TWI549065B - Fingerprint identification method and device thereof - Google Patents

Description

Fingerprint identification method and device thereof

An identification method and device, in particular, a method and device for fingerprint identification.

The so-called fingerprint identification, as the name suggests, is to use the unique fingerprint information on the human finger to identify. A common fingerprint recognition device can be composed of two elements. The first one is the Fingerprint Sensor, the main purpose is to collect a complete fingerprint image. Another element is the Fingerprint Algorithm. After the fingerprint sensor of the current end collects the fingerprint image, the fingerprint image processing and fingerprint feature point extraction are performed by the algorithm. After the fingerprint template is generated, the original fingerprint image is discarded, and then the fingerprint comparison is performed.

Common fingerprint sensors are available in both capacitive and optical versions. At present, capacitive fingerprint sensors are commonly used for RF capacitance sensing, pressure sensing, and thermal sensing. The principle is to integrate a high-density capacitive sensor or a miniature sensor such as a pressure sensor into a chip. When the finger presses the surface of the wafer, the internal miniature capacitive sensor will be based on the peaks and valleys of the fingerprint. Different amounts of charge (or temperature differences) generated by aggregation, which in turn form a fingerprint image.

The advantages of capacitive sensors are thinning and miniaturization, which can be used in a large number of handheld devices, but their disadvantages are high cost and durability. Moreover, the capacitive sensor has to cut the entire wafer in order to maintain a certain pressing area, so the cost per wafer is quite high. Furthermore, since the capacitive sensor itself is a bare semiconductor wafer, it is easy because of the finger The sweat and acid and alkali influence itself, and the surface of the wafer is eroded and the static electricity is easily generated, so that the tolerance and service life of the capacitive sensor are greatly reduced. Therefore, a layer of sapphire substrate is added to the surface of the capacitive sensor for protection, but the manufacturing cost is also relatively increased.

In addition, the optical fingerprint sensor is the earliest fingerprint acquisition device, which uses light. The source, Mitsubishi mirror, and charge coupled device (CCD) form a set of fingerprint acquisition devices. After the Mitsubishi mirror is pressed by the finger, the fingerprint peak and the valley absorb and destroy the total reflection of the light, thereby obtaining a fingerprint image, and then capturing and outputting the image via a charge coupled device (CCD). Since the optical fingerprint sensor is collected by the non-contact wafer itself, that is, the fingerprint pressing portion is composed of optical components such as acrylic or glass, the optical advantage is that the price is low and durable. However, optical fingerprint sensors are difficult to apply to the interior of handheld devices because of their large size and complicated assembly.

In addition, people who are uncomfortable usually fake their fingers with silicone. Silicone material The fake finger can almost accurately have fingerprints and micro blood vessels. Thus, after the fingerprint function is pressed by the fingerprint finger and the fake finger with the fingerprint and the micro blood vessel, the fake finger can also have the characteristics of the finger deformation after pressing and the fingerprint and the micro blood vessel. The feature deceives the fingerprint identification device, and the fingerprint identification device cannot correctly recognize whether it is pressed by a real person's finger, thereby causing a loophole in identification.

Therefore, the conventional capacitive fingerprint sensor has an environmentally sensitive electrostatic effect and is produced. The problem of high cost, and the optical fingerprint sensor has the problem that the bulky size cannot be applied to the handheld device, and the fake finger faked by the silicone can simulate the deformation of the true finger pressing and the fingerprint and microvascular characteristics, thereby making it easy to pass the fingerprint. Identify problems with the 3D finger verification program of the device. Therefore, how to design a fingerprint identifier that can avoid the influence of environmental static electricity, small volume, reduce production cost and identify real finger blood vessels has become a problem that the inventor of the present invention needs to solve.

In view of the false fingers faked by silicone, the finger deformation can be simulated and the fingerprint and micro Vascular properties lead to problems such as easy 3D finger verification procedures through the fingerprint recognition device. Therefore, the main object of the present invention is to provide a fingerprint identification method and apparatus thereof for solving the problem that the silicone fake finger is easily verified by the fingerprint identification device.

A method for identifying an authentic fingerprint according to the present invention includes the following steps Step: placing a finger on a photoelectric sensor module; emitting a non-visible light line toward the finger with a first light-emitting element and emitting a visible light line toward the finger with a second light-emitting element; the non-visible light line penetrates the inside of the finger Reflecting to the photoelectric sensor module, the photoelectric sensor module receives at least one non-visible light intensity signal of the non-visible light line, and the visible light line is reflected to the photoelectric sensor module through the surface of the finger, so that the photoelectric sensor module receives at least one visible light of visible light The photoelectric sensor module converts the at least one visible light current signal according to the visible light intensity signal, and the photoelectric sensor module converts the visible light intensity signal into at least one visible light current signal, and the photoelectric sensor transmits the non-visible current signal and the visible light current signal respectively. To a analog/digital conversion module; the analog/digital conversion module converts the non-visible current signal into at least one first digital signal, and the analog/digital conversion module converts the visible light current signal into at least one second digital signal, analogy/ Digital conversion module will be the first number The bit signal and the second digit signal are respectively transmitted to a processor module; the processor module converts the image into a grayscale fingerprint image according to the first digital signal, and the processor module converts the image into a color fingerprint image according to the second digit signal, and Identify grayscale fingerprint images and color fingerprint images.

