CN105574519A - Method and system for opening intelligent door by identifying dynamic figure characteristics - Google Patents
Method and system for opening intelligent door by identifying dynamic figure characteristics Download PDFInfo
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- CN105574519A CN105574519A CN201610074542.2A CN201610074542A CN105574519A CN 105574519 A CN105574519 A CN 105574519A CN 201610074542 A CN201610074542 A CN 201610074542A CN 105574519 A CN105574519 A CN 105574519A
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- G—PHYSICS
- G07—CHECKING-DEVICES
- G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
- G07C9/00—Individual registration on entry or exit
- G07C9/00174—Electronically operated locks; Circuits therefor; Nonmechanical keys therefor, e.g. passive or active electrical keys or other data carriers without mechanical keys
- G07C9/00563—Electronically operated locks; Circuits therefor; Nonmechanical keys therefor, e.g. passive or active electrical keys or other data carriers without mechanical keys using personal physical data of the operator, e.g. finger prints, retinal images, voicepatterns
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/40—Scenes; Scene-specific elements in video content
- G06V20/46—Extracting features or characteristics from the video content, e.g. video fingerprints, representative shots or key frames
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/40—Scenes; Scene-specific elements in video content
- G06V20/48—Matching video sequences
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Abstract
The invention discloses a method and system for opening an intelligent door by identifying dynamic figure characteristics. The method includes the following steps that: dynamic video images are obtained; a plurality of key frame images are extracted from the dynamic video images; frame images which have been subjected to binaryzation processing are scanned, a dynamic video image characteristic flow is extracted; whether the dynamic video image characteristic flow is in a matching relationship with a matching image characteristic flow is judged; fingerprint identification is triggered to be performed on a user based on a fingerprint identification device on the intelligent door; and when the fingerprint information of the user is consistent with fingerprint identity information, the intelligent door is triggered to be opened. With the method and system of the invention adopted, associated video image content can be found accurately through matching, a corresponding fingerprint identification process is started, and precise matching and identity authentication can be realized, and thus, the security of a whole identity authentication process and the safety of the opening of the intelligent door can be ensured.
Description
Technical field
The present invention relates to video image technical field, be specifically related to a kind of method and system that dynamic character features carries out Intelligent door unlatching that identify.
Background technology
Can relate to the processes such as the collection to vedio data, transmission, process, display and playback in Computer Vision process, these processes together form the integral cycle of a system, can successionally operate.Topmost within the scope of video image processing technology is exactly include the compress technique of image and the treatment technology etc. of video image.At present, on market, the video image processing technology of main flow comprises: intellectual analysis process, technology that video Penetrating Fog is anti-reflection, wide dynamic process, SUPERRESOLUTION PROCESSING FOR ACOUSTIC, introduces above four kinds for the treatment of technologies respectively below.
Intelligent video analysis technology is the important means solving the large data screening of field of video monitoring, retrieval technique problem.Current domestic Intellectual Analysis Technology can be divided into two large classes: a class is detected by the movement of the methods such as foreground extraction to the object in picture, distinguishes different behaviors by setting rule, and as mixed line, article are left over, circumference etc.; Another kind of to be Land use models recognition technology carry out modeling targetedly to the object of monitoring required in picture, thus reach and detect and related application the certain objects in video, as application such as vehicle detection, stream of people's statistics, Face datection.
Existing video acquisition is higher to dynamic requirements, the dynamic of whole video acquisition requires high, existing Intelligent door system is not accurate enough for Dynamic Data Acquiring, also the security mechanisms do not responded, lack a kind of efficient image identification, the mechanism of identification, is applicable to high-grade community, the development of intelligence or intelligence community.
Summary of the invention
The object of this invention is to provide a kind of method and system that dynamic character features carries out Intelligent door unlatching that identify, reduce the search difficulty of matching gathering video data, realize the security control of Intelligent door system.
