CN105913260B - Automate facial-recognition security systems - Google Patents
Automate facial-recognition security systems Download PDFInfo
- Publication number
- CN105913260B CN105913260B CN201610201829.7A CN201610201829A CN105913260B CN 105913260 B CN105913260 B CN 105913260B CN 201610201829 A CN201610201829 A CN 201610201829A CN 105913260 B CN105913260 B CN 105913260B
- Authority
- CN
- China
- Prior art keywords
- image
- equipment
- images
- subgraph
- 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.)
- Expired - Fee Related
Links
- 230000001815 facial effect Effects 0.000 claims abstract description 34
- 238000004891 communication Methods 0.000 claims abstract description 28
- 238000010200 validation analysis Methods 0.000 claims description 24
- 210000001061 forehead Anatomy 0.000 claims description 22
- 238000003860 storage Methods 0.000 claims description 21
- 238000012937 correction Methods 0.000 claims description 18
- 238000009499 grossing Methods 0.000 claims description 18
- 239000000284 extract Substances 0.000 claims description 13
- 230000011218 segmentation Effects 0.000 claims description 12
- 238000001514 detection method Methods 0.000 claims description 11
- 238000012545 processing Methods 0.000 claims description 11
- 238000006073 displacement reaction Methods 0.000 claims description 9
- 238000013519 translation Methods 0.000 claims description 9
- 238000012790 confirmation Methods 0.000 claims description 8
- 238000004458 analytical method Methods 0.000 claims description 7
- 238000003709 image segmentation Methods 0.000 claims description 6
- 238000000034 method Methods 0.000 description 14
- 230000008569 process Effects 0.000 description 8
- 230000007246 mechanism Effects 0.000 description 7
- 230000005540 biological transmission Effects 0.000 description 6
- 238000005516 engineering process Methods 0.000 description 5
- 238000010586 diagram Methods 0.000 description 3
- 238000000605 extraction Methods 0.000 description 3
- 238000012986 modification Methods 0.000 description 3
- 230000004048 modification Effects 0.000 description 3
- 230000009466 transformation Effects 0.000 description 3
- 230000008859 change Effects 0.000 description 2
- 238000001914 filtration Methods 0.000 description 2
- 206010062575 Muscle contracture Diseases 0.000 description 1
- 208000006111 contracture Diseases 0.000 description 1
- 230000007812 deficiency Effects 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- PCHJSUWPFVWCPO-UHFFFAOYSA-N gold Chemical compound [Au] PCHJSUWPFVWCPO-UHFFFAOYSA-N 0.000 description 1
- 239000010931 gold Substances 0.000 description 1
- 229910052737 gold Inorganic materials 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 230000002452 interceptive effect Effects 0.000 description 1
- 230000004807 localization Effects 0.000 description 1
- 230000014759 maintenance of location Effects 0.000 description 1
- 230000005055 memory storage Effects 0.000 description 1
- 239000000203 mixture Substances 0.000 description 1
- 238000005457 optimization Methods 0.000 description 1
- 230000001314 paroxysmal effect Effects 0.000 description 1
- 238000012546 transfer Methods 0.000 description 1
- 230000000007 visual effect Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q20/00—Payment architectures, schemes or protocols
- G06Q20/38—Payment protocols; Details thereof
- G06Q20/40—Authorisation, e.g. identification of payer or payee, verification of customer or shop credentials; Review and approval of payers, e.g. check credit lines or negative lists
- G06Q20/401—Transaction verification
- G06Q20/4014—Identity check for transactions
- G06Q20/40145—Biometric identity checks
-
- 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
- G06V40/12—Fingerprints or palmprints
- G06V40/13—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
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/12—Fingerprints or palmprints
- G06V40/1365—Matching; Classification
-
- 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
- G06V40/165—Detection; Localisation; Normalisation using facial parts and geometric relationships
-
- 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
- G06V40/171—Local features and components; Facial parts ; Occluding parts, e.g. glasses; Geometrical relationships
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Oral & Maxillofacial Surgery (AREA)
- General Physics & Mathematics (AREA)
- Health & Medical Sciences (AREA)
- Theoretical Computer Science (AREA)
- Multimedia (AREA)
- Human Computer Interaction (AREA)
- Business, Economics & Management (AREA)
- General Health & Medical Sciences (AREA)
- Accounting & Taxation (AREA)
- General Business, Economics & Management (AREA)
- Geometry (AREA)
- Computer Security & Cryptography (AREA)
- Strategic Management (AREA)
- Finance (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Collating Specific Patterns (AREA)
Abstract
The present invention relates to one kind to automate facial-recognition security systems, including GPRS communication equipments, two-way speaker, main control device and facial recognition device, facial recognition device and GPRS communication equipment cooperatings, for confirming customer identification based on custom image, main control device is connected with GPRS communication equipments, two-way speaker and facial recognition device respectively, for determining to pay strategy based on customer identification, while also control two-way speaker to play customer identification and confirm result.By means of the invention it is possible to automatic payment function is realized based on customer's facial information.
Description
Technical field
The present invention relates to area of facial recognition, more particularly to a kind of automation facial-recognition security systems.