The invention further provides a fingerprint identification device for recognizing a fingerprint of a finger image. The identification device comprises a photoelectric sensor module, at least one first light emitting component, at least one second light emitting component, an analog/digital conversion module and a processor module. Among them, photoelectric sensor module There is a light receiving surface for the finger to contact. The first illuminating element emits a non-visible line toward the finger, and the second illuminating element emits a visible line toward the finger. The analog/digital conversion module is electrically connected to the photoelectric sensor module, and the processor module is electrically connected to the analog/digital conversion module.

Wherein, the non-visible light penetrates the inside of the finger and then reflects to the photosensor module The light sensor module receives at least one non-visible light intensity signal of the non-visible light line, and the visible light line is reflected to the photoelectric sensor module through the surface of the finger, so that the photoelectric sensor module receives at least one visible light intensity signal of the visible light. The photoelectric sensor module converts the non-visible light intensity signal into a non-visible light current signal and converts the visible light intensity signal into a visible light current signal. The analog/digital conversion module converts the non-visible current signal into a first digital signal and converts the visible current signal into a second digital signal. The processor module respectively outputs the first digital signal into a grayscale fingerprint image and outputs the second digital signal as a color fingerprint image for identification.

Another identification method for authenticating fingerprints according to the present invention includes the following Step: placing a finger on a photoelectric sensor module; emitting a visible light line toward the finger by a second light emitting component; and the visible light is reflected to the photoelectric sensor module through the surface of the finger, so that the photoelectric sensor module receives at least visible light a visible light intensity signal; the photoelectric sensor module converts the visible light intensity signal into at least one visible light current signal, and the photoelectric sensor transmits the visible light current signal to a analog/digital conversion module; the analog/digital conversion module converts the visible light current signal into at least a second digital signal, the analog/digital conversion module transmits the second digital signal to a processor module; the processor module converts the second digital signal into a color fingerprint image and/or a grayscale fingerprint image according to the second digital signal. Color fingerprint images and/or grayscale fingerprint images are identified.

The effect of the invention is to use the photoelectric sensor module to receive the penetrating finger The non-visible light line and the visible light reflected by the finger, and simultaneously recognize the grayscale fingerprint image and the color fingerprint image of the finger, so as to prevent the lack of fingerprint identification, thereby improving the authenticity of the recognition. Therefore, the fingerprint identification device of the present invention can be applied to the inside of the handheld device by the light, thin, short, and small characteristics of the photoelectric sensor module, and the optical fingerprint reader of the prior art can be solved by being too large to be used. Handheld device problems. Moreover, the sensing method of the photoelectric separation can solve the problem that the capacitive fingerprint identifier of the prior art is susceptible to environmental static electricity, and does not require the protection of the sapphire substrate of the prior art, thereby greatly reducing the manufacturing cost. .

Furthermore, if the gelatinized fake finger is designed with a pseudo-microvessel, the chromaticity coordinates can be used. The interactive conversion of the axis re-verifies whether the second skin tone threshold is preset by the second chromaticity coordinate axis. In order to prevent the unscrupulous person from making the forged fingerprint according to the skin color change characteristic of the first chromaticity coordinate axis, the loophole in the fingerprint identification is prevented, thereby improving the authenticity of the authenticity fingerprint.

1‧‧‧ Identification device

10‧‧‧Functional circuit board

11‧‧‧Photoelectric sensor module

111‧‧‧Photoelectric sensing components

1111‧‧‧ Visible light sensing chip

1112‧‧‧Non-visible sensing chip

112‧‧‧Light receiving surface

113‧‧‧ side

114‧‧‧scattering media

12‧‧‧First light-emitting element

13‧‧‧Second light-emitting element

14‧‧‧ Analog/Digital Converter Module

15‧‧‧Processor Module

151‧‧‧ analysis program

152‧‧‧Transition program

153‧‧‧Verification program

2‧‧‧ fingers

21‧‧‧Skin Valley

22‧‧‧Skin ripples

3‧‧‧Color fingerprint image

31‧‧‧Subimage

IL‧‧‧ non-visible line

VL‧‧ Visible light

IS1‧‧‧Non-visible intensity signal

IS2‧‧‧ visible light intensity signal

PS1‧‧‧ non-visible current signal

PS2‧‧‧ Visible current signal

DS1‧‧‧ first digit signal

DS2‧‧‧ second digit signal

1 is a block diagram of a fingerprint identification device of the present invention; FIG. 2 is a schematic diagram of a fingerprint identification device of the present invention; and FIG. 3 is a schematic diagram of a photoelectric sensor module of the fingerprint identification device of the present invention; The figure is a schematic flow chart of the fingerprint identification device method of the present invention; FIG. 5 is a schematic flow chart of identifying a color fingerprint image according to the present invention; FIG. 6 is a schematic diagram of capturing a color fingerprint image according to the present invention; The first chromaticity coordinate axis diagram of the real fingerprint of the present invention; FIG. 8 is a schematic diagram of the first chromaticity coordinate axis of the forged fingerprint of the present invention; 9 is a schematic diagram of a second chromaticity coordinate axis of the real fingerprint of the present invention; FIG. 10 is a schematic diagram of a second chromaticity coordinate axis of the forged fingerprint of the present invention; and FIG. 11 is another flow diagram of the fingerprint identification method of the present invention .

