CN106340096A - Recognition device and method based on fingerprint and finger vein recognition intelligent lock - Google Patents
Recognition device and method based on fingerprint and finger vein recognition intelligent lock Download PDFInfo
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- CN106340096A CN106340096A CN201610742367.XA CN201610742367A CN106340096A CN 106340096 A CN106340096 A CN 106340096A CN 201610742367 A CN201610742367 A CN 201610742367A CN 106340096 A CN106340096 A CN 106340096A
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- G—PHYSICS
- G07—CHECKING-DEVICES
- G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
- G07C9/00—Individual registration on entry or exit
- G07C9/00174—Electronically operated locks; Circuits therefor; Nonmechanical keys therefor, e.g. passive or active electrical keys or other data carriers without mechanical keys
- G07C9/00563—Electronically operated locks; Circuits therefor; Nonmechanical keys therefor, e.g. passive or active electrical keys or other data carriers without mechanical keys using personal physical data of the operator, e.g. finger prints, retinal images, voicepatterns
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/12—Fingerprints or palmprints
- G06V40/1365—Matching; Classification
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/14—Vascular patterns
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/15—Biometric patterns based on physiological signals, e.g. heartbeat, blood flow
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- General Physics & Mathematics (AREA)
- Human Computer Interaction (AREA)
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- Theoretical Computer Science (AREA)
- Measurement Of The Respiration, Hearing Ability, Form, And Blood Characteristics Of Living Organisms (AREA)
- Collating Specific Patterns (AREA)
Abstract
The invention discloses a recognition device and method based on a fingerprint and finger vein recognition intelligent lock. The recognition device comprises a fingerprint recognition module, a finger vein recognition module, a heartbeat recognition module and a personnel matching judgment module. The fingerprint recognition module is used for recognizing fingerprint information, searching for the personnel identifier with the highest matching probability and outputting the corresponding fingerprint matching probability. The finger vein recognition module is used for recognizing finger vein information, searching for the personnel identifier with the highest matching rate and giving a corresponding finger vine matching rate. The heartbeat recognition module is used for recognizing heartbeat information, searching for the personnel identifier with the highest matching rate and giving a corresponding heartbeat matching rate. The personnel matching judgment module is used for judging whether the personnel identifiers matched with fingerprint recognition, finger vine recognition and heartbeat recognition are consistent or not; if the personnel identifiers matched with fingerprint recognition, finger vine recognition and heartbeat recognition are inconsistent, an authentication rejection prompt is given; if the personnel identifiers matched with fingerprint recognition, finger vine recognition and heartbeat recognition are consistent, further submitting is carried out, and the final matching probability is given according to a Bayesian Decision Theory judgment method.
Description
Technical field
The present invention relates to intelligent lock and living things feature recognition field, specifically, it is related to one kind and vein is referred to based on fingerprint
The identifying device of identification intelligent lockset and method.
Background technology
Carrying out identity authentication method currently with finger section feature mainly has fingerprint and refers to vein.Two methods respectively have spy
Point.
Fingerprint is the auth method being formed over the past thousands of years, has been rooted in the hearts of the people by the idea of fingerprint authentication identity,
But fingerprint recognition there is a problem of certain, it is mainly manifested in: 1.) accuracy of identification of fingerprint is not high enough, has the people of certain ratio
Group's fingerprint characteristic is inconspicuous it is impossible to enough correctly identify, the fingerprint of such as schoolgirl is shallower to be difficult to, and long-term work can lead to fingerprint
Feature is inconspicuous；2.) fingerprint is easily forged.Fingerprint is the non-live body characteristicses on surface, is easily obtained by people, and high-precision by printing
The modes such as the fingerprint film of degree are forged.In order to solve this problem, scientific research personnel proposes a variety of methods to solve fingerprint
Forgery problem, mainly includes carrying out In vivo detection with modes such as ultrasound wave acquisition deep layer fingerprints.
