CN111563454A

CN111563454A - Hand vein identification method and device for double in-vivo verification

Info

Publication number: CN111563454A
Application number: CN202010380694.1A
Authority: CN
Inventors: 郑音飞
Original assignee: Zhejiang University ZJU
Current assignee: Zhejiang University ZJU
Priority date: 2020-05-08
Filing date: 2020-05-08
Publication date: 2020-08-21
Anticipated expiration: 2040-05-08
Also published as: CN111563454B

Abstract

The invention discloses a hand vein identification method and device for double in-vivo authentication, and relates to the field of identity authentication. The method comprises the following steps: acquiring physiological parameters of a hand to be verified; performing action characteristic living body verification when the physiological parameter is larger than a first preset threshold value; the palm similarity and the back similarity are successfully calculated through the in vivo verification; and if the palm similarity and the hand back similarity are both greater than a second preset threshold, the hand vein recognition is successful. The invention adopts a mode of combining action characteristics and physiological parameter detection to carry out double in vivo verification, respectively extracts the palm vein image and the back hand vein image to carry out vein identification, improves the reliability through the double in vivo verification and the double vein identification of the palm vein image and the back hand vein image, and is particularly suitable for occasions with particularly high reliability requirements.

Description

Hand vein identification method and device for double in-vivo verification

Technical Field

The invention relates to the field of identity authentication, in particular to a hand vein identification method and device for double in-vivo authentication.

Background

The vein identification is to acquire an image of a hand vein through a near-infrared camera, store the digital image of the vein in a computer system and realize characteristic value storage. When vein is compared, a vein image is adopted in real time, advanced filtering, image binarization and thinning means are used for carrying out feature extraction on the digital image, and a complex matching algorithm is adopted to be compared and matched with a vein feature value stored in a computer system host, so that identity identification is carried out on an individual, and the identity is confirmed. The vein is located inside the human body and is not influenced by rough epidermis and external environment, the vein recognition has the advantages of high accuracy, difficulty in copying, safety, convenience and the like, and the vein recognition is already tried in the fields of entrance guard, social security and the like.

Most of vein recognition equipment in the market adopts a vein recognition mode of the back of the hand, the palm or the fingers, so that the number of feature points is relatively small, and the recognition reliability and accuracy are relatively low. Although the veins are hidden in the skin of a human body, traces are not easy to leave, and the counterfeiting difficulty is higher than that of other biological identification modes, the veins can still be counterfeited and cracked, the most common cracking mode is to draw lines on paper, wear rubber gloves and draw lines on the rubber gloves, for example, on a Chaos Communication convergence hacker held by Laibitin in 2018, researchers Jan Krissler and Julianalbrecht successfully deceive a vein authentication system through a wax hand model; the simplest cracking mode is that vein pattern is obtained by vein collection equipment, the vein pattern of fingers is copied, and the vein pattern can be cracked by the pictures. Therefore, the existing vein recognition device has the problems of low recognition reliability and easy cracking.

Disclosure of Invention

The invention aims to provide a hand vein identification method and device based on double in-vivo verification, and solves the problems that existing vein identification equipment is low in identification reliability and easy to crack.

In order to achieve the purpose, the invention provides the following scheme:

a double-living body verification hand vein identification method comprises the following steps:

acquiring physiological parameters of a hand to be verified detected by a physiological parameter detection sensor;

if the physiological parameter is larger than a first preset threshold value, performing action characteristic living body verification on the hand to be verified to obtain a verification result;

if the verification result shows that the in-vivo verification is successful, acquiring a palm vein image and a back hand vein image of the hand to be verified;

acquiring pre-stored palm vein storage images and hand back vein storage images;

respectively calculating the palm similarity of the palm vein image and the palm vein storage image and the hand back similarity of the hand back vein image and the hand back vein storage image;

and if the palm similarity and the hand back similarity are both greater than a second preset threshold, the hand vein recognition of the hand to be verified is successful.

Optionally, the acquiring of the physiological parameter of the hand to be verified detected by the physiological parameter detection sensor specifically includes:

and acquiring the pulse blood oxygen value of the hand to be verified detected by the blood oxygen heart rate sensor.

Optionally, the performing the living body verification of the motion characteristic on the hand to be verified to obtain a verification result specifically includes:

acquiring a fist making image of the hand to be verified;

if the hand to be verified in the fist image is in a fist state, acquiring a half fist image of the hand to be verified;

if the hand to be verified in the half-fist image is in a half-fist state, acquiring hand images of the hand to be verified in different fist states from the fist state to the half-fist state;

detecting optical flow characteristics of the hand image by using an optical flow method, and comparing the similarity of the optical flow characteristics of the hand image and pre-stored optical flow characteristics;

if the similarity is larger than a third preset threshold, the living body verification is successful;

and if the similarity is less than or equal to the third preset threshold, the in-vivo verification fails.

Optionally, the detecting, by using an optical flow method, the optical flow features of the hand image, and comparing the similarity between the optical flow features of the hand image and the pre-stored optical flow features specifically include:

taking the hand image of the ith frame as a first comparison image, and extracting an interested region of the first comparison image to obtain a first interested region;

taking the hand image of the (i + 1) th frame as a second comparison image, and extracting an interested region of the second comparison image to obtain a second interested region;

detecting the positions of which the variation amplitudes in the first region of interest and the second region of interest are larger than a fourth preset threshold value by using an optical flow method to obtain optical flow characteristics;

returning to the step of taking the hand image of the ith frame as a first comparison image, extracting an interested area of the first comparison image to obtain a first interested area, and obtaining optical flow characteristics of all the hand images;

acquiring prestored optical flow characteristics;

and respectively comparing all the optical flow characteristics with the corresponding pre-stored optical flow characteristics to obtain the similarity.

