CN208351494U - Face identification system - Google Patents
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- CN208351494U CN208351494U CN201820778810.3U CN201820778810U CN208351494U CN 208351494 U CN208351494 U CN 208351494U CN 201820778810 U CN201820778810 U CN 201820778810U CN 208351494 U CN208351494 U CN 208351494U
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Abstract
The utility model provides a kind of face identification system, the face identifying system includes recognition of face terminal and server, the recognition of face terminal is connected with the server communication, the recognition of face terminal includes display panel, image capture module and identification module, the camera of described image acquisition module is mounted on the top of the display panel, the camera is used to acquire the facial image of measurand, and collected facial image is sent to the identification module, the identification module is used to carry out vivo identification to the measurand, and the facial image is compared with the facial image that prestores in face database in the case where identifying that measurand is living body, obtain face recognition result；The identification module includes the first recognition unit and the second recognition unit.Face skin characteristic is detected and is combined with speech detection by the utility model, be can effectively solve the problem that vivo identification fraud problem, is improved the accuracy rate of recognition of face.
Description
Technical field
The utility model relates to technical field of face recognition, more particularly to a kind of face identification system.
Background technique
With the rapid development of face recognition technology, recognition of face is in fields and law enforcement agencies such as business, education
It is used widely, such as recognition of face can help that bank is more acurrate, effectively verifies client identity.But concrete application
In, since to will lead to collected picture quality not high for the influence of the factors such as light, influence face recognition accuracy rate.
In addition, measurand may use photo face or the face video segment prerecorded to carry out recognition of face,
Lead to recognition of face low efficiency.In view of this, having also been proposed vivo identification technology in the prior art, i.e., in the process of recognition of face
In prove facial image it is corresponding be " living person ".Common vivo identification is random action cooperation in the market, generally requires quilt
It surveys object and makes the random actions progress vivo identification identification such as shake the head, blink, opening one's mouth.However, the vivo identification method there is also
Certain security threat, such as measurand can use three-dimensional face model and imitates true man and complete compulsory exercise and carry out
It forges and logs in, it is easy to falsely determine that non-living body for living body.
Utility model content
The purpose of this utility model is at least to solve one of drawbacks described above and deficiency, which is by the following technical programs
It realizes.
The utility model provides a kind of face identification system, including recognition of face terminal and server, and the face is known
Other terminal is connected with the server communication, and the recognition of face terminal includes display panel, image capture module and identification
Module, described image acquisition module are electrically connected with the identification module, and the camera of described image acquisition module is mounted on described
The top of display panel, the camera are used to acquire the facial image of measurand, and collected facial image is sent
To the identification module, the identification module is used to carry out vivo identification to the measurand, and is identifying measurand
The facial image is compared with the facial image that prestores in face database in the case where for living body, obtains recognition of face
As a result；The identification module includes the first recognition unit and the second recognition unit, and first recognition unit is that skin identification is single
Member, for carrying out vivo identification according to the skin characteristic of the facial image；Second recognition unit is voice recognition unit,
Lip reading information for being issued according to measurand carries out further vivo identification.
Further, the identification module further includes authentication unit, and the authentication unit is for identifying measurand
The facial image is compared with the facial image that prestores in face database in the case where for living body, obtains recognition of face
As a result.
Further, the camera includes visible image capturing head and/or black light camera.
Further, second recognition unit includes loudspeaker and the Mike that the recognition of face terminal end surface is arranged in
Wind is provided with 2 microphones.
Further, the skin characteristic of the facial image include forehead, eyebrow, eyes, two cheeks, nose, lip, under
Bar, in ear at least two positions skin characteristic.
The advantages of the utility model, is as follows:
(1) the utility model carries out recognition of face using Multiple recognition, and the identification of face skin characteristic is known with voice
Carry out vivo identification is not combined, be can effectively solve the problem that and is carried out vivo identification using photo, video and three-dimensional face model etc.
And the fraud problem being easy to produce, reach the function of pinpoint accuracy vivo identification and recognition of face, effectively improves recognition of face
Safety.
(2) the utility model uses the dual camera being made of visible light and black light, can be under different light
Facial image is acquired, the image of high quality is obtained, improves face recognition accuracy rate.
