CN104599367A - Multi-user parallel access control recognition method based on three-dimensional face image recognition - Google Patents
Multi-user parallel access control recognition method based on three-dimensional face image recognition Download PDFInfo
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- CN104599367A CN104599367A CN201410846428.8A CN201410846428A CN104599367A CN 104599367 A CN104599367 A CN 104599367A CN 201410846428 A CN201410846428 A CN 201410846428A CN 104599367 A CN104599367 A CN 104599367A
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Abstract
The invention discloses a multi-user parallel access control recognition method based on three-dimensional face image recognition. The method comprises the following steps: S1 registering human faces; S2 when a microwave inductor induces that human bodies are close to an access control, controlling a camera to acquire and sample facial images; S3 sampling the facial images and filtering; S4 carrying out binarization processing on the facial images output by the step S3; S5 recognizing the human faces by an oval, and calculating the number of the human faces; S6 gradually calculating facial image parameter proportion values of the human faces recognized by the step 4; S7 matching the sampled facial image parameter proportion values obtained from the step S6 with the sampled facial image parameter proportion values in a human face sample knowledge base; and S8 alarming the number of unrecognized facial images by voice, and displaying facial image screenshots. The multi-user parallel access control recognition method is capable of recognizing staff statuses, and simultaneously recognizing multi-user travel, and is high in efficiency.
Description
Technical field
The present invention relates to gate inhibition and identify field, particularly relate to a kind of many people based on three-dimensional face images identification and to walk abreast gate inhibition's recognition methods.
Background technology
At present, gate control system is based on card equipment, fingerprint equipment, radio-frequency apparatus, and in use, access card is easily lost for card equipment, radio-frequency apparatus, and the wasting of resources, meanwhile, security performance is low; Fingerprint recognition gate inhibition can solve the deficiency of card series products, but a part of personnel's fingerprint None-identified, and usually need continuous several times just successfully can identify fingerprint, efficiency is low, and fingerprint recognition cross-contact, easily spreads disease.
The gate inhibition of prior art identifies, is all single identification, and the many people of parallelism recognition can not cross gate inhibition, for the gate inhibition that the volume of the flow of passengers is large, length consuming time, easily caused the people line of gate inhibition for a long time, efficiency is low simultaneously.
Summary of the invention
Instant invention overcomes the deficiencies in the prior art, provide a kind of many people based on three-dimensional face images identification to walk abreast gate inhibition's recognition methods, can parallelism recognition personnel identity, identify that many people go together, efficiency is high simultaneously.
Many people based on three-dimensional face images identification walk abreast gate inhibition's recognition methods, comprise the following steps:
S1, registration face: obtain standard three-dimensional facial image by camera, standard three-dimensional facial image is converted to facial image parameter logistic value and puts into face sample knowledge storehouse;
S2, microwave sensor induction human body, when gate inhibition, controls camera and obtains sampling facial image;
S3, sampling facial image carries out filtering;
S4, carries out binary conversion treatment by the facial image that step S3 exports;
S5, uses oval identification face, calculates face number;
S6, face step 4 identified carries out facial image parameter logistic value one by one and calculates;
S7, mates the sampling facial image parameter logistic value that step S6 obtains with the facial image parameter logistic value in face sample knowledge storehouse;
S8, the Unidentified facial image number of audio alert, and facial image sectional drawing is shown.
More preferably, step S1 facial image parameter logistic value comprises:
The ratio value of the distance between two canthus and the distance between eye tail;
Take nose as separation, nose to chin distance shared by the long ratio value of face;
Face and the long ratio value of eye;
Distance between nose and face accounts for the long ratio value of face.
More preferably, step S2 microwave sensor is connected by controller with between camera, and controller controls camera shooting face 3-D view.
