CN111046816A - Real person face recognition system and method thereof - Google Patents
Real person face recognition system and method thereof Download PDFInfo
- Publication number
- CN111046816A CN111046816A CN201911309745.5A CN201911309745A CN111046816A CN 111046816 A CN111046816 A CN 111046816A CN 201911309745 A CN201911309745 A CN 201911309745A CN 111046816 A CN111046816 A CN 111046816A
- Authority
- CN
- China
- Prior art keywords
- module
- illumination
- brightness
- pupil
- recognized
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 19
- 238000005286 illumination Methods 0.000 claims abstract description 91
- 238000010191 image analysis Methods 0.000 claims abstract description 19
- 210000001747 pupil Anatomy 0.000 claims description 63
- 238000001514 detection method Methods 0.000 claims description 26
- 238000004458 analytical method Methods 0.000 claims description 18
- 238000001914 filtration Methods 0.000 claims description 9
- 230000003247 decreasing effect Effects 0.000 claims description 4
- 230000009286 beneficial effect Effects 0.000 abstract description 3
- 230000007423 decrease Effects 0.000 description 8
- 238000005516 engineering process Methods 0.000 description 3
- 210000000887 face Anatomy 0.000 description 3
- 230000001143 conditioned effect Effects 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 230000011514 reflex Effects 0.000 description 2
- 238000004088 simulation Methods 0.000 description 2
- 230000001815 facial effect Effects 0.000 description 1
Images
Classifications
-
- 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
- G06V40/161—Detection; Localisation; Normalisation
- G06V40/166—Detection; Localisation; Normalisation using acquisition arrangements
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/10—Image acquisition
- G06V10/12—Details of acquisition arrangements; Constructional details thereof
- G06V10/14—Optical characteristics of the device performing the acquisition or on the illumination arrangements
- G06V10/141—Control of illumination
-
- 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
- G06V40/18—Eye characteristics, e.g. of the iris
- G06V40/19—Sensors therefor
-
- 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
- G06V40/40—Spoof detection, e.g. liveness detection
- G06V40/45—Detection of the body part being alive
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Multimedia (AREA)
- Theoretical Computer Science (AREA)
- Human Computer Interaction (AREA)
- Health & Medical Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Oral & Maxillofacial Surgery (AREA)
- Ophthalmology & Optometry (AREA)
- Image Processing (AREA)
Abstract
The invention discloses a real person face recognition system and a method thereof, wherein the system comprises: the image acquisition module is used for acquiring the image information of the object to be identified; the illumination module is used for illuminating an object to be identified with certain brightness; the brightness adjusting module is used for adjusting the illumination brightness of the illumination module; and the image analysis module is used for receiving and analyzing the image information acquired by the image acquisition module, and when the brightness adjustment module adjusts the illumination brightness of the illumination module, the image analysis module analyzes the reaction of the object to be recognized on the change of the illumination brightness to judge whether the object to be recognized is a real person. The invention has the beneficial effect that whether the object to be identified is a real person can be judged according to the natural reaction of the human body to the illumination brightness.
Description
Technical Field
The invention relates to a real human face recognition system and a method thereof.
Background
Face recognition is a biometric technology for identity recognition based on facial feature information of a person. A series of related technologies, also commonly called face recognition and face recognition, are used to collect images or video streams containing faces by using a camera or a video camera, automatically detect and track the faces in the images, and then perform face recognition on the detected faces.
The existing face recognition technology is easily attacked by photos, recorded videos, high simulation models and the like, and has a large potential risk. With regard to current hot news, media workers generally collect information of the hot news to form event topics convenient for management and viewing.
Disclosure of Invention
The invention provides a real human face recognition system and a method thereof, which adopt the following technical scheme:
a human face recognition system comprising:
the image acquisition module is used for acquiring the image information of the object to be identified;
the illumination module is used for illuminating an object to be identified with certain brightness;
the brightness adjusting module is used for adjusting the illumination brightness of the illumination module;
and the image analysis module is used for receiving and analyzing the image information acquired by the image acquisition module, and when the brightness adjustment module adjusts the illumination brightness of the illumination module, the image analysis module analyzes the reaction of the object to be recognized on the change of the illumination brightness to judge whether the object to be recognized is a real person.