Please refer to FIG. 1 to FIG. 3 , which are block diagrams, architecture diagrams and schematic diagrams of photoelectric sensor modules of the fingerprint identification device of the present invention. The fingerprint identification device 1 includes a functional circuit board 10, a photosensor sensor 11, a first light emitting component 12, at least one second light emitting component 13, and an analog/digital converter module 14 (A/D). Converter) and a processor module 15. The functional circuit board 10 is provided with the photoelectric sensor module 11, the first light-emitting element 12 and the second light-emitting element 13 electrically disposed thereon. The first light emitting element 12 and the second light emitting element 13 include, but are not limited to, light emitting diodes.

Furthermore, the photoelectric sensor modules 11 are electrically connected to the analog/digital conversion module 14 and the processor module 15, respectively. In this embodiment, the analog/digital conversion module 14 and the processor module 15 can be electrically disposed on the functional circuit board 10, but not limited thereto. The analog/digital conversion module 14 and the processor module 15 can be mounted on a portable electronic device (not shown), and the photoelectric sensor module 11 can be electrically connected to each other by an external electrical connection. The analog/digital conversion module 14 and the processor module 15 in the portable electronic device perform identification processing.

In the present invention, the photosensor module 11 is composed of a plurality of arrays of photo-sensing elements 111, which include a visible light sensing wafer 1111 and a non-visible light sensing wafer 1112. The wafer 1111 and the non-visible light sensing wafer 1112 are adjacently arranged, and a photoreceiving surface 112 is simultaneously formed by the photodetecting elements 111 for contacting a finger 2 to the light receiving surface 112. Furthermore, it further includes a scattering medium 114, A scattering medium 114 is mainly disposed on the light receiving surface 112 of the photosensor module 11, but is not limited thereto. In a preferred embodiment, the scattering medium 114 covers the light receiving surface 112 and the peripheral side surface 113 of the photosensor module 11 at the same time, and the surface of the scattering medium 114 forms an interface for the finger 2 to press. In the present invention, when the light emitted by the first light-emitting element 12 and the second light-emitting element 13 enters the scattering medium 114, the light can be homogenized by the scattering medium 114, so that the scattering medium 114 forms a uniform surface. The light source, in turn, allows the finger 2 to have the most complete light receiving effect.

In the present invention, the first light-emitting element 12 and the second light-emitting element 13 can be respectively phased The first light-emitting element 12 and the second light-emitting element 13 are packaged together or the first light-emitting element 12 and the second light-emitting element 13 are separately packaged, and only need to be separately packaged. The first light-emitting element 12 and the second light-emitting element 13 may be disposed around the photosensor module 11. In addition, the first light-emitting element 12 can emit a non-visible light line IL (Invisible Light), the non-visible light line IL has a wavelength range of 780 nm to 3000 nm of infrared radiation, and the second light-emitting element 13 emits a visible light line VL (Visible Light) The visible light VL has a wavelength range of light ranging from 400 nm to 700 nm.

Therefore, when the finger 2 contacts the light receiving surface 112 of the photosensor module 11 In the case of the scattering medium 114, the functional circuit board 10 can drive the first light-emitting element 12 and the second light-emitting element 13 to emit the non-visible light line IL and the visible light line VL, respectively, and illuminate the finger 2 via the scattering medium 114. It should be noted that the visible light VL emitted by the second illuminating element 13 can be multiple wavelengths of light, and multiple wavelengths of light can provide more image information of the photosensor module 11 to capture multi-color fingerprint images. . When the photoelectric sensor module 11 obtains fingerprint images of visible light and non-visible light, respectively, the photoelectric sensor module 11 transmits the fingerprint images to the processor module 15.

Please refer to FIG. 4 , which is a schematic flowchart of the fingerprint identification method of the present invention, which includes the following steps: Step 210: Place the finger 2 on the light receiving surface 112 of the photoelectric sensor module 11; Step 220: First light The component 12 emits a non-visible light line IL toward the finger 2 and the second light-emitting element 13 emits a visible light line VL toward the finger 2; Step 230: The non-visible light line IL penetrates the inside of the finger 2 and then reflects to the photosensor module 11 to make the photoelectric The sensor module 11 receives at least one non-visible light intensity signal IS1 (Intensity Signal) of the non-visible light line IL, and the visible light line VL is reflected to the photosensor module 11 via the surface of the finger 2, so that the photosensor module 11 receives the visible light line VL. At least one visible light intensity signal IS2; step 240: the photoelectric sensor module 11 converts into at least one non-visible current signal PS1 (Photocurrent Signal) according to the non-visible light intensity signal IS1, and the photoelectric sensor module 11 converts into at least one visible light according to the visible light intensity signal IS2 Current signal PS2, the photoelectric sensor transmits the non-visible current signal PS1 and the visible light current signal PS2 to the class The digital/digital conversion module 14 converts the at least one first digital signal DS1 (Digital Signal) according to the non-visible current signal PS1, and the analog/digital conversion module 14 converts according to the visible current signal PS2. At least one second digit signal DS2; and step 260: the processor module 15 converts into a grayscale fingerprint image according to the first digital signal DS1, and the processor module 15 converts into a color fingerprint according to the second digital signal DS2. Image, and identify grayscale fingerprint images and color fingerprint images.

