fingerprint collation device) similar to that of the other embodiments described above, and the capture control unit 3a operates as shown in FIG. The operation of the capture control unit 3a in the fingerprint collation device according to this embodiment will be described below. It should be noted that description of the configuration requirements equivalent to those in FIG. 9 will be appropriately omitted.

First, the finger placement instructing section 6 instructs the user who performs the collation to place the finger on the detection surface 12 (FIG. 2) of the image capturing section 1 (step S1). Specific examples of the finger placement instruction include a mode in which the instruction is displayed using a display device including a light emitting element such as an LED, and a mode in which a predetermined instruction is turned on or a voice message is output. After the finger placement detection unit 7 detects that the user placed the finger on the detection surface 12 according to the finger placement instruction (step S2), the image capturing unit 1 captures the fingerprint image and outputs the image data 2 (step S2).
3).

When the image data 2 is output, the capture control section 3a first calculates the ridge number index N of the captured image as the image quality evaluation of the image data 2 (step S2).
01). The ridge number index N may be calculated not only from all the pixels of the captured image but also from a predetermined region of the captured image, for example, a region provided near the center of the detection surface 12. In this case, the ridge number index N can be calculated in a shorter time than when all pixels are targeted.

Next steps S202 to S21
2, the capture control unit 3a determines the ridge number index N obtained as described above and the preset threshold values N _th1 and N _th2.
Compare with. First, if it is determined in step S202 that the calculated _ridge count index N is equal to or less than N _th2 , the capture control unit 3a proceeds to step S203 to determine whether the _ridge count index N is equal to or greater than a threshold N _th1. To do. Step S
If it is determined in 203 that the ridge number index N is equal to or greater than the threshold value N _th1 , the process proceeds to step S204, and the capture control unit 3a
Outputs the captured image data to the matching unit 3b.

On the other hand, in step S202, the ridge number index N
If it is determined that the value exceeds the threshold N _th2 , step S
In step 205, it is first determined whether the parameter value B set in the parameter setting unit 1a is the maximum value. When it is determined in step S205 that the set parameter value B is not the maximum value, step S206
Then, the acquisition control unit 3a proceeds to the parameter setting unit 1a.
The parameter value B in is increased by a predetermined value, and the process returns to step S3. When it is determined in step S205 that the parameter value B set in the parameter setting unit 1a is the maximum value, the process proceeds to step S207, and the parameter value A set in the parameter setting unit 1a is the maximum value. Determine if

When it is determined in step S207 that the set parameter value A is not the maximum value, step S207
In step 208, the capture control unit 3a increases the parameter value A in the parameter setting unit 1a by a predetermined value, and the process returns to step S3. If it is determined in step S207 that it is the maximum value, the process proceeds to step S204, and the capture control unit 3a compares the captured image data with the collation unit 3b.
Output to. If N> N _th2 , the captured image is faint and too thin. Therefore, the parameter values A and B are increased and the fingerprint image is captured again.

In the judgment of step S203, the ridge number index N
When it is determined that is less than the threshold N _th1 , the process proceeds to step S209, and here it is determined whether the parameter value A set in the parameter setting unit 1a is the minimum value, for example, 0. When it is determined that the set parameter value A is not 0, the process proceeds to step S210, the capture control unit 3a decreases the parameter value A in the parameter setting unit 1a by a predetermined value, and the process returns to step S3. If it is determined in step S209 that the parameter value A set in the parameter setting unit 1a is 0,
In step S211, it is determined whether the parameter value B set in the parameter setting unit 1a is the minimum value.

When it is determined in step S211 that the set parameter value B is not the minimum value, step S21
In step 212, the capture control unit 3a decreases the parameter value B in the parameter setting unit 1a by a predetermined value, and the process returns to step S3. If it is determined in step S211 that the value is the minimum value, the process proceeds to step S204, and the capture control unit 3a compares the captured image data with the matching unit 3b.
Output to. When N <N _th1 , the captured image is in a collapsed state, and thus the parameter values A and B are reduced and the fingerprint image is captured again.