A dual in-vivo verified hand vein recognition device, comprising: a top collection area, a hand placement panel area, and a bottom collection area; the top collection area and the hand placement panel area are both connected with the bottom collection area;

the top acquisition area is positioned at the top of the hand vein recognition device and is used for acquiring a hand back vein image of the hand to be verified;

the hand placing panel area is positioned below the top collecting area and is used for collecting physiological parameters of the hand to be verified;

the bottom acquisition area is positioned at the bottom of the hand vein recognition device and below the hand placing panel area, and is used for acquiring and processing in-vivo verification information to obtain a hand vein recognition result; the living body verification information includes the hand back vein image, the physiological parameter, and the palm vein image of the hand to be verified.

Optionally, the top acquisition region specifically comprises: a top camera, a top light source and a display screen;

the top camera is used for collecting a hand back vein image of the hand to be verified; the output end of the top camera is connected with the bottom acquisition area;

the top light source is arranged corresponding to the top camera and used for irradiating the back of the hand to be verified;

the display screen is connected with the output end of the bottom acquisition area and used for displaying the hand vein recognition result of the bottom acquisition area.

Optionally, the hand placement panel area specifically includes: a hand placing area, a hand texture map, a bulge and a physiological parameter detection sensor;

the hand placing area is located right below the top camera and used for placing the hand to be verified;

the hand texture map is carved in the center of the hand placement area, the bulge is positioned at the first middle finger joint of the hand texture map, and the hand texture map and the bulge are used for displaying the placement position of the hand to be verified;

the physiological parameter detection sensor is positioned below the protrusion and is used for detecting the physiological parameter.

Optionally, the bottom acquisition region specifically comprises: the hand vein recognition system comprises a bottom camera, a bottom light source, a hand vein recognition system and a power supply;

the bottom camera is used for collecting a palm vein image of the hand to be verified; the output end of the bottom camera is connected with the input end of the hand vein recognition system;

the bottom light source is arranged corresponding to the bottom camera and used for irradiating the palm of the hand to be verified;

the hand vein recognition system is respectively connected with the top camera and the physiological parameter detection sensor; the hand vein recognition system is used for acquiring the in-vivo verification information and processing the in-vivo verification information to obtain a hand vein recognition result;

the power supply is respectively connected with the top light source, the bottom light source, the physiological parameter detection sensor and the hand vein recognition system, and the power supply is used for supplying power to the top light source, the bottom light source, the physiological parameter detection sensor and the hand vein recognition system.

Optionally, the hand vein recognition system specifically includes:

the physiological parameter acquisition module is used for acquiring the physiological parameters of the hand to be verified detected by the physiological parameter detection sensor;

the action characteristic living body verification module is used for performing action characteristic living body verification on the hand to be verified when the physiological parameter is larger than a first preset threshold value to obtain a verification result;

the vein image acquisition module is used for acquiring a palm vein image and a back vein image of the hand to be verified when the verification result shows that the living body verification is successful;

the vein storage image acquisition module is used for acquiring pre-stored palm vein storage images and hand back vein storage images;

the similarity calculation module is used for calculating the palm similarity of the palm vein image and the palm vein storage image and the hand back similarity of the hand back vein image and the hand back vein storage image respectively;

and the hand vein recognition module is used for successfully recognizing the hand veins of the hand to be verified when the palm similarity and the hand back similarity are both greater than a second preset threshold value.

Optionally, the action feature in-vivo verification module specifically includes:

the fist image acquisition unit is used for acquiring a fist image of the hand to be verified;

a half-fist image obtaining unit, configured to obtain a half-fist image of the hand to be verified when the hand to be verified in the fist image is in a fist-making state;

a hand image acquiring unit configured to acquire, when the hand to be verified in the half-fist image is in a half-fist state, hand images of the hand to be verified in different fist states between the first state and the half-fist state;

a similarity comparison unit for detecting the optical flow characteristics of the hand image by an optical flow method and comparing the similarity between the optical flow characteristics of the hand image and the pre-stored optical flow characteristics;

a living body verification success unit, configured to, when the similarity is greater than a third preset threshold, succeed in living body verification;

a living body authentication failure unit configured to fail the living body authentication when the similarity is less than or equal to the third preset threshold.

According to the specific embodiment provided by the invention, the invention discloses the following technical effects:

the invention provides a hand vein identification method and device for double in-vivo verification. The method comprises the following steps: acquiring physiological parameters of a hand to be verified detected by a physiological parameter detection sensor; if the physiological parameter is larger than a first preset threshold value, performing action characteristic living body verification on the hand to be verified to obtain a verification result; if the verification result shows that the living body verification is successful, acquiring a palm vein image and a back vein image of the hand to be verified; acquiring pre-stored palm vein storage images and hand back vein storage images; respectively calculating the palm similarity of the palm vein image and the palm vein storage image and the hand back similarity of the hand back vein image and the hand back vein storage image; and if the palm similarity and the hand back similarity are both greater than a second preset threshold, the hand vein recognition of the hand to be verified is successful. The invention adopts a mode of combining action characteristics and physiological parameter detection to carry out double in vivo verification, respectively extracts the palm vein image and the back hand vein image to carry out vein identification, improves the reliability through the double in vivo verification and the double vein identification of the palm vein image and the back hand vein image, and is particularly suitable for occasions with particularly high reliability requirements.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without inventive exercise.

