CN204791017U - Mobile terminal users authentication device based on many biological characteristics mode - Google Patents
Mobile terminal users authentication device based on many biological characteristics mode Download PDFInfo
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Abstract
The utility model provides a mobile terminal users authentication device based on many biological characteristics mode, the device includes image acquisition module, image transmission module and biological characteristics algorithm processing module, wherein the image acquisition module includes a camera module and infrared light for acquire including people's face of people's eye iris or nearly infrared image near the eyes, the image transmission module be used for with the communication of biological characteristics algorithm processing module, the nearly infrared image that will acquire transmission extremely biological characteristics algorithm processing module, biological characteristics algorithm processing module is used for going on distance prediction and the biological characteristics data processing to gathering, including detect people eye position and distinguish about eye, key point detect, based on near -infrared iris, people's face or regional many biological characteristics discernment near the eyes.
Description
Technical field
The utility model relates to a kind of the utility model and relates to the technical field such as living things feature recognition and information security, particularly relates to personal identification method and device that a kind of mobile terminal iris recognition is combined with recognition of face.
Background technology
In recent years, mobile terminal device function is constantly promoted and is strengthened, and utilizes mobile terminal device, and user can carry out the various functions such as amusement, shopping.Bringing for user greatly easily simultaneously, potential safety hazard also constantly manifests, the personal information of user is maliciously stolen, the camera of mobile phone terminal is maliciously opened, mobile payment, mobile financing also exist huge potential safety hazard, promotes the development of living things feature recognition at mobile terminal device.
Traditional living things feature recognition comprises: fingerprint recognition, recognition of face, iris recognition, Application on Voiceprint Recognition, refer to hand vein recognition etc.Be limited by the restriction of hardware device, mostly integrated in the mobile terminal device of present stage is fingerprint recognition, recognition of face and Application on Voiceprint Recognition.Compared to these three kinds of biological characteristic mode, iris recognition has the features such as untouchable, security is high, uniqueness is strong.Along with the demand of user in mobile payment, mobile financing etc. constantly promotes, user to the safety problem of mobile terminal also in continuous attention.The advantage of iris recognition is also further amplified.
Fingerprint recognition directly presses associated components by user to realize obtaining corresponding finger print data, recognition of face and iris recognition all obtain face and the iris information of user by camera, this non-contacting user data acquisition methods can reduce user profile greatly by the possibility of maliciously stealing, but its drawback is just that the cooperation needing user certain could realize authenticating user identification.This cooperation needs distance and the certain condition of the equal demand fulfillment of user's attitude.The requirement that single iris recognition coordinates user is more harsh, and this just makes Consumer's Experience relatively poor.The security of single recognition of face is relatively on the low side again.How in conjunction with recognition of face and iris recognition, the perfect adaptation reaching ease for use and security is the bottleneck that living things feature recognition obtains at mobile terminal device fully promoting always.
The utility model will detect the reach distinguishing iris recognition and recognition of face by the distance in combination algorithm aspect, at utmost play the feature of iris recognition security and recognition of face ease for use, thus the security performance of lifting mobile terminal device.
Utility model content
The purpose of this utility model is to provide a kind of mobile terminal multi-biometric feature recognition identification authentication system, and it can be used for promoting the security of authenticating user identification and convenience.
For achieving the above object, the utility model provides a kind of mobile phone users identification authentication system based on multi-biological characteristic mode, described device comprises image collection module, image transmission module and biometric algorithm processing module, wherein said image collection module comprises a camera module and infrared illumination lamp, for obtaining the face that comprises human eye iris or near-infrared image near the eyes; Described image transmission module is used for communicating with described biometric algorithm processing module, and the near-infrared image of acquisition is transferred to described biometric algorithm processing module; Described biometric algorithm processing module, for carrying out range prediction and to collected biological attribute data process, comprises and detects position of human eye and distinguish right and left eyes, critical point detection, multi-biometric feature recognition based near infrared iris, face or periocular area.
