CN115082975A - Biological characteristic identification method - Google Patents

Abstract

A biological feature identification method is applied to a biological feature identification device. The biometric feature identification method comprises the steps of calculating a gray scale difference value of a first biometric feature image, defining a first voltage difference value according to the gray scale difference value, performing biometric feature sensing to obtain a second voltage difference value, and identifying whether the biometric feature is true according to the first voltage difference value and the second voltage difference value.

Description

Biological characteristic identification method

Technical Field

The present disclosure relates to a biometric feature identification method.

Background

Most of the current electronic devices have an identity authentication mechanism, and the way of identity recognition using biometric features is a trend in recent years. A common authentication method is fingerprint recognition, because fingerprint recognition is easily integrated in an electronic device.

An electronic device for fingerprint identification using grayscale images needs to extract a plurality of grayscale images and perform fingerprint identification through image processing. However, this method takes a lot of time to extract images and calculate through algorithms, so that the biometric recognition efficiency is difficult to improve.

In view of the above, how to provide a biometric identification method that can solve the above problems is still the goal of the development efforts in the field.

Disclosure of Invention

One aspect of the present disclosure is a biometric feature identification method applied to a biometric feature identification device. The biometric identification device comprises a light source, a photosensitive element and an integrated circuit.

In one embodiment, the biometric feature recognition method includes calculating a gray scale difference of a first biometric image, defining a first voltage difference according to the gray scale difference, performing biometric sensing to obtain a second voltage difference, and recognizing whether a biometric feature is true according to the first voltage difference and the second voltage difference.

In one embodiment, the step of defining the first voltage difference value according to the gray scale difference value includes performing an analog-to-digital conversion on the gray scale difference value to define the first voltage difference value.

In an embodiment, when the second voltage difference is greater than the first voltage difference, the biometric feature is identified as yes.

In one embodiment, the step of calculating the gray scale difference of the biometric features further comprises defining the brightness of the light source as a first brightness; performing biometric sensing to generate a first biometric image; and performing image processing on the first biological characteristic image to calculate a gray-scale difference value of the first biological characteristic image.

In an embodiment, the step of performing the biometric sensing to obtain the second voltage difference further includes the step of receiving the light reflected by the biometric feature by the light sensing element to generate an optical leakage, and the integrated circuit obtaining the second voltage difference according to the optical leakage.

In an embodiment, when the second voltage difference is smaller than the first voltage difference, the biometric recognition result is no, and the biometric recognition method further includes performing biometric sensing to generate a second biometric image and performing image processing on the second biometric image to obtain a heart rate value.

In one embodiment, the biometric identification method further comprises determining whether the heart rate value is in a heart rate interval.

In an embodiment, when the second voltage difference is smaller than the first voltage difference, the biometric feature recognition result is negative, and the biometric feature recognition method further includes defining the brightness of the light source as a second brightness, and the second brightness is greater than the first brightness; and performing biometric sensing to obtain a third voltage difference.

In one embodiment, the biometric feature recognition method further includes recognizing whether the biometric feature is true according to the first voltage difference value and the third voltage difference value.

In an embodiment, when the third voltage difference is greater than the first voltage difference, the biometric feature is identified as yes, and when the third voltage difference is less than the first voltage difference, the biometric feature is identified as no.

In the above embodiment, the biometric feature identification method may be implemented by converting the gray scale difference into a first voltage difference for determining whether the biometric feature is true, and defining a second voltage difference according to a light leakage difference generated after the light sensing element is illuminated. In the first stage of the biological characteristic identification method, the first voltage difference value and the second voltage difference value are used for judging, so that the step of extracting the image by an image processing module and processing the image can be omitted. Therefore, the time for identifying the biological characteristics can be reduced. In addition, the manner of defining the first voltage difference value by the gray scale difference value is not limited to the fingerprint pattern in the present disclosure. The light leakage difference corresponding to different users achieving the same gray scale difference is the same, so the biometric feature identification method of the present disclosure is not limited to a single user.

Drawings

Fig. 1 is a side view of a biometric identification device according to an embodiment of the present disclosure.

Fig. 2 is a block diagram of the biometric device of fig. 1.

Fig. 3A and 3B are schematic diagrams of image processing flows.