In step 210, the finger 2 is first pressed on the light receiving surface 112 of the photosensor module 11, but not limited thereto. The finger 2 can also be pressed against the surface of the scattering medium 114 on the light receiving surface 112. Next, the functional circuit board 10 drives the first light-emitting element 12 to emit the non-visible light line IL to the finger 2, and drives the second light-emitting element 13 to emit the visible light line VL to the finger 2.

In step 220, the order of illumination of the first light-emitting element 12 and the second light-emitting element 13 is provided with at least the following mode: in the first mode, the first light-emitting element 12 and the second light-emitting element 13 respectively emit non-visible light lines IL and visible light. Line VL. In the second mode, after the first light-emitting element 12 emits the non-visible light line IL and obtains the gray-scale fingerprint image, the second light-emitting element 13 emits the visible light line VL. In the third mode, the first light-emitting element 12 and the second light-emitting element 13 may cross the non-visible light line IL and the visible light line VL in chronological order, that is, the first light-emitting element 12 turns off the non-visible light line IL to the finger 2, and then turns off. The second light-emitting element 13 emits a visible light VL to the finger 2, and the repeated turns alternately emit a non-visible light line IL and a visible light line VL to the finger 2.

In step 230, the surface of the finger 2 has a skin grain trough 21 and a skin ripple peak 22, and since the skin grain trough 21 is in contact with the light receiving surface 112, the non-visible light line IL penetrates the inside of the finger 2, and then passes through the skin grain trough 21 Directly entering the light receiving surface 112 to obtain a non-visible light intensity signal IS1 having a high light intensity. Since there is a gap between the skin ripple peak 22 and the light receiving surface 112, a part of the non-visible light line IL is scattered and refracted by the inside of the finger to form the scattering and refraction, and then enters the light receiving surface 112, thereby obtaining a light. The low intensity non-visible light intensity signal IS1, in turn, gives a comparison of the light intensity between the skin grain trough 21 and the skin ripple peak 22.

Similarly, the second light-emitting element 13 is described by a multi-wavelength light source due to the texture The valley 21 contacts the light receiving surface 112, and the visible light VL can be directly reflected to the photosensor module 11 via the grain valley 21 to obtain a visible light intensity signal IS2 having a high light intensity. Similarly, there is a gap between the skin ripple peak 22 and the light receiving surface 112, and the visible light VL enters the skin ripple peak 22 to form scattering and refraction, and then is reflected to the photosensor module 11, thereby obtaining a visible light intensity with low light intensity. Signal IS2.

In step 240, the photosensor module 11 will receive synchronously: entering the finger 2 Afterwards, the non-visible light intensity signal IS1 of the skin trough 22 and the skin ripple peak 22 is penetrated, and converted into the non-visible current signal PS1 according to the non-visible light intensity signal IS1. Similarly, the photoelectric sensor module 11 synchronously receives the visible light intensity signal IS2 reflected by the skin grain trough 21 and the skin ripple peak 22 from the fingerprint 2, and is converted into the visible light current signal PS2 according to the visible light intensity signal IS2, and the photoelectric sensor module 11 The non-visible current signal PS1 and the visible light current signal PS2 are respectively sent to the analog/digital conversion module 14 for processing.

It should be noted that the photosensor module 11 of the present invention generally uses photovoltaic, Photoelectric conversion methods such as light conduction or light emission work. For example, the photovoltaic conversion method usually exists on the junction of two different materials. When the visible light VL or the non-visible light IL is irradiated to the junction, an illuminance-related output voltage is generated at both ends of the junction, for example, The semiconductor material yttrium, lanthanum, or indium hydride is operated using its pn junction. The light-conducting conversion method is usually made of a semiconductor material, and its resistance decreases as the illuminance increases. The conductivity is generated because the material absorbs the energy carried by the incident photons to generate charge carriers. The light emission conversion method emits electrons out of orbit when the incident light energy is high enough. The photoelectric conversion mode of the photoelectric sensor module 11 is only described in an embodiment, and is not limited thereto. The photoelectric sensor module 11 can select a corresponding photoelectric conversion mode according to the needs of use.

In step 250, the analog/digital conversion module 14 is based on the non-visible current signal. The strength of the PS1 is converted into at least one first digital signal DS1, and the analog/digital conversion module 14 converts into at least one second digital signal DS2 according to the strength of the visible current signal PS2. In addition, the analog/digital conversion module 14 can further perform signal filtering or signal amplification processing on the first digital signal DS1 or the second digital signal DS2 according to actual needs, and transmit the processing to the processor module 15.