Preferably, described image collection module also comprises optical filter, imageing sensor and infrared illumination control module.
Preferably, described optical filter is set to the single-pass optical filter of near infrared light or the bilateral optical filter of near infrared light and visible ray.
Preferably, the field angle scope of described camera module is arranged on 20 ° ~ 50 °.
Preferably, described imageing sensor is set to CMOS, ccd sensor or RGB-IR imageing sensor.
Preferably, described infrared illumination module is thrown light on by one or more near-infrared LED and is formed.
Preferably, the centre wavelength 810nm of described infrared illumination module or 850nm.
Preferably, the object distance of described image collection module is 15cm ~ 60cm.
Preferably, described infrared illumination illumination self-adaptive control module is set to lasting infrared illumination or has the infrared illumination of certain frequency.
According to another aspect of the present utility model, provide the mobile terminal comprising above-mentioned authenticating user identification device, described mobile terminal be selected from smart phone, panel computer, intelligent wearable device, intelligent watch, intelligent glasses, Intelligent bracelet, intelligent door lock any one.
Can at multi-biological characteristic according to a kind of mobile terminal multi-biometric feature recognition identification authentication system of the present utility model and method, such as iris, near the eyes and the miniaturization of the recognition device of face, mobile, there is larger improvement the aspects such as ease for use compared with prior art, single image collection module can be adopted full face or comprise iris or part facial image near the eyes synchronously obtains, and the distance range gathered can be extended to 60cm, identify the introducing with recognition of face near the eyes, greatly can promote the ease for use of the mobile terminal authentication method based on living things feature recognition, increase the using method of authentication, the convenience of authentication is significantly promoted.
The utility model has the authentication recognition function of normal operating conditions and the function regulating mobile terminal using state according to user's liveness of low-power consumption, so not only ensure that user security, and greatly improves user's experience.
Should be appreciated that description and the follow-up detailed description of aforementioned cardinal principle are exemplary illustration and explanation, should not be used as the restriction to the claimed content of the utility model.
Accompanying drawing explanation
In order to clearer explanation the utility model embodiment or technical scheme of the prior art, be briefly described to the accompanying drawing used required in embodiment or description of the prior art below, apparently, accompanying drawing in the following describes is only embodiments more of the present utility model, for those of ordinary skill in the art, under the prerequisite not paying creative work, other accompanying drawings can also be obtained according to these accompanying drawings.
Fig. 1 shows according to the mobile terminal schematic diagram carrying out authenticating user identification based on multi-biological characteristic mode of the present utility model;
Fig. 2 shows the structured flowchart according to the mobile phone users authentication module based on multi-biological characteristic mode of the present utility model;
Fig. 3 shows the process flow diagram according to the biometric algorithm processing module in the structured flowchart of Fig. 2 authenticating user identification module;
Fig. 4 shows the process flow diagram according to the mobile phone users identity identifying method based on multi-biological characteristic mode of the present utility model;
Fig. 5 shows according to of the present utility model under closely iris recognition pattern, client iris registration and the process flow diagram identified;
Fig. 6 shows client iris identified region in Fig. 5;
Fig. 7 shows according to of the present utility model under middle distance recognition of face pattern, the process flow diagram of user's face registration and identification;
Fig. 8 shows user's recognition of face region in Fig. 6;
Fig. 9 shows according to of the present utility model under middle distance near the eyes recognition mode, the process flow diagram that user registers near the eyes and identifies;
Figure 10 shows the user's identified region near the eyes in Fig. 9;
Figure 11 shows according to the process flow diagram of mobile terminal under low power mode of operation based on multi-biological characteristic mode of the present utility model.
Figure 12 shows the face that becomes certain anglec of rotation in Fig. 9 step 907 with mobile terminal and image near the eyes.
Embodiment
By reference to one exemplary embodiment, the purpose of this utility model and function and the method for realizing these objects and function will be illustrated.But the utility model is not limited to following disclosed one exemplary embodiment, can be realized by multi-form to it.The essence of instructions is only help various equivalent modifications Integrated Understanding detail of the present utility model.