Detailed description of the invention
By reading the following detailed description of the preferred embodiment, various other advantages and benefits are common for this field
Technical staff will become clear.The drawings are only for the purpose of illustrating a preferred embodiment, and is not considered as practical to this
Novel limitation.And throughout the drawings, the same reference numbers will be used to refer to the same parts.
Fig. 1 is the schematic diagram of face identification system provided by the embodiment of the utility model；
Fig. 2 is the structural schematic diagram of recognition of face terminal provided by the embodiment of the utility model；
Fig. 3 is the concrete structure schematic diagram of recognition of face terminal provided by the embodiment of the utility model；
Appended drawing reference is as follows in figure:
100- recognition of face terminal 200- server
300- terminal device
1- display panel 2- image capture module
21- visible image capturing head 22- infrared camera
3- identification module the first recognition unit of 31-
32- the second recognition unit 33- authentication unit
321- loudspeaker 322- microphone
Specific embodiment
The illustrative embodiments of the disclosure are more fully described below with reference to accompanying drawings.Although showing this public affairs in attached drawing
The illustrative embodiments opened, it being understood, however, that may be realized in various forms the disclosure without the reality that should be illustrated here
The mode of applying is limited.It is to be able to thoroughly understand the disclosure on the contrary, providing these embodiments, and can be by this public affairs
The range opened is fully disclosed to those skilled in the art.
Fig. 1 shows the schematic diagram for the face identification system that embodiment according to the present utility model provides.Such as Fig. 1 institute
Show, which includes recognition of face terminal 100 and server 200, and recognition of face terminal 100 and server 200 are logical
Letter connection.Server 200 can be independent server, or can store the server set of cloud data.
Fig. 2 to Fig. 3 shows the structural schematic diagram for the recognition of face terminal that embodiment according to the present utility model provides.
As shown in Figure 2 to Figure 3, recognition of face terminal 100 includes display panel 1, image capture module 2 and identification module 3, identification
Module 3 is electrically connected with display panel 1 and image capture module 2 respectively.
Image capture module 2 includes camera, and the top of display panel 1 is arranged in camera, and camera is wide-angle imaging
Head, camera can acquire continuous facial image from the distant to the near, and are sent to identification module 3 and carry out recognition of face.Camera shooting
Head can automatically identify at least one face in picture to be captured, and then to the people detected when carrying out personage's shooting
Face is automatically adjusted, such as automatic focusing, adjust automatically image zoom or diminution etc..
The light source of camera can be visible light source, such as feux rouges or blue light etc.；It is also possible to black light light source, example
Such as infrared light supply；It can also be that the dual camera being made of visible light and black light light source, the utility model do not limit specifically.
Such as in present embodiment, camera uses the dual camera being made of visible image capturing head 21 and infrared camera 22.
Infrared camera 22 can capture the infrared image that each subject diffusing reflection is formed in picture to be captured, due to
Human eye can not see infrared ray, therefore, can be to avoid the injury to measurand using infrared camera 22.And night uses
When infrared collecting, infrared camera 22 can adjust automatically exposure intensity, improve shooting quality.
When measurand station is when from recognition of face 100 a certain distance of terminal, camera carries out image to user and adopts
Collection, when face alignment camera, camera can capture, and clear, positive facial image obtains effective face figure
Picture.In preferred implementation, above-mentioned distance is at least 10cm.In image acquisition process, frame image buffer storage preservation is at least acquired.It is tested
Object can adjust oneself camera site, shooting distance etc. according to the preview screen shown on display panel 1.
Identification module 3 is used to according to collected facial image judge whether the personage in image is living body, and true
It is after the fixed facial image is living body, the face of the facial image stored in collected face characteristic and face database is special
Verifying is compared in sign, judges whether to match, and obtains face recognition result and shows in display panel 1.
Identification module 3 includes the first recognition unit 31 and the second recognition unit 32, and the first recognition unit 31 is skin identification
Unit can judge whether the face in facial image is living body according to the skin characteristic of collected facial image frame.