Background technology
Feature workable for face identification system is generally divided into visual signature, pixels statisticses feature, facial image transformation series
Number feature, facial image algebraic characteristic etc..Face characteristic extracts what is carried out aiming at some features of face.Face characteristic carries
Take, also referred to as face characterizes, and it is the process that feature modeling is carried out to face.The method of face characteristic extraction, which is summed up, is divided into two
Major class：One kind is Knowledge based engineering characterizing method；Another is the characterizing method based on algebraic characteristic or statistical learning.
Knowledge based engineering characterizing method mainly according to the shape description of human face and they the distance between characteristic
To obtain the characteristic for contributing to face classification, its characteristic component generally includes Euclidean distance, curvature and the angle between characteristic point
Degree etc..Face is locally made up of eyes, nose, mouth, chin etc., and to these parts and the geometry of structural relation is retouched between them
State, geometric properties can be referred to as the key character of identification face, these features.Knowledge based engineering face, which characterizes, mainly to be included
Method and template matching method based on geometric properties.
Facial image matches as follows with the specific implementation of identification：The characteristic and database of the facial image of extraction
The feature templates of middle storage scan for matching, by setting a threshold value, when similarity exceedes this threshold value, then matching
The result output arrived.Recognition of face is exactly the root by face characteristic to be identified compared with obtained skin detection
The identity information of face is judged according to similarity degree.This process is divided into two classes again：One kind is to confirm, is one-to-one progress
The process that image compares, another kind of is identification, is the process of one-to-many progress images match contrast.
It is by face recognition application to payment platform that recognition of face, which is paid, by customer face feature extraction, confirms to care for
Objective identity, and the spending amount for coordinating cashier to provide completes customer payment process.Whole payment process automaticity is high, people
Work interference link is few, for especially pronounced in queuing checkout customer excessive period, its effect.
However, existing recognition of face payments mechanism there is also some problems：(1) it is excessively simple thick to pay link for identification
Cruelly, necessary secondary authentication mechanism is lacked；(2) when queuing checkout customer is excessive, facial knowledge may be carried out to non-checkout customer
Not and pay；(3) recognition of face still has the space for improving performance in itself.
Therefore, it is necessary to which a kind of new face recognition payment system, is improved to existing recognition of face payments mechanism, increase
Add assistant authentification means and customer to select link, and the mode of facial features localization is optimized, so as to improve shopper checkout
While efficiency, the problem of fundamentally avoiding paying by mistake, occurs.
The content of the invention
In order to solve the above problems, the invention provides one kind to automate facial-recognition security systems, by increasing capacitance it is possible to increase secondary identities
Authenticating device, after face recognition identity, further identity validation is carried out using secondary identities authenticating device, while be cash register
Member provides checkout customer's selection mode, and the situation for avoiding other customers from being settled accounts by mistake occurs, in addition, also optimizing existing face
Identification is paid, and ensure that the accuracy of face recognition, so as to improve the integral working of face recognition payment.
According to an aspect of the present invention, there is provided one kind automation facial-recognition security systems, the system communicate including GPRS
Equipment, two-way speaker, main control device and facial recognition device, facial recognition device and GPRS communication equipment cooperatings,
For confirming customer identification based on custom image, main control device is known with GPRS communication equipments, two-way speaker and face respectively
Other equipment connection, for determining to pay strategy based on customer identification, while it is true also to control two-way speaker to play customer identification
Recognize result.
More specifically, in the automation facial-recognition security systems, including：Eye splitting equipment, set respectively with SD storages
It is standby to be connected with Gaussian smoothing filter equipment to receive preset reference eye profile and images to be recognized, based on preset reference eye wheel
Exterior feature is partitioned into eye subgraph in images to be recognized；Forehead splitting equipment, filtered respectively with eye splitting equipment and Gaussian smoothing
Wave device is connected to receive eye subgraph and images to be recognized, the position based on eye subgraph in images to be recognized, will
Image section in images to be recognized more than eye subgraph is split to obtain forehead subgraph；Nose splitting equipment, respectively with
SD storage devices are connected with Gaussian smoothing filter equipment to receive preset reference nasal contours and images to be recognized, based on default base
Quasi- nasal contours are partitioned into nose subgraph in images to be recognized；Mouth splitting equipment, respectively with SD storage devices and Gauss
Smothing filtering equipment is connected to receive preset reference mouth profile and images to be recognized, is waiting to know based on preset reference mouth profile
Mouth subgraph is partitioned into other image；Chin splitting equipment, connect respectively with mouth splitting equipment and Gaussian smoothing filter equipment
Connect to receive mouth subgraph and images to be recognized, the position based on mouth subgraph in images to be recognized, by figure to be identified
Image section as in below mouth subgraph is split to obtain chin subgraph；Signature analysis equipment, split respectively with eye
Equipment, forehead splitting equipment, nose splitting equipment, mouth splitting equipment connect with chin splitting equipment, determine eye subgraph
Middle eye feature point is located at coordinate in images to be recognized to be exported as eye coordinate, determines forehead feature in forehead subgraph
Point is located at coordinate in images to be recognized to export as forehead coordinate, determines in nose subgraph nose characteristic point positioned at waiting to know
Coordinate in other image determines that mouth feature point is located in images to be recognized in mouth subgraph to be exported as nose coordinate