Fig. 1 shows according to the mobile terminal schematic diagram carrying out authenticating user identification based on multi-biological characteristic mode of the present utility model.As shown in Figure 1, mobile terminal 100 is provided with display screen 101, for showing the face comprising human eye that collects or image near the eyes; The either side of display screen 101 is provided with authenticating user identification module 102, for the identification based on multi-biological characteristic mode.Preferably, authenticating user identification module 102 is arranged on the upside of display screen 101.
Comprise according to the mobile terminal of authenticating user identification of the present utility model can be selected from smart phone, panel computer, intelligent wearable device, intelligent watch, intelligent glasses, Intelligent bracelet, intelligent door lock any one.
Fig. 2 shows the structured flowchart according to the mobile phone users authentication module based on multi-biological characteristic mode of the present utility model.Namely mobile phone users authentication module in Fig. 2 is the authenticating user identification module 102 in Fig. 1.As shown in Figure 2, comprise image collection module 210, image transmission module 220 and biometric algorithm processing module 230 according to a kind of mobile phone users identification authentication system 202 based on multi-biological characteristic mode of the present utility model, wherein,
Image collection module 210 is set to single image acquisition module, for obtaining the face or image near the eyes that comprise human eye iris simultaneously:
Particularly, according to an embodiment of the present utility model, image collection module 210 comprises optical filter, camera module, imageing sensor, infrared illumination module, infrared illumination control module:
Optical filter is set to the single-pass optical filter of near infrared light or the bilateral optical filter of near infrared light and visible ray;
The field angle scope of camera module is arranged on 20 ° ~ 50 °;
Imageing sensor is set to CMOS, ccd sensor or RGB-IR imageing sensor;
Infrared illumination control module is set to illumination adaptive control module, illumination adaptive control module is set to lasting infrared illumination or has the infrared illumination of certain frequency, user distance information can be obtained according to user's real-time status, infrared illumination module can be thrown light on by one or more near-infrared LED and be formed, and the centre wavelength 810nm of infrared illumination module or 850nm.
Image collection module 210 is provided with normal certification mode and low power mode of operation, normal certification mode is closely iris recognition and middle distance face or identify near the eyes, for carrying out authentication to user, low power mode of operation is Real-Time Monitoring human eye or face, for the monitoring of user's liveness.Normal certification mode is set to closely iris recognition, middle distance recognition of face or identifies near the eyes, closely identifies and is set to the recognition method of the single mode of iris recognition, also comprise iris recognition respectively with recognition of face or the recognition method identifying fusion near the eyes.Middle distance identification is set to recognition of face or identifies near the eyes, also comprises recognition of face or identifies the recognition method merged with iris recognition respectively near the eyes.According to the utility model, closely with in the scope of middle distance face or image near the eyes all can be collected, namely iris image can be got.Closely time, the quality of iris image is higher, and security is also comparatively strong, so carry out authentication by iris recognition can have very high precision closely time.When middle distance, relatively poor under the quality closer distance of iris image, the single biological characteristic mode in multi-biological characteristic fusion can be used as, and not as the mode be used alone.Such as, assist face with iris image or identify near the eyes.
According to one embodiment of present invention, the object distance of image collection module 210 is preferably 15cm ~ 60cm, namely image collection module 210 couples of users carry out iris, face, decipherment distance scope be near the eyes 15cm ~ 60cm, preferably, iris and face, separation identification range threshold value are near the eyes the first distance threshold, namely, when being less than the first distance threshold, iris recognition is switched to.When being greater than the first distance threshold, be switched to face or identification near the eyes.Preferably, the first distance threshold can be the arbitrary value in 30cm ~ 40cm.More preferably, the first distance threshold is 35cm.