In step 260, the processor module 15 includes an analysis program 151 and a conversion process. Formula 152 and a verification program 153. The analysis program 151 processes the first digital signal DS1 to obtain a grayscale fingerprint image corresponding to the skin grain trough 21 (bright area) and the skin ripple peak 22 (dark area) of the finger 2. The verification program 153 verifies the identity of the user based on the grayscale fingerprint image (non-visible light).

In addition, the analysis program 151 of the processor module 15 is used for a first color model. (Color Model) Analyze color fingerprint images (visible light), such as the RGB Color Model, but not limited to this. The conversion program 152 is configured to convert a first chromaticity coordinate axis (Chromatic Coordinates) of the first color model into a second chromaticity coordinate axis of the second color model. The verification program 153 is used to verify whether the second chromaticity coordinate axis conforms to a second skin color threshold (Skin Color Threshold).

Please refer to FIG. 5 , which is a schematic flowchart of identifying a color fingerprint image according to the present invention, including the following steps: Step 310: Capture a color fingerprint image 3 of the finger 2; Step 320: Perform an analysis program 151 to A color model analyzes the color fingerprint image 3 to obtain a first chromaticity coordinate axis of the corresponding color fingerprint image 3; step 330: executes a conversion program 152 to convert the first chromaticity coordinate axis with the second color model a second chromaticity coordinate axis; step 340: executing a verification program 153, comparing whether the second chromaticity coordinate axis meets a preset second skin color threshold; step 350: if the second chromaticity coordinate axis meets the second skin color threshold, Determining that the finger is a real fingerprint; and step 360: determining that the finger is a forged fingerprint if the second chromaticity coordinate axis does not meet the second skin color threshold.

In the step 310, in the embodiment, the light-emitting element is described as a multi-wavelength light source, but is not limited thereto. The visible light VL is reflected by the skin troughs 21 and the skin ripples 22 of the finger 2, so that the photosensor module 11 can receive the corresponding color fingerprint image 3 and transmit it to the processor module 15. Please refer to FIG. 6 , which is a schematic diagram of capturing a fingerprint image according to the present invention. The processor module 15 can cut a complete color fingerprint image 3 into a plurality of sub-images 31. Then, these sub-images 31 are sequentially transmitted to the analysis program 151 in step 320, respectively, for analysis processing.

In step 320, the analysis program 151 performs color model analysis on each of the sub-images 31 of the color fingerprint image 3. Please refer to FIG. 7 , which is a schematic diagram of the first chromaticity coordinate axis of the real fingerprint of the present invention. The sub-image 31 of one of the color fingerprint images 3 is subjected to arithmetic processing through the analysis program 151, and the color fingerprint image 3 is analyzed by the first color model to obtain a first chromaticity coordinate axis. In this embodiment, the first color model may be a RGB Color Model, but is not limited thereto.

The X-axis coordinate axis of the first chromaticity coordinate axis represents 640x480 resolution, and the Y-axis coordinate axis represents pixels. The curve R represents the red wavelength, the curve G represents the green wavelength, and the curve B represents Blue wavelength. The above-mentioned X-axis coordinate axis is not limited to 640x480 resolution, and it can also be 320x240 resolution. The X-axis coordinate axis can select the cutting size corresponding to the resolution according to actual needs. Since the skin color changes during the pressing of the finger in the photoelectric sensor module 11, that is, a part of the blood of the finger will remain in the finger pressing area, and the remaining blood will flow from the pressing area to the outside of the pressing area, so that the finger A significant skin tone change is formed when pressed. Therefore, as can be seen from Fig. 7, the red wavelength curve R is significantly higher than the green wavelength curve G and the blue wavelength curve B due to the factor of the finger portion leaving the blood at the pressing area. .

Based on the above principle, if a fake fingerprint is pressed on the photosensor module 11, Then the red wavelength curve R of the first chromaticity coordinate axis will not change significantly. Please refer to FIG. 8 , which is a schematic diagram of the first chromaticity coordinate axis of the forged fingerprint of the present invention. It can be clearly seen from the figure that since the forged fingerprint has no blood flow characteristics and no skin color change, the red wavelength curve R is almost overlapped with the green wavelength curve G and the blue wavelength curve B, and can be judged as forgery. fingerprint.

Further, after step 320, the method further includes the following steps: the verification program 153 compares whether the first chromaticity coordinate axis meets the preset first skin color threshold value, thereby determining the authentic fingerprint. In detail, the present embodiment satisfies the following formula, but is not limited thereto: 1 R-min(B, G)>Z; and 2 10<Z<100.

Where R represents a red wavelength value, G represents a green wavelength value, B represents a blue wavelength value, and Z represents a first skin tone threshold. When 10 < Z < 100 is satisfied, then step 330 is entered. If 10<Z<100 cannot be satisfied, the forged fingerprint is determined. It should be noted that the above formula is only an embodiment, and is not limited to the scope of patent protection of the present invention, and may also be adapted according to actual needs. The formula is used to verify whether the first chromaticity coordinate axis conforms to the first skin color threshold, and the set formula is stored in the verification program 153.

However, there is still a case where a forged fingerprint made of silicone material is specially designed. The pseudo-microvessels are forged such that the red wavelength curve R is higher than the green wavelength curve G and the blue wavelength curve B. Therefore, the verification can be performed again through step 330.