Coordinate to be exported as mouth coordinate, determine chin characteristic point in chin subgraph be located at the coordinate in images to be recognized using as
Chin coordinate exports；Characteristic matching equipment, respectively the face recognition data storehouse with signature analysis equipment and distal end be connected, face know
Other database has prestored coordinate of each characteristic point of everyone face-image in the face-image of place, based on spy
Eye coordinate, forehead coordinate, nose coordinate, mouth coordinate and the chin coordinate of analytical equipment output are levied in face recognition data storehouse
Searching and images to be recognized matching degree highest face-image, and will be corresponding with images to be recognized matching degree highest face-image
Piece identity as identification identity output；GPRS communication equipments, for establishing characteristic matching equipment by GPRS communication links
Connection between the face recognition data storehouse of distal end, be also additionally operable to by GPRS communication links establish fingerprint matching device with it is remote
Connection between the fingerprint database at end；Two-way speaker, it is connected with MSP430 single-chip microcomputers, is lost for playing with identity validation
Lose voice prompted file corresponding to signal or identity validation pass signal；High-definition image collecting device, it is arranged on above POS,
For being shot to the crowd of queuing checkout to obtain high definition crowd's image, high-definition image collecting device is additionally operable to record customer
Pay video；Face detection equipment, it is connected respectively with SD storage devices and high-definition image collecting device, for receiving high definition crowd
Image and preset reference face contour, multiple facial subgraphs are matched in high definition crowd's image based on preset reference face contour
Picture；LCD display device, it is connected with face detection equipment to receive and show multiple facial subgraphs, LCD display device also carries
Touch-screen, so that selection target face subgraph, LCD display device are also used from multiple facial subgraphs based on the input of cashier
In display text prompt information corresponding with identity validation failure signal or identity validation pass signal；Geometrical correction device, point
It is not connected with face detection equipment and LCD display device, receives target face subgraph and target face subgraph is carried out several
What correction process is to obtain geometric correction image；Image orbiting facility, it is connected with geometrical correction device to receive geometric correction figure
Picture, image rotation processing is carried out to geometric correction image to obtain rotation image；Image translation device, connect with image orbiting facility
Connect to receive rotation image, image translation processing is carried out to rotation image to obtain displacement images；Image segmentation apparatus, respectively with
SD storage devices are connected with image translation device, and for receiving pre-set image block size and displacement images, displacement images are carried out
Split to obtain the segmentation figure picture of pre-set image block size；Histogram equalization equipment, is connected with image segmentation apparatus, for connecing
Contracture cuts image and carries out histogram equalization processing to segmentation figure picture, to obtain the grey level histogram of segmentation figure picture；Gauss is put down
Sliding filter apparatus, is connected with histogram equalization equipment, is put down for receiving grey level histogram and carrying out Gauss to grey level histogram
Sliding filtering process, to obtain images to be recognized；SD storage devices, for having prestored preset reference face contour and default figure
As block size, it is additionally operable to prestore preset reference eye profile, preset reference nasal contours and preset reference mouth profile；
Fingerprint receiving device, for gathering the finger print information of customer；Fingerprint matching device, respectively with fingerprint receiving device and the finger of distal end
Line database connects, and fingerprint database has prestored everyone fingerprint characteristic, the finger based on the output of fingerprint receiving device
Line information finds the fingerprint characteristic of matching in fingerprint database, and using piece identity corresponding to the fingerprint characteristic of matching as confirmation
Identity exports；MSP430 single-chip microcomputers, set respectively with LCD display device, characteristic matching equipment, fingerprint receiving device and fingerprint matching
Standby connection, when receiving identification identity at characteristic matching equipment, to the customer currently to settle accounts start fingerprint receiving device and
To receive confirmation identity, the customer currently to settle accounts is in the crowd of queuing checkout fingerprint matching device, when identification identity and really
When recognizing identity and being consistent, it will identify identity and cashier passes through the value data one that the touch-screen of LCD display device inputs and risen
The payment devices of distal end are sent to complete to pay, while is sent to E-mail address corresponding to identification identity and confirms mail, confirm postal
Part includes customer payment video；Wherein, preset reference face contour obtains to carry out contours extract to benchmark face-image
Figure, pre-set image block size elects the pixel of 45 pixels × 50 as；Preset reference eye profile is that benchmark eyes image is carried out
Contours extract and the figure obtained, preset reference nasal contours is carry out the figure that contours extract obtains to benchmark nose image
Shape, preset reference mouth profile is carries out the figure that obtains of contours extract to benchmark mouth image；MSP430 single-chip microcomputers are
When not receiving identification identity after one preset time, identity validation failure signal is sent, MSP430 single-chip microcomputers are when second is default
Between after do not receive when confirming identity, send identity validation failure signal, MSP430 single-chip microcomputers are in identification identity with confirming identity
When inconsistent, identity validation failure signal is sent, MSP430 single-chip microcomputers are sent when identifying identity with confirming that identity is consistent
Identity validation pass signal.
More specifically, in the automation facial-recognition security systems：GPRS communication equipments are arranged on the housing of POS.
More specifically, in the automation facial-recognition security systems：MSP430 single-chip microcomputers connect with characteristic matching equipment, fingerprint
Receiving unit and fingerprint matching device are integrated on one piece of surface-mounted integrated circuit.