FIG. 1 is a flow chart of a hand vein recognition method according to an embodiment of the present invention;

FIG. 2 is a block diagram of a hand vein recognition apparatus according to an embodiment of the present invention;

FIG. 3 is a circuit diagram of a hand vein recognition device according to an embodiment of the present invention;

FIG. 4 is a bottom view of a top acquisition region according to embodiments of the present invention;

FIG. 5 is a block diagram of a hand placement panel area according to an embodiment of the present invention;

FIG. 6 is a view showing a structure of a projection according to an embodiment of the present invention;

FIG. 7 is a flow chart of data processing of the blood oxygen heart rate sensor according to an embodiment of the present invention;

FIG. 8 is a top view of a bottom acquisition region according to an embodiment of the present invention;

FIG. 9 is a flow chart illustrating the use of a hand vein recognition device according to an embodiment of the present invention;

FIG. 10 is a flowchart of an identity registration process according to an embodiment of the present invention;

FIG. 11 is a flowchart of an embodiment of an action feature live registration;

FIG. 12 is a flow chart illustrating the processing of stored pictures according to an embodiment of the present invention;

FIG. 13 is a flow chart of an authentication process according to an embodiment of the present invention;

FIG. 14 is a flow chart of an embodiment of the invention for in vivo verification of an action signature;

FIG. 15 is a flowchart illustrating the processing of hand images according to an embodiment of the present invention.

Description of the symbols: 1. a top collection region; 2. a hand placement panel area; 3. a bottom collection area; 4. a top camera; 5. a top light source; 6. a display screen; 7. a hand placement area; 8. hand texture maps; 9. a protrusion; 10. a physiological parameter detection sensor; 11. a label; 12. a bottom camera; 13. a bottom light source; 14. a main controller; 15. a power source.

Detailed Description

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in further detail below.

Fig. 1 is a flowchart of a hand vein recognition method according to an embodiment of the present invention. Referring to fig. 1, the hand vein recognition method includes:

step 101, acquiring the physiological parameters of the hand to be verified detected by the physiological parameter detection sensor.

Step 101 specifically includes:

And 102, if the physiological parameter is larger than a first preset threshold value, performing action characteristic living body verification on the hand to be verified to obtain a verification result. The first preset threshold is 90.

The method comprises the following steps of performing action characteristic living body verification on a hand to be verified to obtain a verification result, and specifically comprises the following steps:

and acquiring a fist making image of the hand to be verified.

And if the hand to be verified in the fist image is in a fist state, acquiring a half fist image of the hand to be verified.

And if the hand to be verified in the half-fist making image is in the half-fist making state, acquiring hand images of the hand to be verified in different fist making states from the half-fist making state to the half-fist making state.

The method for detecting the optical flow characteristics of the hand image by using the optical flow method and comparing the similarity of the optical flow characteristics of the hand image and the prestored optical flow characteristics specifically comprises the following steps:

and taking the ith frame hand image as a first comparison image, and extracting an interested region of the first comparison image to obtain a first interested region.

And taking the i +1 frame hand image as a second comparison image, and extracting an interested region of the second comparison image to obtain a second interested region.

And detecting the positions of the first interested area and the second interested area with the variation amplitude larger than a fourth preset threshold value by using an optical flow method to obtain optical flow characteristics. This step is based on the principle that the optical flow method can detect the position of a moving object.

This embodiment utilizes the light stream method through the image of gathering everyone and making a fist to half the process of making a fist, can detect out the articular change of back of the hand of this in-process, and everyone's articular change is different, and then reaches the effect of living body discernment.

And (5) returning to the step of taking the ith frame hand image as a first comparison image, extracting the region of interest of the first comparison image to obtain a first region of interest, and obtaining the optical flow characteristics of all the hand images, wherein i is i + 1.

And acquiring prestored optical flow characteristics.

And comparing all the optical flow characteristics with the corresponding pre-stored optical flow characteristics respectively to obtain the similarity.

And if the similarity is greater than a third preset threshold, the living body verification is successful.

And if the similarity is less than or equal to a third preset threshold, the in-vivo verification fails.

And 103, if the verification result shows that the living body verification is successful, acquiring a palm vein image and a back hand vein image of the hand to be verified.

And step 104, acquiring pre-stored palm vein storage images and hand back vein storage images.

And 105, respectively calculating the palm similarity of the palm vein image and the palm vein storage image and the hand back similarity of the hand back vein image and the hand back vein storage image.

And 106, if the palm similarity and the back similarity are both greater than a second preset threshold, successfully identifying the hand veins of the hand to be verified.

The optical flow method can detect the instantaneous speed of the pixel motion of the space moving object on the observation imaging surface. When the object moves, the brightness mode of the corresponding point on the image also moves correspondingly, and the apparent motion of the brightness mode of the image is the optical flow. The optical flow study uses the temporal variation and correlation of intensity data of pixels in an image sequence to determine the "motion" of the respective pixel location. The optical flow expresses the change of the image and can therefore be used by the observer to determine the movement of the object. In general, optical flow results from camera motion, object motion in a scene, or the common motion of both.