Fig. 4 is a circuit diagram of a fingerprint sensing module.

FIG. 5 is a graph showing the relationship between the light leakage and the bias voltage of the photosensitive element.

Fig. 6A to 6B are flowcharts illustrating a biometric method according to an embodiment of the disclosure.

Fig. 7A to 7B are flowcharts of a biometric method according to another embodiment of the disclosure.

[ notation ] to show

100 biometric feature recognition device

110 light source

120 fingerprint sensing module

122 pixel circuit

1222 thin film transistor switch

1224 photosensitive element

124 integrated circuit

1242 integrator

1244 temporary storage

1244A first temporary memory

1244B second temporary memory

1244C third temporary memory

1246 first switch

1248 second switch

130 protective layer

140 analog-to-digital converter

150 image processing module

160 electronic device

170A, 170B logical operation unit

180 within the interval

190 gray scale difference

200, finger

300, 400 biometric feature identification method

I is a back charging current

A sensing region

V _bias Bias voltage

V _ref Reference voltage

V _out Output voltage

V _data Data voltage

C1, C2 curve

S1-S20

Detailed Description

In the following description, numerous implementation details are set forth in order to provide a thorough understanding of the present invention. It should be understood, however, that these implementation details are not to be interpreted as limiting the invention. That is, in some embodiments of the invention, such implementation details are not necessary. In addition, for the sake of simplicity, some conventional structures and elements are shown in the drawings in a simple schematic manner. And the thickness of layers and regions in the drawings may be exaggerated for clarity, and the same reference numerals denote the same elements in the description of the drawings.

Fig. 1 is a side view of a biometric identification device 100 according to an embodiment of the present disclosure. The biometric device 100 includes a light source 110, a fingerprint sensing module 120, and a protection layer 130. The biometric device 100 is used for fingerprint recognition and calculating heart rate. When the finger 200 is pressed on the sensing area a, the light emitted from the light source 110 is reflected by the finger 200. The pulse is periodically pulsed so that the image generated by the reflected light received by the fingerprint sensing module 120 has gray scale variation. The heart rate value can be obtained by extracting the fingerprint gray scale image and performing image processing on the fingerprint gray scale image to calculate the gray scale change frequency of the image. In the present disclosure, the light source 110 has a single wavelength band as long as the wavelength band can be absorbed by the fingerprint sensing module 120.

Fig. 2 is a block diagram of the biometric device 100 of fig. 1. The biometric device 100 includes a fingerprint sensing module 120, an analog-to-digital converter 140, an image processing module 150, and an electronic device 160 electrically connected to each other.

Fig. 3A and 3B are schematic diagrams of image processing flows. When biometric sensing is performed, a plurality of fingerprint grayscale images are extracted at regular time intervals within a time period by the fingerprint sensing module 120. For example, the fingerprint sensing module 120 may extract a fingerprint grayscale image every 0.1 seconds. The biometric image referred to herein is a fingerprint grayscale image received by the sensing region a (see fig. 1).

The image processing module 150 can calculate the average gray-scale value of a specific region in each fingerprint gray-scale image. For example, a region having a range of approximately 0.1 inch by 0.1 inch is framed in the sensing region a pressed by the finger 200 as a range of image processing. The width of the adult fingerprint occupied by a group of peaks and valleys is about 0.45 mm to 0.5 mm. Therefore, the range selected by the box is at least greater than 0.5 mm by 0.5 mm, but the disclosure is not limited thereto.

FIG. 3A shows the average gray-scale values of 150 fingerprint gray-scale images. FIG. 3B shows the average gray-scale values of 150 fingerprint gray-scale images after being processed by the algorithm. Fig. 3B is a graph showing the result of calculating the oscillation size of the average gray scale value distribution by redefining the overall average value of the average gray scale value distribution to zero after reducing the high frequency noise from the average gray scale value calculated by the image processing module 150 shown in fig. 3A. The broken line in fig. 3B indicates a range in which the oscillation size is 1. In this embodiment, when the oscillation size is larger than 1, the fingerprint gray-scale image in the interval can be used to detect the heart rate, i.e. the fingerprint gray-scale image is from the live fingerprint.