More specifically, in the automation facial-recognition security systems：Surface-mounted integrated circuit is arranged on the control box below POS
It is interior.
More specifically, in the automation facial-recognition security systems：SD is replaced using MSP430 single-chip microcomputers internal memory
Storage device.
Brief description of the drawings
Embodiment of the present invention is described below with reference to accompanying drawing, wherein：
Fig. 1 is the block diagram of the automation facial-recognition security systems according to embodiment of the present invention.
Fig. 2 is the knot of the high-definition image collecting device of the automation facial-recognition security systems according to embodiment of the present invention
Structure block diagram.
Reference：1GPRS communication equipments；2 two-way speakers；3 main control devices；4 facial recognition devices；5 brightness are examined
Survey unit；6 shooting units；7 recording elements；8 control units
Embodiment
The embodiment of the automation facial-recognition security systems of the present invention is described in detail below with reference to accompanying drawings.
It is directly to be remitted money because recognition of face is paid, therefore, its security performance is particularly critical.Existing recognition of face
Payment is to determine that face feature is remitted money after meeting, and does not account for the situation of face feature identification mistake, meanwhile, it is lined up
The customer of checkout is a lot, it is easy to facial characteristics identification is carried out to non-checkout customer, moreover, existing recognition of face mechanism is in itself
Structural redundancy is high, is also improved the space of precision and optimization function.
In order to overcome above-mentioned deficiency, the present invention has built a kind of automation facial-recognition security systems, can solve the problem that above-mentioned technology
Problem, cumbersome manual operation is being replaced, while improving shopper checkout efficiency, improving payments mechanism on the whole, ensured every
The economic interests of one customer.
Fig. 1 be according to embodiment of the present invention automation facial-recognition security systems block diagram, the system
Including GPRS communication equipments, two-way speaker, main control device and facial recognition device, facial recognition device and GPRS communications are set
Standby cooperating, for confirming customer identification based on custom image, main control device is raised one's voice with GPRS communication equipments, two-channel respectively
Device connects with facial recognition device, for determining to pay strategy based on customer identification, while also controls two-way speaker to play
Customer identification confirms result.
Then, continue that the concrete structure of the automation facial-recognition security systems of the present invention is further detailed.
The system includes：Eye splitting equipment, it is connected respectively with SD storage devices and Gaussian smoothing filter equipment to connect
Preset reference eye profile and images to be recognized are received, eye is partitioned into images to be recognized based on preset reference eye profile
Image；Forehead splitting equipment, be connected respectively with eye splitting equipment and Gaussian smoothing filter equipment with receive eye subgraph and
Images to be recognized, the position based on eye subgraph in images to be recognized, by images to be recognized more than eye subgraph
Image section is split to obtain forehead subgraph.
The system includes：Nose splitting equipment, it is connected respectively with SD storage devices and Gaussian smoothing filter equipment to connect
Preset reference nasal contours and images to be recognized are received, nose is partitioned into images to be recognized based on preset reference nasal contours
Image.
The system includes：Mouth splitting equipment, it is connected respectively with SD storage devices and Gaussian smoothing filter equipment to connect
Preset reference mouth profile and images to be recognized are received, mouth is partitioned into images to be recognized based on preset reference mouth profile
Image.
The system includes：Chin splitting equipment, be connected respectively with mouth splitting equipment and Gaussian smoothing filter equipment with
Receive mouth subgraph and images to be recognized, the position based on mouth subgraph in images to be recognized, by images to be recognized
Image section below mouth subgraph is split to obtain chin subgraph.
The system includes：Signature analysis equipment, set respectively with eye splitting equipment, forehead splitting equipment, nose segmentation
Standby, mouth splitting equipment connects with chin splitting equipment, determines that eye feature point is located in images to be recognized in eye subgraph
Coordinate using as eye coordinate export, determine that forehead characteristic point is located at the coordinate in images to be recognized to make in forehead subgraph
Exported for forehead coordinate, determine that nose characteristic point in nose subgraph is located at the coordinate in images to be recognized to be used as nose coordinate
Output, determine that mouth feature point in mouth subgraph be located at the coordinate in images to be recognized using as the output of mouth coordinate, it is determined that
Chin characteristic point is located at coordinate in images to be recognized to be used as the output of chin coordinate in chin subgraph.
The system includes：Characteristic matching equipment, connect respectively with the face recognition data storehouse of signature analysis equipment and distal end
Connect, face recognition data storehouse has prestored seat of each characteristic point of everyone face-image in the face-image of place
Mark, eye coordinate, forehead coordinate, nose coordinate, mouth coordinate and the chin coordinate of feature based analytical equipment output are in face
Identification database is found and images to be recognized matching degree highest face-image, and will be with images to be recognized matching degree highest face
Piece identity corresponding to portion's image is as identification identity output.
The system includes：GPRS communication equipments, for establishing characteristic matching equipment and distal end by GPRS communication links
Face recognition data storehouse between connection, be also additionally operable to establish the finger of fingerprint matching device and distal end by GPRS communication links
Connection between line database.
The system includes：Two-way speaker, it is connected with MSP430 single-chip microcomputers, unsuccessfully believes with identity validation for playing
Number or identity validation pass signal corresponding to voice prompted file.
