CN111445640A - Express delivery pickup method, device, equipment and storage medium based on iris recognition - Google Patents
Express delivery pickup method, device, equipment and storage medium based on iris recognition Download PDFInfo
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- CN111445640A CN111445640A CN202010119452.7A CN202010119452A CN111445640A CN 111445640 A CN111445640 A CN 111445640A CN 202010119452 A CN202010119452 A CN 202010119452A CN 111445640 A CN111445640 A CN 111445640A
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- G—PHYSICS
- G07—CHECKING-DEVICES
- G07F—COIN-FREED OR LIKE APPARATUS
- G07F17/00—Coin-freed apparatus for hiring articles; Coin-freed facilities or services
- G07F17/10—Coin-freed apparatus for hiring articles; Coin-freed facilities or services for means for safe-keeping of property, left temporarily, e.g. by fastening the property
- G07F17/12—Coin-freed apparatus for hiring articles; Coin-freed facilities or services for means for safe-keeping of property, left temporarily, e.g. by fastening the property comprising lockable containers, e.g. for accepting clothes to be cleaned
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/18—Eye characteristics, e.g. of the iris
- G06V40/197—Matching; Classification
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/40—Spoof detection, e.g. liveness detection
- G06V40/45—Detection of the body part being alive
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- G—PHYSICS
- G07—CHECKING-DEVICES
- G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
- G07C9/00—Individual registration on entry or exit
- G07C9/00174—Electronically operated locks; Circuits therefor; Nonmechanical keys therefor, e.g. passive or active electrical keys or other data carriers without mechanical keys
- G07C9/00563—Electronically operated locks; Circuits therefor; Nonmechanical keys therefor, e.g. passive or active electrical keys or other data carriers without mechanical keys using personal physical data of the operator, e.g. finger prints, retinal images, voicepatterns
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Abstract
The invention discloses an express delivery pickup method, device, equipment and storage medium based on iris recognition, which are applied to the technical field of intelligent logistics and are used for solving the problems of low efficiency and strict pickup requirement of the conventional express delivery pickup. The method provided by the invention comprises the following steps: when a pickup request is received, starting a camera with an iris function on the express cabinet; performing living body detection on personnel in front of the express delivery cabinet through a camera to obtain a living body detection result; if the living body detection result is a non-living body, rejecting the pickup request; if the living body detection result is a living body, acquiring a human face image of a person through a camera, and extracting iris features in the human face image to obtain first iris features; comparing the first iris characteristic with the reserved iris characteristics in the characteristic library; and if the reserved iris features with the consistent comparison exist, responding to the pickup request, and opening an express window corresponding to the reserved iris features with the consistent comparison on the express cabinet.
Description
Technical Field
The invention relates to the technical field of intelligent logistics, in particular to an express delivery pickup method, device, equipment and storage medium based on iris recognition.
Background
At present, more and more districts are equipped with express delivery cabinets, so that great convenience is brought to people to take goods, and the time for couriers to get goods at home is saved. After the express delivery person stores the express in the express cabinet, the system can automatically send a short message pickup code to the addressee, and the addressee can manually input the pickup code or scan a two-dimensional code on a self-picking cabinet by a mobile phone to pick up the express. What's more, people feel headache is that people forget to take the mobile phone, the signal of the mobile phone is poor, and the verification code is input wrongly. Moreover, the mobile phone is easy to be implanted into a Trojan horse, and a short message check code is intercepted, so that certain risk exists.
The scheme of piece is got to the brush face that ant golden uniform released, nevertheless because of the user all gets in the morning and evening usually, the requirement of the challenge to face discernment of light is very high, "brush face" the time need eyes directly to look at the camera, considers user's height difference, this is difficult to do. There will be certain interference when other waiters get when getting, and generally speaking, the discernment speed of brushing face and getting is expected to be longer than 5 seconds, and user experience is relatively poor. It is thus clear that no matter be traditional express delivery cabinet get or neotype brush face get, all have the drawback, need a more convenient, friendly mode of getting to satisfy user's demand.
Disclosure of Invention
The embodiment of the invention provides an express delivery pickup method and device based on iris recognition, computer equipment and a storage medium, and aims to solve the problems of low efficiency and strict pickup requirement of the conventional express delivery pickup.
An express delivery pickup method based on iris recognition comprises the following steps:
when a pickup request is received, starting a camera with an iris function on the express cabinet;
performing living body detection on personnel positioned in front of the express delivery cabinet through the camera to obtain a living body detection result;
if the living body detection result is a non-living body, rejecting the pickup request;
if the living body detection result is a living body, acquiring a face image of the person through the camera, and extracting iris features in the face image to obtain first iris features;
comparing the first iris feature with a reserved iris feature in a feature library;
and if the reserved iris features with the consistent comparison exist, responding to the pickup request, and opening an express delivery window corresponding to the reserved iris features with the consistent comparison on the express delivery cabinet.