For this reason, the invention provides a kind of method that dynamic character features carries out Intelligent door unlatching that identifies, comprise the steps:
Based on camera, dynamic video collection is carried out to the personage entered within the scope of video acquisition, obtain dynamic video image;
Video image pre-service is carried out to described dynamic video image, and motion detection is carried out to described dynamic video image, extract the some key frame images in dynamic video image;
Carry out binary conversion treatment to each two field picture in the some key frame images extracted, the two field picture after scanning binary conversion treatment also extracts dynamic video image feature stream;
Dynamic video image feature stream is mated with the matching image feature stream of all matching images in Intelligent door system, judges whether dynamic video image feature stream and matching image feature stream exist matching relationship;
Judging that the feature stream to be matched of a certain matching image in dynamic video image feature stream and all matching images is deposited after the matching, activated user carries out fingerprint recognition based on the fingerprint identification device on Intelligent door;
Whether consistent with the Fingerprint Identity information associated by described a certain matching image based on the user fingerprints information obtained;
When described user fingerprints information is consistent with described Fingerprint Identity information, trigger the unlatching of Intelligent door.
Describedly based on camera, dynamic video collection is carried out to the personage entered within the scope of video acquisition, obtains dynamic video image and comprise:
Statistical learning method based on Adaboost algorithm detects character features, judges whether personage enters into video acquisition scope;
When judging that personage enters into video acquisition scope, dynamic video collection being carried out to described personage, obtaining dynamic video image.
Describedly video image pre-service carried out to described dynamic video image comprise:
Noise reduction and image enhaucament are carried out to dynamic video image.
Describedly carry out motion to described dynamic video image and detect, the some key frame images extracted in dynamic video image comprise:
Motion based on three-frame difference detects the extraction described dynamic video image being carried out to some key frames.
Two field picture after described scanning binary conversion treatment also extracts dynamic video image feature stream and comprises:
Two field picture after binary conversion treatment is divided into 4,9,16 parts of formed objects;
To the every sub-fraction in 4,9,16 parts, then be equally divided into 4 subregions;
From top to bottom, from left to right, scan each Minimum Area of whole binary map successively, check the distribution situation of each area pixel point, obtain the different character symbol in this region according to different distribution situations;
Two field picture after scan process complete binary conversion treatment, obtains 3 feature streams of the two field picture after binary conversion treatment based on 4,9,16 parts.
Described distribution situation of checking each area pixel point, obtains in the step of the different character symbol in this region according to different distribution situations, pixel and character symbol corresponding relation are: a=1000; B=0100; C=0010; D=0001; E=1100; F=0110; G=0011; H=1001; I=1010; J=0101; K=0111; L=1011; M=1101; N=1110; O=1111; P=0000, wherein 1 represent this region and have pixel to distribute, 0 represents this region distributes without pixel, and a to p representation feature accords with.
Described dynamic video image feature stream to be mated with the matching image feature stream of all matching images in Intelligent door system, judges whether dynamic video image feature stream and matching image feature stream exist matching relationship:
Take out the matching image feature stream in all matching images corresponding to each matching image and dynamic video image feature stream;
Contrast 3 feature streams of matching image feature stream and dynamic video image feature stream respectively, the similarity of statistics characteristic of correspondence stream, and draw each matching image and dynamic video Similarity value in all matching images;
When judging that the Similarity value corresponding to a certain matching image in Intelligent door system is greater than threshold value, then judge that the matching image in dynamic video image and Intelligent door system exists matching relationship, otherwise judge that the matching image in described dynamic video image and Intelligent door system does not exist matching relationship.
Accordingly, present invention also offers a kind of system that dynamic character features carries out Intelligent door unlatching that identifies, comprising:
Video acquisition module, for carrying out dynamic video collection based on camera to the personage entered within the scope of video acquisition, obtains dynamic video image;
Video pre-filtering module, for carrying out video image pre-service to described dynamic video image, and carrying out motion detection to described dynamic video image, extracting the some key frame images in dynamic video image;
Computer Vision module, for carrying out binary conversion treatment to each two field picture in the some key frame images extracted, the two field picture after scanning binary conversion treatment also extracts dynamic video image feature stream;
Video image matching module, for being mated with the matching image feature stream of all matching images in Intelligent door system by dynamic video image feature stream, judges whether dynamic video image feature stream and matching image feature stream exist matching relationship;
Finger print information acquisition module, for judging that the feature stream to be matched of a certain matching image in dynamic video image feature stream and all matching images is deposited after the matching, activated user is carrying out fingerprint recognition based on the fingerprint identification device on Intelligent door;
Whether finger print information identification module, for consistent with the Fingerprint Identity information associated by described a certain matching image based on the user fingerprints information obtained;
Intelligent door opening module, for when described user fingerprints information is consistent with described Fingerprint Identity information, triggers the unlatching of Intelligent door.