As shown in Fig. 2 the system includes：High-definition image collecting device, by brightness detection unit, shooting unit, recording
Unit and control unit composition, are arranged on above POS, for being shot to the crowd of queuing checkout to obtain high definition crowd
Image, high-definition image collecting device are additionally operable to record customer payment video；Face detection equipment, respectively with SD storage devices and height
Clear image capture device connection, for receiving high definition crowd image and preset reference face contour, taken turns based on preset reference face
Exterior feature matches multiple facial subgraphs in high definition crowd's image.
The system includes：LCD display device, it is connected with face detection equipment to receive and show multiple facial subgraphs
Picture, LCD display device also carry touch-screen, so that based on the input of cashier, selection target face is sub from multiple facial subgraphs
Image, LCD display device are additionally operable to display text prompt corresponding with identity validation failure signal or identity validation pass signal
Information.
The system includes：Geometrical correction device, it is connected respectively with face detection equipment and LCD display device, receives mesh
Mark facial subgraph and geometric correction processing is carried out to target face subgraph to obtain geometric correction image；Image rotation is set
It is standby, it is connected with geometrical correction device to receive geometric correction image, image rotation processing is carried out to geometric correction image to obtain
Rotate image；Image translation device, it is connected with image orbiting facility to receive rotation image, image translation is carried out to rotation image
Handle to obtain displacement images.
The system includes：Image segmentation apparatus, it is connected respectively with SD storage devices and image translation device, for receiving
Pre-set image block size and displacement images, displacement images are split to obtain the segmentation figure picture of pre-set image block size；Directly
Side's figure equalization equipment, is connected with image segmentation apparatus, for receiving segmentation figure picture and carrying out histogram equalization to segmentation figure picture
Change is handled, to obtain the grey level histogram of segmentation figure picture；Gaussian smoothing filter equipment, it is connected, uses with histogram equalization equipment
In receiving grey level histogram and carrying out Gaussian smoothing filter processing to grey level histogram, to obtain images to be recognized.
The system includes：SD storage devices are big for having prestored preset reference face contour and pre-set image block
It is small, it is additionally operable to prestore preset reference eye profile, preset reference nasal contours and preset reference mouth profile；Fingerprint connects
Receiving unit, for gathering the finger print information of customer；Fingerprint matching device, respectively with fingerprint receiving device and the finger print data of distal end
Storehouse connects, and fingerprint database has prestored everyone fingerprint characteristic, the finger print information based on the output of fingerprint receiving device
The fingerprint characteristic of matching is found in fingerprint database, and piece identity corresponding to the fingerprint characteristic of matching is defeated as confirmation identity
Go out.
The system includes：MSP430 single-chip microcomputers, respectively with LCD display device, characteristic matching equipment, fingerprint receiving device
Connected with fingerprint matching device, when receiving identification identity at characteristic matching equipment, start to the customer currently to settle accounts and refer to
To receive confirmation identity, the customer currently to settle accounts is in the crowd of queuing checkout for line receiving device and fingerprint matching device, when
When identification identity is with confirming that identity is consistent, identification identity and cashier are passed through to the gold of the touch-screen input of LCD display device
Specified number evidence is sent collectively to the payment devices of distal end to complete to pay, while sends and confirm to E-mail address corresponding to identification identity
Mail, confirm that mail includes customer payment video.
Wherein, preset reference face contour presets figure to carry out the figure that contours extract obtains to benchmark face-image
As block size elects the pixel of 45 pixels × 50 as；Preset reference eye profile obtains to carry out contours extract to benchmark eyes image
Figure, preset reference nasal contours are to carry out the figure that obtains of contours extract, preset reference mouth to benchmark nose image
Profile is carries out the figure that obtains of contours extract to benchmark mouth image；MSP430 single-chip microcomputers do not connect after the first preset time
When receiving identification identity, identity validation failure signal is sent, MSP430 single-chip microcomputers do not receive confirmation after the second preset time
During identity, identity validation failure signal is sent, MSP430 single-chip microcomputers send body when identifying identity with confirming that identity is inconsistent
Part confirms failure signal, and MSP430 single-chip microcomputers send identity validation pass signal when identifying identity with confirming that identity is consistent.
Alternatively, in the system：GPRS communication equipments are arranged on the housing of POS；MSP430 single-chip microcomputers and spy
Sign matching unit, fingerprint receiving device and fingerprint matching device are integrated on one piece of surface-mounted integrated circuit；Surface-mounted integrated circuit is arranged on
In control box below POS；And MSP430 single-chip microcomputers internal memory can be used to replace SD storage devices.
In addition, the abbreviation of general packet radio service technology (General Packet Radio Service), he is GSM
A kind of available mobile data services of mobile phone user.GPRS can say be GSM continuity.GPRS continuously passes with conventional in channel
Defeated mode is different, is to be transmitted with package (Packet) formula, therefore the expense that user is born is with its data transmission list
Position calculates, not using its whole channel, in theory inexpensively.GPRS transmission rate can be promoted to 56 even 114Kbps.