Face characteristic includes the skin of face feature of face, and skin of face feature includes dermatoglyph feature and/or skin
Pore feature.Dermatoglyph feature includes the main features such as the depth, number of nodes and the texture thickness of dermatoglyph, and skin pore is special
Sign includes quantity and size of pore of pore etc..
Since the skin of face feature of real human face different parts is different, for example, real human face forehead and chin position line
Reason is compared with thick, pore is larger, and texture is relatively thin at cheek, pore is smaller, rather than real human face does not have by shooting image
Texture and pore of real skin etc..Therefore, can by the skin of face feature differentiation real skins of different parts with it is non-real
Real skin, to carry out vivo identification.
First recognition unit 31 includes corresponding first identification model, and face characteristic is inputted the first identification model can be into
Row vivo identification.First identification model can classify to facial image, if the face characteristic extracted meets living body faces figure
When the face characteristic of picture, living body faces image class is classified to the facial image of picture by tested.If the face characteristic extracted meets
When the face characteristic of non-living body facial image, non-living body facial image class is classified to the facial image of picture by tested.
First identification model is the depth convolutional neural networks model that training obtains in advance, and convolutional neural networks are artificial minds
One kind through network can allow image avoid feature complicated in tional identification algorithm directly as the input of network
Extraction and data reconstruction processes.
Convolutional neural networks include convolutional layer and output layer, and convolutional layer is mainly using trainable convolution kernel come to input number
According to progress convolution operation, and by result, form is exported in some combination, and essence is the feature extraction to input data.Output layer
It is converted using nonlinear function, so that model is obtained nonlinear characteristic and export-restriction in given range with this, become
Activation primitive.I.e. output layer is used to carry out specific vivo identification.
After obtaining training sample, disaggregated model is trained, the first identification model can be obtained.Passing through instruction
It gets to after the first identification model, is just able to use first identification model and classifies, judge the facial image of measurand
In skin characteristic be real skin be still non-genuine skin, to realize the vivo identification of facial image.
Include the face sample set of multiple classifications in training sample, includes more in the face sample set of each classification
A facial image sample includes real human face, photo face, video human face, 3D model face, certificate face that is, in training sample
Etc. multiple groups sample set.
Using convolutional layer carry out feature extraction when, it is first determined the skin area in acquired facial image, then from
The skin characteristic of facial image is extracted in identified skin area.The skin characteristic of extracted facial image includes: difference
At least one of the dermatoglyph feature and skin pore feature at position.Different parts include extracting forehead, eyebrow, eye
It is eyeball, two cheeks, nose, lip, chin, at least two kinds of in ear.
In one embodiment, the dermatoglyph feature of two cheeks and forehead is extracted as training sample；In another embodiment, example
There are when mask shelter, extract the dermatoglyph feature at forehead, place between the eyebrows and canthus as training sample for such as face head portrait.
In specific implementation, the quantity of facial image is as more as possible, and the skin characteristic as much as possible for obtaining different parts, training sample
The first identification model that the more how final training of this quantity obtains is more accurate.
Second recognition unit 32 is voice recognition unit, and the lip reading information that can be issued according to facial image carries out living body knowledge
Not, judge whether the face in facial image is living body.In order to improve the accuracy of vivo identification, when the first recognition unit of utilization
31 when being mistaken for non-living body for living body or non-living body being mistaken for living body, carries out speech recognition using the second recognition unit 32,
Prevent illegal user from attacking.
Voice recognition unit includes the loudspeaker 321 and microphone 322 that 100 surface of recognition of face terminal is arranged in, loudspeaking
For device 321 for playing voice, microphone 322 is used to receive extraneous voice signal, in present embodiment, if there are two microphones
322, form two wheat linear arrays, can it is significantly more efficient inhibit noise, echo interference, greatly improve the sensitive of phonetic incepting
The accuracy rate of degree and speech recognition.
Voice recognition unit can issue stochastic instruction, prompt user to read number combination providing with the machine, carry out voice
Identification.Digital group is combined into the number combination being randomly generated in 1-9.Three random digits are included at least in random digit combination.
Second recognition unit 32 carries out vivo identification to measurand by the second identification model, and the second identification model is language
Sound identification model, speech recognition modeling issue phonetic order to measurand, and measurand is prompted to read number providing with the machine
Combination, measurand read corresponding random digit combination password according to the phonetic order and carry out vivo identification.