Described video acquisition module is used for detecting character features based on the statistical learning method of Adaboost algorithm, judges whether personage enters into video acquisition scope; When judging that personage enters into video acquisition scope, dynamic video collection being carried out to described personage, obtaining dynamic video image.
Described video pre-filtering module is used for carrying out noise reduction and image enhaucament to dynamic video image, and detects based on the motion of three-frame difference the extraction described dynamic video image being carried out to some key frames.
Compared with prior art, the Face datection algorithm that the present invention is based on Adaboost is a kind of statistical learning algorithm, it is face by differentiating the statistics of Haar feature, can identify personage and whether enter into video acquisition scope, thus start whole video acquisition process.For the dynamic gathering video, take to carry out motion to video image to detect, obtain key frame images, form the key frame video flowing of key frame images, thus feature stream extraction is carried out to the key frame images in key frame video flowing, thus have submitted the precision of the target image of video image needs coupling, feature is extracted in video area distributed intelligence according to target image, target image and image to be matched are carried out characteristic matching, thus identify or search associated video region, can also follow the tracks of in video simultaneously.For the capacity in matching database, the feature stream of each matching image in matching database can be obtained in advance, feature stream in for each image, concrete condition according to the distribution of each fritter impact point draws character symbol and morphogenesis characters stream carries out images match, and only need the whole target area of single pass, avoid double counting, coupling, accelerates images match speed and efficiency greatly.For whole matching process, the video image content matching accurately and be associated can be handed over, and start corresponding fingerprint identification process, reach the object of exact matching and authentication, thus ensure the security that whole identification is verified, the security that Intelligent door is opened.
Accompanying drawing explanation
In order to be illustrated more clearly in the embodiment of the present invention 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 some embodiments of the present invention, for those of ordinary skill in the art, under the prerequisite not paying creative work, other accompanying drawing can also be obtained according to these accompanying drawings.
Fig. 1 is the method flow diagram that the dynamic character features of identification of the embodiment of the present invention carries out Intelligent door unlatching;
Fig. 2 is the system construction drawing that the dynamic character features of identification of the embodiment of the present invention carries out Intelligent door unlatching.
Embodiment
Below in conjunction with the accompanying drawing in the embodiment of the present invention, be clearly and completely described the technical scheme in the embodiment of the present invention, obviously, described embodiment is only the present invention's part embodiment, instead of whole embodiments.Based on the embodiment in the present invention, those of ordinary skill in the art, not making other embodiments all obtained under creative work prerequisite, belong to the scope of protection of the invention.
As mentioned above, the present invention proposes a kind of method that dynamic character features carries out Intelligent door unlatching that identifies, it obtains dynamic video image by carrying out dynamic video collection based on camera to the personage entered within the scope of video acquisition; Video image pre-service is carried out to dynamic video image, and motion detection is carried out to dynamic video image, extract the some key frame images in dynamic video image; Carry out binary conversion treatment to each two field picture in the some key frame images extracted, the two field picture after scanning binary conversion treatment also extracts dynamic video image feature stream; Dynamic video image feature stream is mated with the matching image feature stream of all matching images in Intelligent door system, judges whether dynamic video image feature stream and matching image feature stream exist matching relationship; Judging that the feature stream to be matched of a certain matching image in dynamic video image feature stream and all matching images is deposited after the matching, activated user carries out fingerprint recognition based on the fingerprint identification device on Intelligent door; Whether consistent with the Fingerprint Identity information associated by described a certain matching image based on the user fingerprints information obtained; When user fingerprints information is consistent with described Fingerprint Identity information, trigger the unlatching of Intelligent door.