Further, the image analysis module includes:
the face recognition submodule is used for recognizing a face area in the image information;
the pupil detection submodule is used for detecting the size of a pupil in the face area;
the comparison analysis submodule is used for analyzing the change of the size of the pupil detected by the pupil detection submodule;
when the illumination brightness of the illumination module is adjusted by the brightness adjusting module, the comparison analysis sub-module analyzes whether the size change of the pupil detected by the pupil detection sub-module is consistent with the illumination brightness change of the illumination module so as to judge whether the object to be identified is a real person.
Further, the contrast analysis sub-module judges that the object to be identified is a real person when the size of the pupil detected by the pupil detection sub-module decreases when the illumination brightness of the illumination module increases and/or the size of the pupil detected by the pupil detection sub-module increases when the illumination brightness of the illumination module decreases.
Further, the image analysis module further comprises:
and the image processing submodule is used for carrying out filtering and noise reduction processing on the image information acquired by the image acquisition module.
Further, the image display module is configured to display the image information acquired by the image acquisition module.
A real human face recognition method comprises the following steps:
acquiring image information of an object to be identified;
adjusting the illumination brightness of an object to be recognized;
and judging whether the object to be recognized is a real person or not according to the reaction of the object to be recognized to the change of the illumination brightness.
Further, the specific step of judging whether the object to be recognized is a real person according to the reaction of the object to be recognized to the change of the illumination brightness is as follows:
identifying a face region in the image information;
detecting the size of a pupil in the face region;
whether the size change of the pupil is consistent with the illumination brightness change is analyzed to judge whether the object to be identified is a real person.
Further, when the size of the pupil is decreased when the illumination luminance is increased and/or the size of the pupil is increased when the illumination luminance is decreased, it is determined that the object to be recognized is a real person.
Further, after acquiring the image information of the object to be recognized, the method for recognizing the human face of the real person further comprises the following steps:
and carrying out filtering and noise reduction processing on the acquired image information.
Further, after acquiring the image information of the object to be recognized, the method for recognizing the human face of the real person further comprises the following steps:
and displaying the image information.
The human face recognition system and the human face recognition method have the beneficial effects that whether the object to be recognized is a real person can be judged according to the natural reaction of the human body to the brightness.
The human face recognition system and the human face recognition method have the beneficial effects that whether the object to be recognized is a real person can be judged according to the conditional reflection of the pupil of the human body to the change of the illumination brightness.
Drawings
FIG. 1 is a schematic diagram of a human face recognition system of the present invention;
fig. 2 is a schematic diagram of the human face recognition method of the present invention.
The system comprises a human face recognition system 100, an image acquisition module 10, an illumination module 20, a brightness adjustment module 30, an image analysis module 40, a face recognition sub-module 41, a pupil detection sub-module 42, a contrast analysis sub-module 43, an image processing sub-module 44 and a display module 50.
Detailed Description
The invention is described in detail below with reference to the figures and the embodiments.
As shown in fig. 1, a human face recognition system 100 of the present invention mainly includes: an image acquisition module 10, an illumination module 20, a brightness adjustment module 30, and an image analysis module 40. The image acquisition module 10 is used for acquiring image information of an object to be identified. The illumination module 20 is used to illuminate an object to be recognized with a certain brightness. The brightness adjusting module 30 is used for adjusting the illumination brightness of the illumination module 20. The image analysis module 40 is configured to receive and analyze the image information acquired by the image acquisition module 10. When the brightness adjustment module 30 adjusts the illumination brightness of the illumination module 20, the image analysis module 40 analyzes the reaction of the object to be recognized to the change in illumination brightness to determine whether the object to be recognized is a real person. In the present invention, the image obtaining module 10 is a camera, and can obtain video data of an object to be identified. The lighting module 20 is an LED lamp, and the brightness adjusting module 30 adjusts the brightness of the LED lamp. It is understood that the lighting module 20 may also be other types of lighting devices, such as a display screen of a portable device, and the lighting brightness is adjusted by adjusting the brightness of the display screen of the portable device, such as a mobile phone and a tablet computer. The photo, video and high simulation models cannot react correctly to the change of the illumination brightness, so the image analysis module 40 can judge whether the object to be recognized is a real person according to the reaction of the object to be recognized to the change of the illumination brightness.
