CN105678290A - Face payment platform based on image detection - Google Patents
Face payment platform based on image detection Download PDFInfo
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- CN105678290A CN105678290A CN201610204736.XA CN201610204736A CN105678290A CN 105678290 A CN105678290 A CN 105678290A CN 201610204736 A CN201610204736 A CN 201610204736A CN 105678290 A CN105678290 A CN 105678290A
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- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
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Abstract
The invention relates to a face payment platform based on image detection. The face payment platform comprises a face identification device, a control device, a payment device and a display device. The face identification device is used for detecting an image of a customer to determine the identity of the customer; the control device is connected with the face identification device, the payment device and the display device, and is used for determining payment operation of the payment device based on the identity of the customer; and the display device is used for displaying the identification result of the face identification device. The face payment platform can provide convenience for money collection work of a shop, and prevents tedious manual operation.
Description
Technical field
The present invention relates to field of image detection, particularly relate to a kind of facial payment platform based on image detection.
Background technology
Traditional face recognition technology is mainly based upon the recognition of face of visible images, and this is also the recognition method that people are familiar with, the development history of existing more than 30 year. But this mode has the defect being difficult to overcome, especially when ambient lighting changes, recognition effect can sharply decline, it is impossible to meets the needs of real system. The scheme solving lighting issues has 3-D view recognition of face and thermal imaging recognition of face. But both technology are also far immature, and recognition effect is unsatisfactory.
The a solution developed rapidly is based on the multiple light courcess face recognition technology of actively near-infrared image. He can overcome the impact that light changes, and has been achieved for the recognition performance of brilliance, and the integral systematicness in precision, stability and speed can exceed that 3-D view recognition of face. This technology quickly grew at nearly 1 year, made face recognition technology move towards practical gradually.
Recognition of face payment is an important applied field of recognition of face. Under tradition charging mode, customer need provides bank card to cashier, and bank card is swiped the card operation by cashier according to toll amount, and is inputted corresponding bank card password by client, payment system can enter and carry out operation of remitting money in clients account, and client also needs to sign to confirm subsequently. Whole process needs the seamless cooperation of lasting manual operation and client cashier, it is evident that operates excessively loaded down with trivial details, and expends the plenty of time. And recognition of face pay can Direct Recognition client's facial characteristics, confirm customer identification, it is not necessary to client operating, namely can complete the process of remitting money.
But, it is be made directly to remit money owing to recognition of face pays, therefore, its security performance is particularly critical. Existing recognition of face pays and determines that namely face feature remits money after meeting, do not account for the situation of face feature identification mistake, simultaneously, the client of queuing checkout is a lot, it is easy to non-checkout client is carried out facial characteristics identification, and, the existing recognition of face structural redundancy of mechanism own is high, is also improved precision and optimizes the space of function.
Accordingly, it would be desirable to a kind of new facial payment platform, it is possible to solve above-mentioned technical problem, replacing loaded down with trivial details manual operation, while improving shopper checkout efficiency, improving payments mechanism on the whole, it is ensured that the account number safety of each client.
Summary of the invention
In order to solve the problems referred to above, the invention provides a kind of facial payment platform based on image detection, secondary identities authenticating device can be increased, after facial recognition identity, use secondary identities authenticating device to carry out further identity validation, provide checkout client to select pattern for cashier simultaneously, the situation that other clients are settled accounts by mistake is avoided to occur, pay it addition, also optimize existing facial recognition, it is ensured that the accuracy of facial recognition.
According to an aspect of the present invention, provide a kind of facial payment platform based on image detection, described platform includes facial recognition device, control equipment, payment devices and display device, facial recognition device is for detecting to determine customer identification to custom image, control equipment is connected with facial recognition device, payment devices and display device respectively, for determining the delivery operation of payment devices based on customer identification, display device is for showing the recognition result of facial recognition device.