The capture controller 3a repeats the above series of operations until the image quality of the image data satisfies a predetermined condition, and when the condition is satisfied, outputs the image data to the collating means 3b as an image suitable for authentication. To do. As described above, according to the present embodiment, it is possible to obtain a fingerprint image that is not crushed or rubbed without being affected by the shading of the fingerprint pattern, individual differences, and state changes. As an exceptional process, if the condition is not satisfied even if the values of the parameters A and B reach the maximum value or the minimum value, the captured image at this time is output. In the present embodiment, the location and size of the fingerprint determination area can be freely set as needed.

<Embodiment 4> In this embodiment, a histogram index and a ridge count index are applied in combination with the evaluation index in the image processing apparatus and the fingerprint collation apparatus. For example, the parameters A and B are set so that each of the histogram index and the ridge number index falls within a predetermined range.
May be changed. Further, a new index may be derived from the histogram index and the ridge number index by a predetermined calculation, and the parameters A and B may be changed based on this index.

With such a configuration, it is possible to obtain a fingerprint image with high contrast and without being crushed or rubbed, without being affected by the light and shade of the fingerprint pattern, individual differences and state changes. In the present embodiment, the ridge number index may be replaced with the ridge number index calculated using the valley line described in the second embodiment and applied.

Further, in the above-mentioned embodiment, the case where the analog value is converted into the digital value of 256 gradations has been described, but it is also possible to convert to the gradation other than 256. In the present invention, the parameter value A and the parameter value B are set as the parameters set in the parameter setting unit 1a and used for conversion in the image capturing unit 1, but the present invention is not limited to this. For example, the same applies when the minimum value and the maximum value of the signal conversion region are used as the parameter value A and the parameter value B, respectively, in order to control the brightness and the resolution. Further, the number of parameters to be set is not limited to this, and can be freely changed as necessary.

In the above embodiment, the evaluation index is generated from a combination of a gradation index indicating the gradation level of image data and an index indicating the spatial frequency component of the image, and a histogram expressing the gradation of the image. An example in which the histogram index described above and the ridge number index generated based on the number of ridges in the image are combined has been exemplified, but the combination is not limited to these. It goes without saying that each evaluation index may be combined appropriately and used as a new evaluation index.

[0101]

As described above, according to the present invention,
For example, since the image data in which the evaluation index of the image falls within a certain range is taken in as a target of fingerprint matching, an excellent effect that an image in a desired state can be obtained is obtained. Will be able to improve the accuracy of.

[Brief description of drawings]

FIG. 1 is a configuration diagram showing a configuration of a fingerprint matching device using an image capturing device according to an embodiment of the present invention.

FIG. 2 is a perspective view showing a partial configuration of an image capturing section of the fingerprint matching device of FIG.

FIG. 3 is an explanatory diagram showing a state of image data of a fingerprint captured by an image capturing unit.

FIG. 4 is a configuration diagram showing a schematic configuration of an image capturing unit.

5 is an explanatory diagram showing an example of parameters set in the A / D conversion circuit 14. FIG.

FIG. 6 is a flowchart showing an operation of the fingerprint collation device according to the embodiment of the present invention.

FIG. 7 is an explanatory diagram showing the captured image data and a histogram expressing the shade of the image represented by this image data.

FIG. 8 is an explanatory diagram showing the captured image data and a histogram expressing the shade of the image represented by this image data.

FIG. 9 is a flowchart showing an operation of the fingerprint collation device according to another embodiment of the present invention.

FIG. 10 is a configuration diagram showing a partial configuration of a fingerprint collation device according to another embodiment of the present invention.

FIG. 11 is a configuration diagram showing a partial configuration of a fingerprint collation device according to another embodiment of the present invention.

FIG. 12 is a configuration diagram showing a partial configuration of a fingerprint matching device according to another embodiment of the present invention.

FIG. 13 is a circuit diagram showing a partial configuration of a fingerprint collation device according to another embodiment of the present invention.

FIG. 14 is a timing chart showing a specific operation example of the fingerprint matching device shown in FIG.

FIG. 15 is an explanatory diagram illustrating a ridge index.

FIG. 16 is a characteristic diagram illustrating a ridge determination condition.

FIG. 17 is a flowchart showing the operation of the fingerprint collation device according to another embodiment of the present invention.