The optical flow field is derived from optical flow, and refers to a two-dimensional instantaneous velocity field formed by projecting three-dimensional velocity vectors of visible pixel points in a scene on an imaging surface. The motion field in the space is transferred to the image and is expressed as an optical flow field, and the optical flow field reflects the gray scale change trend of each point on the image. The optical flow field contains information about the motion of the observed object and information about the rich three-dimensional structure of the scene.

The optical flow method detects a moving object, and the basic idea is to give a velocity vector to each pixel point in an image, so that a motion field of the image is formed. The points on the image and the points on the three-dimensional object are in one-to-one correspondence at a certain specific motion moment, and the image is dynamically analyzed according to the speed vector characteristics of each pixel point. If no moving object exists in the image, the optical flow vector is continuously changed in the whole image area, and when the object and the image background have relative motion, the velocity vector formed by the moving object is necessarily different from the velocity vector of the neighborhood background, so that the position of the moving object can be detected.

Fig. 2 is a structural diagram of a hand vein recognition apparatus according to an embodiment of the present invention; fig. 3 is a circuit connection diagram of a hand vein recognition apparatus according to an embodiment of the present invention. Referring to fig. 2 and 3, the hand vein recognition apparatus includes: a top collection area 1, a hand placement panel area 2 and a bottom collection area 3; the top collection area 1 and the hand placement panel area 2 are both connected with the bottom collection area 3.

The top collection area 1 is located at the top of the hand vein recognition device, and the top collection area 1 is used for collecting hand back vein images and hand motions of a hand to be verified and displaying hand vein recognition results of the bottom collection area 3.

The hand placing panel area 2 is located below the top collecting area 1, and the hand placing panel area 2 is used for placing a hand to be verified and collecting physiological parameters of the hand to be verified.

The bottom acquisition area 3 is positioned at the bottom of the hand vein recognition device and below the hand placing panel area 2, and the bottom acquisition area 3 is used for acquiring and processing the in-vivo authentication information to obtain a hand vein recognition result; the living body authentication information includes a hand back vein image, a physiological parameter, and a palm vein image of the hand to be authenticated. The bottom acquisition zone 3 processes the in-vivo authentication information through a hand vein recognition system, which may be implemented using the master controller 14.

Fig. 4 is a bottom view of a top acquisition region according to an embodiment of the present invention. Referring to fig. 4, the top acquisition zone 1 comprises in particular: a top camera 4, a top light source 5 and a display screen 6.

The top camera 4 is used for collecting a hand back vein image of a hand to be verified; the output of the top camera 4 is connected to the bottom acquisition region 3. The top camera 4 is also used for collecting hand movements of the hand to be verified and transmitting the collected image data to a hand vein recognition system in the bottom collection area.

The top light source 5 is arranged corresponding to the top camera 4, and the top light source 5 is used for irradiating the back of the hand to be verified. The top light source 5 is connected with a power supply of the bottom acquisition area, and the power supply of the bottom acquisition area supplies power to the top light source. The top light source 5 is a near-infrared lamp group including 6 near-infrared lamps having a diameter of 850 nanometers (nm).

The display screen 6 is connected with the output end of the bottom acquisition area, and the display screen 6 is used for displaying the hand vein recognition result of the bottom acquisition area. The display screen 6 is a touch screen and is also used for human-computer interaction, and the human-computer interaction comprises user operation prompts.

Fig. 5 is a structural diagram of a hand placement panel area according to an embodiment of the present invention. Referring to fig. 5, the hand placement panel area 2 specifically includes: the hand placing area 7, a hand pattern figure 8, a bulge 9 and a physiological parameter detection sensor 10.

The hand placement area 7 is located right below the top camera 4, and the hand placement area 7 is used for placing a hand to be authenticated. The hand placement area 7 is a glass panel, preferably a clear acrylic plate, which also supports hand placement.

The hand pattern figure 8 is carved in the center of the hand placing area 7. Fig. 6 is a structural diagram of a protrusion according to an embodiment of the present invention, and referring to fig. 6, the protrusion 9 is located at the first joint of the middle finger of the hand texture chart 8. The hand pattern figure 8 and the bulge 9 are used for displaying the placement position of the hand to be verified. The height of the protrusions 9 is 1 millimeter (mm). When in use, one side of the palm faces downwards, the first joint of the middle finger of the hand is arranged right above the bulge 9, and the middle finger is arranged in the middle finger area of the hand grain diagram; the use of the bulge and the hand grain pattern can ensure that the position of the hand to be verified placed every time is relatively fixed.

The physiological parameter detection sensor 10 is located below the protrusion 9, and the physiological parameter detection sensor 10 is used for detecting a physiological parameter. The physiological parameter detection sensor needs to be in close contact with the finger, so it is placed below the hand placement area. The physiological parameter detection sensor 10 is connected with the bottom acquisition area 3 and transmits acquired physiological parameters to a hand vein recognition system of the bottom acquisition area. The physiological parameter detection sensor 10 is specifically positioned below the finger area close to the bulge 9 in the hand texture chart 8, and judges whether the hand to be verified is a living body or not by detecting the physiological parameter of the middle finger. The physiological parameter detection sensor 10 adopts an MAX30100 blood oxygen heart rate sensor, can detect physiological parameters of a human body such as blood oxygen heart rate and the like, and transmits the detected physiological parameters to a hand vein identification system, wherein the physiological parameters are pulse blood oxygen values of a hand to be verified.