More specifically, in the described facial payment platform based on image detection, including: two-way speaker, it is connected with dsp processor, for playing the voice prompted file corresponding with identity validation failure signal or identity validation pass signal; Payment devices, is connected with dsp processor, is used for receiving identity information and payment to complete to pay; Flash memory device, for having prestored preset reference face contour, pre-set image average, pre-set image variance and presetted pixel block size, it is additionally operable to prestore default supercilium thickness weighted value, presets supercilium flexibility weighted value, presets mouth thickness weighted value, presets eye opening degree weighted value, preset reference supercilium profile, preset reference mouth profile and preset reference eye profile; Wireless Telecom Equipment, is used for the connection being set up by wireless communication link between the face recognition data storehouse of characteristic matching equipment and far-end, is additionally operable to set up the connection between voice match equipment and the speech database of far-end by wireless communication link; Mike, for gathering the voice messaging of client; Voice match equipment, it is connected with the speech database of mike and far-end respectively, speech database has prestored everyone phonetic feature, voice messaging based on mike output finds the phonetic feature mated at speech database, and using piece identity corresponding for the phonetic feature of coupling as confirming identity output; CMOS visual sensing equipment, is arranged on above cashier, for shooting to obtain high definition crowd's image to the crowd of queuing checkout; Face detection equipment, is connected with flash memory device and CMOS visual sensing equipment respectively, is used for receiving high definition crowd's image and preset reference face contour, matches multiple face subimage based on preset reference face contour in high definition crowd's image; LCD display device, the equipment that detects with face is connected to receive and shows multiple face subimage, and LCD display device is also with touch screen, to select target face subimage based on the input of cashier from multiple face subimages; Mean filter equipment, is connected with LCD display device and face detection equipment respectively, is used for receiving target face subimage and target face subimage being carried out mean filter process, to obtain the mean filter image of correspondence; Histogram equalization equipment, is connected with mean filter equipment, is used for receiving mean filter image and mean filter image being carried out histogram equalization process, to obtain the grey level histogram of mean filter image;Illumination compensation equipment, it is connected with flash memory device and histogram equalization equipment respectively, for receiving grey level histogram, pre-set image average and pre-set image variance, grey level histogram is carried out image correction so that the image average of image is equal to pre-set image variance equal to the image variance of image after pre-set image average and correction after revising, normalized equipment, it is connected with flash memory device and illumination compensation equipment respectively, for image after receiving presetted pixel block size and revising, image is oriented the position of right eye in face after correction, with right eye position for datum mark, after correction, image marks off the image to be identified with presetted pixel block size, supercilium splitting equipment, is connected with flash memory device and normalized equipment to receive preset reference supercilium profile and image to be identified respectively, is partitioned into supercilium subimage based on preset reference supercilium profile in image to be identified, mouth splitting equipment, is connected with flash memory device and normalized equipment to receive preset reference mouth profile and image to be identified respectively, is partitioned into mouth subimage based on preset reference mouth profile in image to be identified, eye splitting equipment, is connected with flash memory device and normalized equipment to receive preset reference eye profile and image to be identified respectively, is partitioned into eye subimage based on preset reference eye profile in image to be identified, feature analysis equipment, it is connected with supercilium splitting equipment, mouth splitting equipment and eye splitting equipment respectively, determine supercilium thickness and supercilium flexibility based on supercilium subimage, determine mouth thickness based on mouth subimage, determine eye opening degree based on eye subimage, characteristic matching equipment, respectively with flash memory device, the face recognition data storehouse of feature analysis equipment and far-end connects, face recognition data storehouse has prestored the supercilium thickness of everyone face-image, supercilium flexibility, mouth thickness and eye opening degree, the supercilium thickness of everyone face-image prestored with face recognition data storehouse by the supercilium thickness that feature analysis equipment exports carries out mating to obtain supercilium thickness matching degree, the supercilium flexibility of everyone face-image supercilium flexibility that feature