Second recognition unit 32 is used for the starting when the first recognition unit 31 can not identify whether measurand is living body
Identification.The at most identification of second recognition unit 32 three times, if prompting vivo identification to fail after recognition failures three times, and by living body
Recognition result is sent to the display of display panel 1, and the prompt of such as " non-living body " is issued by loudspeaker 321, exits recognition of face
Program.
Loudspeaker 321 can be also used for entire recognition of face terminal 100, issues such as " please be directed at camera lens ", " verifies logical
Cross ", the prompt tone of " authentication failed " etc..
Vivo identification is carried out compared to requiring measurand to make the random actions such as shake the head, blink, open one's mouth, using actively matching
The random digit speech recognition of conjunction, it is ensured that the reliability of system, and anti-attack ability is improved, guarantee the accurate of vivo identification
Property.
Identification module 3 further includes authentication unit 33, for determine measurand be living body after, will it is collected be tested pair
The face characteristic of elephant is compared with the face characteristic in standard database, carries out face verification to the facial image.
Standard database includes local data base and remote data base, and the data in local data base are stored in recognition of face
In the memory module of terminal 100, the data in remote data base are stored in server 200.
When recognition of face is verified, authentication unit 33 calls local data base first, if existing subscriber's data, according to guarantor
The user's facial feature information deposited, and the facial image feature of measurand of input are compared, if similarity is higher than threshold
Value is then identified and is verified.If local useless user data, will be in the facial image feature of measurand by server 200
It reaches remote data base and carries out identification verifying；Authentication unit 33 calls the identity stored in remote data base by server 200
The facial image feature of information and measurand is compared, and identification verification result is sent to display panel 1 and is shown, if
Similarity is greater than threshold value and is then identified by, and otherwise identifies authentication failed.
It in one embodiment, such as company's access control system, can be by brush face mode come the discrepancy of controllers, Yuan Gongxu
When entering company, it can stand in the position apart from 100 certain distance of recognition of face terminal, utilize the camera shooting of image capture module 2
Head acquisition user images, and then determine that user schemes according to the first recognition unit 31 of identification module 3 and the second recognition unit 32
Whether the user as in is living body, if it is living body, enters identification proving program in next step, verifies whether as the said firm person
Work allows access into if so, opening the door.
Recognition of face terminal 100 further includes communication module, by wired or wireless between communication module and other equipment
Mode connects.Recognition of face terminal 100 can access the wireless network based on communication standard, for example, WiFi, 3G, 4G or it
Combination.In one embodiment, communication module further includes near-field communication (NFC) unit for short range communication.NFC unit can
It is realized based on Bluetooth technology, radio frequency identification (RFID) technology, infrared technique, ultra wide band (UWB) technology and other technologies.
Recognition of face terminal 100 further includes the power supply (such as battery) for the power supply of each component, it is preferable that power supply and each component
Pass through circuit connection.Power supply may include one or more direct current or AC power source, power failure detection circuit, power supply
The random components such as converter or inverter, power supply status indicator.
Above-mentioned face identification system further includes terminal device 300, terminal device 300 respectively with recognition of face terminal 100 and
Server 200 communicates to connect, and can remotely control recognition of face terminal 100 by terminal device 300 and carry out recognition of face.Terminal
Equipment 300 can be one of smart phone, tablet computer, PC computer, personal digital assistant (PDA) etc. or a variety of.
It is to be appreciated that recognition of face terminal 100 has a set of corresponding application program matched, in terminal device 300
Also there is a set of corresponding application program matched.
The specific work process of above-mentioned face identification system includes:
(1) it obtains the facial image of measurand and the facial image detected is marked.
Wherein, facial image can be living body faces image and be also possible to non-living body facial image.Non-living body includes face
Existing image, such as the two dimensional image or identity document that are shown on human face photo, screen according to etc..
In specific implementation, facial image can be marked by indicia framing, indicia framing is usually to use rectangle frame, to people
Face is demarcated up to the crown, down toward neck, left and right to the region of ears.