When carrying out iris recognition, preferably, in the iris image photographed, the resolution of iris region is not less than 70 pixels.Iris image region refers to the outward flange of iris image, i.e. number of pixels in the diametric(al) of iris region is not less than 70 pixels.When being greater than the first distance threshold, being switched to face or identifying near the eyes.Image acquisition resolution is set to higher than 2,000,000 pixels.Low-power consumption certification mode is set to Real-Time Monitoring human eye or face, and for monitor user ' liveness, image acquisition resolution scope is set to 300,000 pixels ~ 2,000,000 pixels.
Image transmission module 220 for obtaining the image collected from image collection module 210, and communicates with biometric algorithm processing module 230, by the image transmitting extremely described biometric algorithm processing module 230 obtained.Image transmission module 220 comprises coupling assembling, image framing conciliates frame program, namely from the sensor of image collection module 210, data assemblies is become image and transmits, and at receiving end, the picture frame be combined into decomposition is obtained corresponding image.
Biometric algorithm processing module 230 is for carrying out range prediction and prompting, and to collected biological attribute data process, comprise and detect position of human eye and distinguish right and left eyes, critical point detection, multi-biometric feature recognition based near infrared iris, face or periocular area.
As shown in Figure 2, mobile phone users identification authentication system 202 carries out information interaction by human-computer interaction module 240 with user, such as range information prompting is carried out to user, in iris image acquiring processing procedure, described mobile phone users identification authentication system be configured for making user and realize human-computer interaction function with described device.Preferably, human-computer interaction module 240 can adopt the multiple prompting mode such as auditory tone cues, picture cues.Touch-screen, loudspeaker etc. that human-computer interaction module 240 can utilize mobile terminal to carry realize its function.
Fig. 3 shows the process flow diagram according to the mobile phone users identity identifying method based on multi-biological characteristic mode of the present utility model, and as shown in Figure 3, the method step is:
First, Identity Authentication Mode is started;
In step 301, by image collection module gather near infrared comprise user's human eye face or biometric image near the eyes, enter step 302;
In step 302, carry out human eye area location based on the biometric image gathered, calculate the decipherment distance of user according to human eye positioning result, enter step 303;
According to an embodiment of the present utility model, human eye area location realizes the location of carrying out human eye area within the scope of whole or local facial region, and distinguishes right and left eyes.
In step 303, decipherment distance is judged, if hypertelorism or excessively closely return step 301 Resurvey; Otherwise enter step 304;
According to an embodiment of the present utility model, decipherment distance between user and described mobile terminal is between 15cm to 60cm, i.e. object distance, if gather distance not within the scope of 15cm ~ 60cm, then return step 301 Resurvey, if gather distance within the scope of 15cm ~ 60cm, then enter step 304;
In step 304, face critical point detection is carried out, by judging whether user's attitude meets collection requirement, enters step 305 to the critical point detection of face based on the biometric image gathered;
In step 305, judge that whether biometric image meets the condition of iris recognition, and whether the distance namely between human eye and image collection module is less than the first distance threshold, if be less than, enters step 306; Otherwise enter step 307; Preferably, the distance between human eye and image collection module can utilize the result obtained in step 303.
Preferably, the first distance threshold is 30 ~ 40cm, and more preferably, the first distance threshold is 35cm.How first distance threshold is selected to decide according to the application scenarios of reality or recognizer performance.
Within step 306, iris image is taken off biometric image from the gathered face comprising user's human eye or near the eyes, utilize described iris image to carry out iris recognition to carry out the certification of user identity, concrete iris recognition mode is described with reference to Fig. 5 and Fig. 6 below;
In step 307, the described biometric image gathered is utilized to carry out face or identify to carry out the certification of user identity near the eyes, the recognition method of concrete face is described with reference to Fig. 7 and Fig. 8 below, and recognition method is near the eyes described with reference to Fig. 9 and Figure 10 below;
In step 308, the result of authenticating user identification is exported.