analysis equipment exports prestored with face recognition data storehouse carries out mating to obtain supercilium flexibility matching degree, the mouth thickness of everyone face-image prestored with face recognition data storehouse by the mouth thickness that feature analysis equipment exports carries out mating to obtain mouth thickness matching degree, the eye opening degree of everyone face-image prestored with face recognition data storehouse by the eye opening degree that feature analysis equipment exports carries out mating to obtain eye opening degree matching degree, based on supercilium thickness matching degree, preset supercilium thickness weighted value, supercilium flexibility matching degree, preset supercilium flexibility weighted value, mouth thickness matching degree, preset mouth thickness weighted value, eye opening degree matching degree and default eye opening degree weighted value determine the matching degree of everyone face-image that image to be identified and face recognition data storehouse prestore, using piece identity corresponding for face-image the highest for matching degree as identifying identity output, dsp processor, respectively with LCD display device, characteristic matching equipment, mike and voice match equipment connect, when receiving identification identity from characteristic matching equipment, client to current checkout starts mike and voice match equipment to receive confirmation identity, the client of current checkout is in the crowd of queuing checkout, when identifying that identity is consistent with confirmation identity, to identify that identity and cashier are sent collectively to the payment devices of far-end to complete to pay by the value data that the touch screen of LCD display device inputs, simultaneously to the E-mail address transmission confirmation mail identifying that identity is corresponding, confirm that mail includes customer payment video,Wherein, when dsp processor does not receive identification identity after the first Preset Time, send identity validation failure signal, when dsp processor does not receive confirmation identity after the second Preset Time, sending identity validation failure signal, dsp processor, when identifying that identity is inconsistent with confirmation identity, sends identity validation failure signal, dsp processor, when identifying identity and confirmation identity is consistent, sends identity validation pass signal; Wherein, LCD display device is additionally operable to the text prompt information that display is corresponding with identity validation failure signal or identity validation pass signal.
More specifically, in the described facial payment platform based on image detection: CMOS visual sensing equipment is additionally operable to record customer payment video.
More specifically, in the described facial payment platform based on image detection: preset reference face contour is that benchmark face-image is carried out the figure that contours extract obtains, pre-set image average elects 140 as, and pre-set image variance elects 50 as, and presetted pixel block size elects 60 pixel × 65 pixels as.
More specifically, in the described facial payment platform based on image detection: preset reference supercilium profile is that benchmark supercilium image is carried out the figure that contours extract obtains, preset reference mouth profile is that benchmark mouth image carries out the figure that contours extract obtains, and preset reference eye profile is that benchmark eyes image is carried out the figure that contours extract obtains.
More specifically, in the described facial payment platform based on image detection: LCD display device is positioned at above cashier.
Accompanying drawing explanation
Below with reference to accompanying drawing, embodiment of the present invention are described, wherein:
Fig. 1 is the block diagram of the facial payment platform based on image detection illustrated according to an embodiment of the present invention.
Accompanying drawing labelling: 1 facial recognition device; 2 control equipment; 3 payment devices; 4 display devices
Detailed description of the invention
Below with reference to accompanying drawings the embodiment based on the facial payment platform of image detection of the present invention is described in detail.
Technically, face identification system mainly includes four ingredients, is respectively as follows: man face image acquiring and detection, facial image pretreatment, facial image feature extraction and coupling and identifies.
Man face image acquiring: different facial images can be transferred through pick-up lens and collects, the aspect such as such as still image, dynamic image, different positions, different expressions can well be gathered. When user is in the coverage of collecting device, collecting device can search for and shoot the facial image of user automatically.
Face datection: Face datection is mainly used in the pretreatment of recognition of face in practice, namely accurate calibration goes out position and the size of face in the picture. The pattern feature comprised in facial image is very abundant, such as histogram feature, color characteristic, template characteristic, architectural feature and Haar feature etc. Face datection is exactly that the information that this is wherein useful is picked out, and utilizes these features to realize Face datection.