GPRS is often described as " 2.5G ", that is to say, that this technology is located at the second generation (2G) and the third generation (3G) is mobile
Between mechanics of communication.He is by using untapped TDMA channels in GSM network, there is provided the data transfer of middling speed.GPRS breaks through
GSM nets can only provide the mode of thinking of circuit switching, only by increasing corresponding functional entity and to existing base station system
Part transformation is carried out to realize packet switch, the input of this transformation is comparatively and little, but obtained user data rate
It is considerable.Moreover, because no longer needing intermediary's converter required for existing wireless application, connection and transmission all can
It is more convenient easy.In this way, user can both connect to the internet, the interactive communications such as video conference are participated in, and in same video signal net
The user of (VRN) on network, it might even be possible to without by dialling up on the telephone, and continue and network connection.
For the communication mode of GPRS packet switches in the communication mode of packet switch, data are divided into the bag of certain length
(packet), each wrap before have a packets headers (address mark therein indicates the packet is sent to where).Data transmit it
It is preceding and channel need not be allocated in advance, establish connection.But when each packet reaches, the information in datagram header
(such as destination address), an available channel resource is found temporarily and sends the datagram.In this transmission mode, number
According to the side's of sending and receiving cochannel between there is no the occupancy relation of fixation, channel resource can be regarded as being total to by all users
Enjoy use.Because data service all shows a kind of paroxysmal business characteristic in most cases, to channel width
Changes in demand is larger, therefore can better profit from channel resource using packet mode progress data transmission.Such as one entered
The user that row WWW is browsed, the most of the time is in browse state, and the time for being really used for data transmission only accounts for very little ratio.
In this case according to the mode of fixed busy channel, it will cause the larger wasting of resources.
Using the automation facial-recognition security systems of the present invention, precision is paid for face recognition payment system in the prior art
Not high technical problem, first, structure improvement is carried out to facial feature recognition mechanism, improves the reliable of facial characteristics identification itself
Property, secondly, introduce fingerprinting mechanism is further confirmed to facial recognition result, in addition, also increasing in certification link
Customer's selection course of cashier is added, so as to provide help to improving payment system precision in all fields.
It is understood that although the present invention is disclosed as above with preferred embodiment, but above-described embodiment and it is not used to
Limit the present invention.For any those skilled in the art, without departing from the scope of the technical proposal of the invention,
Many possible changes and modifications are all made to technical solution of the present invention using the technology contents of the disclosure above, or are revised as
With the equivalent embodiment of change.Therefore, every content without departing from technical solution of the present invention, the technical spirit pair according to the present invention
Any simple modifications, equivalents, and modifications made for any of the above embodiments, still fall within the scope of technical solution of the present invention protection
It is interior.
Claims (5)
1. one kind automation facial-recognition security systems, it is characterised in that the system includes：
GPRS communication equipments, the GPRS communication equipments are used to establish characteristic matching equipment and distal end by GPRS communication links
Connection between face recognition data storehouse, it is additionally operable to establish the finger of fingerprint matching device and distal end by the GPRS communication links
Connection between line database；
Two-way speaker, the two-way speaker are connected with MSP430 single-chip microcomputers, are unsuccessfully believed with identity validation for playing
Number or identity validation pass signal corresponding to voice prompted file；
Main control device；
Facial recognition device, the facial recognition device and the GPRS communication equipments cooperating, for based on custom image
Confirm customer identification, main control device is set with the GPRS communication equipments, the two-way speaker and the face recognition respectively
Standby connection, for determining to pay strategy based on customer identification, while it is true also to control the two-way speaker to play customer identification
Recognize result；
High-definition image collecting device, it is arranged on above POS, for being shot to the crowd of queuing checkout to obtain high definition people
Group's image, high-definition image collecting device are additionally operable to record customer payment video；
Face detection equipment, it is connected respectively with SD storage devices and high-definition image collecting device, for receiving high definition crowd's image
With preset reference face contour, multiple facial subgraphs are matched in high definition crowd's image based on preset reference face contour；
LCD display device, it is connected with face detection equipment to receive and show multiple facial subgraphs, LCD display device also band
Have touch-screen, with based on the input of cashier from multiple facial subgraphs selection target face subgraph, LCD display device is also
For showing text prompt information corresponding with identity validation failure signal or identity validation pass signal；
Geometrical correction device, it is connected respectively with face detection equipment and LCD display device, receives target face subgraph and to mesh
Mark facial subgraph and carry out geometric correction processing to obtain geometric correction image；
Image orbiting facility, it is connected with geometrical correction device to receive geometric correction image, image is carried out to geometric correction image
Rotation processing is to obtain rotation image；
Image translation device, it is connected with image orbiting facility to receive rotation image, image translation processing is carried out to rotation image
To obtain displacement images；
Image segmentation apparatus, be connected respectively with SD storage devices and image translation device, for receive pre-set image block size and
Displacement images, displacement images are split to obtain the segmentation figure picture of pre-set image block size, described image splitting equipment bag