Referring to hand vein recognition is a kind of biological feather recognition method growing up in recent years, penetrates finger using near infrared ray
The veinprint image of gained, to carry out personal identification, is to have high accuracy, the biological identification technology at the tip of high speed afterwards.Refer to
Hand vein recognition is the technology being identified using the biology interior feature that outside be can't see, so having high antifalsification.Meanwhile, by
Be to be identified using body interior feature in it and must be that live body just can be utilized, compare with the technology of identification of fingerprint etc again across
Enter major step, the blood that to refer to vein must be that live body has flowing just can be identified, and is natural vivo identification feature.But
Due to refer to vein pattern in the second knuckle of finger the most obvious, first knuckle, that is, popular finger tripe part refers to vein pattern
Then far away from second knuckle substantially, therefore product is difficult to miniaturization.
Content of the invention
The technical problem to be solved in the present invention is to provide a kind of identifying device referring to hand vein recognition intelligent lock based on fingerprint
And method, fingerprint and the finger respective advantage of vein are complementary to one another, develop a kind of identification ability and higher being combined of protection capability
The method of biometric devices.
The present invention adopts the following technical scheme that and realizes goal of the invention:
A kind of device referring to hand vein recognition intelligent lock based on fingerprint, including,
Fingerprint identification module: finger print information is identified, retrieves matching probability highest giver identification, and export right
The fingerprint probability answered；
It is characterized in that: also include,
Refer to hand vein recognition module: be identified to referring to venous information, retrieve matching degree highest giver identification, and provide
Corresponding finger vein matching degree；
Heart beating identification module: heartbeat message is identified, retrieves matching degree highest giver identification, and provide correspondence
Heart beating matching degree；
Personnel mate determination module: judge fingerprint recognition, refer to hand vein recognition, heart beating the mated giver identification of identification whether
Cause；If fingerprint, refer to vein, giver identification that heart beating is mated inconsistent, provide certification refusal prompting；If fingerprint, refer to quiet
The giver identification that arteries and veins, heart beating are mated is consistent, submits to further to be given according to Bayesian decision decision method and is finally mated generally
Rate, if matching probability is more than unlocking threshold value set in advance, otherwise, provides certification refusal prompting.
As the restriction further to the technical program, described fingerprint identification module is currently referred to by fingerprint sensor scans
Stricture of vagina, submits to the validated user fingerprint register storehouse registered with intelligent lock of fingerprint recognition system to compare fingerprint image, retrieves
Join probability highest giver identification, and export corresponding fingerprint probability；If fingerprint image is unavailable, matching probability is output as
0.5.
As the restriction further to the technical program, described finger hand vein recognition module is passed through finger intravenous sensor scanning and is worked as
Front finger vein, referring to, vein image is sent to finger vein recognition system and the validated user of intelligent lock registration refers to vein registry
Compare, retrieve matching degree highest giver identification, and provide corresponding finger vein matching degree；Can not if referring to vein image
With matching probability is output as 0.5.
As the restriction further to the technical program, described heart beating identification module passes through heartbeat sensor detecting
Heart beating microseismic data is sent to the validated user heart beating registry that heart beating identifying system registered with intelligent lock and compares, and retrieves
Degree of joining highest giver identification, and provide corresponding heart beating matching degree；If heart beat detection module does not monitor heart beating, heart beating
Degree of joining is output as 0, provides certification refusal prompting.
As the restriction further to the technical program, described personnel mate the Bayesian decision decision method of determination module
Detailed process be: set x as fingerprint matching degree, y is to refer to vein matching degree, and z is heart beating matching degree, and p (x) goes out for fingerprint matching degree
Existing probability, p (x |+) is the probability that during x, coupling certification is passed through for fingerprint matching degree, and p (y) is finger vein matching degree probability of occurrence, p
(y |+) it is to refer to the probability that vein matching degree is passed through for coupling certification during y, p (z) is heart beating matching degree probability of occurrence, p (z |+) be
Heart beating matching degree is the coupling probability that passes through of certification during z, p (+) it is the prior probability fitting through, fingerprint matching degree is x, it is quiet to refer to
Arteries and veins matching degree is y, heart beating matching degree be the probability fitting through during z be p (+| xyz)=p (+) p (x |+) p (y |+) p (z |
+)/(p(x)p(y)p(z))；Wherein p (x), p (y), p (z), p (x |+), p (y |+), p (z |+), p (+) be given data, can thing
First obtained according to real data statistics.