[Explanation of symbols]

1 ... Image capturing unit, 1a ... Parameter setting unit, 2 ... Image data, 3 ... Control unit, 3a ... Capture control unit, 3b ...
Checking means, 4 ... storage unit, 5 ... verification result, 6 ... finger rest instructing unit, 7 ... finger rest detector, G ₁ ~G _N ... registration image data.

   ─────────────────────────────────────────────────── ─── Continued front page    (72) Inventor Kenichi Saito             2-3-1, Otemachi, Chiyoda-ku, Tokyo             Inside Telegraph and Telephone Corporation (72) Inventor Yukio Okazaki             2-3-1, Otemachi, Chiyoda-ku, Tokyo             Inside Telegraph and Telephone Corporation (72) Inventor Tsutomu Kuraki             2-3-1, Otemachi, Chiyoda-ku, Tokyo             Inside Telegraph and Telephone Corporation (72) Inventor Tsuyoshi Yamaguchi             2-3-1, Otemachi, Chiyoda-ku, Tokyo             Inside Telegraph and Telephone Corporation (72) Inventor Hiroki Suto             2-3-1, Otemachi, Chiyoda-ku, Tokyo             Inside Telegraph and Telephone Corporation (72) Inventor Satoshi Shigematsu             2-3-1, Otemachi, Chiyoda-ku, Tokyo             Inside Telegraph and Telephone Corporation F term (reference) 2F065 AA56 BB02 CC16 DD09 EE00                       FF04 FF61 JJ03 JJ26 NN13                       NN17 PP11 QQ03 QQ16 QQ25                       QQ26 QQ27 QQ32 QQ42 QQ43                 5B047 AA25 BA02 BB04 BC14 BC23                       CB22 DB01 DC04 DC09

Claims (43)