The method for detecting human face of main flow adopts Adaboost learning algorithm based on features above, and Adaboost algorithm is a kind of method for classifying, and it is combined the sorting technique that some are more weak, the very strong sorting technique that combination makes new advances.
Face datection process use Adaboost algorithm pick out some rectangular characteristic (Weak Classifier) that can represent face, according to the mode of Nearest Neighbor with Weighted Voting, Weak Classifier is configured to a strong classifier, some strong classifiers that training obtains are composed in series the cascade filtering of a cascade structure again, are effectively improved the detection speed of grader.
Facial image pretreatment: the Image semantic classification for face is based on Face datection result, and image processes and finally serves the process of feature extraction.The original image that system obtains, owing to being subject to restriction and the random disturbances of various condition, tends not to direct use, it is necessary to it is carried out the Image semantic classification such as gray correction, noise filtering by the commitment at image procossing. For facial image, its preprocessing process mainly includes the light compensation of facial image, greyscale transformation, histogram equalization, normalization, geometric correction, filtering and sharpening etc.
Facial image feature extraction: the spendable feature of face identification system is generally divided into visual signature, pixels statistics feature, facial image conversion coefficient feature, facial image algebraic characteristic etc. Face characteristic extracts what some feature being aiming at face carried out. Face characteristic extracts, and characterizes also referred to as face, and it is the process that face carries out feature modeling. The method that face characteristic extracts is summed up and is divided into two big classes: a kind of characterizing method being based on knowledge; Another is based on the characterizing method of algebraic characteristic or statistical learning.
Knowledge based engineering characterizing method mainly obtains, according to the shape description of human face and the range performance between them, the characteristic contributing to face classification, and its characteristic component generally includes the Euclidean distance between characteristic point, curvature and angle etc. Face is made up of the local such as eyes, nose, mouth, chin, to these local and the geometric description of structural relation between them, can as the key character identifying face, and these features are referred to as geometric properties. Knowledge based engineering face characterizes and mainly includes the method based on geometric properties and template matching method.
Facial image coupling and identification: the characteristic of the facial image of extraction scans for mating with the feature templates of storage in data base, by setting a threshold value, when similarity exceedes this threshold value, then result output coupling obtained. Recognition of face is exactly compared with the skin detection obtained by face characteristic to be identified, according to similarity degree, the identity information of face is judged. This process is divided into again two classes: a class is to confirm, is the process that image compares that carries out one to one, and another kind of is identification, is the one-to-many process that carries out images match contrast.
It is by face recognition application to payment platform that recognition of face pays, and by customer face feature extraction, confirms customer identification, and coordinates the spending amount that cashier provides to complete customer payment process. Whole payment process automaticity is high, and artificial interference link is few, and for the time period too much queuing checkout client, its effect is especially pronounced.
But, existing recognition of face payments mechanism there is also several drawback. First, identify that payment link is excessively simple and crude, lack the secondary authentication mechanism of necessity; Second, when queuing checkout client is too much, it is possible to non-checkout client is carried out facial recognition and payment; 3rd, recognition of face itself still has the space improving performance.
In order to overcome above-mentioned deficiency, the present invention has built a kind of facial payment platform based on image detection, existing recognition of face payments mechanism is improved, increase assistant authentification means and client selects link, and the mode of facial features localization is optimized, thus improve the safety and reliability of face payment platform comprehensively.
Fig. 1 is the block diagram of the facial payment platform based on image detection illustrated according to an embodiment of the present invention, described platform includes facial recognition device, control equipment, payment devices and display device, facial recognition device is for detecting to determine customer identification to custom image, control equipment is connected with facial recognition device, payment devices and display device respectively, for determining the delivery operation of payment devices based on customer identification, display device is for showing the recognition result of facial recognition device.
Then, continue the concrete structure based on the facial payment platform of image detection of the present invention is further detailed.