Specifically, the image analysis module 40 includes: a face recognition sub-module 41, a pupil detection sub-module 42 and a contrast analysis sub-module 43. The face recognition sub-module 41 is used to recognize a face region in the image information. The pupil detection sub-module 42 is used to detect the size of the pupil in the face region. The contrast analysis sub-module 43 is used for analyzing the change in the size of the pupil detected by the pupil detection sub-module 42. When the illumination brightness of the illumination module 20 is adjusted by the brightness adjustment module 30, the pupil of the real person makes a conditioned reflex according to the change of the illumination brightness, and the contrast analysis sub-module 43 analyzes whether the change of the size of the pupil detected by the pupil detection sub-module 42 is consistent with the change of the illumination brightness of the illumination module 20 to determine whether the object to be recognized is the real person. It is understood that if the object to be recognized is a real person, the size of the pupil detected by the pupil detection sub-module 42 decreases when the illumination brightness of the illumination module 20 increases, and the size of the pupil detected by the pupil detection sub-module 42 increases when the illumination brightness of the illumination module 20 decreases. Therefore, when the contrast analysis sub-module 43 concludes, through the contrast analysis, that the size of the pupil detected by the pupil detection sub-module 42 decreases when the illumination brightness of the illumination module 20 increases and/or that the size of the pupil detected by the pupil detection sub-module 42 increases when the illumination brightness of the illumination module 20 decreases, the contrast analysis sub-module 43 may determine that the object to be recognized is a real person. It is understood that when the face recognition sub-module 41 cannot recognize the face in the image information acquired by the image acquisition module 10 or when the pupil detection sub-module 42 cannot recognize the pupil, the real-person face recognition system 100 re-acquires the image information through the image acquisition module 10 until the pupil information can be accurately detected.
As a preferred embodiment, the image analysis module 40 further includes: an image processing sub-module 44.
Specifically, the image processing sub-module 44 is configured to perform filtering and denoising processing on the image information acquired by the image acquisition module 10. Filtering and denoising the image information can improve the recognition accuracy of the subsequent face recognition submodule 41 and pupil detection submodule 42.
As a preferred embodiment, the human face recognition system 100 further comprises an image display module 50.
Specifically, the image display module 50 is configured to display the image information acquired by the image acquisition module 10.
The invention also discloses a real person face recognition method, which is used for the real person face recognition system 100 and comprises the following steps: and S1, acquiring the image information of the object to be recognized. And S2, adjusting the illumination brightness of the object to be recognized. And S3, judging whether the object to be recognized is a real person according to the reaction of the object to be recognized to the change of the illumination brightness.
For step S1, image information of the object to be recognized is acquired.
Firstly, image information of an object to be identified is acquired through the image acquisition module 10, in the invention, the image acquisition module 10 is a camera, and video data of the object to be identified is acquired through the camera.
Further, after the image information of the object to be recognized is acquired, the acquired image information is subjected to filtering noise reduction processing by image processing.
For step S2, the illumination intensity of the object to be recognized is adjusted.
The brightness of the illumination module 20 is adjusted by the brightness adjusting module 30, and the illumination module 20 is an LED lamp.
With respect to step S3, it is determined whether the object to be recognized is a real person based on the reaction of the object to be recognized to the change in the illumination brightness.
The image information acquired by the image acquisition module 10 is received and analyzed by the image analysis module 40. When the brightness adjustment module 30 adjusts the illumination brightness of the illumination module 20, the image analysis module 40 analyzes the reaction of the object to be recognized to the change in illumination brightness to determine whether the object to be recognized is a real person.
The specific steps of judging whether the object to be recognized is a real person according to the reaction of the object to be recognized to the change of the illumination brightness are as follows: face regions in the image information are identified. The size of the pupil in the face region is detected. Whether the size change of the pupil is consistent with the illumination brightness change is analyzed to judge whether the object to be identified is a real person. Specifically, the face region in the image information is recognized by the face recognition sub-module 41. The size of the pupils in the face region is detected by the pupil detection sub-module 42. The change in the size of the pupil detected by the pupil detection sub-module 42 is analyzed by the contrast analysis sub-module 43. When the illumination brightness of the illumination module 20 is adjusted by the brightness adjustment module 30, the pupil of the real person makes a conditioned reflex according to the change of the illumination brightness, and the contrast analysis sub-module 43 analyzes whether the change of the size of the pupil detected by the pupil detection sub-module 42 is consistent with the change of the illumination brightness of the illumination module 20 to determine whether the object to be recognized is the real person. It is understood that when the contrast analysis sub-module 43 concludes, through the contrast analysis, that the size of the pupil detected by the pupil detection sub-module 42 decreases when the illumination brightness of the illumination module 20 increases and/or that the size of the pupil detected by the pupil detection sub-module 42 increases when the illumination brightness of the illumination module 20 decreases, the contrast analysis sub-module 43 may determine that the object to be recognized is a real person.