Include：Eye splitting equipment, forehead splitting equipment, nose splitting equipment, mouth splitting equipment, chin splitting equipment；Wherein：
The eye splitting equipment, it is connected respectively with SD storage devices and Gaussian smoothing filter equipment to receive preset reference eye
Profile and images to be recognized, eye subgraph is partitioned into images to be recognized based on preset reference eye profile；
The forehead splitting equipment, it is connected respectively with eye splitting equipment and Gaussian smoothing filter equipment to receive eye subgraph
And images to be recognized, the position based on eye subgraph in images to be recognized, by images to be recognized more than eye subgraph
Image section split to obtain forehead subgraph；
The nose splitting equipment, it is connected respectively with SD storage devices and Gaussian smoothing filter equipment to receive preset reference nose
Profile and images to be recognized, nose subgraph is partitioned into images to be recognized based on preset reference nasal contours；
The mouth splitting equipment, it is connected respectively with SD storage devices and Gaussian smoothing filter equipment to receive preset reference mouth
Profile and images to be recognized, mouth subgraph is partitioned into images to be recognized based on preset reference mouth profile；
The chin splitting equipment, it is connected respectively with mouth splitting equipment and Gaussian smoothing filter equipment to receive mouth subgraph
And images to be recognized, the position based on mouth subgraph in images to be recognized, by images to be recognized below mouth subgraph
Image section split to obtain chin subgraph；
Signature analysis equipment, respectively with eye splitting equipment, forehead splitting equipment, nose splitting equipment, mouth splitting equipment and
Chin splitting equipment connects, and determines that eye feature point in eye subgraph is located at the coordinate in images to be recognized to be sat as eye
Mark output, determine that forehead characteristic point in forehead subgraph be located at the coordinate in images to be recognized using as the output of forehead coordinate, really
Coordinate that nose characteristic point in nose subgraph is located in images to be recognized is determined to be exported as nose coordinate, determines mouth subgraph
Mouth feature point be located at coordinate in images to be recognized to export as mouth coordinate as in, determines time Bart in chin subgraph
Coordinate of the sign point in images to be recognized is to be used as chin coordinate to export；
Characteristic matching equipment, respectively the face recognition data storehouse with signature analysis equipment and distal end be connected, face recognition data storehouse
Coordinate of each characteristic point of everyone face-image in the face-image of place is prestored, feature based analysis is set
Eye coordinate, forehead coordinate, nose coordinate, mouth coordinate and the chin coordinate of standby output are found with treating in face recognition data storehouse
Images match degree highest face-image is identified, and will personage's body corresponding with images to be recognized matching degree highest face-image
Part is as identification identity output；
Histogram equalization equipment, is connected with image segmentation apparatus, for receiving segmentation figure picture and carrying out Nogata to segmentation figure picture
Figure equalization processing, to obtain the grey level histogram of segmentation figure picture；
Gaussian smoothing filter equipment, it is connected with histogram equalization equipment, for receiving grey level histogram and to grey level histogram
Gaussian smoothing filter processing is carried out, to obtain images to be recognized；
SD storage devices, for having prestored preset reference face contour and pre-set image block size, it is additionally operable to prestore
Preset reference eye profile, preset reference nasal contours and preset reference mouth profile；
Fingerprint receiving device, for gathering the finger print information of customer；
Fingerprint matching device, respectively the fingerprint database with fingerprint receiving device and distal end be connected, fingerprint database prestores
Everyone fingerprint characteristic, the finger print information based on the output of fingerprint receiving device find the fingerprint of matching in fingerprint database
Feature, and using piece identity corresponding to the fingerprint characteristic of matching as confirmation identity output；
MSP430 single-chip microcomputers, connect respectively with LCD display device, characteristic matching equipment, fingerprint receiving device and fingerprint matching device
Connect, when receiving identification identity at characteristic matching equipment, start fingerprint receiving device and fingerprint to the customer currently to settle accounts
To receive confirmation identity, the customer currently to settle accounts is in the crowd of queuing checkout matching unit, when identification identity is with confirming body
When part is consistent, it will identify that the value data that identity and cashier are inputted by the touch-screen of LCD display device is sent collectively to
The payment devices of distal end send to E-mail address corresponding to identification identity to complete to pay and confirm mail, confirm in mail
Including customer payment video；
Wherein, preset reference face contour is to carry out the figure that obtains of contours extract, pre-set image block to benchmark face-image
Size elects the pixel of 45 pixels × 50 as；
Wherein, preset reference eye profile is to carry out the figure that obtains of contours extract, preset reference nose to benchmark eyes image
For contouring to carry out the figure that contours extract obtains to benchmark nose image, preset reference mouth profile is to benchmark mouth figure
As the figure for carrying out contours extract and obtaining；
Wherein, when MSP430 single-chip microcomputers do not receive identification identity after the first preset time, identity validation failure signal is sent,
When MSP430 single-chip microcomputers do not receive confirmation identity after the second preset time, identity validation failure signal is sent, MSP430 is mono-
Piece machine sends identity validation failure signal, MSP430 single-chip microcomputers are in identification body when identifying identity with confirming that identity is inconsistent
When part is with confirming that identity is consistent, identity validation pass signal is sent.
2. facial-recognition security systems are automated as claimed in claim 1, it is characterised in that：
GPRS communication equipments are arranged on the housing of POS.
3. automation facial-recognition security systems as claimed in claim 1, it is characterised in that：
MSP430 single-chip microcomputers are integrated in one piece of surface-mounted integrated circuit with characteristic matching equipment, fingerprint receiving device and fingerprint matching device
On.