Described platform includes: two-way speaker, is connected with dsp processor, for playing the voice prompted file corresponding with identity validation failure signal or identity validation pass signal; Payment devices, is connected with dsp processor, is used for receiving identity information and payment to complete to pay; Flash memory device, for having prestored preset reference face contour, pre-set image average, pre-set image variance and presetted pixel block size, it is additionally operable to prestore default supercilium thickness weighted value, presets supercilium flexibility weighted value, presets mouth thickness weighted value, presets eye opening degree weighted value, preset reference supercilium profile, preset reference mouth profile and preset reference eye profile.
Described platform includes: Wireless Telecom Equipment, for being set up the connection between the face recognition data storehouse of characteristic matching equipment and far-end by wireless communication link, it is additionally operable to set up the connection between voice match equipment and the speech database of far-end by wireless communication link; Mike, for gathering the voice messaging of client; Voice match equipment, it is connected with the speech database of mike and far-end respectively, speech database has prestored everyone phonetic feature, voice messaging based on mike output finds the phonetic feature mated at speech database, and using piece identity corresponding for the phonetic feature of coupling as confirming identity output.
Described platform includes: CMOS visual sensing equipment, is arranged on above cashier, for shooting to obtain high definition crowd's image to the crowd of queuing checkout; Face detection equipment, is connected with flash memory device and CMOS visual sensing equipment respectively, is used for receiving high definition crowd's image and preset reference face contour, matches multiple face subimage based on preset reference face contour in high definition crowd's image; LCD display device, the equipment that detects with face is connected to receive and shows multiple face subimage, and LCD display device is also with touch screen, to select target face subimage based on the input of cashier from multiple face subimages.
Described platform includes: mean filter equipment, is connected with LCD display device and face detection equipment respectively, is used for receiving target face subimage and target face subimage being carried out mean filter process, to obtain the mean filter image of correspondence; Histogram equalization equipment, is connected with mean filter equipment, is used for receiving mean filter image and mean filter image being carried out histogram equalization process, to obtain the grey level histogram of mean filter image; Illumination compensation equipment, it is connected with flash memory device and histogram equalization equipment respectively, for receiving grey level histogram, pre-set image average and pre-set image variance, grey level histogram is carried out image correction so that the image average of image is equal to pre-set image variance equal to the image variance of image after pre-set image average and correction after revising.
Described platform includes: normalized equipment, it is connected with flash memory device and illumination compensation equipment respectively, for image after receiving presetted pixel block size and revising, image is oriented the position of right eye in face after correction, with right eye position for datum mark, after correction, image marks off the image to be identified with presetted pixel block size; Supercilium splitting equipment, is connected with flash memory device and normalized equipment to receive preset reference supercilium profile and image to be identified respectively, is partitioned into supercilium subimage based on preset reference supercilium profile in image to be identified;Mouth splitting equipment, is connected with flash memory device and normalized equipment to receive preset reference mouth profile and image to be identified respectively, is partitioned into mouth subimage based on preset reference mouth profile in image to be identified.
Described platform includes: eye splitting equipment, is connected with flash memory device and normalized equipment to receive preset reference eye profile and image to be identified respectively, is partitioned into eye subimage based on preset reference eye profile in image to be identified; Feature analysis equipment, it is connected with supercilium splitting equipment, mouth splitting equipment and eye splitting equipment respectively, determine supercilium thickness and supercilium flexibility based on supercilium subimage, determine mouth thickness based on mouth subimage, determine eye opening degree based on eye subimage.