An express delivery pickup device based on iris discernment includes:
the camera starting module is used for starting a camera with an iris function on the express cabinet when receiving a pickup request;
the living body detection module is used for carrying out living body detection on personnel positioned in front of the express delivery cabinet through the camera to obtain a living body detection result;
the first request rejection module is used for rejecting the pickup request if the living body detection result is a non-living body;
the iris feature extraction module is used for acquiring a face image of the person through the camera if the living body detection result is a living body, and extracting iris features in the face image to obtain first iris features;
the iris comparison module is used for comparing the first iris characteristic with the reserved iris characteristics in the characteristic library;
and the request response module is used for responding the pickup request if the reserved iris features with consistent comparison exist, and opening an express window corresponding to the reserved iris features with consistent comparison on the express cabinet.
A computer device comprises a memory, a processor and a computer program stored in the memory and operable on the processor, wherein the processor implements the steps of the above-mentioned express delivery pickup method based on iris recognition when executing the computer program.
A computer-readable storage medium, which stores a computer program that, when executed by a processor, implements the steps of the above-described iris recognition-based express delivery pickup method.
According to the express delivery pickup method and device based on iris recognition, the computer equipment and the storage medium, firstly, when a pickup request is received, a camera with an iris function on an express cabinet is started; then, performing living body detection on the personnel in front of the express delivery cabinet through the camera to obtain a living body detection result; if the living body detection result is a non-living body, rejecting the pickup request; if the living body detection result is a living body, acquiring a face image of the person through the camera, and extracting iris features in the face image to obtain first iris features; then, comparing the first iris feature with the reserved iris features in the feature library; and if the reserved iris features with the consistent comparison exist, responding to the pickup request, and opening an express delivery window corresponding to the reserved iris features with the consistent comparison on the express delivery cabinet. Therefore, the invention can complete living body detection and iris recognition of personnel through the camera with the iris function, can quickly realize identity verification and complete express delivery pickup without additional operation of personnel, improves the safety of express delivery pickup, and improves pickup efficiency and user experience.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the description of the embodiments of the present invention will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to these drawings without inventive labor.
Fig. 1 is a schematic view of an application environment of an express delivery pickup method based on iris recognition in an embodiment of the present invention;
FIG. 2 is a flowchart of an express delivery pickup method based on iris recognition according to an embodiment of the present invention;
fig. 3 is a schematic flow chart of an application scenario of step 102 of an express delivery pickup method based on iris recognition according to an embodiment of the present invention;
fig. 4 is a schematic flow chart illustrating rPPG heartbeat detection performed by an express delivery pickup method based on iris recognition in an application scenario according to an embodiment of the present invention;
fig. 5 is a schematic flow chart of an express delivery pickup method based on iris recognition in an application scenario for temporarily storing and reserving iris features in accordance with an embodiment of the present invention;
fig. 6 is a schematic flow chart of a face recognition link in an application scene of an express delivery pickup method based on iris recognition in an embodiment of the present invention;
fig. 7 is a schematic flow chart of the step 302 of the express delivery pickup method based on iris recognition in an application scenario according to an embodiment of the present invention;
fig. 8 is a schematic structural diagram of an express delivery pickup device based on iris recognition in an embodiment of the present invention;
FIG. 9 is a schematic diagram of a computer device according to an embodiment of the invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The express delivery pickup method based on iris recognition can be applied to the application environment as shown in figure 1, wherein the express delivery cabinet is communicated with the server through a network. The server may be implemented by an independent server or a server cluster composed of a plurality of servers.
In an embodiment, as shown in fig. 2, an express pickup method based on iris recognition is provided, which is described by taking the example that the method is applied to the server in fig. 1, and includes the following steps:
101. when a pickup request is received, starting a camera with an iris function on the express cabinet;
when the express delivery needs to be taken, the user can click an iris pick-up button on the screen of the express delivery cabinet and initiate a pick-up request to the server. And after receiving the pickup request, the server starts a camera with an iris function on the express cabinet.
102. Performing living body detection on personnel positioned in front of the express delivery cabinet through the camera to obtain a living body detection result;
it can be understood that, in order to ensure the security of express delivery pickup, in view of the fact that many illegal persons use stolen photos, videos and other ways to trick the identity recognition system, thereby stealing the express delivery in the express delivery cabinet, in order to prevent this situation from happening, in this embodiment, the server performs live body detection on the personnel before identity verification, so as to ensure that the personnel participating in identity recognition are live persons. Therefore, the server firstly performs living body detection on the personnel in front of the express delivery cabinet through the camera to obtain a living body detection result, if the living body detection result is a living body, the personnel in front of the express delivery cabinet is indicated to be a living person, and otherwise, if the living body detection result is a non-living body, the personnel in front of the express delivery cabinet is indicated to be a non-living person. Therefore, the theft behavior of deceiving the express delivery by pictures, videos and the like can be prevented by the preposition means of the living body detection.