Fig. 4 shows the process flow diagram of the biometric algorithm processing module 230 of the structured flowchart according to authenticating user identification module 202 in Fig. 2; As shown in Figure 4, the workflow of biometric algorithm processing module 430 is:
In step 401, image information inputs to biometric algorithm processing module 430, and judges to gather distance, enters step 402;
In step 402, according to recognition threshold, the distance gathering image is differentiated, if gather distance to exceed threshold value, carry out step 406, otherwise enter step 403;
According to an embodiment of the present utility model, described object distance is 15cm ~ 60cm, namely identifies the acquisition range of authentication, if gather distance not within the scope of 15cm ~ 60cm, then carry out step 406;
In a step 406, collect the pose information being greater than recognition threshold, send adjustment signal by mobile terminal, human-computer interaction, until adjustment posture is within the scope of recognition threshold, enter step 403;
In step 403, the image being not more than threshold value is carried out mode selection according to iris, face or identification range near the eyes, and identification range is less than the first distance threshold, such as 30cm ~ 40cm, enters step 404, otherwise enters step 405;
In step 404, iris feature is adopted to carry out authentication identification;
In step 405, adopt near the eyes or face carry out authentication identification.
Fig. 5 shows according to of the present utility model under closely iris recognition pattern, client iris registration and the process flow diagram identified, namely in Fig. 3, step 306 takes off iris image from the gathered face comprising user's human eye or near the eyes biometric image, utilizes described iris image to carry out iris recognition to carry out the specific works flow process of authenticating user identification.Described iris region as shown in Figure 6, be positioned at ocular 601a and 601b, user's eye locations can be obtained by human eye 602a and 602b detection method, can from high-resolution face 603 or near the eyes 601a and 601b image intercept the iris recognition image met the demands, the diameter of iris region should between 70 ~ 300 pixels.As shown in Figure 5, client iris registration and the flow process identified, registration step is as follows:
First enter iris registration mode, enter step 501;
In step 501, according to human eye area positioning result real-time Transmission iris image, step 502 is entered;
In step 502, by Iris preprocessing and feature extracting method, obtain the iris feature of user, enter step 503;
In step 503, iris feature is existed in the iris feature template base of user;
Iris recognition step is as follows:
First enter iris recognition pattern, enter step 504;
In step 504, according to human eye detection result real-time Transmission iris image, step 505 is entered;
In step 505, by Iris preprocessing and feature extracting method, obtain the iris feature of user, enter step 506;
In step 506, the iris feature in the iris feature template base of iris feature and user is compared, enters step 507;
In step 507, export the authentication information of user.
Fig. 7 shows according to of the present utility model under middle distance recognition of face pattern, the process flow diagram of user's face registration and identification, the described biometric image that namely in Fig. 3, the utilization of step 307 gathers carries out recognition of face to carry out the specific works flow process of the certification of user identity.As shown in Figure 8, face 801 refers to the region comprising the organs such as eyes, nose, eyebrow to described human face region.As shown in Figure 7, the flow process of user's face registration and identification, registration step is as follows:
First open face registration pattern, enter step 701;
In step 701, face is detected, enter step 702;
In a step 702, according to Face datection result, face key point is positioned, enter step 703;
In step 703, according to face's key point information, facial image is normalized, enters step 704;
In step 704, face characteristic is extracted, enter step 705;
In step 705, form user's skin detection storehouse;
Identification step is as follows:
First start recognition mode, enter step 706;
In step 706, face is detected, enter step 707;
In step 707, according to Face datection result, face key point is positioned, enter step 708;
In step 708, according to face's key point information, facial image is normalized, enters step 709;
In step 709, face characteristic is extracted, enter step 710;
In step 720, carry out face characteristic comparison with user's skin detection storehouse, enter step 711;
In step 711, authentication information result is exported.