[Claims] 1. A shape of an object is converted into an electric quantity according to a parameter value set in a parameter setting unit,
An image capturing unit that outputs image data representing an image corresponding to the shape of the object, an image index output from the image capturing unit, and an evaluation index for evaluating the image quality of the image from the image data. Calculated, if this evaluation index is outside the range of the preset reference value, the parameter value set in the parameter setting unit is changed to be within the range of the reference value, and the evaluation index is An image capturing device, comprising: a capturing control unit that outputs image data received from the image capturing unit within a range of a reference value. 2. The image capturing device according to claim 1, wherein when the parameter value set in the parameter setting unit is changed, the image capturing unit reconverts the image data according to the changed parameter value. An image capturing device characterized by outputting 3. The image capturing device according to claim 1, wherein the image capturing unit includes a detection element that converts the shape of the object into an analog signal, and an analog signal output from the detection element. And an A / D conversion circuit for converting into a digital signal according to the parameter value set in the parameter setting unit and outputting the digital signal as the image data. The parameter value set in the parameter setting unit is an analog signal. An image capturing device having a conversion range and a conversion resolution when converting into the digital signal. 4. The image capturing device according to claim 1, wherein the evaluation index calculated by the capture control unit is a shade index indicating a shade level of image data output by the image capture unit. An image capturing device characterized by being present. 5. The image capturing device according to claim 1, wherein the evaluation index calculated by the capturing control unit is an index indicating a spatial frequency component of image data output by the image capturing unit. An image capturing device characterized by being present. 6. The image capturing device according to claim 1, wherein the evaluation index calculated by the capture control unit is a shade index indicating a shade level of image data output by the image capture unit. An image capturing device characterized by being combined with an index indicating a spatial frequency component of an image output by the image capturing unit. 7. The image capturing device according to claim 1, wherein the evaluation index calculated by the capture control unit is a histogram index generated from a histogram expressing the grayscale of the image. An image capturing device characterized by. 8. The image capturing device according to claim 1, wherein the evaluation index calculated by the capturing control unit is the number of ridges generated based on the number of ridges in the image. An image capturing device characterized by being an index. 9. The image capturing device according to claim 1, wherein the evaluation index calculated by the import control unit is a histogram index generated from a histogram expressing the shade of the image and the image. An image capturing device characterized by being combined with a ridge number index generated based on the number of ridges in the inside. 10. The image capturing device according to claim 7, wherein the capture control unit includes a maximum value on a gradation side where the image has a high density and a gray level of the image that is higher than the gradation value indicating the maximum value. The image capturing apparatus is characterized in that a ratio of the local maximum value to the local minimum value on the light gray scale side is calculated as the histogram index. 11. The image capturing device according to claim 8, wherein the capturing control unit includes a horizontal average ridge number that is an average number of ridges per unit length in the horizontal direction of the image, and a vertical direction of the image. The number of vertical ridges, which is the average number of ridges per unit length in the direction, is obtained, and the larger one of the average number of horizontal ridges and the number of vertical ridges is calculated as the ridge number index. An image capturing device characterized by the above. 12. An image data representing an image corresponding to the shape of the object is generated by converting the shape of the object into an electric signal according to a preset parameter value, and the image quality of the image is obtained from the image data. The image capturing method is characterized in that an evaluation index for evaluating is calculated, and the parameter value is changed so that the evaluation index falls within a preset reference value range. 13. The image capturing method according to claim 12, wherein the parameter value is a conversion range and conversion resolution when an analog signal is converted into a digital signal, and a shape of an object is converted into an analog signal, An image capturing method comprising converting an analog signal into a digital signal according to the parameter value and outputting the digital signal as the image data. 14. The image capturing method according to claim 12, wherein the evaluation index is a density index indicating a gradation level of the image data. 15. The image capturing method according to claim 12, wherein the evaluation index is an index indicating a spatial frequency component of the image data. 16. The image capturing method according to claim 12, wherein the evaluation index is a combination of a density index indicating a gradation level of the image data and an index indicating a spatial frequency component of the image data. An image capturing method characterized by the above. 17. The image capturing method according to claim 12 or 13, wherein the evaluation index is a histogram index generated from a histogram expressing the shade of the image. 18. The image capturing method according to claim 12 or 13, wherein the evaluation index is a ridge number index generated based on the number of ridges in the image. . 19. The image capturing method according to claim 12 or 13, wherein the evaluation index is generated based on a histogram index generated from a histogram expressing the grayscale of the image and the number of ridges in the image. An image capturing method characterized by being combined with a ridge line number index. 20. The image capturing method according to claim 17, wherein the histogram index has a lighter image density than a maximum value on a gradation side where the image has a high density and a gradation value showing the maximum value in the histogram. An image capturing method characterized in that the ratio is a ratio of the local maximum value to the local minimum value on the gradation side. 21. The image capturing method according to claim 18, wherein the ridge number index is an average number of ridges per unit length in a horizontal direction of the image and an average number of ridges per unit length in a vertical direction. An image capturing method characterized by being the larger of the two. 22. An image capturing unit for converting unevenness due to a fingerprint into an electric quantity according to a parameter value set in a parameter setting unit and outputting image data representing a fingerprint image corresponding to the unevenness of the fingerprint, and the image capturing unit. The image data output from the capturing unit is received, an evaluation index for evaluating the image quality of the fingerprint image is calculated from this image data, and if this evaluation index is