The dynamic character features of identification shown in the embodiment of the present invention with reference to figure 1, Fig. 1 carries out the method flow diagram of Intelligent door unlatching, and the method comprises as follows:
S101, based on camera, dynamic video collection is carried out to the personage entered within the scope of video acquisition, obtain dynamic video image;
It should be noted that, in specific implementation process, the statistical learning method first based on Adaboost algorithm detects character features, judges whether personage enters into video acquisition scope; When judging that personage enters into video acquisition scope, dynamic video collection being carried out to described personage, obtaining dynamic video image.When character features is not comprehensive in whole video acquisition process, generally do not start video acquisition, these character features comprise face, whole human body contour outline etc.
S102, video image pre-service is carried out to dynamic video image;
It should be noted that, in whole Image semantic classification process, need to relate to carry out noise reduction and image enhaucament to dynamic video image, ensure key-frame extraction in video data.
S103, dynamic video image carried out to motion and detect, extract the some key frame images in dynamic video image;
In specific implementation process, the motion based on three-frame difference detects extraction dynamic video image being carried out to some key frames.
S104, carry out binary conversion treatment to each two field picture in the some key frame images extracted, the two field picture after scanning binary conversion treatment also extracts dynamic video image feature stream;
It is as follows that whole characteristics of image flows through journey:
Two field picture after binary conversion treatment is divided into 4,9,16 parts of formed objects;
To the every sub-fraction in 4,9,16 parts, then be equally divided into 4 subregions;
From top to bottom, from left to right, scan each Minimum Area of whole binary map successively, check the distribution situation of each area pixel point, obtain the different character symbol in this region according to different distribution situations;
Two field picture after scan process complete binary conversion treatment, obtains 3 feature streams of the two field picture after binary conversion treatment based on 4,9,16 parts.
It should be noted that, check the distribution situation of each area pixel point, obtain in the step of the different character symbol in this region according to different distribution situations, pixel and character symbol corresponding relation are: a=1000; B=0100; C=0010; D=0001; E=1100; F=0110; G=0011; H=1001; I=1010; J=0101; K=0111; L=1011; M=1101; N=1110; O=1111; P=0000, as shown in following table table 1, wherein 1 represent this region and have pixel to distribute, 0 represents this region distributes without pixel, and a to p representation feature accords with.
The corresponding table of table 1 pixel distributed isomerism symbol
| a | b | c | d | ||||||||
| 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | ||||
| 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | ||||
| e | f | g | h | ||||||||
| 1 | 1 | 0 | 1 | 0 | 0 | 1 | 0 | ||||
| 0 | 0 | 0 | 1 | 1 | 1 | 1 | 0 | ||||
| i | j | k | l | ||||||||
| 1 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | ||||
| 0 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | ||||
| m | n | o | p | ||||||||
| 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | ||||
| 1 | 0 | 0 | 1 | 1 | 1 | 0 | 0 |
Define a character x, the method of the matching degree of y, in correspondence, table mates, and the similarity of definition two characters is the number of after dis (x, y): x and y XOR 1, dis (x, y) numerical value indicates more greatly character x, and the Regional Similarity of y representative is not higher (such as, after x and x coupling, dis=0, indicates that these two regions are infinitely similar).
S105, dynamic video image feature stream to be mated with the matching image feature stream of all matching images in Intelligent door system;
S106, judge whether dynamic video image feature stream and matching image feature stream exist matching relationship, if there is matching relationship, then enter into S107, otherwise process ends;
In specific implementation process, the process of Intelligent Recognition piece identity, judge that whether people information in dynamic video image feature is the sub-picture in matching image, concrete implementation step comprises: first take out the matching image feature stream in all matching images corresponding to each matching image and dynamic video image feature stream; Contrast 3 feature streams of matching image feature stream and dynamic video image feature stream respectively, the similarity of statistics characteristic of correspondence stream, and draw each matching image and dynamic video Similarity value in all matching images; When judging that the Similarity value corresponding to a certain matching image in Intelligent door system is greater than threshold value, then judge that the matching image in dynamic video image and Intelligent door system exists matching relationship, otherwise judge that the matching image in described dynamic video image and Intelligent door system does not exist matching relationship.