Described platform includes: characteristic matching equipment, respectively with flash memory device, the face recognition data storehouse of feature analysis equipment and far-end connects, face recognition data storehouse has prestored the supercilium thickness of everyone face-image, supercilium flexibility, mouth thickness and eye opening degree, the supercilium thickness of everyone face-image prestored with face recognition data storehouse by the supercilium thickness that feature analysis equipment exports carries out mating to obtain supercilium thickness matching degree, the supercilium flexibility of everyone face-image supercilium flexibility that feature analysis equipment exports prestored with face recognition data storehouse carries out mating to obtain supercilium flexibility matching degree, the mouth thickness of everyone face-image prestored with face recognition data storehouse by the mouth thickness that feature analysis equipment exports carries out mating to obtain mouth thickness matching degree, the eye opening degree of everyone face-image prestored with face recognition data storehouse by the eye opening degree that feature analysis equipment exports carries out mating to obtain eye opening degree matching degree, based on supercilium thickness matching degree, preset supercilium thickness weighted value, supercilium flexibility matching degree, preset supercilium flexibility weighted value, mouth thickness matching degree, preset mouth thickness weighted value, eye opening degree matching degree and default eye opening degree weighted value determine the matching degree of everyone face-image that image to be identified and face recognition data storehouse prestore, using piece identity corresponding for face-image the highest for matching degree as identifying identity output.
Described platform includes: dsp processor, respectively with LCD display device, characteristic matching equipment, mike and voice match equipment connect, when receiving identification identity from characteristic matching equipment, client to current checkout starts mike and voice match equipment to receive confirmation identity, the client of current checkout is in the crowd of queuing checkout, when identifying that identity is consistent with confirmation identity, to identify that identity and cashier are sent collectively to the payment devices of far-end to complete to pay by the value data that the touch screen of LCD display device inputs, simultaneously to the E-mail address transmission confirmation mail identifying that identity is corresponding, confirm that mail includes customer payment video.
Wherein, when dsp processor does not receive identification identity after the first Preset Time, send identity validation failure signal, when dsp processor does not receive confirmation identity after the second Preset Time, sending identity validation failure signal, dsp processor, when identifying that identity is inconsistent with confirmation identity, sends identity validation failure signal, dsp processor, when identifying identity and confirmation identity is consistent, sends identity validation pass signal.
Wherein, LCD display device is additionally operable to the text prompt information that display is corresponding with identity validation failure signal or identity validation pass signal.
Alternatively, in described platform: CMOS visual sensing equipment is additionally operable to record customer payment video; Preset reference face contour is that benchmark face-image is carried out the figure that contours extract obtains, and pre-set image average elects 140 as, and pre-set image variance elects 50 as, and presetted pixel block size elects 60 pixel × 65 pixels as; Preset reference supercilium profile is that benchmark supercilium image is carried out the figure that contours extract obtains, preset reference mouth profile is that benchmark mouth image carries out the figure that contours extract obtains, and preset reference eye profile is that benchmark eyes image is carried out the figure that contours extract obtains; And LCD display device may be located at above cashier.
It addition, dsp chip, also referred to as digital signal processor, being a kind of microprocessor being particularly suitable for carrying out Digital Signal Processing computing, it is mainly applied is realize various digital signal processing algorithm real-time.
Requirement according to Digital Signal Processing, dsp chip generally has following main feature: (1) can complete a multiplication and a sub-addition within an instruction cycle; (2) program and data space is separately, it is possible to access instruction and data simultaneously; (3) there is quick RAM in sheet, generally can pass through independent data/address bus and access in two pieces simultaneously; (4) there is low overhead or without overhead loop and the hardware supported that redirects; (5) quickly interrupt processing and Hardware I/O support; (6) there are multiple hardware address generators of operation within the monocycle; (7) can the multiple operation of executed in parallel; (8) supporting pile line operation, making fetching, decoding and execution etc. operate can Overlapped Execution.
Adopt the facial payment platform based on image detection of the present invention, for the technical problem that prior art face payments mechanism is excessively simple and crude, by increase secondary identities authentication mechanism be facial recognition to identity further confirm, neighbouring multiple custom image are provided to select the client of current checkout for cashier for cashier, particularly critical is, face feature identification pattern is carried out performance improvement, thus improve the accuracy of whole face payments mechanism.