Fig. 9 shows according to of the present utility model under middle distance near the eyes recognition mode, the process flow diagram that user registers near the eyes and identifies, the described biometric image that namely in Fig. 3, the utilization of step 308 gathers identifies the specific works flow process of the certification carrying out user identity near the eyes.Describedly refer to the rectangular region 1002 comprising eyes 1001a and 1001b near the eyes as shown in Figure 10, this region is except the texture information of iris, and also comprise the eyelashes of user, eyelid, eyebrow etc. are information near the eyes.As shown in Figure 9, the flow process that user registers near the eyes and identifies, registration step is as follows:
First open registration mode near the eyes, enter step 901;
In step 901, take off parts of images near the eyes according to during human eye detection fructufy, enter step 902;
In step 902, according to the relative position of eyes, image is near the eyes rotated, enter step 903;
In step 903, according to eye key point information, image is near the eyes normalized, enters step 904;
In step 904, carry out feature extraction near the eyes, enter step 905;
In step 905, form user feature templates storehouse near the eyes;
Identification step is as follows near the eyes:
First open recognition mode near the eyes, enter step 906;
In step 906, take off parts of images near the eyes according to during human eye detection fructufy, enter step 907;
In step 907, according to the relative position of eyes, image is near the eyes rotated, as shown in figure 12, comprise human face region 1201 and periocular area 1202, by calculating eyes line and horizontal angle α, periocular area 1202 being rotated, enters step 908;
In step 908, according to eye key point information, image is near the eyes normalized, enters step 909;
In step 909, carry out feature extraction near the eyes, enter step 910;
In step 910, carry out face characteristic comparison in feature templates storehouse near the eyes with user, enter step 911;
In step 911, export identity authentication result.
Image collection module of the present utility model also comprises the low power mode of operation for carrying out the monitoring of user's liveness, the biometric image resolution gathered under low power mode of operation 300,000 pixels and 2,000,000 pixels it.Figure 11 shows according to the process flow diagram of mobile terminal under low power mode of operation based on multi-biological characteristic mode of the present utility model, and step is as follows:
First open low power mode of operation, enter step 1101;
In step 1101, carry out real-time image acquisition, enter step 1102;
In step 1102, carry out real-time Face datection or human eye detection, detect the liveness that user uses mobile terminal, enter step 1103;
In step 1103, judge the liveness of the current use mobile terminal device of user, thus realize the adjustment to the using state of mobile terminal device, enter step 1104;
In step 1104, according to the using state of user's liveness adjustment mobile terminal, when user's liveness is lower, the brightness of mobile terminal screen is reduced; When user's liveness is higher, ensure that mobile terminal screen brightness is constant.
It is more than the utility model preferably example, be not limit the utility model practical range, therefore all equivalences done according to structure, feature and the principle described in the utility model claim change or modify, and all should be included in the utility model patent claim.
Claims (10)
1., based on a mobile phone users identification authentication system for multi-biological characteristic mode, described device comprises image collection module, image transmission module and biometric algorithm processing module, wherein
Described image collection module comprises a camera module and infrared illumination lamp, for obtaining the face that comprises human eye iris or near-infrared image near the eyes;
Described image transmission module is used for communicating with described biometric algorithm processing module, and the near-infrared image of acquisition is transferred to described biometric algorithm processing module;
Described biometric algorithm processing module, for carrying out range prediction and to collected biological attribute data process, comprises and detects position of human eye and distinguish right and left eyes, critical point detection, multi-biometric feature recognition based near infrared iris, face or periocular area.
2. authenticating user identification device as claimed in claim 1, is characterized in that: described image collection module also comprises optical filter, imageing sensor and infrared illumination control module.
3. authenticating user identification device as claimed in claim 2, is characterized in that: described optical filter is set to the single-pass optical filter of near infrared light or the bilateral optical filter of near infrared light and visible ray.
4. authenticating user identification device as claimed in claim 2, is characterized in that: the field angle scope of described camera module is arranged on 20 ° ~ 50 °.
5. authenticating user identification device as claimed in claim 2, is characterized in that: described imageing sensor is set to CMOS, ccd sensor or RGB-IR imageing sensor.