As a preferred embodiment, after the image information of the object to be recognized is acquired, the acquired image information is subjected to filtering and noise reduction processing by the image processing sub-module 44.
As a preferred embodiment, after the image information of the object to be recognized is acquired, the image information is also displayed through the display module 50. It is understood that the displayed image information may be the image information directly acquired by the image acquisition module 10, or the image information after the filtering and noise reduction processing by the image processing sub-module 44.
The foregoing illustrates and describes the principles, general features, and advantages of the present invention. It should be understood by those skilled in the art that the above embodiments do not limit the present invention in any way, and all technical solutions obtained by using equivalent alternatives or equivalent variations fall within the scope of the present invention.
Claims (10)
1. A system for human face recognition, comprising:
the image acquisition module is used for acquiring the image information of the object to be identified;
the illumination module is used for illuminating an object to be identified with certain brightness;
the brightness adjusting module is used for adjusting the illumination brightness of the illumination module;
and the image analysis module is used for receiving and analyzing the image information acquired by the image acquisition module, and when the brightness adjustment module adjusts the illumination brightness of the illumination module, the image analysis module analyzes the reaction of the object to be recognized to the change of the illumination brightness to judge whether the object to be recognized is a real person.
2. The system of claim 1, further comprising:
the image analysis module includes:
the face recognition submodule is used for recognizing a face area in the image information;
the pupil detection submodule is used for detecting the size of a pupil in the face area;
the comparison analysis sub-module is used for analyzing the change of the size of the pupil detected by the pupil detection sub-module;
when the brightness adjusting module adjusts the illumination brightness of the illumination module, the contrast analysis sub-module analyzes whether the size change of the pupil detected by the pupil detection sub-module is consistent with the illumination brightness change of the illumination module so as to judge whether the object to be identified is a real person.
3. The system of claim 2, further comprising:
when the illumination brightness of the illumination module is increased, the size of the pupil detected by the pupil detection sub-module is decreased and/or when the illumination brightness of the illumination module is decreased, the size of the pupil detected by the pupil detection sub-module is increased, and the contrast analysis sub-module judges that the object to be identified is a real person.
4. The human face recognition system of claim 2,
the image analysis module further comprises:
and the image processing submodule is used for carrying out filtering and noise reduction processing on the image information acquired by the image acquisition module.
5. The system of claim 1, further comprising:
and the image display module is used for displaying the image information acquired by the image acquisition module.
6. A human face recognition method is characterized by comprising the following steps:
acquiring image information of an object to be identified;
adjusting the illumination brightness of an object to be recognized;
and judging whether the object to be recognized is a real person or not according to the reaction of the object to be recognized to the change of the illumination brightness.
7. The method of claim 6, wherein the human face recognition,
the specific steps of judging whether the object to be recognized is a real person according to the reaction of the object to be recognized to the change of the illumination brightness are as follows:
identifying a face region in the image information;
detecting the size of a pupil in the face region;
whether the size change of the pupil is consistent with the illumination brightness change is analyzed to judge whether the object to be identified is a real person.
8. The method of claim 7, wherein the human face recognition,
and when the size of the pupil is reduced when the illumination brightness is increased and/or the size of the pupil is increased when the illumination brightness is reduced, judging that the object to be identified is a real person.
9. The method of claim 7, wherein the human face recognition,
after the image information of the object to be recognized is acquired, the method for recognizing the human face of the real person further comprises the following steps:
and carrying out filtering and noise reduction processing on the acquired image information.