The invention also discloses a kind of identification side referring to hand vein recognition intelligent lock device using claim 1 based on fingerprint
Method, is characterized in that, comprises the steps:
(1) fingerprint identification module carries out fingerprint recognition, and exports corresponding fingerprint probability；
(2) refer to hand vein recognition module to carry out referring to hand vein recognition, and export corresponding finger vein matching degree；
(3) heart beating identification module is identified to heartbeat message, and provides corresponding heart beating matching degree；
(4) personnel's coupling determination module judges fingerprint recognition, whether refers to hand vein recognition, heart beating the mated giver identification of identification
Unanimously；If fingerprint, refer to vein, giver identification that heart beating is mated inconsistent, provide certification refusal prompting；If fingerprint, referred to
The giver identification that vein, heart beating are mated is consistent, submits to further to be given according to Bayesian decision decision method and is finally mated
Probability, if matching probability is more than unlocking threshold value set in advance, otherwise, provides certification refusal prompting.
As the restriction further to the technical program, described step (1) comprises the steps: described fingerprint identification module
By fingerprint sensor scans current finger print, fingerprint image is submitted to the validated user of fingerprint recognition system and intelligent lock registration
Fingerprint register storehouse compares, and retrieves matching probability highest giver identification, and exports corresponding fingerprint probability；If fingerprint image
As unavailable, matching probability is output as 0.5.
As the restriction further to the technical program, described step (2) comprises the steps: described finger hand vein recognition mould
Block pass through refer to intravenous sensor scanning currently refer to vein, refer to vein image be sent to refer to vein recognition system step on intelligent lock
The validated user of note refers to vein registry and compares, and retrieves matching degree highest giver identification, and provides corresponding finger vein
Degree of joining；If it is unavailable to refer to vein image, matching probability is output as 0.5.
As the restriction further to the technical program, described step (3) comprises the steps: described heart beating identification module
By heartbeat sensor, the heart beating microseismic data detecting is sent to the legal use of heart beating identifying system and intelligent lock registration
Heart beating registry in family compares, and retrieves matching degree highest giver identification, and provides corresponding heart beating matching degree；If heart beating is examined
Survey module and do not monitor heart beating, heart beating matching degree is output as 0, provide certification refusal prompting.
As the restriction further to the technical program, the concrete mistake of the Bayesian decision decision method of described step (4)
Cheng Wei: set x as fingerprint matching degree, y is to refer to vein matching degree, z is heart beating matching degree, p (x) is fingerprint matching degree probability of occurrence, p
The probability that (x |+) passes through for coupling certification during x for fingerprint matching degree, p (y) is to refer to vein matching degree probability of occurrence, p (y |+) be
Refer to the probability that vein matching degree is passed through for coupling certification during y, p (z) is heart beating matching degree probability of occurrence, p (z |+) mate for heart beating
Spend for the coupling probability that passes through of certification during z, p (+) it is the prior probability fitting through, fingerprint matching degree is x, refers to vein matching degree
For y, heart beating matching degree be the probability fitting through during z be p (+| xyz)=p (+) p (x |+) p (y |+) p (z |+)/(p (x) p
(y)p(z))；Wherein p (x), p (y), p (z), p (x |+), p (y |+), p (z |+), p (+) be given data, can be in advance according to reality
Border data statisticss obtain.