MAX30100 is a sensor integrated with pulse oximeter and heart rate detection, and the blood oximeter and heart rate sensor is integrated with a red Light LED (Light Emitting Diode), an infrared Light LED, an optical device, a photoelectric sensor, and a low-noise electronic circuit with ambient Light suppression, and is a pulse oximetry monitoring sensor with minimum size and low power consumption in the industry at present.

The detection of the blood oxygen heart rate sensor is based on a photoplethysmography. The photoplethysmography mainly determines the change of blood volume by detecting the change of light intensity of reflected light and/or transmitted light through a photoelectric sensor according to the absorption characteristics of human body tissues to light. Blood oxygen heart rate sensor shines the human body tissue with the light irradiation that the wavelength is known, and through lambert-beer law can know that non-blood tissue such as human skin, muscle is the absorption of light is unchangeable, but human heart flexible can cause blood volume and pressure to present periodic change, imitates the beat of heart as the change of light intensity, consequently the light intensity that detects through photoelectric sensor just can know the condition of heart beat promptly pulse. Meanwhile, the size of the blood vessel volume depends on the size of the ejection volume, and when the heart contracts, the ejection volume is increased, so that the blood vessel volume is increased; on the contrary, when the heart is in diastole, the ejection volume is reduced, so the volume of the blood vessel is reduced, the increase of the volume of the blood vessel indicates that the absorption volume of the blood to the light is increased, and the light intensity of the incident light source is constant, so the light intensity received by the receiving end is reduced; conversely, the decrease of the blood vessel volume means that the absorption amount of the blood to the light is decreased, the light intensity received by the receiving end is increased, and the pulse wave is obtained through photoelectric conversion.

FIG. 7 is a flow chart of data processing of the blood oxygen heart rate sensor according to the embodiment of the present invention. Referring to fig. 7, the working principle of the blood oxygen saturation and pulse measurement of the blood oxygen heart rate sensor is that an LED driver inside a photoelectric sensor drives an LED of the photoelectric sensor to alternately irradiate red light and infrared light according to a preset time sequence, then the photoelectric sensor collects reflected optical signals, and simultaneously the photoelectric sensor converts the reflected optical signals into analog electrical signals. Analog electric signals Output by the photoelectric sensor are amplified, filtered, subjected to analog-to-digital conversion and converted into digital signals, and finally the digital signals are stored in a First Input First Output (FIFO) buffer, and the MAX30100 sensor can communicate through a serial port, specifically through I²The C bus transmits the digital signal to the main controller, thereby obtaining the pulse blood oxygen value. The main controller receives the pulse blood oxygen value and then judges whether the pulse blood oxygen value is larger than 90; if the pulse blood oxygen value is greater than 90, passing the physiological parametersBody verification; otherwise, the pulse blood oxygen value is less than or equal to 90, and the physiological parameter in vivo verification is not passed.

The hand placement panel area 2 further includes a label 11, and the label 11 is located at the upper left of the hand placement area 7. The label 11 is a prompt label, and the label 11 is used for indicating the use steps and cautions of the hand vein recognition device, so that the hand vein recognition device is convenient to use for the first time and is convenient to operate by a user with less use.

Fig. 8 is a top view of a bottom acquisition region according to an embodiment of the present invention, and referring to fig. 8, the bottom acquisition region 3 specifically comprises: a bottom camera 12, a bottom light source 13, a hand vein recognition system and a power supply 15.

The bottom camera 12 is used for collecting a palm vein image of a hand to be verified; the output end of the bottom camera is connected with the input end of the hand vein recognition system, and specifically, the collected image is transmitted to the hand vein recognition system through a Universal Serial Bus (USB), and the hand vein recognition system processes the image. The top camera 4 and the bottom camera 12 should correspond to the center of the hand texture map 8. The frame rate of the top camera 4 and the bottom camera 12 is greater than 30.

The bottom light source 13 is disposed corresponding to the bottom camera 12, and the bottom light source 13 is used for irradiating the palm of the hand to be verified. The bottom light source 13 is a near-infrared lamp group including 6 near-infrared lamps having a diameter of 850 nanometers (nm).

The top collection area and the bottom collection area respectively collect vein images of the palm and the back of the hand under the irradiation of the near-infrared lamp according to the absorption principle of hemoglobin on near-infrared light. According to the vein biometric identification method, the vein images of the back and the palm of the hand are required to be simultaneously identified and verified, and the safety of vein biometric identification is improved.

The hand vein recognition system is also respectively connected with the top camera 4 and the physiological parameter detection sensor 10, and the input end of the hand vein recognition system is also respectively connected with the output end of the top camera 4 and the physiological parameter detection sensor 10; the hand vein recognition system is used for acquiring the living body verification information and processing the living body verification information to obtain a hand vein recognition result. The hand vein recognition system is also used for information interaction with a touch screen, such as: and receiving an instruction of the touch screen, and displaying a hand vein recognition result on the touch screen. The hand vein recognition system obtains a hand vein recognition result through biopsy, the biopsy comprises a physiological parameter biopsy and an action characteristic biopsy, and the prosthesis can be hardly counterfeited through the combination of the two biopsy modes; the processing of the living body authentication information includes processing and recognition of vein images of the palm and the back of the hand, and processing of living body detection.