In step 330, the conversion program 152 converts the first chromaticity coordinate axis into a second chromaticity coordinate axis in accordance with the second color model. For example, the conversion program 152 converts the RGB Color Model into a CMYK Color Model and converts the first chromaticity coordinate axis of the red, blue, and green color model into a printed color model. The second chromaticity coordinate axis, the conversion formula is as follows: t _RGB ={ R , G , B }

RGB chromaticity coordinate axis is first converted to tri-color

t _CMY ={ C' , M' , Y' }={1- R ,1- G ,1- B }

If min{ C' , M' , Y' }=1, then t _CMYK ={0,0,0,1}

Otherwise, convert to a quad color

K =min{ C' , M' , Y' }

Therefore, the RGB chromaticity coordinate axis is converted into a CMYK chromaticity coordinate axis by the conversion program 152. It should be noted that the conversion of the first chromaticity coordinate axis to the second chromaticity coordinate axis is not limited to the conversion of the RGB chromaticity coordinate axis into the CMYK chromaticity coordinate axis. It can also be required to convert the RGB chromaticity coordinate axis to the YUV chromaticity coordinate axis or convert the RGB chromaticity coordinate axis to CIE XYZ The chromaticity coordinate axis, or the RGB chromaticity coordinate axis is converted into an HSV chromaticity coordinate axis and other interactive coordinate axis transformations to obtain skin color changes with different chromaticity coordinates. However, the first color model is not limited to a red, blue, and green color model, and the first color model may also be a YUV color model, a YCbCr color model, a RAW Bayer color model, a CCIR color model, an ITU color model, or A RAW RGB color model, the first color model can select the corresponding color model according to actual needs. Therefore, after converting the first chromaticity coordinate axis into the second chromaticity coordinate axis, the process proceeds to step 340 for verification.

In steps 340 to 360, the verification program 153 compares the second chromaticity coordinates. Whether the axis conforms to the preset second skin color threshold, thereby determining the authentic fingerprint. In this embodiment, a statistical analysis method is used to analyze the skin color distribution of real fingerprints on various chromaticity coordinate axes (such as CMYK chromaticity coordinate axis, YUV chromaticity coordinate axis, CIE XYZ chromaticity coordinate axis, or HSV chromaticity coordinate axis). In this way, the second skin color threshold corresponding to each second chromaticity coordinate axis is set.

Please refer to Figure 9 and Figure 10. Among them, the ninth figure is a schematic diagram of the second chromaticity coordinate axis of the real fingerprint of the present invention. Figure 10 is a schematic view of the second chromaticity coordinate axis of the forged fingerprint of the present invention. In this embodiment, the verification program 153 determines whether the authenticity fingerprint is determined by comparing the second chromaticity coordinate axis with the preset second skin color threshold. For example, the present embodiment satisfies the following formula, but is not limited thereto: 1Y<Z'; 210<Z'<100.

Where Y represents a yellow gradation value and Z' represents a second skin tone threshold. When 10<Z'<100 is satisfied, the verification program 153 determines that it is a real fingerprint, and if 10<Z'<100 cannot be satisfied, it is judged. Forged fingerprints. It should be noted that the above formula is only an embodiment, and is not limited to the scope of patent protection of the present invention. It may also be set according to actual requirements to determine whether the second chromaticity coordinate axis meets the second skin color threshold. The set formula is stored in the verification program 153.

In this way, if the fake finger is based on the first color model (red, blue, green, color model) To design the pseudo-microvessels, although the red wavelength curve R can be forged significantly higher than the green wavelength curve G and the blue wavelength curve B, the preset second skin color valve can still be determined by the verification program 153 with the second chromaticity coordinate axis. Value, verify whether it is a real fingerprint. If the converted second chromaticity coordinate axis meets the second skin color threshold, it is determined that the finger is a real fingerprint. If the second chromaticity coordinate axis does not meet the second skin color threshold, it is determined that the finger is a fake fingerprint.

Please refer to FIG. 11 , which is another schematic flowchart of the fingerprint identification method of the present invention. The specific implementation manner is substantially the same as the fingerprint identification method of the foregoing embodiment, and the following only describes the differences, and the rest are not in the same place. The description includes the following steps: Step 410: Place the finger 2 on the light receiving surface 112 of the photosensor module 11; Step 420: The second light emitting element 13 emits a visible line VL toward the finger 2; Step 430: Visible light VL The photoelectric sensor module 11 receives at least one visible light intensity signal IS2 of the visible light VL through the surface of the finger 2, and the photoelectric sensor module 11 converts the visible light intensity signal IS2 into at least one visible light current according to the visible light intensity signal IS2. The signal PS2, the photoelectric sensor transmits the visible light current signal PS2 to the analog/digital conversion module 14; Step 450: The analog/digital conversion module 14 converts the visible light current signal PS2 into at least one The second digital signal DS2; and step 460: the processor module 15 converts the color image into a color fingerprint image and/or a grayscale fingerprint image according to the second digital signal DS2, and performs a color fingerprint image and/or a grayscale fingerprint image. Like to identify.