Although it is understood that the present invention discloses as above with preferred embodiment, but above-described embodiment is not limited to the present invention. For any those of ordinary skill in the art, without departing under technical solution of the present invention ambit, all may utilize the technology contents of the disclosure above and technical solution of the present invention is made many possible variations and modification, or be revised as the Equivalent embodiments of equivalent variations. Therefore, every content without departing from technical solution of the present invention, the technical spirit of the foundation present invention, to any simple modification made for any of the above embodiments, equivalent variations and modification, all still falls within the scope of technical solution of the present invention protection.
Claims (6)
1. the facial payment platform based on image detection, described platform includes facial recognition device, control equipment, payment devices and display device, facial recognition device is for detecting to determine customer identification to custom image, control equipment is connected with facial recognition device, payment devices and display device respectively, for determining the delivery operation of payment devices based on customer identification, display device is for showing the recognition result of facial recognition device.
2. the facial payment platform based on image detection as claimed in claim 1, it is characterised in that described platform includes:
Two-way speaker, is connected with dsp processor, for playing the voice prompted file corresponding with identity validation failure signal or identity validation pass signal;
Payment devices, is connected with dsp processor, is used for receiving identity information and payment to complete to pay;
Flash memory device, for having prestored preset reference face contour, pre-set image average, pre-set image variance and presetted pixel block size, it is additionally operable to prestore default supercilium thickness weighted value, presets supercilium flexibility weighted value, presets mouth thickness weighted value, presets eye opening degree weighted value, preset reference supercilium profile, preset reference mouth profile and preset reference eye profile;
Wireless Telecom Equipment, is used for the connection being set up by wireless communication link between the face recognition data storehouse of characteristic matching equipment and far-end, is additionally operable to set up the connection between voice match equipment and the speech database of far-end by wireless communication link;
Mike, for gathering the voice messaging of client;
Voice match equipment, it is connected with the speech database of mike and far-end respectively, speech database has prestored everyone phonetic feature, voice messaging based on mike output finds the phonetic feature mated at speech database, and using piece identity corresponding for the phonetic feature of coupling as confirming identity output;
CMOS visual sensing equipment, is arranged on above cashier, for shooting to obtain high definition crowd's image to the crowd of queuing checkout;
Face detection equipment, is connected with flash memory device and CMOS visual sensing equipment respectively, is used for receiving high definition crowd's image and preset reference face contour, matches multiple face subimage based on preset reference face contour in high definition crowd's image;
LCD display device, the equipment that detects with face is connected to receive and shows multiple face subimage, and LCD display device is also with touch screen, to select target face subimage based on the input of cashier from multiple face subimages;
Mean filter equipment, is connected with LCD display device and face detection equipment respectively, is used for receiving target face subimage and target face subimage being carried out mean filter process, to obtain the mean filter image of correspondence;
Histogram equalization equipment, is connected with mean filter equipment, is used for receiving mean filter image and mean filter image being carried out histogram equalization process, to obtain the grey level histogram of mean filter image;
Illumination compensation equipment, it is connected with flash memory device and histogram equalization equipment respectively, for receiving grey level histogram, pre-set image average and pre-set image variance, grey level histogram is carried out image correction so that the image average of image is equal to pre-set image variance equal to the image variance of image after pre-set image average and correction after revising;
Normalized equipment, it is connected with flash memory device and illumination compensation equipment respectively, for image after receiving presetted pixel block size and revising, image is oriented the position of right eye in face after correction, with right eye position for datum mark, after correction, image marks off the image to be identified with presetted pixel block size;
Supercilium splitting equipment, is connected with flash memory device and normalized equipment to receive preset reference supercilium profile and image to be identified respectively, is partitioned into supercilium subimage based on preset reference supercilium profile in image to be identified;