The power supply 15 is respectively connected with the top light source 5, the bottom light source 13, the physiological parameter detection sensor 10 and the hand vein recognition system, and the power supply 15 is used for supplying power to the top light source 5, the bottom light source 13, the physiological parameter detection sensor 10 and the hand vein recognition system, namely supplying voltage.

The hand vein recognition system specifically includes:

and the physiological parameter acquisition module is used for acquiring the physiological parameters of the hand to be verified detected by the physiological parameter detection sensor.

The physiological parameter acquisition module specifically comprises:

and the physiological parameter acquisition unit is used for acquiring the pulse blood oxygen value of the hand to be verified detected by the blood oxygen heart rate sensor.

And the action characteristic living body verification module is used for performing action characteristic living body verification on the hand to be verified when the physiological parameter is greater than a first preset threshold value to obtain a verification result.

The action characteristic in vivo verification module specifically comprises:

and the fist image acquisition unit is used for acquiring a fist image of the hand to be verified.

And the half-fist image acquisition unit is used for acquiring the half-fist image of the hand to be verified when the hand to be verified in the fist image is in a fist-making state.

And the hand image acquisition unit is used for acquiring hand images of the hand to be verified in different fist making states from the fist making state to the half fist making state when the hand to be verified in the half fist making image is in the half fist making state.

And the similarity comparison unit is used for detecting the optical flow characteristics of the hand image by using an optical flow method and comparing the similarity of the optical flow characteristics of the hand image and the prestored optical flow characteristics.

The similarity comparison unit specifically includes:

and the first interesting area extracting subunit is used for taking the ith frame hand image as a first comparison image, extracting the interesting area of the first comparison image and obtaining a first interesting area.

And the second interested area extracting subunit is used for taking the i +1 th frame hand image as a second comparison image, extracting the interested area of the second comparison image and obtaining a second interested area.

And the optical flow characteristic detection subunit is used for detecting the positions, with the variation amplitude larger than a fourth preset threshold value, of the first region of interest and the second region of interest by using an optical flow method to obtain optical flow characteristics.

And the returning subunit is used for returning the first region-of-interest extracting subunit to obtain the optical flow characteristics of all the hand images by making i equal to i + 1.

And the pre-stored optical flow characteristic acquisition subunit is used for acquiring the pre-stored optical flow characteristics.

And the similarity calculation subunit is used for comparing all the optical flow characteristics with the corresponding pre-stored optical flow characteristics respectively to obtain the similarity.

And the living body verification success unit is used for successfully verifying the living body when the similarity is greater than a third preset threshold value.

And a living body authentication failure unit configured to fail the living body authentication when the similarity is less than or equal to a third preset threshold.

And the vein image acquisition module is used for acquiring the palm vein image and the back vein image of the hand to be verified when the verification result shows that the living body verification is successful.

And the vein storage image acquisition module is used for acquiring pre-stored palm vein storage images and hand back vein storage images.

And the similarity calculation module is used for calculating the palm similarity of the palm vein image and the palm vein storage image and the hand back similarity of the hand back vein image and the hand back vein storage image respectively.

The use process of the hand vein recognition device mainly comprises the following steps: identity registration and identity verification; the identity registration is to store biological information of a user, wherein the biological information comprises the biological characteristics of the hand of the user; the identity authentication is to extract the biological characteristics of the hand to be authenticated and match the biological characteristics with the pre-stored biological characteristics, and the pre-stored biological characteristics are the biological information of the user stored during identity registration; the use flow of identity registration and identity verification is basically the same. Fig. 9 is a flow chart of the hand vein recognition device according to the embodiment of the present invention, and referring to fig. 9, the flow chart of the hand vein recognition device is as follows: selecting touch screen functions, wherein the touch screen function selection comprises identity registration and identity verification, and identity registration is carried out through the touch screen selection registration function; and selecting an authentication function through the touch screen to perform identity authentication.

Fig. 10 is a flowchart of an identity registration process according to an embodiment of the present invention, and referring to fig. 10, the identity registration process includes: placing the hand to be registered in a designated area according to requirements; the requirements are as follows: the back of the hand is facing up and the palm is facing down, the middle finger is placed in the middle finger area of the palm image of the hand texture map, and the first joint of the middle finger is placed on the bulge.

And acquiring physiological parameters detected by a physiological parameter detection sensor, and verifying the activity through the physiological parameters.

Judging whether the verification of the physiological parameter verification activity passes or not; if the verification is passed, the activity is verified through the action characteristics; otherwise, the liveness verification fails.

Action characteristics verify liveness: and acquiring optical flow characteristics when the hand to be registered performs the registration action.

Optical flow features are stored.

Acquiring hand images through a top camera (top camera) respectively to obtain a hand back vein image; the hand images are collected through a bottom camera (bottom camera) to obtain a palm vein image. The hand image collected by the top camera is a hand image containing fingers and the back of the hand, and the hand back vein image is an image only containing the back of the hand. The hand image collected by the bottom camera is a hand image containing fingers and a palm, and the palm vein image is an image only containing a palm part.