In step 460, the flow of the processor module 15 for identifying the color fingerprint image is as described in the contents of FIGS. 5-10. In addition, the conversion program 152 of the processor module 15 can further convert the color fingerprint image into a grayscale fingerprint image, and then use the verification program 153 to identify the converted grayscale fingerprint image to determine whether it is a real finger.

Therefore, the fingerprint identification method and the device thereof according to the present invention use a photoelectric sensor module to receive a non-visible light line that is reflected after penetrating the inside of the finger, and is emitted through a skin ripple and a skin ripple peak from the finger. The difference of visible light intensity signals enables the photoelectric sensor module to be converted into non-visible intensity signals of different strengths, and then the analog/digital conversion module converts the non-visible intensity signals of different strengths into corresponding first digital signals. Output to the processor module for processing to obtain a grayscale fingerprint image of light and dark contrast stripes.

And, by converting the first chromaticity coordinate axis into the second chromaticity coordinate axis, verifying whether the color fingerprint image is a forged fingerprint by using the second skin color threshold preset by the second chromaticity coordinate axis. In order to prevent the unscrupulous person from making the forged fingerprint according to the skin color change characteristic of the first chromaticity coordinate axis, the loophole of fingerprint identification is prevented, thereby improving the authenticity of identifying the authentic fingerprint.

Therefore, the optical sensor module is light, thin, short, and small, so that the authenticity fingerprint identification device of the present invention can be mounted inside the handheld device, and the light of the prior art can be solved. The problem that the fingerprint reader is too large to be used in a handheld device. Moreover, the gray fingerprint image can be recognized while the grayscale fingerprint image is recognized, and whether the finger is forged is verified, thereby improving the authenticity of the finger during recognition. In this way, an illegal user cannot achieve a fraudulent fingerprint identification device by forging a finger, thereby preventing a loophole in fingerprint identification.

1‧‧‧ Identification device

10‧‧‧Functional circuit board

11‧‧‧Photoelectric sensor module

111‧‧‧Photoelectric sensing components

1111‧‧‧ Visible light sensing chip

1112‧‧‧Non-visible sensing chip

12‧‧‧First light-emitting element

13‧‧‧Second light-emitting element

14‧‧‧ Analog/Digital Converter Module

15‧‧‧Processor Module

151‧‧‧ analysis program

152‧‧‧Transition program

153‧‧‧Verification program

2‧‧‧ fingers

IL‧‧‧ non-visible line

VL‧‧ Visible light

IS1‧‧‧Non-visible intensity signal

IS2‧‧‧ visible light intensity signal

PS1‧‧‧ non-visible current signal

PS2‧‧‧ Visible current signal

DS1‧‧‧ first digit signal

DS2‧‧‧ second digit signal

Claims (16)