10. The method of claim 6, wherein the human face recognition,
after the image information of the object to be recognized is acquired, the method for recognizing the human face of the real person further comprises the following steps:
and displaying the image information.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911309745.5A CN111046816A (en) | 2019-12-18 | 2019-12-18 | Real person face recognition system and method thereof |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911309745.5A CN111046816A (en) | 2019-12-18 | 2019-12-18 | Real person face recognition system and method thereof |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN111046816A true CN111046816A (en) | 2020-04-21 |
Family
ID=70237860
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201911309745.5A Pending CN111046816A (en) | 2019-12-18 | 2019-12-18 | Real person face recognition system and method thereof |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111046816A (en) |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105139006A (en) * | 2015-09-29 | 2015-12-09 | 清华大学 | Iris-change-based living body identification method and system |
| WO2016197389A1 (en) * | 2015-06-12 | 2016-12-15 | 北京释码大华科技有限公司 | Method and device for detecting living object, and mobile terminal |
| US20180227472A1 (en) * | 2015-07-29 | 2018-08-09 | Kyocera Corporation | Image processing apparatus, imaging apparatus, driver monitoring system, vehicle, and image processing method |
| CN109657531A (en) * | 2018-09-18 | 2019-04-19 | 深圳先牛信息技术有限公司 | A kind of human face in-vivo detection method and detection device based on hot spot on eyeball |
| CN109858337A (en) * | 2018-12-21 | 2019-06-07 | 普联技术有限公司 | A kind of face identification method based on pupil information, system and equipment |
-
2019
- 2019-12-18 CN CN201911309745.5A patent/CN111046816A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2016197389A1 (en) * | 2015-06-12 | 2016-12-15 | 北京释码大华科技有限公司 | Method and device for detecting living object, and mobile terminal |
| US20180227472A1 (en) * | 2015-07-29 | 2018-08-09 | Kyocera Corporation | Image processing apparatus, imaging apparatus, driver monitoring system, vehicle, and image processing method |
| CN105139006A (en) * | 2015-09-29 | 2015-12-09 | 清华大学 | Iris-change-based living body identification method and system |
| CN109657531A (en) * | 2018-09-18 | 2019-04-19 | 深圳先牛信息技术有限公司 | A kind of human face in-vivo detection method and detection device based on hot spot on eyeball |
| CN109858337A (en) * | 2018-12-21 | 2019-06-07 | 普联技术有限公司 | A kind of face identification method based on pupil information, system and equipment |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108090458B (en) | Human body falling detection method and device | |
| CN106446873B (en) | Face detection method and device | |
| WO2019033572A1 (en) | Method for detecting whether face is blocked, device and storage medium | |
| CN109766779B (en) | Loitering person identification method and related product | |
| US11849998B2 (en) | Method for pupil detection for cognitive monitoring, analysis, and biofeedback-based treatment and training | |
| Raja et al. | Video presentation attack detection in visible spectrum iris recognition using magnified phase information | |
| CN111542856B (en) | Skin detection method and electronic equipment | |
| US20150358549A1 (en) | Image capturing parameter adjustment in preview mode | |
| US20190065829A1 (en) | Decreasing lighting-induced false facial recognition | |
| EP2336949B1 (en) | Apparatus and method for registering plurality of facial images for face recognition | |
| CN104143086A (en) | Application technology of portrait comparison to mobile terminal operating system | |
| KR20180138300A (en) | Electronic device for providing property information of external light source for interest object | |
| US20130202159A1 (en) | Apparatus for real-time face recognition | |
| CN104133548A (en) | Method and device for determining viewpoint area and controlling screen luminance | |
| CN107346419B (en) | Iris recognition method, electronic device, and computer-readable storage medium | |
| CN111553266A (en) | Identification verification method and device and electronic equipment | |
| CN111368944B (en) | Method and device for recognizing copied image and certificate photo and training model and electronic equipment | |
| US20200085296A1 (en) | Eye state detection system and method of operating the same for utilizing a deep learning model to detect an eye state | |
| KR20110128059A (en) | Method and apparatus for preventing driver from driving while drowsy based on detection of driver's pupils, and recording medium containing computer readable programs performing the method | |
| CN111582118A (en) | Face recognition method and device | |
| CN112528888A (en) | Optical fingerprint acquisition method and device, electronic equipment and storage medium | |
| WO2015131571A1 (en) | Method and terminal for implementing image sequencing | |
| CN105718033A (en) | Fatigue detection system and method | |
| CN108769521B (en) | Photographing method, mobile terminal and computer readable storage medium | |
| KR100565959B1 (en) | Method for Detecting Counterfeit Iris using Visible Light |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20200421 |
|
| RJ01 | Rejection of invention patent application after publication |