More preferably, step S5 specifically comprises the following steps:
501, use oval snare eyes;
502, when distance between the canthus of two eyes is less than twice eye-length, by described two eyes circles in an ellipse, and mobile, zoom in or out ellipse, will belong to the nose of same facial image and face is included in described ellipse with described two eyes;
503, circulation step 502, until often pair of eyes occurred in pairs are by oval snare;
504, calculate the number of the ellipse of the paired eyes of snare;
505, remaining eyes in facial image after using oval snare step S503, each oval snare eyes;
506, calculate the number of the ellipse of snare eyes.
More preferably, Unidentified facial image described in step S8 to comprise in step 505 the unmatched facial image of parameter logistic value of the facial image in the only oval facial image of snare eyes and the facial image of sampling and face sample knowledge storehouse.
More preferably, step S7 coupling matches for error in restriction threshold range belongs to facial image parameter logistic value.
More preferably, limiting threshold value is 0.1 ~ 0.2.
Compared with prior art, comprise following beneficial effect: the present invention can parallelism recognition personnel identity, and identify that many people go together, efficiency is high simultaneously.
Embodiment
Many people based on three-dimensional face images identification walk abreast gate inhibition's recognition methods, comprise the following steps:
S1, registration face: obtain standard three-dimensional facial image by camera, standard three-dimensional facial image is converted to facial image parameter logistic value and puts into face sample knowledge storehouse;
S2, microwave sensor induction human body, when gate inhibition, controls camera and obtains sampling facial image;
S3, sampling facial image carries out filtering;
S4, carries out binary conversion treatment by the facial image that step S3 exports;
S5, uses oval identification face, calculates face number;
S6, face step 4 identified carries out facial image parameter logistic value one by one and calculates;
S7, mates the sampling facial image parameter logistic value that step S6 obtains with the facial image parameter logistic value in face sample knowledge storehouse;
S8, the Unidentified facial image number of audio alert, and facial image sectional drawing is shown.
Step S1 facial image parameter logistic value comprises:
The ratio value of the distance between two canthus and the distance between eye tail;
Take nose as separation, nose to chin distance shared by the long ratio value of face;
Face and the long ratio value of eye;
Distance between nose and face accounts for the long ratio value of face.
Step S2 microwave sensor is connected by controller with between camera, and controller controls camera shooting face 3-D view.
Step S5 specifically comprises the following steps:
501, use oval snare eyes;
502, when distance between the canthus of two eyes is less than twice eye-length, by described two eyes circles in an ellipse, and mobile, zoom in or out ellipse, will belong to the nose of same facial image and face is included in described ellipse with described two eyes;
503, circulation step 502, until often pair of eyes occurred in pairs are by oval snare;
504, calculate the number of the ellipse of the paired eyes of snare;
505, remaining eyes in facial image after using oval snare step S503, each oval snare eyes;
506, calculate the number of the ellipse of snare eyes.
Unidentified facial image described in step S8 to comprise in step 505 the unmatched facial image of parameter logistic value of the facial image in the only oval facial image of snare eyes and the facial image of sampling and face sample knowledge storehouse.
Step S7 coupling matches for error in restriction threshold value (0.1 ~ 0.2) scope belongs to facial image parameter logistic value.
Below be only the preferred embodiment of the present invention; be noted that for those skilled in the art; under the premise without departing from the principles of the invention, can also make some improvements and modifications, these improvements and modifications also should be considered as protection scope of the present invention.
Claims (7)
1. to walk abreast gate inhibition's recognition methods based on many people of three-dimensional face images identification, it is characterized in that, comprise the following steps:
S1, registration face: obtain standard three-dimensional facial image by camera, standard three-dimensional facial image is converted to facial image parameter logistic value and puts into face sample knowledge storehouse;
S2, microwave sensor induction human body, when gate inhibition, controls camera and obtains sampling facial image;
S3, sampling facial image carries out filtering;
S4, carries out binary conversion treatment by the facial image that step S3 exports;
S5, uses oval identification face, calculates face number;
S6, face step 4 identified carries out facial image parameter logistic value one by one and calculates;
S7, mates the sampling facial image parameter logistic value that step S6 obtains with the facial image parameter logistic value in face sample knowledge storehouse;
S8, the Unidentified facial image number of audio alert, and facial image sectional drawing is shown.
2. the many people based on three-dimensional face images identification according to claim 1 walk abreast gate inhibition's recognition methods, it is characterized in that,
Step S1 facial image parameter logistic value comprises:
The ratio value of the distance between two canthus and the distance between eye tail;
Take nose as separation, nose to chin distance shared by the long ratio value of face;
Face and the long ratio value of eye;
Distance between nose and face accounts for the long ratio value of face.
3. the many people based on three-dimensional face images identification according to claim 1 walk abreast gate inhibition's recognition methods, it is characterized in that,
Step S2 microwave sensor is connected by controller with between camera, and controller controls camera shooting face 3-D view.
4. the many people based on three-dimensional face images identification according to claim 1 walk abreast gate inhibition's recognition methods, it is characterized in that,
Step S5 specifically comprises the following steps:
501, use oval snare eyes;
502, when distance between the canthus of two eyes is less than twice eye-length, by described two eyes circles in an ellipse, and mobile, zoom in or out ellipse, will belong to the nose of same facial image and face is included in described ellipse with described two eyes;
503, circulation step 502, until often pair of eyes occurred in pairs are by oval snare;
504, calculate the number of the ellipse of the paired eyes of snare;
505, remaining eyes in facial image after using oval snare step S503, each oval snare eyes;
506, calculate the number of the ellipse of snare eyes.
5. the many people based on three-dimensional face images identification according to claim 4 walk abreast gate inhibition's recognition methods, it is characterized in that,
Unidentified facial image described in step S8 to comprise in step 505 the unmatched facial image of parameter logistic value of the facial image in the only oval facial image of snare eyes and the facial image of sampling and face sample knowledge storehouse.
6. the many people based on three-dimensional face images identification according to claim 1 walk abreast gate inhibition's recognition methods, it is characterized in that,
Step S7 coupling matches for error in restriction threshold range belongs to facial image parameter logistic value.
7. the many people based on three-dimensional face images identification according to claim 6 walk abreast gate inhibition's recognition methods, and it is characterized in that, described restriction threshold value is 0.1 ~ 0.2.
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| CN104978566A (en) * | 2015-06-05 | 2015-10-14 | 深圳市金立通信设备有限公司 | Picture processing method and terminal |
| CN106340139A (en) * | 2016-08-25 | 2017-01-18 | 广州御银自动柜员机科技有限公司 | VTM (Virtual Teller Machine) capable of automatically recognizing human face |
| CN106778474A (en) * | 2016-11-14 | 2017-05-31 | 深圳奥比中光科技有限公司 | 3D human body recognition methods and equipment |
| CN106778468A (en) * | 2016-11-14 | 2017-05-31 | 深圳奥比中光科技有限公司 | 3D face identification methods and equipment |
| CN107172453A (en) * | 2017-06-28 | 2017-09-15 | 深圳市九洲电器有限公司 | Many spectators' TV programme suggesting methods and system |
| CN108376434A (en) * | 2018-02-22 | 2018-08-07 | 陈崇 | A kind of intelligent home control system based on Internet of Things |
| CN108389290A (en) * | 2018-02-22 | 2018-08-10 | 陈崇 | A kind of intelligent home furnishing control method based on Internet of Things |
| CN110874878A (en) * | 2018-08-09 | 2020-03-10 | 深圳云天励飞技术有限公司 | Pedestrian analysis method, device, terminal and storage medium |
| CN111275873A (en) * | 2018-11-19 | 2020-06-12 | 深圳云天励飞技术有限公司 | Passage control management method and device, electronic equipment and storage medium |
| CN112904451A (en) * | 2021-01-20 | 2021-06-04 | 浙江洁特智慧科技有限公司 | Presence type inductor |
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| CN112904451A (en) * | 2021-01-20 | 2021-06-04 | 浙江洁特智慧科技有限公司 | Presence type inductor |
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