It should be noted that there are many living body detection methods that can be adopted by the server, such as living body face detection, motion instruction living body detection, and the like. However, different in-vivo detection methods have different hardware devices, and are suitable for different application scenarios. In order to be better suitable for a pickup scene of an express cabinet, the eye movement live body detection is combined with the method, other hardware cost is not required to be increased, the eye movement live body detection and the iris recognition can be combined together, the situation that a live body detection link prolongs pickup time for a user is avoided, and pickup efficiency is guaranteed while pickup safety is improved. To this end, as shown in fig. 3, further, the step 102 may include:
201. acquiring eye images of people in front of the express delivery cabinet in real time through the camera;
202. analyzing the eye images by using an eye tracking technology, determining the current eye position of the person in real time, and updating and displaying the current eye position on a display screen of the express delivery cabinet in real time by using a preset first mark;
203. guiding the person to move the eye to enable the preset first mark to move to a preset specified position;
204. acquiring a current eye image of the person when the preset first mark is moved to a preset designated position;
205. judging whether the collected eye images and the preset designated position meet the preset matching requirement or not through a pre-trained static point location model;
206. if so, determining that the living body detection result is a living body;
207. and if not, determining that the living body detection result is a non-living body.
To step 201, the server can pass through the camera acquires in real time and is located the eye image of the personnel in express delivery cabinet the place ahead, can know, all need operate on the display screen of express delivery cabinet when getting a person and getting it, for example click "get a" button, this camera can set up in the display screen top of express delivery cabinet, the standing position of alignment person of getting for shoot get person's the image of the upper half of the body or face, thereby, the server can follow the image of the upper half of the body or face and acquire get person's eye image.
For step 202, in order to implement the eye movement live body detection, after acquiring the eye image of the person in real time, the server may analyze the eye image by using an eye tracking technology, determine the current eye position of the person in real time, and update and display the current eye position on the display screen of the express delivery cabinet in real time by using a preset first mark, where a dot in fig. 4 is a position mark of the current eye of the person in an application scene.
Specifically, the server can determine the eye position of the person by using a single-point calibration method, acquire an eye image of the person through single-point calibration, compensate the difference between the current person and the existing reference person pupil-puerh qin spot vector through operations such as rotation and translation, then match a mapping model of the reference, and quickly calculate the fixation point of the person, namely the current eye position of the person. The mapping model can use a neural network algorithm to automatically learn the existing sample set, can simulate a nonlinear relation and has strong fault tolerance. The input layer of the mapping model is pupil coordinates and Pu' er Qin spot coordinates, the output layer is coordinates of a fixation point in a screen, the hidden layer neuron is used for calculating a mapping relation, and an activation function is sigmoid.
The Sigmoid function is defined by the following equation:
its derivative to x can be expressed by itself as:
for step 203, the eye positions are marked on the display screen to better guide the person to move the eyes as required so that the server confirms whether the person is a living body. Specifically, the server may prompt on a display screen of the courier cabinet, for example, "please see 1234 in sequence", and display 4 points of 1, 2, 3, and 4 on the display screen, and the person may complete the detection of the living eye movement by moving the eye spirit to move the first mark (a dot in fig. 4) to 1, 2, 3, and 4 in sequence.
In step 204, it can be seen that, in order to verify whether the eye spirit of the person moves in place, the server may acquire the current eye image of the person whenever the preset first mark moves to the preset designated position. When the eye spirit of the person moves to the positions 1, 2, 3 and 4 after receiving the distance of the figure 4, the server collects the current eye image of the person, and at least 4 eye images can be collected in total.
In step 205, after acquiring the current eye image of the person, the server may determine, through a pre-trained static point location model, whether the acquired eye image and the preset designated position meet a preset matching requirement, so as to obtain a determination result. The preset matching requirement may be whether the pupil focus in the eye image coincides with the preset designated position, or a certain coincidence degree is reached. The static point location model can carry out deep learning on the red point digital pictures displayed by various eyes by carrying out digital modeling on the red point and using a convolutional neural network algorithm, thereby judging whether the red point of the eye pupil part is consistent with a preset specified position, wherein the red point refers to the reflection of the preset specified position seen by a user in the eyes of the user. Therefore, the static point location model is trained in the above manner, and a pre-trained judgment model which can judge whether the eye image and the preset specified position coincide or whether the coincidence degree is sufficient can be obtained.
With respect to step 206 and step 207, it is understood that when the judgment result is yes, the person can be considered as a living person, and therefore, the server can determine that the living body detection result is a living body; when the determination result is no, the person may be considered as not a living person, and therefore, the server may determine that the living body detection result is a non-living body.
In order to further ensure that the person is a living person and improve the express delivery cabinet pickup safety, the embodiment may further perform heartbeat detection on the person before determining that the living body detection result is a living body. Because rPPG heartbeat detection can judge whether personnel have normal heartbeat through images, other hardware and complicated operation links are not needed, the heartbeat detection can be finished in the iris identification process without perception by a user, and the piece taking safety and the user use experience are improved while the piece taking efficiency is ensured. Therefore, as shown in fig. 4, in this embodiment, after determining that the acquired eye image and the preset designated position meet the preset matching requirement and before determining that the living body detection result is a living body, the method may further include:
301. continuously acquiring a plurality of face images of the person through the camera;
302. performing rPPG heartbeat detection on the plurality of face images;
303. if yes, go to step 206;
304. and if the detection result is negative, determining that the living body detection result is a non-living body.
As to step 301, it can be understood that, in the above steps, a person needs to participate in a living body detection link, at this time, a face of the person is aligned with the camera, and the server simultaneously performs eye movement living body detection, heartbeat detection and iris recognition on the person through the camera, so that the server can continuously acquire a plurality of face images of the person through the camera, which are not sensible to the person, for example, continuously take 0.5 second of face images of the person to acquire a plurality of face images, the number of face images depends on an acquisition frequency of the camera, and is not limited herein.
For step 302, after acquiring a plurality of facial images of the person, the server may perform rPPG heartbeat detection on the plurality of facial images to obtain a heartbeat detection result, where the detection result is generally a normal heartbeat or not a normal heartbeat.
Further, as shown in fig. 7, step 302 may specifically include:
701. respectively intercepting regional images of a preset ROI (region of interest) from the plurality of face images;
702. calculating the intercepted spatial mean value of the color RGB of each region image;
703. processing each spatial mean value by applying a preset signal processing method to obtain components containing heart rate information corresponding to the plurality of face images;
704. processing each component by adopting fast Fourier transform to obtain heart rate signals corresponding to the plurality of face images;
705. integrating the heart rate signals according to the acquisition sequence of the plurality of face images to obtain continuous heart rate signals of the person in a continuous acquisition time period;
706. judging whether the continuous heart rate signal is in a preset live heart rate signal range, if so, executing a step 707, and if not, executing a step 708;
707. determining that the detection result of the rPPG heartbeat detection is positive;
708. and determining whether the detection result of the rPPG heartbeat detection is negative.
For step 701, in rPPG heartbeat detection, several face regions may be pre-selected as ROI (region of interest) regions, and the selection of these ROI regions may be manually selected or automatically detected and tracked by some algorithm. In this embodiment, because the scene of express delivery pickup is single, the pickup personnel usually do not have a large range of motion, and in addition, the personnel need to complete the requirements of iris recognition and eye movement tracking detection, and in the process of acquiring the face image, the personnel are basically fixed at one position. Therefore, in the embodiment, the forehead area and/or the cheek area of the face can be manually selected as the ROI area in advance, so that the skin of the forehead is relatively flat and thin, and is less affected when a person speaks or makes an expression, which is more beneficial to extracting the center rate information in the subsequent step; the cheek area may supplement the forehead area, and is less likely to be blocked than the forehead area, and the cheek of the person is usually exposed.
In step 701, in this embodiment, specifically, the server may intercept, as the region image, a forehead region partial image in each face image.
As for step 702, it can be understood that the principle of rPPG is that different structures of the human body absorb and reflect light to different extents, and therefore, in order to analyze the signal variation contained in the image, the server needs to calculate the spatial mean value of the color RGB of each captured image of each region. Specifically, when calculating the spatial mean value of the color RGB, a certain channel may be calculated, and multiple channels may also be calculated.
For step 703, specifically, the preset signal processing method may adopt methods such as low-pass filtering, blind source separation, and the like, which are not described herein again. The components obtained after signal processing contain heart rate information, and then the heart rate information is extracted through the subsequent steps.
For step 704, finally, the server may apply a Fast Fourier Transform (FFT) or peak detection algorithm to the component to estimate the corresponding heart beat frequency Fs (or number of peaks Ns during the processing duration T (s)), in particular the heart rate in beats per minute (bpm) may be calculated as 60 × Fs (or Ns/T × 60).
As for step 705, it can be understood that the above-mentioned processing is performed on each facial image to obtain a heart rate signal corresponding to each facial image, but these heart rate signals are scattered, and since a plurality of facial images are continuously acquired, the heart rate signals corresponding to the facial images are integrated to obtain a continuous heart rate signal of the person within a continuous acquisition time period.
With respect to step 706-. If yes, the person is considered to be a live person, step 707 is executed, and the detection result of the rPPG heartbeat detection is determined to be yes; otherwise, if not, the person may be considered as not a live person, and may be a carrier such as a picture, a video, and the like, so step 708 may be performed to determine whether the detection result of the rPPG heartbeat detection is negative.
With respect to steps 303 and 304, it is understood that when the detection result is normal heartbeat, the person may be considered as a living person, and thus, the server may perform step 206; conversely, when the detection result is abnormal heartbeat, the person may be considered not to be a living person, such as a paper photo, an electronic video, or the like, and thus the server may determine that the living body detection result is a non-living body.
It can be known from the foregoing step 301 and step 304 that, in this embodiment, the server can effectively prevent illegal molecules from deceiving the identity recognition system by using paper photos, mobile phone videos, and other manners by adding rPPG heartbeat detection, so that it can be ensured that the acquired face images come from live people, and the security of express delivery pickup is improved.
Preferably, the server can also select more than one face image from the collected face images and send the face images to an identity inquiry system of a public security agency for identity verification, and the accuracy and the authenticity of the identity of the person are further ensured by using the strength of the public security agency.
103. If the living body detection result is a non-living body, rejecting the pickup request;
if the live body detection result is a non-live body, the server may reject the pickup request because the information from the person is considered dangerous and the pickup request should be rejected.
104. If the living body detection result is a living body, acquiring a face image of the person through the camera, and extracting iris features in the face image to obtain first iris features;
if the living body detection result is a living body, the person is known to be a living person, the possibility that the identity recognition system is deceived by illegal molecules through pictures and videos is eliminated, and the server can perform identity recognition on the person next. In this embodiment, the identity of the person is determined by means of iris recognition, and specifically, the server acquires a face image of the person through the camera, and extracts iris features in the face image to obtain first iris features. It can be understood that the camera head has an iris function, the server can shoot the face image and collect iris characteristics of the face image through the camera head at the same time, other additional operations are not needed for the person, and convenience in taking the part is improved.
It should be noted that iris recognition can be free from external interference, and normal recognition can be completed in a multi-person situation or other environments (such as dark sky), which has certain advantages compared with other recognition methods.
105. Comparing the first iris feature with a reserved iris feature in a feature library;
it can be understood that the server may be provided with a feature library in advance, and the feature library may be stored in the storage of the express delivery cabinet, or may be stored in a database connected to the server, and the feature library is used for storing the reserved iris features of all registered accounts. Each user registered on the server can leave his own iris features on the feature library in advance so as to use the iris recognition function in the method to quickly pick up the iris.
Therefore, after the server obtains the first iris feature, the server can compare the first iris feature with the reserved iris feature in the feature library, and if the reserved iris feature which is consistent with the first iris feature in comparison exists in the feature library, the server can confirm that the person is the registered user of the reserved iris feature which is consistent in comparison, so that the identity of the person is determined.
It can be understood that, in order to facilitate the implementation of the iris pickup function, before implementing the method, the pickup should be registered with the real name, and therefore, the method may further include: acquiring a mobile phone number and an identity card number input by a registrant; inquiring first identity information of the mobile phone number through a telecommunication operator; inquiring second identity information of the citizen through the identity card number; if the first identity information is consistent with the second identity information, iris features of the registrant are collected, the collected iris features are stored in a feature library, and an association relation is established between the iris features and the mobile phone number and the identity card number of the registrant. For example, in an application scenario, a user may register on an express cabinet, input a personal mobile phone number, click iris acquisition, and face eyes to an iris recognition instrument built in an operation terminal of the express cabinet to complete iris acquisition. After the iris collection is successful, the server actively sends a real-name authentication link to the personal mobile phone number, and the user clicks the real-name authentication link to complete the registration.
Furthermore, in the user registration process, the server may further request the user to perform real-name authentication, and in the real-name authentication link, the server may request the user to provide the own identity card number, and in order to ensure that the identity card number is true, the method may further include the following steps: acquiring an identity card photo uploaded by a registrant; carrying out identity card different-image verification on the identity card photo, and judging whether the identity card photo comes from the shooting of an identity card original; if not, the registration is refused; if so, extracting the ID card number from the ID card picture. It can be understood that the identity card picture is subjected to identity card different-image verification, whether the identity card picture comes from an original, a copy or a screen shooting piece can be distinguished, the identity of a user can be ensured to be real only by the identity card picture from the original, and the safety factor is increased. Therefore, the server can also carry out the identification real-name body checking and the mobile phone number real-name body checking at the same time, and the double body checking can prevent all the behaviors of impersonation, counterfeiting and the like. Verifying true name of the testimony: the method comprises the steps that a picture is shot on site, and identity card information identified by OCR is transmitted to a citizen information inquiry center together to confirm whether the identity card is the principal or not; the mobile phone number is real-name and is verified: and uploading the mobile phone number and the identity information identified by the OCR, and transmitting the mobile phone number and the identity information to a corresponding operator for verification to confirm whether the mobile phone number is the mobile phone number of the user.
Considering that the reserved iris features in the feature library are more and more along with the increase of the number of users, therefore, in order to reduce the pressure of the server for storing data, the server can be provided with an iris database for storing the reserved iris features of all registered users, the feature library is locally arranged in the express cabinet and used for temporarily storing the reserved iris features of the users with the express items stored in the express cabinet, and when the express items of the users are taken away, the reserved iris features are deleted from the local feature library, so that the data volume of the reserved iris features in the local feature library can be effectively controlled, the server can conveniently call and compare the reserved iris features, the hardware load of the express cabinet is reduced, and the condition that network signals do not influence the pickup is avoided. As shown in fig. 5, further, the method may further include:
401. when receiving a delivery request, acquiring a receiver in the delivery request;
402. if the recipient has registered an account and reserves iris features, extracting the iris features of the recipient from an iris database to a feature library of the express cabinet;
403. and deleting the iris characteristics corresponding to the receiver from the characteristic library after the express corresponding to the delivery request is taken away.
For step 401, in the courier delivery stage, the courier operates on the courier cabinet and delivers the courier, and at this time, the server may receive the delivery request. Therefore, in the current express delivery process, the courier usually scans the two-dimensional code on the courier, and the server identifies the recipient information of the courier while initiating a delivery request. Of course, the method of the mobile phone number, the name and the like of the receiver can be input during the delivery, and the server can confirm who the receiver in the delivery request is according to the information.
For step 402, it can be understood that, in order to be applicable to more express delivery pickup situations, it is generally not mandatory that all recipients reserve iris features, and for a user who does not reserve iris features, delivery and pickup of an express delivery can be completed by using an existing pickup manner, which is not described herein again. And for the recipients who have registered accounts and reserve the iris characteristics, the server can extract the iris characteristics of the recipients from the iris database to the characteristic library of the express cabinet.
For step 403, in order to control the data amount of the reserved iris features stored in the feature library of the express delivery cabinet, after the express delivery corresponding to the delivery request is taken away, the server may delete the iris features corresponding to the recipient from the feature library, so that the data amount of the reserved iris features in the feature library is maintained within a limit, which not only reduces the storage burden of the feature library, but also provides the comparison efficiency of the server for comparing the first iris features with the reserved iris features in the feature library.
106. And if the reserved iris features with the consistent comparison exist, responding to the pickup request, and opening an express delivery window corresponding to the reserved iris features with the consistent comparison on the express delivery cabinet.
When the reserved iris features with the same comparison are available, the server can recognize the identity of the person, so that the person who takes the express delivery at present is determined, the registered user information can be used for knowing which express delivery window in the express delivery cabinet belongs to the person, and therefore the server can respond to the express delivery taking request and open the express delivery window corresponding to the reserved iris features with the same comparison on the express delivery cabinet.
In order to further enhance the express delivery pickup security, a human face recognition link can be added on the basis of iris recognition in the embodiment, because the human face recognition and the iris recognition can use the same camera, extra hardware burden is not needed, meanwhile, a human face image based on the human face recognition can be the same as a human face image acquired during the iris recognition or acquired simultaneously, and the human face image is not sensed by a pickup person, so that the pickup security can be improved while the pickup timeliness and convenience are guaranteed. Specifically, as shown in fig. 6, before step 106, the method may further include:
501. acquiring contrast similarity between the reserved iris features with consistent contrast and the first iris features;
502. if the contrast similarity exceeds a preset threshold, executing step 106;
503. if the contrast similarity does not exceed a preset threshold, extracting a first face feature in the face image;
504. comparing the first face features with reserved target face features, wherein the target face features refer to face features of users reserved with iris features and consistent in comparison;
505. if the comparison is not consistent, rejecting the pickup request;
506. if the comparison is consistent, step 106 is executed.
For step 501, the server calculates a contrast similarity between the first iris feature and the compared and consistent reserved iris feature when comparing the first iris feature and the compared and consistent reserved iris feature.
For step 502, it is understood that a threshold value, for example, 90%, may be preset on the server, and when the contrast similarity exceeds the threshold value, it indicates that the first iris feature is extremely similar to the pre-reserved iris feature consistent with the contrast, and the identity of the person may be considered to be undoubted, so the server may directly perform step 106 without performing face recognition verification on the person.
As for step 503, step 506, it is known that when the comparison similarity does not exceed the preset threshold, it indicates that the identity of the person is not enough to be confirmed, and there is a certain risk of false identification, therefore, in order to improve the pickup security, the server may extract the first face feature in the face image, and then compare the first face feature with the reserved target face feature, and if the comparison is not consistent, it indicates that the persons corresponding to the two are not the same person, at this time, the server should reject the pickup request; otherwise, if the comparison is consistent, it indicates that the two corresponding persons are the same person, and at this time, the server may execute step 106.
For example, when the contrast similarity is lower than the threshold, the first facial feature and the target facial feature perform 1: 1, comparing human faces, and if the comparison score is higher than a preset threshold value, determining that the comparison between the human faces and the express cabinet is consistent, and opening a corresponding cabinet door of the express cabinet; if the comparison score is lower than the preset threshold value, the comparison fails, the comparison between the two is considered to be inconsistent, the pickup request is rejected, and the server can prompt the user that pickup information is not available temporarily.
It should be noted that, when performing the secondary comparison (face comparison), since the camera with the iris function is adopted, the user does not need to take a picture again, and the user does not have perception, which not only improves the safety factor, but also does not affect the convenience of the user.
In the embodiment of the invention, firstly, when a pickup request is received, a camera with an iris function on an express cabinet is started; then, performing living body detection on the personnel in front of the express delivery cabinet through the camera to obtain a living body detection result; if the living body detection result is a non-living body, rejecting the pickup request; if the living body detection result is a living body, acquiring a face image of the person through the camera, and extracting iris features in the face image to obtain first iris features; then, comparing the first iris feature with the reserved iris features in the feature library; and if the reserved iris features with the consistent comparison exist, responding to the pickup request, and opening an express delivery window corresponding to the reserved iris features with the consistent comparison on the express delivery cabinet. Therefore, the invention can complete living body detection and iris recognition of personnel through the camera with the iris function, can quickly realize identity verification and complete express delivery pickup without additional operation of personnel, improves the safety of express delivery pickup, and improves pickup efficiency and user experience.
It should be understood that, the sequence numbers of the steps in the foregoing embodiments do not imply an execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.
In an embodiment, an express delivery pickup device based on iris recognition is provided, and the express delivery pickup device based on iris recognition corresponds to the express delivery pickup method based on iris recognition in the embodiment one to one. As shown in fig. 8, the express pickup device based on iris recognition includes a camera starting module 601, a living body detection module 602, a first request rejection module 603, an iris feature extraction module 604, an iris comparison module 605 and a request response module 606. The functional modules are explained in detail as follows:
the camera starting module 601 is used for starting a camera with an iris function on the express cabinet when receiving a pickup request;
the living body detection module 602 is configured to perform living body detection on a person located in front of the express delivery cabinet through the camera to obtain a living body detection result;
a first request rejection module 603, configured to reject the pickup request if the living body detection result is a non-living body;
an iris feature extraction module 604, configured to collect, by the camera, a face image of the person if the living body detection result is a living body, and extract iris features in the face image to obtain a first iris feature;
an iris comparison module 605, configured to compare the first iris feature with a reserved iris feature in a feature library;
and the request response module 606 is configured to respond to the pickup request if the reserved iris features consistent in comparison exist, and open an express window corresponding to the reserved iris features consistent in comparison on the express cabinet.
Further, the living body detecting module may include:
the eye image acquisition unit is used for acquiring eye images of people in front of the express delivery cabinet in real time through the camera;
the eye tracking unit is used for analyzing the eye images by using an eye tracking technology, determining the current eye position of the person in real time, and updating and displaying the current eye position on a display screen of the express delivery cabinet in real time by using a preset first mark;
the guiding unit is used for guiding the person to move the catch of eyes so that the preset first mark moves to a preset specified position;
the eye image acquisition unit is used for acquiring the current eye image of the person when the preset first mark moves to a preset specified position;
the judging unit is used for judging whether the collected eye images and the preset designated position meet the preset matching requirement or not through a pre-trained static point location model;
a first determination unit configured to determine that the living body detection result is a living body if the determination result of the determination unit is yes;
a second determination unit configured to determine that the living body detection result is a non-living body if the determination result of the determination unit is negative.
Further, the express delivery pickup device based on iris recognition may further include:
the human face image acquisition module is used for acquiring a plurality of human face images of the personnel through the camera;
the heartbeat detection module is used for carrying out rPPG heartbeat detection on the plurality of face images;
and the first triggering module is used for triggering the first determining unit if the detection result of the heartbeat detecting module is positive.
And the non-living body determining module is used for determining that the living body detection result is a non-living body if the detection result of the heartbeat detecting module is negative.
Further, the heartbeat detection module may include:
the regional image intercepting unit is used for respectively intercepting regional images of a preset ROI (region of interest) from the plurality of face images;
the spatial mean value calculation unit is used for calculating the spatial mean value of the color RGB of each intercepted area image;
the signal processing unit is used for processing each space mean value by applying a preset signal processing method to obtain components which respectively correspond to the plurality of face images and contain heart rate information;
the heart rate signal processing unit is used for processing each component by adopting fast Fourier transform to obtain heart rate signals corresponding to the plurality of face images;
the heart rate signal integration unit is used for integrating the heart rate signals according to the acquisition sequence of the plurality of face images to obtain continuous heart rate signals of the person in a continuous acquisition time period;
the heart rate judging unit is used for judging whether the continuous heart rate signal is in a preset range of the heart rate signal of the living person;
a first determining unit, configured to determine that a detection result of rPPG heartbeat detection is yes if a determination result of the heart rate determining unit is yes;
and the second determining unit is used for determining whether the detection result of the rPPG heartbeat detection is negative if the judgment result of the heart rate judging unit is negative.
Further, the express delivery pickup device based on iris recognition may further include:
the receiver acquisition module is used for acquiring the receiver in the delivery request when the delivery request is received;
the iris feature extraction module is used for extracting the iris features of the addressee from an iris database to a feature library of the express cabinet if the addressee has a registered account and reserved iris features;
and the iris characteristic deleting module is used for deleting the iris characteristics corresponding to the receiver from the characteristic library after the express delivery corresponding to the delivery request is taken away.