outside the preset reference value range, the reference A capture control unit that changes the parameter value set in the parameter setting unit so as to be within a range of values, and outputs the image data received from the image capture unit in which the evaluation index is within the range of the reference value. And collating means for comparing and collating the image data output from the capture control unit with the registered image data prepared in advance. Fingerprint verification device, characterized in that. 23. The fingerprint collation apparatus according to claim 22, wherein when the parameter value set in the parameter setting unit is changed, the image capturing unit reconverts the image data according to the changed parameter value. A fingerprint collation device characterized by outputting 24. The fingerprint collation apparatus according to claim 22 or 23, wherein the image capturing unit sets a parameter for converting a detection element for converting unevenness due to a fingerprint into an analog signal, to an analog signal output from the detection element. And an A / D conversion circuit for converting the digital signal into a digital signal according to the parameter value set in the section and outputting the digital signal as the image data. The parameter value set in the parameter setting section is an analog signal for the digital signal. A fingerprint collation device having a conversion range and conversion resolution when converting into a signal. 25. The fingerprint collation device according to claim 22, wherein the evaluation index calculated by the capture control unit is a shade index indicating a shade level of image data output by the image capture unit. A fingerprint collation device characterized in that 26. The fingerprint collation apparatus according to claim 22, wherein the evaluation index calculated by the capture control unit is an index indicating a spatial frequency component of image data output by the image capture unit. A fingerprint collation device characterized in that 27. The fingerprint collation apparatus according to claim 22, wherein the evaluation index calculated by the capture control unit is a shade index indicating a shade level of image data output by the image capture unit. A fingerprint collation device, which is a combination of an index indicating a spatial frequency component of an image output by the image capturing unit. 28. The fingerprint collation apparatus according to claim 22, wherein the evaluation index calculated by the capture control unit is a histogram index generated from a histogram expressing the shade of the image. A fingerprint matching device characterized by. 29. The fingerprint collation apparatus according to claim 22, wherein the evaluation index calculated by the capture control unit is the number of ridges generated based on the number of ridges in the image. A fingerprint matching device characterized by being an index. 30. The fingerprint collation device according to claim 22, wherein the evaluation index calculated by the capture control unit is a histogram index generated from a histogram expressing the shade of the image, and the image. A fingerprint collation device characterized by being combined with a ridge number index generated based on the number of ridges in the middle. 31. The image capturing device according to claim 28, wherein the histogram index has a lighter image density than a maximum value on a gradation side where the image has a high density and a gradation value showing this maximum value in the histogram. A fingerprint collation device characterized by a ratio of the local maximum value to the nearest local minimum value on the gradation side. 32. The fingerprint collation apparatus according to claim 29, wherein the ridge number index calculates an average number of ridges per unit length in the horizontal direction and the vertical direction of the image, and the calculated horizontal direction. A fingerprint collation device, wherein the larger one of the average number of ridges in the vertical direction is used as the ridge number index. 33. Image data representing a fingerprint image corresponding to the unevenness of the fingerprint is generated by converting the unevenness of the fingerprint into an electric signal according to a preset parameter value, and the image quality of the fingerprint image is obtained from this image data. Calculating an evaluation index for evaluating, changing the parameter value so that this evaluation index falls within the range of a preset reference value, and the image data in which the evaluation index falls within the range of the reference value And a registered image data prepared in advance are compared with each other to perform collation. 34. The fingerprint matching method according to claim 33, wherein the parameter value is a conversion range and conversion resolution when an analog signal is converted into a digital signal, and unevenness due to a fingerprint is converted into an analog signal. A fingerprint collation method comprising converting a signal into a digital signal according to the parameter value and outputting the digital signal as the image data. 35. The fingerprint matching method according to claim 33 or 34, wherein the evaluation index is a density index indicating a density level of the image data. 36. The fingerprint matching method according to claim 33, wherein the evaluation index is an index indicating a spatial frequency component of the image data. 37. The fingerprint matching method according to claim 33 or 34, wherein the evaluation index is a combination of a density index indicating a gradation level of the image data and an index indicating a spatial frequency component of the image data. A fingerprint matching method characterized by the above. 38. The fingerprint collation method according to claim 33 or 34, wherein the evaluation index is a histogram index generated from a histogram expressing the shade of the image. 39. The fingerprint matching method according to claim 33, wherein the evaluation index is a ridge number index generated based on the number of ridges in the image. . 40. The fingerprint matching method according to claim 33 or 34, wherein the evaluation index is generated based on a histogram index generated from a histogram expressing the grayscale of the image and the number of ridges in the image. A fingerprint matching method characterized by being combined with a ridge line number index. 41. The fingerprint matching method according to claim 38, wherein the histogram index has a lighter image density than a maximum value on a gradation side where the image has a high gradation and a gradation value showing this maximum value in the histogram. A fingerprint collation method, characterized in that the ratio is a ratio of the local maximum value to the local minimum value on the gradation side. 42. The fingerprint matching method according to claim 39, wherein the ridge count index is an average ridge count per unit length in a horizontal direction of the image and an average ridge count per unit length in a vertical direction. A fingerprint collation method, which is the larger of the two. 43. The fingerprint collation apparatus according to claim 22, further comprising a finger placement detection unit that detects that a finger is placed on the image capturing unit, wherein the image capturing unit is When the finger placement detection unit detects that a finger is placed on the image capturing unit, the unevenness due to the fingerprint is converted into an electric quantity according to the parameter value set in the parameter setting unit, and corresponds to the unevenness of the fingerprint. A fingerprint collation device, which outputs image data representing a fingerprint image.