S107, activated user carry out fingerprint recognition based on the fingerprint identification device on Intelligent door;
After meeting identification, find that this user is a member in images match storehouse, then enter into fingerprint identification process, guarantee is the legal input process under validated user information.Have corresponding decoded information involved by each matching image, this decoded information ensures the security of user's input information, thus ensures the security that Intelligent door is opened.
S108, whether consistent with the Fingerprint Identity information associated by a certain matching image based on the user fingerprints information obtained, if consistent, then enter into S109, otherwise process ends;
S109, when user fingerprints information is consistent with described Fingerprint Identity information, trigger the unlatching of Intelligent door.
Terminate.
In specific implementation process, first achieve the identification of dynamic character features, thus restart the unlatching of gate inhibition, ensured the security that whole Intelligent door is opened, ensured whole community or house safety, realize intelligent residence.
Fig. 2 dynamic character features of identification that also show in the embodiment of the present invention carries out the system architecture schematic diagram of Intelligent door unlatching, and this system comprises:
Video acquisition module, for carrying out dynamic video collection based on camera to the personage entered within the scope of video acquisition, obtains dynamic video image;
Video pre-filtering module, for carrying out video image pre-service to described dynamic video image, and carrying out motion detection to described dynamic video image, extracting the some key frame images in dynamic video image;
Computer Vision module, for carrying out binary conversion treatment to each two field picture in the some key frame images extracted, the two field picture after scanning binary conversion treatment also extracts dynamic video image feature stream;
Video image matching module, for being mated with the matching image feature stream of all matching images in Intelligent door system by dynamic video image feature stream, judges whether dynamic video image feature stream and matching image feature stream exist matching relationship;
Finger print information acquisition module, for judging that the feature stream to be matched of a certain matching image in dynamic video image feature stream and all matching images is deposited after the matching, activated user is carrying out fingerprint recognition based on the fingerprint identification device on Intelligent door;
Whether finger print information identification module, for consistent with the Fingerprint Identity information associated by described a certain matching image based on the user fingerprints information obtained;
Intelligent door opening module, for when described user fingerprints information is consistent with described Fingerprint Identity information, triggers the unlatching of Intelligent door.
In specific implementation process, this video acquisition module is used for detecting character features based on the statistical learning method of Adaboost algorithm, judges whether personage enters into video acquisition scope; When judging that personage enters into video acquisition scope, dynamic video collection being carried out to described personage, obtaining dynamic video image.
In specific implementation process, this video pre-filtering module is used for carrying out noise reduction and image enhaucament to dynamic video image, and detects based on the motion of three-frame difference extraction dynamic video image being carried out to some key frames.
In specific implementation process, in this Computer Vision module, to flow through journey as follows for characteristics of image: 4,9,16 parts two field picture after binary conversion treatment being divided into formed objects; To the every sub-fraction in 4,9,16 parts, then be equally divided into 4 subregions; From top to bottom, from left to right, scan each Minimum Area of whole binary map successively, check the distribution situation of each area pixel point, obtain the different character symbol in this region according to different distribution situations; Two field picture after scan process complete binary conversion treatment, obtains 3 feature streams of the two field picture after binary conversion treatment based on 4,9,16 parts.
In specific implementation process, this video image matching module is for taking out matching image feature stream in all matching images corresponding to each matching image and dynamic video image feature stream; Contrast 3 feature streams of matching image feature stream and dynamic video image feature stream respectively, the similarity of statistics characteristic of correspondence stream, and draw each matching image and dynamic video Similarity value in all matching images; When judging that the Similarity value corresponding to a certain matching image in Intelligent door system is greater than threshold value, then judge that the matching image in dynamic video image and Intelligent door system exists matching relationship, otherwise judge that the matching image in described dynamic video image and Intelligent door system does not exist matching relationship.