Fig. 4 is a circuit diagram of the fingerprint sensing module 120. The fingerprint sensing module 120 includes a pixel circuit 122 and an integrated circuit 124 electrically connected to each other. In the present embodiment, the pixel circuit 122 includes a Thin Film Transistor (TFT) switch 1222 and a light sensing element 1224. The tft switch 1222 is connected to the light sensing element 1224, and the light sensing element 1224 is a photodiode (photo diode). The integrated circuit 124 includes an integrator 1242 and a register 1244. The integrator 1242 is electrically connected to the tft switch 1222.

Refer to fig. 4. The integrated circuit 124 generates a charging current I due to light leakage generated after the light sensing element 1224 illuminates. The charging voltage corresponding to the charging current I can be temporarily stored in the register 1244 through the integrator 1242. V _bias Is the bias voltage, V, of the positive electrode of the photosensitive element 1224 _ref Is a reference voltage, V _out Is the output voltage. When the first switch 1246 is turned on, the data voltage V can be switched on _data Reset to reference voltage V _ref . When the second switch 1248 is turned on, the output voltage V can be adjusted _out Recorded in the register 1244. It should be understood that the circuit diagram shown in fig. 4 is merely an example, which is not intended to be limitingTo limit the disclosure.

Fig. 5 is a diagram illustrating the relationship between the light leakage and the bias voltage of the photosensitive element 1224. As shown in fig. 5, the reflected light of the light-dark change causes a difference in light leakage generated by the light-sensing element 1224. The curves C1 and C2 represent the relationship between the photo leakage and the bias voltage generated by the photosensitive element 1224 during the pulse diastole and the pulse systole, respectively. The difference between the curve C1 and the curve C2 is the light leakage difference.

Refer to fig. 2. The biometric device 100 further includes a first register 1244A, a second register 1244B, a third register 1244C, a logic unit 170A and a logic unit 170B. The logic unit 170A is configured to determine the difference between the values temporarily stored in the second register 1244B and the third register 1244C, and the logic unit 170B then determines the difference between the difference and the value temporarily stored in the first register 1244A.

In the present embodiment, the pulse periodically beats to make the light leakage generated by the light sensing element 1224 have a difference, so that the integrated circuit 124 can record the voltage difference corresponding to the light leakage change. The adc 140 converts the voltage difference into a corresponding gray-scale value, and also converts the gray-scale value into a voltage difference. The electronic device 160 is a device having the fingerprint sensing module 120, such as a mobile phone, a tablet, or other electronic devices having an identity authentication mechanism.

The biometric feature recognition method disclosed by the present disclosure uses the voltage difference as a criterion for recognizing whether the fingerprint is true (whether the fingerprint is a live fingerprint), thereby achieving the effect of fast recognition. The detailed steps of the biometric identification method will be described below.

Fig. 6A to 6B are flowcharts illustrating a biometric method 300 according to an embodiment of the disclosure. Refer to fig. 1 and 6A simultaneously. In step S1 of the biometric authentication method, the brightness of the light source 110 is defined as a first brightness. For example, in the present embodiment, the light of the light source 110 is reflected by the standard sheet with a reflectivity of 79%, and the light source brightness when the grayscale image received by the fingerprint sensing module 120 has the grayscale average value of 180 is defined as the first brightness of the light source 110. The definition of the first brightness by the grayscale value 180 is only an example, as long as the biometric device 100 can clearly recognize the grayscale value of the fingerprint grayscale image.

Refer to fig. 6A, 3A, and 3B simultaneously. In step S2 of the biometric identification method, biometric sensing is performed to generate a biometric image, and image processing is performed on the biometric image to calculate a grayscale difference of the biometric image. After the image processing steps described above, the gray-scale difference value can be calculated from the average gray-scale value shown in fig. 3A. For example, a gray level difference 190 of 1.4 is calculated in the interval 180 as shown in fig. 3A. In other words, after the fingerprint grayscale image is calculated by the algorithm in this embodiment, the grayscale difference 190 greater than 1.4 indicates that the fingerprint grayscale image is from a live fingerprint.

It should be understood that the detailed steps of the image processing described above are only examples, and are not intended to limit the present invention. Those skilled in the art should be able to adjust the present invention according to the actual requirement, as long as the gray-scale difference 190 for identifying whether the biometric image is from a live fingerprint can be calculated.