Compared with prior art, advantages of the present invention and good effect are: the present invention adopts ultrasound examination, carry out fingerprint
In vivo detection, and then carry out the identification of fingerprint, the degree of membership of the identification of output fingerprint characteristic as identification criterion it
One；Shone based near infrared light, be proposed for the finger vein identification method of first knuckle, output refers to the identification degree of membership conduct of vein
One of foundation of identification.First knuckle is adopted with the illumination of specific wavelength, carries out reflecting, refraction is processed, and obtains heart beating special
Levy, as one of the mode of In vivo detection.Meanwhile, using heart beating off-note as a kind of means of antifraud.Finger in method
Stricture of vagina and finger hand vein recognition adopt soft decision mode, export the probability of identification according to two kinds of recognition methodss respectively, carry out data fusion
Process, the court verdict that output optimizes.In conjunction with heartbeat detection, when heart beating occurs extremely, self adaptation heightens the threshold value of identification, prevents
The only generation of fraud.By fingerprint, refer to the coverage rate that two kinds of features of vein improve data acquisition crowds, when one of which data no
During method collection, corresponding matching probability is set to 0.5, does not affect another kind of feature identification application；Using heart beating feature identification, permissible
Prevent non-living body Data attack, at the same time as weak supplementary meanss and above two kinds of Feature Fusion, lifting identification is accurate further
Property.
Brief description
Fig. 1 is assembly of the invention structural representation.
Fig. 2 is the side view of the decorating structure of the present invention.
Fig. 3 is the functional-block diagram of the present invention.
In figure: 1, refer to intravenous sensor, 2, fingerprint sensor, 3, heartbeat sensor, 4, infrared auxiliary light, 5, switch.
Specific embodiment
Below in conjunction with the accompanying drawings, a specific embodiment of the present invention is described in detail, it is to be understood that the present invention
Protection domain do not limited by specific embodiment.
As shown in Figure 1-Figure 3, the present invention includes,
Fingerprint identification module: finger print information is identified, retrieves matching probability highest giver identification, and export right
The fingerprint probability answered；
It is characterized in that: also include,
Refer to hand vein recognition module: be identified to referring to venous information, retrieve matching degree highest giver identification, and provide
Corresponding finger vein matching degree；
Heart beating identification module: heartbeat message is identified, retrieves matching degree highest giver identification, and provide correspondence
Heart beating matching degree；
Personnel mate determination module: judge fingerprint recognition, refer to hand vein recognition, heart beating the mated giver identification of identification whether
Cause；If fingerprint, refer to vein, giver identification that heart beating is mated inconsistent, provide certification refusal prompting；If fingerprint, refer to quiet
The giver identification that arteries and veins, heart beating are mated is consistent, submits to further to be given according to Bayesian decision decision method and is finally mated generally
Rate, if matching probability is more than unlocking threshold value set in advance, otherwise, provides certification refusal prompting.
Described fingerprint identification module passes through fingerprint sensor scans current finger print, and fingerprint image is submitted to fingerprint recognition system
With intelligent lock registration validated user fingerprint register storehouse compare, retrieve matching probability highest giver identification, and export right
The fingerprint probability answered；If fingerprint image is unavailable, matching probability is output as 0.5.
Described finger hand vein recognition module is passed through to refer to intravenous sensor scanning currently finger vein, is sent to finger referring to vein image
The validated user that vein recognition system is registered with intelligent lock refers to vein registry and compares, and retrieves matching degree highest personnel mark
Know, and provide corresponding finger vein matching degree；If it is unavailable to refer to vein image, matching probability is output as 0.5.
Described heart beating identification module passes through heartbeat sensor and the heart beating microseismic data detecting is sent to heart beating identification system
System with intelligent lock register validated user heart beating registry compare, retrieve matching degree highest giver identification, and be given right
The heart beating matching degree answered；If heart beat detection module does not monitor heart beating, heart beating matching degree is output as 0, provides certification refusal and carries
Show.Fingerprint sensor, to refer to intravenous sensor and heartbeat sensor be all using existing matured product, will not be described here.