And segmenting the hand back vein image from the hand back vein image. The hand back vein image is an image including a hand back part vein.

The palm vein image is segmented from the palm vein image. The palm vein image is an image including a palm partial vein.

Respectively calculating image characteristic values of the hand back vein image and the palm vein image, storing, and returning to the step of respectively acquiring hand images through a top camera (top camera) to obtain a hand back vein image; the method comprises the steps of collecting hand images through a bottom camera (bottom camera), obtaining a palm vein image, circularly executing three times, and storing image characteristic values obtained through three times of calculation.

Fig. 11 is a flowchart of the live action feature registration according to the embodiment of the present invention, and referring to fig. 11, the live action feature verification includes:

the display screen prompts 'please make a fist', the top camera collects hand images, and judges whether the hand images are in a fist making state or not; if the hand is in a fist-making state, prompting 'please make a half fist' by the display screen, and starting to store the collected hand pictures; otherwise, returning to the step of collecting hand images by the top camera and judging whether the hand images are in a fist making state or not.

The top camera collects hand images, and judges whether the hand images are in a half fist making state or not; if the image is in the half-fist making state, stopping storing the hand image; otherwise, returning to the step of collecting hand images by the top camera and judging whether the hand images are in a half-fist making state or not through the hand images.

Processing the stored hand picture by using an optical flow method to obtain an optical flow characteristic; specifically referring to fig. 12, a hand picture stored in the second frame is extracted, and an area of interest in the hand picture stored in the second frame is extracted, where the area of interest is between the first joint of the finger and the wrist, that is, the back of the hand; comparing the extracted hand picture with a previous frame picture, wherein before comparison, the optical flow characteristic of the region of interest of the previous frame picture needs to be extracted, and the previous frame picture is a hand picture stored in the previous frame of the currently extracted hand picture; judging whether the extracted hand picture is the hand picture stored in the last frame; if the hand picture is stored in the last frame, drawing the optical flow angle and the module value of the hand picture stored in the first frame, and taking the optical flow angle and the module value as optical flow characteristics; and if the image is not the hand image stored in the last frame, extracting the hand image stored in the next frame, and returning to the step of comparing the extracted hand image with the previous frame of image, wherein the optical flow characteristics of the region of interest of the previous frame of image need to be extracted before comparison. Drawing the distribution situation that the optical flow angle and the modulus of the hand picture stored in the first frame are compared with the speed u in the x direction (horizontal direction) and the speed v in the y direction (vertical direction) of each pixel point in the hand pictures stored in the two adjacent frames, drawing a speed curve graph of each point from the first frame to the last frame, wherein the tangent angle between the starting point and the end point of the speed curve is the optical flow angle, the distance between the starting point and the end point is the modulus, the optical flow angle and the modulus are the characteristic values of the optical flow characteristics of the starting point, and if the tangent angle and the distance are larger than a preset threshold value, judging the starting point as the characteristic point and storing the characteristic value of the starting point.

Optical flow features are stored.

Fig. 13 is a flowchart of an authentication process according to an embodiment of the present invention, and referring to fig. 13, the authentication process includes: placing the hand to be verified in a designated area according to requirements; the requirements are as follows: the back of the hand is facing up and the palm is facing down, the middle finger is placed in the middle finger area of the palm image of the hand texture map, and the first joint of the middle finger is placed on the bulge.

Judging whether the verification of the activity of the action characteristic verification passes; if the verification is passed, acquiring a hand image through a top camera (a top camera) to acquire a hand back vein image, and acquiring a palm vein image through a bottom camera (a bottom camera) to acquire a hand image; otherwise, the liveness verification fails.

And segmenting the hand back vein image from the hand back vein image.

The palm vein image is segmented from the palm vein image.

And respectively calculating the similarity between the hand vein image and the pre-stored hand vein storage image and the similarity between the palm vein image and the pre-stored palm vein storage image, judging whether the hand vein identification verification passes according to the similarity, and displaying a hand vein identification verification result on the touch screen. The pre-stored hand back vein storage image and the pre-stored palm vein storage image are the hand back vein image and the palm vein image stored in identity registration.

The action characteristic verification liveness comprises the following steps: the touch-sensitive screen suggestion is held a fist, and the top camera detects the image of holding a fist, begins to detect half the action of holding a fist, and the action of holding a fist is ended to detecting half. Prompting by a touch screen: please hold a fist, after the top camera detects the fist action, the touch screen prompts: please half-fist, if no fist making action is detected within 2s, the living body verification is failed. All pictures between the two actions of the fist making action to the half fist making action are extracted, the pictures of two adjacent frames are taken for comparison from the beginning of the fist making action to the end of the half fist making action, the position with larger variation amplitude in the pictures is tracked by an optical flow method, the position with larger variation amplitude is stored as an optical flow feature, and the stored optical flow feature is as follows: the position of a point on the back of the hand with a large fluctuation range and the direction information of the movement of the point. And repeating the comparison of the pictures of two adjacent frames, comparing the extracted optical flow characteristics with the pre-stored optical flow characteristics in terms of similarity, and judging the similarity according to a third preset threshold value. The basis of the action characteristic for verifying the activity is as follows: the joint movement of each person in the process from fist making to half fist making is specific, and the optical flow characteristic of the whole process from first making to half fist making is used as a judgment basis. The optical flow features are fewer, and the third preset threshold is lower and is only used as primary identity screening.