Refer to fig. 2 and 6A simultaneously. In step S3 of the biometric method, an analog-to-digital converter 140 performs an analog-to-digital conversion on the grayscale difference 190 to obtain a first voltage difference. In this embodiment, the first voltage difference value can be converted into a gray scale signal by the adc 140. Similarly, in the case where the gray-scale difference 190 is known to be 1.4, the gray-scale difference 190 can be converted into a first voltage difference required for identifying whether the biometric feature is true through the adc 140.

Refer to fig. 2 and 6A simultaneously. In step S4 of the biometric method, the first voltage difference is defined as a voltage difference required to be generated by the pulse beat. In this step, the first voltage difference obtained by the back-stepping is temporarily stored in the first register 1244A to be defined as the first voltage difference for identifying whether the fingerprint is true.

Reference is also made to fig. 4 and 6A. In step S5 of the biometric method, biometric sensing is performed. After the light reflected by the fingerprint irradiates the light-sensing element 1224, the light-sensing element 1224 generates light leakage. In this step, a finger 200 is pressed on the sensing region a (see fig. 1). The pulse beat causes the reflected light received by the fingerprint sensing module 120 to show a bright-dark change, and thus the light sensing element 1224 generates a light leakage change along with the pulse beat.

Refer to fig. 2 and 6A simultaneously. In step S6 of the biometric method, the integrated circuit 124 temporarily stores the charging voltage to obtain a second voltage difference. In this step, the integrated circuit 124 generates a back-charging voltage corresponding to the optical leakage difference. For example, the charging voltage during the pulse diastole can be temporarily stored in the second register 1244B through the integrator 1242. The back-charge voltage during the pulse systole can be temporarily stored in the third register 1244C through the integrator 1242. The logic operation unit 170A determines the difference between the charging voltages temporarily stored in the second register 1244B and the third register 1244C. Therefore, the recharging voltage difference value corresponding to the light leakage difference can be obtained, and the recharging voltage difference value is defined as a second voltage difference value.

Refer to fig. 2 and 6A simultaneously. In step S7 of the biometric authentication method, it is determined whether the second voltage difference is greater than the first voltage difference. The logic unit 170B may determine a difference between the first voltage difference and the second voltage difference.

Refer to fig. 2 and 6A simultaneously. In step S8 of the biometric feature recognition method, when the second voltage difference is greater than the first voltage difference, the recognition result is yes. The biometric characteristic is determined to be a live fingerprint. The electronic device 160 can display the recognition result. In some embodiments, the image processing module 150 may selectively perform image processing to calculate the heart rate after completing steps S1 to S8, and display the heart rate value through the electronic device 160.

The second voltage difference value is greater than the first voltage difference value, which is equivalent to the gray scale difference value of the fingerprint gray scale image generated by pulse beating being greater than the calculated gray scale difference value 190. However, since the present disclosure converts the gray-scale difference value 190 into the first voltage difference value, the determining step can omit the time required for extracting the image and performing the image processing.

Refer to fig. 6A and 6B simultaneously. And when the second voltage difference value is smaller than the first voltage difference value, the identification result is negative. The biometric determination is made as a non-live fingerprint, and the steps of FIG. 6B are continued to further identify whether the biometric is true. In other words, steps S1 to S7 in fig. 6A are the first stage identification process, and steps S9 to S14 in fig. 6B are the second stage identification process. When the first stage identification process is not, the second stage identification process is continued to avoid misjudgment and improve the accuracy of the biological characteristic identification.

Refer to fig. 6B. In step S9 of the biometric recognition method, biometric sensing is performed again. In this step, the finger 200 presses the sensing region a again (see fig. 1), and the fingerprint sensing module 120 extracts a fingerprint grayscale image.

Refer to fig. 2 and 6B simultaneously. In step S10 of the biometric authentication method, the image processing module 150 performs image processing on the biometric image. For example, the image processing module 150 extracts 150 fingerprint grayscale images to calculate an average grayscale value.

Refer to fig. 6B. In step S11 of the biometric feature recognition method, a heart rate value is obtained by calculating a gray-scale variation frequency through an algorithm.