The detailed process that described personnel mate the Bayesian decision decision method of determination module is: set x as fingerprint matching degree,
Y is to refer to vein matching degree, and z is heart beating matching degree, and p (x) is fingerprint matching degree probability of occurrence, and p (x |+) is x for fingerprint matching degree
When the coupling probability that passes through of certification, p (y) is to refer to vein matching degree probability of occurrence, and p (y |+) is coupling during y for referring to vein matching degree
The probability that certification is passed through, p (z) is heart beating matching degree probability of occurrence, p (z |+) pass through for coupling certification during z for heart beating matching degree
Probability, p (+) be the prior probability fitting through, fingerprint matching degree be x, refer to vein matching degree be y, heart beating matching degree be z when
The probability fitting through be p (+| xyz)=p (+) p (x |+) p (y |+) p (z |+)/(p (x) p (y) p (z))；Wherein p (x), p
(y), p (z), p (x |+), p (y |+), p (z |+), p (+) be given data, can be counted according to real data in advance and obtain.
The invention also discloses a kind of identification side referring to hand vein recognition intelligent lock device using claim 1 based on fingerprint
Method, comprises the steps:
(1) fingerprint identification module carries out fingerprint recognition, and exports corresponding fingerprint probability；Finger first knuckle is placed on
Fingerprint sensor 2 is gently pressed above, and fingerprint sensor 2 pressure switch starts activation identifying system；
(2) refer to hand vein recognition module to carry out referring to hand vein recognition, and export corresponding finger vein matching degree；
(3) heart beating identification module is identified to heartbeat message, and provides corresponding heart beating matching degree；
(4) personnel's coupling determination module judges fingerprint recognition, whether refers to hand vein recognition, heart beating the mated giver identification of identification
Unanimously；If fingerprint, refer to vein, giver identification that heart beating is mated inconsistent, provide certification refusal prompting；If fingerprint, referred to
The giver identification that vein, heart beating are mated is consistent, submits to further to be given according to Bayesian decision decision method and is finally mated
Probability, if matching probability is more than unlocking threshold value set in advance, otherwise, provides certification refusal prompting.
Described step (1) comprises the steps: that described fingerprint identification module passes through fingerprint sensor scans current finger print,
Fingerprint image submits to the validated user fingerprint register storehouse that fingerprint recognition system is registered with intelligent lock to compare, and retrieves matching probability
Highest giver identification, and export corresponding fingerprint probability；If fingerprint image is unavailable, matching probability is output as 0.5.
Described step (2) comprises the steps: that described finger hand vein recognition module is passed through to refer to intravenous sensor scanning currently finger
Vein, referring to vein image and be sent to refer to the validated user registered with intelligent lock of vein recognition system and refer to vein registry ratio
Right, retrieve matching degree highest giver identification, and provide corresponding finger vein matching degree；If it is unavailable to refer to vein image,
Matching probability is output as 0.5.
Described step (3) comprises the steps: that described heart beating identification module passes through heartbeat sensor the heart beating detecting
Microseismic data is sent to the validated user heart beating registry that heart beating identifying system registered with intelligent lock and compares, and retrieves matching degree
Highest giver identification, and provide corresponding heart beating matching degree；If heart beat detection module does not monitor heart beating, heart beating matching degree
It is output as 0, provide certification refusal prompting.
The detailed process of the Bayesian decision decision method of described step (4) is: sets x as fingerprint matching degree, y is to refer to vein
Matching degree, z is heart beating matching degree, and p (x) is fingerprint matching degree probability of occurrence, and p (x |+) is coupling certification during x for fingerprint matching degree
The probability passing through, p (y) is to refer to vein matching degree probability of occurrence, and it is to mate certification during y to pass through that p (y |+) refers to vein matching degree
Probability, p (z) is heart beating matching degree probability of occurrence, p (z |+) for heart beating matching degree for mating the probability that certification is passed through during z, p (+)
The prior probability fitting through, fingerprint matching degree be x, refer to vein matching degree be y, heart beating matching degree be z when fitting through
Probability be p (+| xyz)=p (+) p (x |+) p (y |+) p (z |+)/(p (x) p (y) p (z))；Wherein p (x), p (y), p (z), p
(x |+), p (y |+), p (z |+), p (+) be given data, can be counted according to real data in advance and obtain.