If camera has collected the image comprising people, animal and background, animal and background image are invalid images,
In order to get effective facial image, the information in image is detected, identifies label, to obtain in image about people
Or the image of the object of characterization people.In the present embodiment, facial image can only include the image of face facial area.
Specifically, recognition of face terminal 100 is by external camera, under the current visual field of camera, acquisition camera shooting
Image (for example, frame, picture etc.) in head range, by taking frame as an example.Recognition of face terminal 100 can be examined after collecting picture frame
It surveys with the presence or absence of facial image in the picture frame, facial image, then be marked the facial image if it exists, and caches guarantor
It deposits.
The picture frame of acquisition can also be sent to server 200 after collecting picture frame by recognition of face terminal 100, by
Server 200 is detected again with the presence or absence of facial image in the picture frame, and facial image, then mark the facial image if it exists
Note.
(2) vivo identification is carried out to the facial image that detects according to identification model, judge the facial image whether be
Living body then carries out next step face alignment verifying if living body；If not living body, then send vivo identification failure information to institute
Display panel is stated, recognition of face is terminated.
Specifically, it after the facial image for obtaining measurand, is lived according to the first identification model to the facial image
Body identification, judges whether the facial image is living body.
The skin characteristic of different parts in same facial image is compared using the first identification model, if obtained skin
The similarity of skin feature be less than preset similarity threshold, then, judge facial image currently entered for living body, so that it is determined that
By vivo identification, into next step face verification；If the similarity of obtained skin characteristic is greater than preset similarity threshold,
So, judge that facial image currently entered is not living body, then further voice living body is carried out according to the second identification model and known
Not.
When carrying out speech recognition using the second identification model, the lip characteristics of image for the random digit that measurand is read
Matching ratio is carried out as the standard lip characteristics of image in the input of the second identification model, with the second identification model of training in advance
It is right, obtain vivo identification result.If the lip characteristics of image for each random digit that measurand is read and the mark of random digit
Quasi- lip characteristics of image matches, it is determined that measurand is living body, and otherwise measurand is non-living body.
When carrying out speech recognition, if may further comprise: recognition result be non-living body, prompt measurand again into
Row speech recognition, that is, measurand is made to read corresponding digital combining random according to the stochastic instruction that the second identification model issues
Number combination password；If obtained recognition result is still non-living body after the speech recognition of preset times, then judgement is tested
Object is non-living body, exits whole recognition of face program.
In specific implementation, the number of speech recognition is at most 3 times.By multiple speech recognition, work can be further promoted
The accuracy of body identification, reduces the interference of enchancement factor.
The utility model is trained by using convolutional neural networks and obtains corresponding identification model, then directly will be to
The facial image of identification, which is input in identification model, can be realized vivo identification, and user experience is good, practical.
(3) face characteristic of the facial image is compared with the facial image that prestores in standard database, is determined
Face recognition result.
Face characteristic number of the face characteristic including geometrical characteristic (such as Euclidean distance), algebraic characteristic (eigenmatrix)
According to.Known face in face to be identified and standard database is compared, matching result is obtained.If successful match, face
Identification is verified；If matching is unsuccessful, recognition of face authentication failed.
The facial image that prestores in standard database can store in recognition of face terminal 100, also can store service
It is called in device 200 by recognition of face terminal 100.
The utility model using Multiple recognition carry out recognition of face, and by face skin characteristic identification and speech recognition phase
In conjunction with vivo identification is carried out, it can effectively solve the problem that and carry out vivo identification using photo, video and three-dimensional face model etc. and hold
The fraud problem being also easy to produce reaches the function of pinpoint accuracy vivo identification and recognition of face, effectively improves the safety of recognition of face
Property.In addition, the utility model uses the dual camera being made of visible light and black light, can be acquired under different light
Facial image obtains the image of high quality, improves face recognition accuracy rate.
It should be pointed out that in the description of the present invention, term " first ", " second " be only used to an entity or
Person's operation is distinguished with another entity or operation, is appointed without necessarily requiring or implying existing between these entities or operation
What this actual relationship or sequence.
The preferable specific embodiment of the above, only the utility model, but the protection scope of the utility model is not
It is confined to this, anyone skilled in the art within the technical scope disclosed by the utility model, can readily occur in
Change or replacement, should be covered within the scope of the utility model.Therefore, the protection scope of the utility model should be with
Subject to the scope of protection of the claims.