6. authenticating user identification device as claimed in claim 2, is characterized in that: described infrared illumination module is thrown light on by one or more near-infrared LED and formed.
7. authenticating user identification device as claimed in claim 2, is characterized in that: the centre wavelength 810nm of described infrared illumination module or 850nm.
8. authenticating user identification device as claimed in claim 2, is characterized in that: the object distance of described image collection module is 15cm ~ 60cm.
9. authenticating user identification device as claimed in claim 8, is characterized in that: described infrared illumination illumination self-adaptive control module is set to lasting infrared illumination or has the infrared illumination of certain frequency.
10. comprise a mobile terminal for the authenticating user identification device in the claims 1 to 9 described in any one, described mobile terminal be selected from smart phone, panel computer, intelligent wearable device, intelligent watch, intelligent glasses, Intelligent bracelet, intelligent door lock any one.
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Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN104933344A (en) * | 2015-07-06 | 2015-09-23 | 北京中科虹霸科技有限公司 | Mobile terminal user identity authentication device and method based on multiple biological feature modals |
| CN106548152A (en) * | 2016-11-03 | 2017-03-29 | 厦门人脸信息技术有限公司 | Near-infrared three-dimensional face tripper |
| CN107341928A (en) * | 2017-06-01 | 2017-11-10 | 厦门快商通科技股份有限公司 | A kind of intelligent control device and its control method for public resource granting |
| CN108353137A (en) * | 2016-04-07 | 2018-07-31 | 托比股份公司 | The imaging sensor of human-computer interaction for view-based access control model |
| CN110414490A (en) * | 2019-08-23 | 2019-11-05 | 洛阳师范学院 | A kind of biological attribute data detection device |
| CN111103922A (en) * | 2018-10-26 | 2020-05-05 | 华为技术有限公司 | Camera, electronic equipment and identity verification method |
| CN113505357A (en) * | 2021-07-27 | 2021-10-15 | 深兰盛视科技（苏州）有限公司 | Biological characteristic authentication method and device and intelligent terminal equipment |
| CN115938018A (en) * | 2022-09-28 | 2023-04-07 | 杭州指安科技股份有限公司 | Biological identification integrated equipment and method |
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- 2015-07-06 CN CN201520481232.3U patent/CN204791017U/en active Active
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104933344A (en) * | 2015-07-06 | 2015-09-23 | 北京中科虹霸科技有限公司 | Mobile terminal user identity authentication device and method based on multiple biological feature modals |
| CN104933344B (en) * | 2015-07-06 | 2019-01-04 | 北京中科虹霸科技有限公司 | Mobile terminal user identity authentication device and method based on multi-biological characteristic mode |
| CN108353137A (en) * | 2016-04-07 | 2018-07-31 | 托比股份公司 | The imaging sensor of human-computer interaction for view-based access control model |
| CN106548152A (en) * | 2016-11-03 | 2017-03-29 | 厦门人脸信息技术有限公司 | Near-infrared three-dimensional face tripper |
| CN107341928A (en) * | 2017-06-01 | 2017-11-10 | 厦门快商通科技股份有限公司 | A kind of intelligent control device and its control method for public resource granting |
| CN111103922A (en) * | 2018-10-26 | 2020-05-05 | 华为技术有限公司 | Camera, electronic equipment and identity verification method |
| CN111103922B (en) * | 2018-10-26 | 2023-08-25 | 华为技术有限公司 | Camera, electronic equipment and identity verification method |
| CN110414490A (en) * | 2019-08-23 | 2019-11-05 | 洛阳师范学院 | A kind of biological attribute data detection device |
| CN113505357A (en) * | 2021-07-27 | 2021-10-15 | 深兰盛视科技（苏州）有限公司 | Biological characteristic authentication method and device and intelligent terminal equipment |
| CN115938018A (en) * | 2022-09-28 | 2023-04-07 | 杭州指安科技股份有限公司 | Biological identification integrated equipment and method |
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