The Face datection algorithm that the present invention is based on Adaboost is a kind of statistical learning algorithm, and it is face by differentiating the statistics of Haar feature, can identify personage and whether enter into video acquisition scope, thus start whole video acquisition process.For the dynamic gathering video, take to carry out motion to video image to detect, obtain key frame images, form the key frame video flowing of key frame images, thus feature stream extraction is carried out to the key frame images in key frame video flowing, thus have submitted the precision of the target image of video image needs coupling, feature is extracted in video area distributed intelligence according to target image, target image and image to be matched are carried out characteristic matching, thus identify or search associated video region, can also follow the tracks of in video simultaneously.For the capacity in matching database, the feature stream of each matching image in matching database can be obtained in advance, feature stream in for each image, concrete condition according to the distribution of each fritter impact point draws character symbol and morphogenesis characters stream carries out images match, and only need the whole target area of single pass, avoid double counting, coupling, accelerates images match speed and efficiency greatly.For whole matching process, the video image content matching accurately and be associated can be handed over, and start corresponding fingerprint identification process, reach the object of exact matching and authentication, thus ensure the security that whole identification is verified, the security that Intelligent door is opened.
The method and system that the dynamic character features of identification provided the embodiment of the present invention above carries out Intelligent door unlatching are described in detail, apply specific case herein to set forth principle of the present invention and embodiment, the explanation of above embodiment just understands method of the present invention and core concept thereof for helping; Meanwhile, for one of ordinary skill in the art, according to thought of the present invention, all will change in specific embodiments and applications, in sum, this description should not be construed as limitation of the present invention.
Claims (10)
1. identify that dynamic character features carries out a method for Intelligent door unlatching, is characterized in that, comprises the steps:
Based on camera, dynamic video collection is carried out to the personage entered within the scope of video acquisition, obtain dynamic video image;
Video image pre-service is carried out to described dynamic video image, and motion detection is carried out to described dynamic video image, extract the some key frame images in dynamic video image;
Carry out binary conversion treatment to each two field picture in the some key frame images extracted, the two field picture after scanning binary conversion treatment also extracts dynamic video image feature stream;
Dynamic video image feature stream is mated with the matching image feature stream of all matching images in Intelligent door system, judges whether dynamic video image feature stream and matching image feature stream exist matching relationship;
Judging that the feature stream to be matched of a certain matching image in dynamic video image feature stream and all matching images is deposited after the matching, activated user carries out fingerprint recognition based on the fingerprint identification device on Intelligent door;
Whether consistent with the Fingerprint Identity information associated by described a certain matching image based on the user fingerprints information obtained;
When described user fingerprints information is consistent with described Fingerprint Identity information, trigger the unlatching of Intelligent door.
2. as claimed in claim 1 identify the method that dynamic character features carries out Intelligent door unlatching, it is characterized in that, describedly based on camera, dynamic video collection is carried out to the personage entered within the scope of video acquisition, obtain dynamic video image and comprise:
Statistical learning method based on Adaboost algorithm detects character features, judges whether personage enters into video acquisition scope;
When judging that personage enters into video acquisition scope, dynamic video collection being carried out to described personage, obtaining dynamic video image.
3. as claimed in claim 1 identify the method that dynamic character features carries out Intelligent door unlatching, it is characterized in that, describedly video image pre-service is carried out to described dynamic video image comprise:
Noise reduction and image enhaucament are carried out to dynamic video image.
4. as claimed in claim 1 identify the method that dynamic character features carries out Intelligent door unlatching, it is characterized in that, describedly carry out motion to described dynamic video image and detect, the some key frame images in extraction dynamic video image comprise:
Motion based on three-frame difference detects the extraction described dynamic video image being carried out to some key frames.
5. as claimed in claim 1 identify the method that dynamic character features carries out Intelligent door unlatching, it is characterized in that, the two field picture after described scanning binary conversion treatment also extracts dynamic video image feature stream and comprises:
Two field picture after binary conversion treatment is divided into 4,9,16 parts of formed objects;
To the every sub-fraction in 4,9,16 parts, then be equally divided into 4 subregions;
From top to bottom, from left to right, scan each Minimum Area of whole binary map successively, check the distribution situation of each area pixel point, obtain the different character symbol in this region according to different distribution situations;
Two field picture after scan process complete binary conversion treatment, obtains 3 feature streams of the two field picture after binary conversion treatment based on 4,9,16 parts.