First articulations digitorum manus of identification all concentrations of fingerprint of the present invention and finger vein, i.e. the part of finger tripe, carry out identity knowledge
Not.Rather than fingerprint is carried out with the identification of the first articulations digitorum manus, to the identification referring to vein and carrying out full finger.
Claims (10)
1. a kind of device referring to hand vein recognition intelligent lock based on fingerprint, including,
Fingerprint identification module: finger print information is identified, retrieves matching probability highest giver identification, and export corresponding
Fingerprint probability；
It is characterized in that: also include,
Refer to hand vein recognition module: be identified to referring to venous information, retrieve matching degree highest giver identification, and provide correspondence
Finger vein matching degree；
Heart beating identification module: heartbeat message is identified, retrieves matching degree highest giver identification, and provide the corresponding heart
Jump matching degree；
Personnel mate determination module: judge fingerprint recognition, refer to hand vein recognition, heart beating identification mated giver identification whether consistent；
If fingerprint, refer to vein, giver identification that heart beating is mated inconsistent, provide certification refusal prompting；If fingerprint, refer to vein,
The giver identification that heart beating is mated is consistent, submits to further and provides final institute matching probability according to Bayesian decision decision method,
If matching probability is more than unlocking threshold value set in advance, otherwise, provide certification refusal prompting.
2. according to the device referring to hand vein recognition intelligent lock based on fingerprint, it is characterized in that: described fingerprint identification module passes through fingerprint
Sensor scan current finger print, submits fingerprint image to the validated user fingerprint register of fingerprint recognition system and intelligent lock registration
Storehouse compares, and retrieves matching probability highest giver identification, and exports corresponding fingerprint probability；If fingerprint image can not
With matching probability is output as 0.5.
3. the device being referred to hand vein recognition intelligent lock based on fingerprint according to claim 1, be is characterized in that: described finger vein
Identification module passes through to refer to intravenous sensor scanning currently finger vein, is sent to finger vein recognition system and intelligence referring to vein image
The validated user of lockset registration refers to vein registry and compares, and retrieves matching degree highest giver identification, and provides corresponding finger
Vein matching degree；If it is unavailable to refer to vein image, matching probability is output as 0.5.
4. the device being referred to hand vein recognition intelligent lock based on fingerprint according to claim 1, be is characterized in that: described heart beating is known
Other module is passed through heartbeat sensor and the heart beating microseismic data detecting is sent to heart beating identifying system and intelligent lock registration
Validated user heart beating registry compares, and retrieves matching degree highest giver identification, and provides corresponding heart beating matching degree；If
Heart beat detection module does not monitor heart beating, and heart beating matching degree is output as 0, provides certification refusal prompting.
5. the device being referred to hand vein recognition intelligent lock based on fingerprint according to claim 1, be is characterized in that: described personnel
The detailed process joining the Bayesian decision decision method of determination module is: sets x as fingerprint matching degree, y is to refer to vein matching degree, z
For heart beating matching degree, p (x) is fingerprint matching degree probability of occurrence, and p (x |+) is general for mate during x that certification passes through for fingerprint matching degree
Rate, p (y) is to refer to vein matching degree probability of occurrence, p (y |+) it is to refer to the probability that vein matching degree is passed through, p for coupling certification during y
Z () is heart beating matching degree probability of occurrence, p (z |+) is to mate the probability that certification is passed through during z for heart beating matching degree, p (+) it is to mate
The prior probability passing through, fingerprint matching degree be x, refer to vein matching degree be y, heart beating matching degree be z when the probability fitting through
For p (+| xyz)=p (+) p (x |+) p (y |+) p (z |+)/(p (x) p (y) p (z))；Wherein p (x), p (y), p (z), p (x |+), p
(y |+), p (z |+), p (+) be given data, can be counted according to real data in advance and obtain.