4. automation facial-recognition security systems as claimed in claim 3, it is characterised in that：
Surface-mounted integrated circuit is arranged in the control box below POS.
5. automation facial-recognition security systems as claimed in claim 1, it is characterised in that：
SD storage devices are replaced using MSP430 single-chip microcomputers internal memory.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610201829.7A CN105913260B (en) | 2016-04-01 | 2016-04-01 | Automate facial-recognition security systems |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610201829.7A CN105913260B (en) | 2016-04-01 | 2016-04-01 | Automate facial-recognition security systems |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN105913260A CN105913260A (en) | 2016-08-31 |
| CN105913260B true CN105913260B (en) | 2018-03-27 |
Family
ID=56744568
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201610201829.7A Expired - Fee Related CN105913260B (en) | 2016-04-01 | 2016-04-01 | Automate facial-recognition security systems |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN105913260B (en) |
Families Citing this family (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108197445A (en) * | 2016-10-11 | 2018-06-22 | 新疆信息产业有限责任公司 | Computer user's identity recognition device and application method |
| CN111553313B (en) * | 2020-05-13 | 2021-04-13 | 广州喜淘信息科技有限公司 | Face matching system using cloud storage and corresponding terminal |
Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN204680060U (en) * | 2015-04-13 | 2015-09-30 | 济南舜软信息科技有限公司 | The identification of Network Based and biological characteristic and payment mechanism |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR100438841B1 (en) * | 2002-04-23 | 2004-07-05 | 삼성전자주식회사 | Method for verifying users and updating the data base, and face verification system using thereof |
-
2016
- 2016-04-01 CN CN201610201829.7A patent/CN105913260B/en not_active Expired - Fee Related
Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN204680060U (en) * | 2015-04-13 | 2015-09-30 | 济南舜软信息科技有限公司 | The identification of Network Based and biological characteristic and payment mechanism |
Also Published As
| Publication number | Publication date |
|---|---|
| CN105913260A (en) | 2016-08-31 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| WO2020135096A1 (en) | Method and device for determining operation based on facial expression groups, and electronic device | |
| CN105681351B (en) | Verification method and system, user equipment, server based on interactive operation | |
| US20150120557A1 (en) | Fingerprint payment method and related device and system | |
| CN106408413A (en) | Multi-cycle installment decision making method and system | |
| CN105809415A (en) | Human face recognition based check-in system, method and device | |
| CN108922074A (en) | Without card withdrawal method, apparatus, computer equipment and storage medium | |
| CN103577801A (en) | Quality metrics method and system for biometric authentication | |
| CN108304827A (en) | Automate facial-recognition security systems | |
| CN107194833A (en) | Hotel management method, system and storage medium based on recognition of face | |
| EP3905174A1 (en) | Method and device for authenticating near-field information, electronic apparatus, and computer storage medium | |
| CN106941503A (en) | Bank data collection and authentication method and system based on smart mobile phone | |
| CN105913264B (en) | Face payment mechanism based on the identification of fingerprint secondary identities | |
| CN110288755A (en) | The invoice method of inspection, server and storage medium based on text identification | |
| CN106384146A (en) | Financial IC card, payment system and payment method | |
| CN105678290A (en) | Face payment platform based on image detection | |
| CN109919607A (en) | Transfer benefit method and device and electronic equipment based on offline code by bus | |
| CN105913260B (en) | Automate facial-recognition security systems | |
| CN105913241A (en) | Application method of customer authentication system based on image identification | |
| CN105894261A (en) | Usage method of cashier desk face payment system | |
| CN107025558A (en) | A kind of transaction system and transaction processing method | |
| CN102568125A (en) | System and method for performing credit card consumption through fingerprint identification | |
| CN105913262B (en) | Facial payment system based on bluetooth assistant authentification | |
| TWM592131U (en) | Characteristic encoding system and internet bank service system applying the same | |
| CN107742214A (en) | A kind of method of payment and payment system based on face recognition | |
| CN108009921A (en) | Option trading systems based on computer vision and fingerprint recognition |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| CB03 | Change of inventor or designer information |
Inventor after: Huang Zhenqiang Inventor before: Zhang Haidong |
|
| CB03 | Change of inventor or designer information | ||
| TA01 | Transfer of patent application right |
Effective date of registration: 20180228 Address after: 210000 the 4 layer of Zhongshan North Road 99, Drum Tower District, Nanjing, Jiangsu Applicant after: NANJING RUICHI DINGXIN TECHNOLOGY CO.,LTD. Address before: 210029 Nanjing Yisheng facial recognition Co., Ltd., No. 18, Guangzhou Road, Nanjing City, Jiangsu Province Applicant before: Zhang Haidong |
|
| TA01 | Transfer of patent application right | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| TR01 | Transfer of patent right | ||
| TR01 | Transfer of patent right |
Effective date of registration: 20211125 Address after: 210000 Room 501, unit 3, No. 5, Dinghuaimen, Gulou District, Nanjing, Jiangsu Province Patentee after: Huang Zhenqiang Address before: 210000 4, Zhongshan North Road 99, Gulou District, Nanjing, Jiangsu. Patentee before: NANJING RUICHI DINGXIN TECHNOLOGY CO.,LTD. |
|
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20180327 |
|
| CF01 | Termination of patent right due to non-payment of annual fee |