A fingerprint identification method includes the steps of: placing a finger on a photoelectric sensor module; emitting a non-visible light line toward the finger by a first light-emitting element; and emitting a visible light line toward the finger by a second light-emitting element; The non-visible light line is reflected by the inside of the finger and then reflected to the photosensor module, so that the photosensor module receives at least one non-visible light intensity signal of the invisible light line, and the visible light line is reflected to the photosensor module via the surface of the finger The photoelectric sensor module receives at least one visible light intensity signal of the visible light; the photoelectric sensor module converts the at least one non-visible current signal according to the non-visible light intensity signal, and the photoelectric sensor module converts according to the visible light intensity signal Forming at least one visible light current signal, the photoelectric sensor module respectively transmitting the non-visible current signal and the visible current signal to an analog/digital conversion module; the analog/digital conversion module is replaced with at least one according to the non-visible current signal a digital signal, the analog/digital Converting the module to the at least one second digit signal according to the visible current signal, the analog/digital conversion module respectively transmitting the first digit signal and the second digit signal to a processor module; and the processor module The group converts the first digital signal into a grayscale fingerprint image, and the processor module converts the color image into a color fingerprint image according to the second digital signal, and identifies the grayscale fingerprint image and the color fingerprint image. The fingerprint identification method of claim 1, wherein the processor module includes an analysis program, a conversion program, and a verification program, and the step of identifying the color fingerprint image further comprises: Performing the analysis program, analyzing the color fingerprint image by a first color model to obtain a first chromaticity coordinate axis corresponding to the color fingerprint image; executing the conversion program to perform the first color with a second color model Converting the coordinate axis into a second chromaticity coordinate axis; performing the verification program, whether the second chromaticity coordinate axis meets a preset second skin color threshold; if the second chromaticity coordinate axis meets the second skin color threshold, Then determining that the finger is a real fingerprint; and if the second chromaticity coordinate axis does not meet the second skin color threshold, determining that the finger is a forged fingerprint. The fingerprint identification method of claim 2, wherein the color fingerprint image is cut into a plurality of sub-images, and the sub-images are sequentially transmitted to the analysis program for analysis processing. The fingerprint identification method of claim 2, wherein the step of analyzing the color fingerprint image by the first color model further comprises: setting the first color model to an RGB color model; and obtaining corresponding according to the red, blue, and green color model The first chromaticity coordinate axis obtains a red wavelength curve, a green wavelength curve and a blue wavelength curve according to the first chromatic coordinate axis; and determines whether the red wavelength curve and the green wavelength curve and the blue wavelength curve are mutually Overlapping; and if the red wavelength curve does not overlap the green wavelength curve and the blue wavelength curve, the conversion program is executed. The fingerprint identification method of claim 2, wherein the first of the corresponding color fingerprint images is obtained The step of the chromaticity coordinate axis further includes: executing the verification program to determine whether the first chromaticity coordinate axis conforms to a preset first skin color threshold. A fingerprint identification device for recognizing a fingerprint image of a finger, the identification device comprising: a photoelectric sensor module having a light receiving surface for the finger to contact thereon; at least one first light emitting element facing The finger emits a non-visible light line; at least one second light-emitting element emits a visible light line toward the finger; an analog/digital conversion module electrically connected to the photoelectric sensor module; and a processor module electrically connected The invisible/digital conversion module; wherein the non-visible light line penetrates the inside of the finger and then is reflected to the photosensor module, so that the photosensor module receives at least one non-visible light intensity signal of the invisible line, the visible light line Reflecting to the photosensor module via the surface of the finger, the photosensor module receives at least one visible light intensity signal of the visible light, and the photosensor module respectively converts the non-visible light intensity signal into a non-visible current signal and The visible light intensity signal is converted into a visible light current signal, and the analog/digital conversion mode component Converting the non-visible current signal into a first digital signal and converting the visible current signal into a second digital signal, the processor module respectively outputting the first digital signal into a grayscale fingerprint image and the second digital signal The output is a color fingerprint image for identification. The fingerprint identification device of claim 6, wherein the photosensor module is composed of a plurality of arrayed photo-sensing elements, the photo-sensing element includes a plurality of visible-light sensing wafers and a plurality of non-visible light The sensing wafers are arranged adjacent to each other and constitute the light receiving surface. The fingerprint identification device of claim 7, further comprising a scattering medium, the scattering medium is covered Covering the light receiving surface of the photosensor module, the scattering medium is for the finger to contact. The fingerprint identification device of claim 6, wherein the processor module further comprises: an analysis program, analyzing the color fingerprint image by a first color model to obtain a first chromaticity coordinate axis; a conversion program, Converting the first chromaticity coordinate axis into a second chromaticity coordinate axis by a second color model; and a verification program for comparing whether the second chromaticity coordinate axis conforms to a preset second skin color threshold. The fingerprint identification device of claim 9, wherein the processor module can cut the fingerprint image into a plurality of sub-images, and sequentially transmit the sub-images to the analysis program for analysis processing. A fingerprint identification method includes the steps of: placing a finger on a photosensor module; emitting a visible light line toward the finger by a second light emitting component; and the visible light is reflected to the photosensor module via the surface of the finger Having the photoelectric sensor module receive at least one visible light intensity signal of the visible light; the photoelectric sensor module converts the visible light intensity signal into at least one visible light current signal, and the photoelectric sensor transmits the visible light current signal to an analog/digital position a conversion module; the analog/digital conversion module converts the visible light current signal into at least one digital signal, the analog/digital conversion module transmits the digital signal to a processor module; and the processor module is based on the digital Converting a signal into a color fingerprint image and/or a grayscale index The image is imaged and the color fingerprint image and/or the grayscale fingerprint image is identified. The fingerprint identification method of claim 11, wherein the processor module includes an analysis program, a conversion program, and a verification program, and the step of identifying the color fingerprint image further comprises: executing the analysis program to a first color model analyzes the color fingerprint image to obtain a first chromaticity coordinate axis corresponding to the color fingerprint image; and executing the conversion program to convert the first chromaticity coordinate axis into a second color by a second color model a chromaticity coordinate axis; executing the verification program, whether the second chromaticity coordinate axis meets a preset second skin color threshold; if the second chromaticity coordinate axis meets the second skin color threshold, determining that the finger is a a true fingerprint; and if the second chromaticity coordinate axis does not conform to the second skin color threshold, determining that the finger is a forged fingerprint. The fingerprint identification method of claim 12, wherein the fingerprint image is cut into a plurality of sub-images, and the sub-images are sequentially transmitted to the analysis program for analysis processing. The fingerprint identification method of claim 12, wherein the step of analyzing the color fingerprint image by the first color model further comprises: setting the first color model to an RGB color model; and obtaining corresponding according to the red, blue, and green color model The first chromaticity coordinate axis obtains a red wavelength curve, a green wavelength curve and a blue wavelength curve according to the first chromatic coordinate axis; and determines whether the red wavelength curve and the green wavelength curve and the blue wavelength curve are mutually Overlapping; If the red wavelength curve does not overlap the green wavelength curve and the blue wavelength curve, the conversion program is executed. The fingerprint identification method of claim 12, wherein the step of obtaining the first chromaticity coordinate axis of the fingerprint image further comprises: executing the verification program, whether the first chromaticity coordinate axis conforms to a preset one A skin tone threshold. The fingerprint identification method of claim 12, wherein the conversion program further converts the color fingerprint image into the grayscale fingerprint image, and determines, by the verification program, whether the grayscale fingerprint image is a real fingerprint.