Referring to fig. 6B, in step S12 of the biometric authentication method, it is determined whether the heart rate value is in a reasonable heart rate interval. For example, in the present embodiment, 50 to 120 heartbeats per minute is a reasonable heart rate interval, but it is not limited to this disclosure.

Refer to fig. 2 and 6B simultaneously. When the heart rate value is within the reasonable heart rate interval, the recognition result is yes and the second stage recognition process ends as shown in step S13. The biometric characteristic is determined as a live fingerprint. The electronic device 160 can display the identification result. In some embodiments, the electronic device 160 may selectively display the heart rate value after the recognition step is completed.

Refer to fig. 2 and 6B simultaneously. In step S14, when the heart rate value is outside the reasonable heart rate interval, the recognition result is no and the second stage recognition process is ended. The biometric characteristic is determined to be a non-live fingerprint. The electronic device 160 displays the recognition result.

According to the above, the biometric feature identification method of the present disclosure can convert the gray scale difference into a first voltage difference for determining whether the biometric feature is true, and define a second voltage difference according to the light leakage difference generated after the light sensing element is illuminated. In the first stage of the biometric feature recognition method, the first voltage difference and the second voltage difference are used for determination, so that the step of extracting an image by the image processing module 150 and processing the image can be omitted. Therefore, the time for identifying the biological characteristics can be reduced. In addition, if the first stage identification result is negative, the second stage identification process can be performed to avoid misjudgment and improve the accuracy of the biological feature identification. The manner of defining the first voltage difference value by the gray scale difference value in the present disclosure is not limited to the fingerprint pattern. The light leakage difference corresponding to different users achieving the same gray scale difference is the same, so the biometric feature identification method of the present disclosure is not limited to a single user.

Fig. 7A to 7B are flowcharts illustrating a biometric method 400 according to another embodiment of the disclosure. Steps S1 to S8 of the biometric identification method 400 are the same as the biometric identification method 300 shown in fig. 6A (i.e., the identification process in the first stage is the same), and are not repeated herein. The biometric feature recognition method 400 is different from the biometric feature recognition method 300 in that when the second voltage difference is smaller than the first voltage difference, the steps S15 to S19 are continued, which is referred to as the third stage recognition.

Refer to fig. 1 and 7B simultaneously. In step S15 of the biometric authentication method 400, the brightness of the light source 110 is defined as the second brightness. The second luminance is greater than the first luminance in step S1. For example, by reflecting light with a standard sheet having a reflectivity of 79%, the light source brightness when the grayscale image received by the fingerprint sensing module 120 has a grayscale value of 200 is defined as the second brightness. Therefore, the probability of misjudgment caused by poor fingerprint reflection when the first brightness is adopted can be avoided. The second brightness is defined by the gray scale value 200 as an example, as long as the second brightness is greater than the first brightness and the biometric device 100 can clearly identify the gray scale value of the fingerprint gray scale image.

Refer to fig. 7B. In step S16 of the biometric recognition method 400, biometric sensing is performed again. In this step, the finger 200 presses the sensing region a again (see fig. 1), and the fingerprint sensing module 120 extracts a fingerprint grayscale image.

Refer to fig. 2 and 7B simultaneously. In step S17 of the biometric authentication method 400, the integrated circuit 124 temporarily stores the charging voltage to obtain a third voltage difference. In this step, the integrated circuit 124 generates a back-charging voltage corresponding to the optical leakage. The back-charged voltage during the pulse diastole can be temporarily stored in the second register 1244B through the integrator 1242. The back-charge voltage during the pulse systole can be temporarily stored in the third register 1244C through the integrator 1242. The logic operation unit 170A determines the difference between the charging voltages temporarily stored in the second register 1244B and the third register 1244C. Therefore, the back charging voltage difference generated by the light leakage difference can be obtained, and the back charging voltage difference is defined as a third voltage difference.

Refer to fig. 2 and 7B simultaneously. In step S18 of the biometric authentication method 400, it is determined whether the third voltage difference is greater than the first voltage difference. The logic operation unit 170B may determine a difference between the first voltage difference and the third voltage difference.