Flow of action feature live body verification see fig. 14 in particular:

Processing the stored hand picture by using an optical flow method to obtain an optical flow feature, carrying out similarity comparison on the optical flow feature and the optical flow feature stored during identity registration, and if the similarity is greater than a third preset threshold, indicating that the living body verification is passed; otherwise, it indicates that the liveness verification failed.

In this embodiment, the fist-making state is determined as the fist joint of the index finger, the middle finger and the ring finger of the hand is protruded. The half-fist state is determined to be a state in which the second joint protrudes in the process from fist making to palm flattening, and the state is the half-fist state, so that the half-fist state can be determined by identifying the second joints of the index finger, the middle finger and the ring finger to protrude.

Fig. 15 is a flow chart of processing hand images according to the embodiment of the present invention, and referring to fig. 15, the steps "acquire hand images through a top camera (top camera) to obtain a hand back vein image, and acquire hand images through a bottom camera (bottom camera) to obtain a palm vein image; segmenting a hand back vein image from the hand back vein image; segmenting a palm vein image from the palm vein image; calculate the similarity of back of the hand vein image and the hand vein memory image of prestoring respectively to and the similarity of palm vein image and the palm vein memory image of prestoring, judge whether hand vein identification verifies and pass according to the similarity, and show hand vein identification verification result "specifically include at the touch-sensitive screen: the top camera and the bottom camera collect hand images; carrying out image segmentation on the hand back vein image and the palm vein image to obtain a hand back vein image and a palm vein image; sequentially carrying out image normalization, Niblack binarization, median filtering and SIFT (Scale-invariant feature transform) feature extraction on the hand dorsal vein image and the palm vein image to obtain a hand dorsal feature and a palm feature; respectively carrying out feature matching on the hand back feature and the palm feature with the pre-stored hand back feature and palm feature to obtain matching scores; judging whether the matching score is larger than a second preset threshold value or not; if the matching score is larger than a second preset threshold value, the hand vein identification verification is successful; if the matching score is smaller than or equal to a second preset threshold value, the hand vein identification verification fails; dorsal and palmar features are stored. Algorithms adopted in the part are common, and the part is completed only for ensuring the flow integrity of the whole hand vein recognition device. The pre-stored hand back characteristics are obtained through a hand back vein storage image stored during identity registration, and the pre-stored palm characteristics are obtained through a palm vein storage image stored during identity registration.

Firstly, a blood oxygen heart rate sensor is adopted to detect whether real blood flow exists or not, the blood oxygen heart rate sensor is used to detect the pulse blood oxygen value to judge whether the hand to be verified is a living body or not, and prosthesis counterfeiting can be cracked; then, motion recognition is adopted, so that the person to be verified can do fist making motion and half fist making motion, when the person makes a fist to half fist making, the jumping of joints of each person on the back of the hand is different, the optical flow method is utilized to analyze the vitality according to the jumping path of the joints and the fist making motion, the fist making motion is utilized to judge whether the hand to be verified is a living body, and the reliability of the living body verification is improved; vein lines of the palm and the back of the hand are extracted, and the mode of combining the back of the hand and the palm is adopted, so that the safety and the reliability are improved.

The embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. For the system disclosed by the embodiment, the description is relatively simple because the system corresponds to the method disclosed by the embodiment, and the relevant points can be referred to the method part for description.

The principles and embodiments of the present invention have been described herein using specific examples, which are provided only to help understand the method and the core concept of the present invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, the specific embodiments and the application range may be changed. In view of the above, the present disclosure should not be construed as limiting the invention.

Claims

1. A hand vein identification method for double in-vivo authentication is characterized by comprising the following steps:

2. The hand vein recognition method for double in-vivo authentication according to claim 1, wherein the acquiring of the physiological parameter of the hand to be authenticated detected by the physiological parameter detection sensor specifically comprises:

3. The hand vein recognition method for double living body verification according to claim 1, wherein the living body verification of the motion characteristics of the hand to be verified to obtain a verification result specifically comprises:

acquiring a fist making image of the hand to be verified;

4. The method for recognizing hand veins of a double living body verification as claimed in claim 3, wherein the detecting optical flow features of the hand image by an optical flow method and comparing the optical flow features of the hand image with the similarity of the pre-stored optical flow features specifically comprises:

acquiring prestored optical flow characteristics;

5. A dual in-vivo verified hand vein recognition device, comprising: a top collection area, a hand placement panel area, and a bottom collection area; the top collection area and the hand placement panel area are both connected with the bottom collection area;

6. A dual in-vivo verified hand vein recognition device according to claim 5, wherein said top collection zone specifically comprises: a top camera, a top light source and a display screen;

7. A dual in-vivo verified hand vein recognition device according to claim 6, wherein said hand placement panel zone specifically comprises: a hand placing area, a hand texture map, a bulge and a physiological parameter detection sensor;

8. A dual in-vivo verified hand vein recognition device according to claim 7, wherein said bottom collection zone specifically comprises: the hand vein recognition system comprises a bottom camera, a bottom light source, a hand vein recognition system and a power supply;

9. A dual in-vivo verified hand vein recognition device according to claim 8, wherein said hand vein recognition system specifically comprises:

10. The dual in-vivo verified hand vein recognition device of claim 9, wherein said action feature in-vivo verification module specifically comprises: