CN107657248A - A kind of infrared binocular In vivo detections of Android based on recognition of face certification - Google Patents
A kind of infrared binocular In vivo detections of Android based on recognition of face certification Download PDFInfo
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- CN107657248A CN107657248A CN201711016920.2A CN201711016920A CN107657248A CN 107657248 A CN107657248 A CN 107657248A CN 201711016920 A CN201711016920 A CN 201711016920A CN 107657248 A CN107657248 A CN 107657248A
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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
- G06V40/16—Human faces, e.g. facial parts, sketches or expressions
- G06V40/168—Feature extraction; Face representation
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- Computer Vision & Pattern Recognition (AREA)
- General Physics & Mathematics (AREA)
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- Measurement Of The Respiration, Hearing Ability, Form, And Blood Characteristics Of Living Organisms (AREA)
Abstract
A kind of infrared binocular In vivo detections of Android based on recognition of face certification, are mainly included the following steps that, step 1：Open infrared binocular camera, infrared binocular camera pickup area video flowing；Step 2：Image processing module captures two frame pictures from video flowing respectively, and one is colour picture A, and another is black and white picture B；Step 3：Face recognition module carries out feature extraction to colour picture A, obtains face characteristic P1；Step 4：Judge whether face characteristic P1 reaches the threshold value of setting, if it is, into next step, otherwise, return to step 2；Step 5：Face recognition module carries out feature extraction to black and white picture B, detects ROI to black and white picture B zonules, obtains face characteristic P2.Live body can be authenticated using face recognition technology using infrared binocular camera.
Description
Technical field
The present invention relates to field of face identification, and in particular to a kind of infrared binoculars of Android based on recognition of face certification
In vivo detection.
Background technology
In the current technology that binocular In vivo detection is realized using infrared ray, common infrared binocular can in real time simultaneously
Two kinds of images of near-infrared and visible ray are gathered, and PC end subscribers video software can be handled in real time.It is but not favourable
The method handled in real time with other platforms, automatic detection face and it can not particularly sentence inside Android application systems
Disconnected live body.In order to solve the above problems, there is provided a kind of infrared binocular In vivo detections of Android based on recognition of face certification.
The content of the invention
The present invention in view of the shortcomings of the prior art, proposes a kind of VIP recognition methods based on recognition of face certification, specific skill
Art scheme is as follows：
A kind of infrared binocular In vivo detections of Android based on recognition of face certification, it is characterised in that：Using following step
Suddenly,
Step 1：Open infrared binocular camera, infrared binocular camera pickup area video flowing；
Step 2：Image processing module captures two frame pictures from video flowing respectively, and one is colour picture A, and another is
Black and white picture B；
Step 3：Face recognition module carries out feature extraction to colour picture A, obtains face characteristic P1；
Step 4：Judge whether face characteristic P1 reaches the threshold value of setting, if it is, into next step, otherwise, return
To step 2；
Step 5：Face recognition module carries out feature extraction to black and white picture B, detects ROI to black and white picture B zonules, obtains
To face characteristic P2；
Step 6：Live body judgement is carried out with reference to face characteristic P1 and face characteristic P2, determines whether live body, if it is,
Into next step, otherwise, step 8 is entered；
Step 7：Optimal facial image is exported, into step 13；
Step 8：Face recognition module carries out feature extraction to colour picture C, obtains face characteristic P3；
Step 9：Judge whether face characteristic P3 reaches the threshold value of setting, if it is, into next step, otherwise, return
To step 8；
Step 10：Face recognition module carries out feature extraction to black and white picture D, and ROI is detected to black and white picture D zonules,
Obtain face characteristic P4；
Step 11：Live body judgement is carried out with reference to face characteristic P3 and face characteristic P4, determines whether live body, if it is,
Then enter next step, otherwise, enter step 13；
Step 12：Export optimal facial image；
Step 13：Terminate.
Beneficial effects of the present invention are：First, infrared binocular camera can be utilized using face recognition technology to live body
It is authenticated.Second, it is colour picture and a black and white picture that crawl, which has one, respectively, passes through contrast, it is possible to increase resolution ratio.
3rd, it is provided with and detects twice, can effectively avoids judging by accident.
Brief description of the drawings
Fig. 1 is the flow chart of the present invention.
Embodiment
Presently preferred embodiments of the present invention is described in detail below in conjunction with the accompanying drawings, so that advantages and features of the invention energy
It is easier to be readily appreciated by one skilled in the art, apparent is clearly defined so as to be made to protection scope of the present invention.
As shown in Figure 1：A kind of infrared binocular In vivo detections of Android based on recognition of face certification, using following steps,
Step 1：Open infrared binocular camera, infrared binocular camera pickup area video flowing；
Step 2：Image processing module captures two frame pictures from video flowing respectively, and one is colour picture A, and another is
Black and white picture B；
Step 3：Face recognition module carries out feature extraction to colour picture A, obtains face characteristic P1；
Step 4：Judge whether face characteristic P1 reaches the threshold value of setting, if it is, into next step, otherwise, return
To step 2；
Step 5：Face recognition module carries out feature extraction to black and white picture B, detects ROI to black and white picture B zonules, obtains
To face characteristic P2；
Step 6：Live body judgement is carried out with reference to face characteristic P1 and face characteristic P2, determines whether live body, if it is,
Into next step, otherwise, step 8 is entered；
Step 7：Optimal facial image is exported, into step 13；
Step 8：Face recognition module carries out feature extraction to colour picture C, obtains face characteristic P3；
Step 9：Judge whether face characteristic P3 reaches the threshold value of setting, if it is, into next step, otherwise, return
To step 8；
Step 10：Face recognition module carries out feature extraction to black and white picture D, and ROI is detected to black and white picture D zonules,
Obtain face characteristic P4；
Step 11：Live body judgement is carried out with reference to face characteristic P3 and face characteristic P4, determines whether live body, if it is,
Then enter next step, otherwise, enter step 13；
Step 12：Export optimal facial image；
Step 13：Terminate.
Claims (1)
- A kind of 1. infrared binocular In vivo detections of Android based on recognition of face certification, it is characterised in that：Using following steps,Step 1：Open infrared binocular camera, infrared binocular camera pickup area video flowing；Step 2：Image processing module captures two frame pictures from video flowing respectively, and one is colour picture A, and another is black and white Picture B；Step 3：Face recognition module carries out feature extraction to colour picture A, obtains face characteristic P1；Step 4：Judge whether face characteristic P1 reaches the threshold value of setting, if it is, into next step, otherwise, return to step Rapid 2；Step 5：Face recognition module carries out feature extraction to black and white picture B, detects ROI to black and white picture B zonules, obtains people Face feature P2；Step 6：Live body judgement is carried out with reference to face characteristic P1 and face characteristic P2, determines whether live body, if it is, into Next step, otherwise, enter step 8；Step 7：Optimal facial image is exported, into step 13；Step 8：Face recognition module carries out feature extraction to colour picture C, obtains face characteristic P3；Step 9：Judge whether face characteristic P3 reaches the threshold value of setting, if it is, into next step, otherwise, return to step Rapid 8；Step 10：Face recognition module carries out feature extraction to black and white picture D, detects ROI to black and white picture D zonules, obtains Face characteristic P4；Step 11：Live body judgement is carried out with reference to face characteristic P3 and face characteristic P4, live body is determined whether, if it is, entering Enter next step, otherwise, enter step 13；Step 12：Export optimal facial image；Step 13：Terminate.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
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| CN201711016920.2A CN107657248A (en) | 2017-10-26 | 2017-10-26 | A kind of infrared binocular In vivo detections of Android based on recognition of face certification |
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| CN201711016920.2A CN107657248A (en) | 2017-10-26 | 2017-10-26 | A kind of infrared binocular In vivo detections of Android based on recognition of face certification |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109359634A (en) * | 2018-12-11 | 2019-02-19 | 西安第六镜网络科技有限公司 | A kind of human face in-vivo detection method based on binocular camera |
| CN110555930A (en) * | 2019-08-30 | 2019-12-10 | 北京市商汤科技开发有限公司 | Door lock control method and device, electronic equipment and storage medium |
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| CN102779274A (en) * | 2012-07-19 | 2012-11-14 | 冠捷显示科技（厦门）有限公司 | Intelligent television face recognition method based on binocular camera |
| CN103593598A (en) * | 2013-11-25 | 2014-02-19 | 上海骏聿数码科技有限公司 | User online authentication method and system based on living body detection and face recognition |
| CN106874871A (en) * | 2017-02-15 | 2017-06-20 | 广东光阵光电科技有限公司 | A kind of recognition methods of living body faces dual camera and identifying device |
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2017
- 2017-10-26 CN CN201711016920.2A patent/CN107657248A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102779274A (en) * | 2012-07-19 | 2012-11-14 | 冠捷显示科技（厦门）有限公司 | Intelligent television face recognition method based on binocular camera |
| CN103593598A (en) * | 2013-11-25 | 2014-02-19 | 上海骏聿数码科技有限公司 | User online authentication method and system based on living body detection and face recognition |
| CN106874871A (en) * | 2017-02-15 | 2017-06-20 | 广东光阵光电科技有限公司 | A kind of recognition methods of living body faces dual camera and identifying device |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109359634A (en) * | 2018-12-11 | 2019-02-19 | 西安第六镜网络科技有限公司 | A kind of human face in-vivo detection method based on binocular camera |
| CN109359634B (en) * | 2018-12-11 | 2021-11-16 | 西安第六镜网络科技有限公司 | Face living body detection method based on binocular camera |
| CN110555930A (en) * | 2019-08-30 | 2019-12-10 | 北京市商汤科技开发有限公司 | Door lock control method and device, electronic equipment and storage medium |
| CN110555930B (en) * | 2019-08-30 | 2021-03-26 | 北京市商汤科技开发有限公司 | Door lock control method and device, electronic equipment and storage medium |
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Address after: 511457 Guangdong city of Guangzhou province Nansha District Golden Road No. 26 room 1306 (only for office use) Applicant after: Yuncong Technology Group Co., Ltd Address before: 518000 Guangdong city of Guangzhou province Nansha District Golden Road No. 26 room 1306 Applicant before: GUANGZHOU YUNCONG INFORMATION TECHNOLOGY CO., LTD. |
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Application publication date: 20180202 |