Refer to fig. 2 and 7B simultaneously. In step S19 of the biometric feature recognition method, when the third voltage difference is greater than the first voltage difference, the recognition result is yes. The biometric characteristic is determined as a live fingerprint. The electronic device 160 can display the recognition result. In some embodiments, the image processing module 150 may selectively perform image processing to calculate the heart rate after completing the recognition steps S15 to S19, and display the heart rate value through the electronic device 160.

Refer to fig. 2 and 7B simultaneously. In step S20 of the biometric feature recognition method, when the third voltage difference is smaller than the first voltage difference, the recognition result is negative and the third stage recognition process ends. The electronic device 160 displays the recognition result.

In summary, the biometric feature identification method of the present disclosure can convert the gray scale difference into a first voltage difference for determining whether the biometric feature is true, and define a second voltage difference according to the light leakage difference generated after the light sensing device is illuminated. In the first stage identification process of the biological feature identification method, the judgment is performed by the first voltage difference value and the second voltage difference value, so that the step of extracting the image by an image processing module and performing image processing can be omitted. Therefore, the time for identifying the biological characteristics can be reduced. In addition, if the result of the first stage identification process is negative, the second stage identification process or the third stage identification process can be performed to avoid misjudgment and improve the accuracy of the biological characteristic identification. The second stage identification process can adopt a heart rate calculation mode to carry out biological feature identification, and the third stage identification process can adopt larger light source brightness to carry out biological feature identification. The manner of defining the first voltage difference value by the gray scale difference value in the present disclosure is not limited to the fingerprint pattern. The light leakage difference corresponding to different users achieving the same gray scale difference is the same, so the biometric feature identification method of the present disclosure is not limited to a single user.

Although the present disclosure has been described with reference to the above embodiments, it will be understood by those skilled in the art that various changes and modifications may be made without departing from the spirit and scope of the disclosure, and therefore the scope of the disclosure should be determined by that of the appended claims.

Claims (10)

1. A biological characteristic identification method is applied to a biological characteristic identification device, the biological characteristic identification device comprises a light source, a photosensitive element and an integrated circuit, and the biological characteristic identification method comprises the following steps:

calculating a gray scale difference value of the first biological characteristic image;

defining a first voltage difference value according to the gray scale difference value;

performing biometric sensing to obtain a second voltage difference; and

and identifying whether the biological feature is true according to the first voltage difference value and the second voltage difference value.

2. The method of claim 1, wherein the step of defining the first voltage difference according to the gray-scale difference comprises:

performing analog-to-digital conversion on the gray scale difference value to define the first voltage difference value.

3. The method according to claim 1, wherein the biometric identification result is yes when the second voltage difference is greater than the first voltage difference.

4. The method of claim 1, wherein the step of calculating the gray-scale difference of the biometric feature further comprises:

defining the brightness of the light source as a first brightness;

performing biometric sensing to generate a first biometric image; and

and performing image processing on the first biological characteristic image to calculate the gray-scale difference value of the first biological characteristic image.

5. The method of claim 4, wherein the step of performing biometric sensing to obtain the second voltage difference further comprises:

the light sensing element receives the light reflected by the biological characteristic to generate light leakage; and

the integrated circuit obtains the second voltage difference value according to the light leakage.

6. The method according to claim 4, wherein when the second voltage difference is smaller than the first voltage difference, the biometric identification result is negative, and the method further comprises:

performing biometric sensing to generate a second biometric image

Image processing is performed on the second biometric image to derive a heart rate value.

7. The biometric identification method as in claim 6, further comprising:

and judging whether the heart rate value is in the heart rate interval.

8. The method according to claim 4, wherein when the second voltage difference is smaller than the first voltage difference, the biometric identification result is negative, and the method further comprises:

defining the brightness of the light source as a second brightness, wherein the second brightness is greater than the first brightness; and

performing biometric sensing to obtain a third voltage difference.

9. The biometric method as recited in claim 8, further comprising:

and identifying whether the biological feature is true according to the first voltage difference value and the third voltage difference value.

10. The method according to claim 9, wherein when the third voltage difference is greater than the first voltage difference, the biometric identification result is yes;

when the third voltage difference is smaller than the first voltage difference, the biometric feature identification result is negative.

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