Claims (5)
1. a kind of face identification system, which is characterized in that including recognition of face terminal and server, the recognition of face terminal and
Server communication connection, the recognition of face terminal include display panel, image capture module and identification module, described
Image capture module is electrically connected with the identification module, and the camera of described image acquisition module is mounted on the display panel
Top, the camera are used to acquire the facial image of measurand, and collected facial image is sent to the identification
Module, the identification module is used to carry out the measurand vivo identification, and is identifying that measurand is the feelings of living body
The facial image is compared with the facial image that prestores in face database under condition, obtains face recognition result；It is described
Identification module includes the first recognition unit and the second recognition unit, and first recognition unit is skin-identification unit, is used for root
Vivo identification is carried out according to the skin characteristic of the facial image；Second recognition unit is voice recognition unit, is used for basis
The lip reading information that measurand issues carries out further vivo identification.
2. face identification system according to claim 1, which is characterized in that the identification module further includes authentication unit,
The authentication unit is used for will be in the facial image and face database in the case where identifying that measurand is living body
It prestores facial image to be compared, obtains face recognition result.
3. face identification system according to claim 1, which is characterized in that the camera includes visible image capturing head
And/or black light camera.
4. face identification system according to claim 1, which is characterized in that second recognition unit includes being arranged in institute
The loudspeaker and microphone for stating recognition of face terminal end surface are provided with 2 microphones.
5. according to face identification system described in claim 1, which is characterized in that the skin characteristic of the facial image includes volume
Head, eyebrow, eyes, two cheeks, nose, lip, chin, in ear at least two positions skin characteristic.
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| CN201820778810.3U CN208351494U (en) | 2018-05-23 | 2018-05-23 | Face identification system |
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| CN201820778810.3U CN208351494U (en) | 2018-05-23 | 2018-05-23 | Face identification system |
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110866563A (en) * | 2019-11-20 | 2020-03-06 | 咪咕文化科技有限公司 | Similar video detection and recommendation method, electronic device and storage medium |
| CN111325139A (en) * | 2020-02-18 | 2020-06-23 | 浙江大华技术股份有限公司 | Lip language identification method and device |
| CN111340014A (en) * | 2020-05-22 | 2020-06-26 | 支付宝(杭州)信息技术有限公司 | Living body detection method, living body detection device, living body detection apparatus, and storage medium |
| CN113449137A (en) * | 2020-03-27 | 2021-09-28 | 杭州海康威视数字技术股份有限公司 | Face image display method and device of face front-end device and storage medium |
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2018
- 2018-05-23 CN CN201820778810.3U patent/CN208351494U/en active Active
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110866563A (en) * | 2019-11-20 | 2020-03-06 | 咪咕文化科技有限公司 | Similar video detection and recommendation method, electronic device and storage medium |
| CN110866563B (en) * | 2019-11-20 | 2022-04-29 | 咪咕文化科技有限公司 | Similar video detection and recommendation method, electronic device and storage medium |
| CN111325139A (en) * | 2020-02-18 | 2020-06-23 | 浙江大华技术股份有限公司 | Lip language identification method and device |
| CN111325139B (en) * | 2020-02-18 | 2023-08-04 | 浙江大华技术股份有限公司 | Lip language identification method and device |
| CN113449137A (en) * | 2020-03-27 | 2021-09-28 | 杭州海康威视数字技术股份有限公司 | Face image display method and device of face front-end device and storage medium |
| CN111340014A (en) * | 2020-05-22 | 2020-06-26 | 支付宝(杭州)信息技术有限公司 | Living body detection method, living body detection device, living body detection apparatus, and storage medium |
| CN111340014B (en) * | 2020-05-22 | 2020-11-17 | 支付宝(杭州)信息技术有限公司 | Living body detection method, living body detection device, living body detection apparatus, and storage medium |
| CN112507831A (en) * | 2020-05-22 | 2021-03-16 | 支付宝(杭州)信息技术有限公司 | Living body detection method, living body detection device, living body detection apparatus, and storage medium |
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