6. a kind of recognition methodss being referred to hand vein recognition intelligent lock device using claim 1 based on fingerprint, be is characterized in that, including
Following steps:
(1) fingerprint identification module carries out fingerprint recognition, and exports corresponding fingerprint probability；
(2) refer to hand vein recognition module to carry out referring to hand vein recognition, and export corresponding finger vein matching degree；
(3) heart beating identification module is identified to heartbeat message, and provides corresponding heart beating matching degree；
(4) personnel's coupling determination module judges fingerprint recognition, refers to hand vein recognition, heart beating the mated giver identification of identification whether
Cause；If fingerprint, refer to vein, giver identification that heart beating is mated inconsistent, provide certification refusal prompting；If fingerprint, refer to quiet
The giver identification that arteries and veins, heart beating are mated is consistent, submits to further to be given according to Bayesian decision decision method and is finally mated generally
Rate, if matching probability is more than unlocking threshold value set in advance, otherwise, provides certification refusal prompting.
7. the recognition methodss being referred to hand vein recognition intelligent lock based on fingerprint according to claim 6, be is characterized in that, described step
Suddenly (1) comprises the steps: that described fingerprint identification module passes through fingerprint sensor scans current finger print, fingerprint image is submitted to and refers to
The validated user fingerprint register storehouse that stricture of vagina identifying system is registered with intelligent lock compares, and retrieves matching probability highest personnel mark
Know, and export corresponding fingerprint probability；If fingerprint image is unavailable, matching probability is output as 0.5.
8. the recognition methodss being referred to hand vein recognition intelligent lock based on fingerprint according to claim 6, be is characterized in that, described step
Suddenly (2) comprise the steps: that described finger hand vein recognition module is passed through to refer to intravenous sensor scanning currently finger vein, referring to vein figure
The validated user registered with intelligent lock as being sent to finger vein recognition system is referred to vein registry and compares, and retrieves matching degree
High giver identification, and provide corresponding finger vein matching degree；If it is unavailable to refer to vein image, matching probability is output as 0.5.
9. the recognition methodss being referred to hand vein recognition intelligent lock based on fingerprint according to claim 6, be is characterized in that, described step
Suddenly (3) comprise the steps: that described heart beating identification module is sent to, by heartbeat sensor, the heart beating microseismic data detecting
The validated user heart beating registry that heart beating identifying system is registered with intelligent lock compares, and retrieves matching degree highest personnel mark
Know, and provide corresponding heart beating matching degree；If heart beat detection module does not monitor heart beating, heart beating matching degree is output as 0, is given
Certification refusal prompting.
10. the recognition methodss being referred to hand vein recognition intelligent lock based on fingerprint according to claim 6, be is characterized in that, described
The detailed process of the Bayesian decision decision method of step (4) is: sets x as fingerprint matching degree, y is to refer to vein matching degree, z is the heart
Jump matching degree, p (x) is fingerprint matching degree probability of occurrence, p (x |+) is for fingerprint matching degree for mating the probability that certification is passed through, p during x
Y () is to refer to vein matching degree probability of occurrence, p (y |+) it is to refer to the probability that vein matching degree is passed through for coupling certification during y, p (z) is
Heart beating matching degree probability of occurrence, the probability that p (z |+) passes through for coupling certification during z for heart beating matching degree, p (+) fit through
Prior probability, fingerprint matching degree be x, refer to vein matching degree be y, heart beating matching degree be z when the probability fitting through be p (+|
Xyz)=p (+) p (x |+) p (y |+) p (z |+)/(p (x) p (y) p (z))；Wherein p (x), p (y), p (z), p (x |+), p (y |+),
P (z |+), p (+) be given data, can be counted according to real data in advance and obtain.
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN109033931A (en) * | 2018-05-12 | 2018-12-18 | 广东可穿戴数字技术有限公司 | A kind of system confirmed based on fingerprint and electrocardio dual identity |
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