Mouth splitting equipment, is connected with flash memory device and normalized equipment to receive preset reference mouth profile and image to be identified respectively, is partitioned into mouth subimage based on preset reference mouth profile in image to be identified;
Eye splitting equipment, is connected with flash memory device and normalized equipment to receive preset reference eye profile and image to be identified respectively, is partitioned into eye subimage based on preset reference eye profile in image to be identified;
Feature analysis equipment, it is connected with supercilium splitting equipment, mouth splitting equipment and eye splitting equipment respectively, determine supercilium thickness and supercilium flexibility based on supercilium subimage, determine mouth thickness based on mouth subimage, determine eye opening degree based on eye subimage;
Characteristic matching equipment, respectively with flash memory device, the face recognition data storehouse of feature analysis equipment and far-end connects, face recognition data storehouse has prestored the supercilium thickness of everyone face-image, supercilium flexibility, mouth thickness and eye opening degree, the supercilium thickness of everyone face-image prestored with face recognition data storehouse by the supercilium thickness that feature analysis equipment exports carries out mating to obtain supercilium thickness matching degree, the supercilium flexibility of everyone face-image supercilium flexibility that feature analysis equipment exports prestored with face recognition data storehouse carries out mating to obtain supercilium flexibility matching degree, the mouth thickness of everyone face-image prestored with face recognition data storehouse by the mouth thickness that feature analysis equipment exports carries out mating to obtain mouth thickness matching degree, the eye opening degree of everyone face-image prestored with face recognition data storehouse by the eye opening degree that feature analysis equipment exports carries out mating to obtain eye opening degree matching degree, based on supercilium thickness matching degree, preset supercilium thickness weighted value, supercilium flexibility matching degree, preset supercilium flexibility weighted value, mouth thickness matching degree, preset mouth thickness weighted value, eye opening degree matching degree and default eye opening degree weighted value determine the matching degree of everyone face-image that image to be identified and face recognition data storehouse prestore, using piece identity corresponding for face-image the highest for matching degree as identifying identity output,
Dsp processor, respectively with LCD display device, characteristic matching equipment, mike and voice match equipment connect, when receiving identification identity from characteristic matching equipment, client to current checkout starts mike and voice match equipment to receive confirmation identity, the client of current checkout is in the crowd of queuing checkout, when identifying that identity is consistent with confirmation identity, to identify that identity and cashier are sent collectively to the payment devices of far-end to complete to pay by the value data that the touch screen of LCD display device inputs, simultaneously to the E-mail address transmission confirmation mail identifying that identity is corresponding, confirm that mail includes customer payment video,
Wherein, when dsp processor does not receive identification identity after the first Preset Time, send identity validation failure signal, when dsp processor does not receive confirmation identity after the second Preset Time, sending identity validation failure signal, dsp processor, when identifying that identity is inconsistent with confirmation identity, sends identity validation failure signal, dsp processor, when identifying identity and confirmation identity is consistent, sends identity validation pass signal;
Wherein, LCD display device is additionally operable to the text prompt information that display is corresponding with identity validation failure signal or identity validation pass signal.
3. the facial payment platform based on image detection as claimed in claim 2, it is characterised in that:
CMOS visual sensing equipment is additionally operable to record customer payment video.
4. the facial payment platform based on image detection as claimed in claim 2, it is characterised in that:
Preset reference face contour is that benchmark face-image is carried out the figure that contours extract obtains, and pre-set image average elects 140 as, and pre-set image variance elects 50 as, and presetted pixel block size elects 60 pixel × 65 pixels as.
5. the facial payment platform based on image detection as claimed in claim 2, it is characterised in that:
Preset reference supercilium profile is that benchmark supercilium image is carried out the figure that contours extract obtains, preset reference mouth profile is that benchmark mouth image carries out the figure that contours extract obtains, and preset reference eye profile is that benchmark eyes image is carried out the figure that contours extract obtains.
6. the facial payment platform based on image detection as claimed in claim 2, it is characterised in that:
LCD display device is positioned at above cashier.
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