6. the dynamic character features of identification as claimed in claim 5 carries out the method for Intelligent door unlatching, it is characterized in that, described distribution situation of checking each area pixel point, obtain in the step of the different character symbol in this region according to different distribution situations, pixel and character symbol corresponding relation are: a=1000; B=0100; C=0010; D=0001; E=1100; F=0110; G=0011; H=1001; I=1010; J=0101; K=0111; L=1011; M=1101; N=1110; O=1111; P=0000, wherein 1 represent this region and have pixel to distribute, 0 represents this region distributes without pixel, and a to p representation feature accords with.
7. the dynamic character features of identification as claimed in claim 6 carries out the method for Intelligent door unlatching, it is characterized in that, described dynamic video image feature stream to be mated with the matching image feature stream of all matching images in Intelligent door system, judges whether dynamic video image feature stream and matching image feature stream exist matching relationship and comprise:
Take out the matching image feature stream in all matching images corresponding to each matching image and dynamic video image feature stream;
Contrast 3 feature streams of matching image feature stream and dynamic video image feature stream respectively, the similarity of statistics characteristic of correspondence stream, and draw each matching image and dynamic video Similarity value in all matching images;
When judging that the Similarity value corresponding to a certain matching image in Intelligent door system is greater than threshold value, then judge that the matching image in dynamic video image and Intelligent door system exists matching relationship, otherwise judge that the matching image in described dynamic video image and Intelligent door system does not exist matching relationship.
8. identify that dynamic character features carries out a system for Intelligent door unlatching, is characterized in that, comprising:
Video acquisition module, for carrying out dynamic video collection based on camera to the personage entered within the scope of video acquisition, obtains dynamic video image;
Video pre-filtering module, for carrying out video image pre-service to described dynamic video image, and carrying out motion detection to described dynamic video image, extracting the some key frame images in dynamic video image;
Computer Vision module, for carrying out binary conversion treatment to each two field picture in the some key frame images extracted, the two field picture after scanning binary conversion treatment also extracts dynamic video image feature stream;
Video image matching module, for being mated with the matching image feature stream of all matching images in Intelligent door system by dynamic video image feature stream, judges whether dynamic video image feature stream and matching image feature stream exist matching relationship;
Finger print information acquisition module, for judging that the feature stream to be matched of a certain matching image in dynamic video image feature stream and all matching images is deposited after the matching, activated user is carrying out fingerprint recognition based on the fingerprint identification device on Intelligent door;
Whether finger print information identification module, for consistent with the Fingerprint Identity information associated by described a certain matching image based on the user fingerprints information obtained;
Intelligent door opening module, for when described user fingerprints information is consistent with described Fingerprint Identity information, triggers the unlatching of Intelligent door.
9. the dynamic character features of identification as claimed in claim 8 carries out the system of Intelligent door unlatching, it is characterized in that, described video acquisition module is used for detecting character features based on the statistical learning method of Adaboost algorithm, judges whether personage enters into video acquisition scope; When judging that personage enters into video acquisition scope, dynamic video collection being carried out to described personage, obtaining dynamic video image.
10. the dynamic character features of identification as claimed in claim 8 carries out the system of Intelligent door unlatching, it is characterized in that, described video pre-filtering module is used for carrying out noise reduction and image enhaucament to dynamic video image, and detects based on the motion of three-frame difference the extraction described dynamic video image being carried out to some key frames.
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
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| CN107168379A (en) * | 2017-06-07 | 2017-09-15 | 深圳市鑫益嘉科技股份有限公司 | A kind of dynamic tracing device and method for tracing |
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| CN116453245A (en) * | 2023-04-20 | 2023-07-18 | 东莞市伟创动力科技有限公司 | Unlocking management method and system for electronic lock |
| CN116453245B (en) * | 2023-04-20 | 2023-11-14 | 东莞市伟创动力科技有限公司 | Unlocking management method and system for electronic lock |
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