Further, the express delivery pickup device based on iris recognition may further include:
the similarity obtaining module is used for obtaining the contrast similarity between the reserved iris features with consistent contrast and the first iris features;
the second triggering module is used for triggering the request response module if the contrast similarity exceeds a preset threshold;
the face feature extraction module is used for extracting a first face feature in the face image if the contrast similarity does not exceed a preset threshold;
the face feature comparison module is used for comparing the first face feature with a reserved target face feature, wherein the target face feature refers to the face feature of a user reserved with the reserved iris feature and consistent in comparison;
the request rejection module is used for rejecting the pickup request if the comparison result of the face feature comparison module is inconsistent;
and the third triggering module is used for triggering the request response module if the comparison results of the face feature comparison module are consistent in comparison.
For specific definition of the express pickup device based on iris recognition, reference may be made to the above definition of the express pickup method based on iris recognition, and details are not repeated here. All or part of each module in the express delivery pickup device based on iris recognition can be realized through software, hardware and a combination thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as shown in fig. 9. The computer device includes a processor, a memory, a network interface, and a database connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The database of the computer equipment is used for storing data related to the express delivery pickup method based on iris recognition. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to realize an express delivery pickup method based on iris recognition.
In one embodiment, a computer device is provided, which includes a memory, a processor, and a computer program stored on the memory and executable on the processor, and when the processor executes the computer program, the steps of the method for express delivery based on iris recognition in the above embodiments are implemented, for example, steps 101 to 106 shown in fig. 2. Alternatively, the processor, when executing the computer program, implements the functions of the modules/units of the express pickup device based on iris recognition in the above embodiments, such as the functions of the modules 601 to 606 shown in fig. 8. To avoid repetition, further description is omitted here.
In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored, and the computer program is executed by a processor to implement the steps of the express delivery pickup method based on iris recognition in the above embodiments, such as the steps 101 to 106 shown in fig. 2. Alternatively, the computer program, when executed by the processor, implements the functions of the modules/units of the express pickup device based on iris recognition in the above embodiments, such as the functions of the modules 601 to 606 shown in fig. 8. To avoid repetition, further description is omitted here.
It will be understood by those of ordinary skill in the art that all or a portion of the processes of the methods of the embodiments described above may be implemented by a computer program that may be stored on a non-volatile computer-readable storage medium, which when executed, may include the processes of the embodiments of the methods described above, wherein any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-mentioned division of the functional units and modules is illustrated, and in practical applications, the above-mentioned function distribution may be performed by different functional units and modules according to needs, that is, the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-mentioned functions.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present invention, and are intended to be included within the scope of the present invention.
Claims (10)
1. An express delivery pickup method based on iris recognition is characterized by comprising the following steps:
when a pickup request is received, starting a camera with an iris function on the express cabinet;
performing living body detection on personnel positioned in front of the express delivery cabinet through the camera to obtain a living body detection result;
if the living body detection result is a non-living body, rejecting the pickup request;
if the living body detection result is a living body, acquiring a face image of the person through the camera, and extracting iris features in the face image to obtain first iris features;
comparing the first iris feature with a reserved iris feature in a feature library;
if the reserved iris features with consistent comparison exist, responding to the pickup request, and opening an express delivery window corresponding to the reserved iris features with consistent comparison on the express delivery cabinet;
through the camera is to being located carry out the live body detection to the personnel in express delivery cabinet the place ahead, obtain the live body testing result and include:
acquiring eye images of people in front of the express delivery cabinet in real time through the camera;
analyzing the eye images by using an eye tracking technology, determining the current eye position of the person in real time, and updating and displaying the current eye position on a display screen of the express delivery cabinet in real time by using a preset first mark;
guiding the person to move the eye to enable the preset first mark to move to a preset specified position;
acquiring a current eye image of the person when the preset first mark is moved to a preset designated position;
judging whether the collected eye images and the preset designated position meet the preset matching requirement or not through a pre-trained static point location model;
if so, determining that the living body detection result is a living body;
and if not, determining that the living body detection result is a non-living body.
2. The express delivery pickup method based on iris recognition according to claim 1, wherein after judging that the collected eye image and the preset designated position meet the preset matching requirement and before determining that the living body detection result is a living body, the method further comprises:
collecting a plurality of face images of the person through the camera;
performing rPPG heartbeat detection on the plurality of face images;
and if the detection result is yes, executing the step of determining that the living body detection result is the living body.
And if the detection result is negative, determining that the living body detection result is a non-living body.
3. The express pickup method based on iris recognition of claim 2, wherein the performing rPPG heartbeat detection on the plurality of facial images comprises:
respectively intercepting regional images of a preset ROI (region of interest) from the plurality of face images;
calculating the intercepted spatial mean value of the color RGB of each region image;
processing each spatial mean value by applying a preset signal processing method to obtain components containing heart rate information corresponding to the plurality of face images;
processing each component by adopting fast Fourier transform to obtain heart rate signals corresponding to the plurality of face images;
integrating the heart rate signals according to the acquisition sequence of the plurality of face images to obtain continuous heart rate signals of the person in a continuous acquisition time period;
judging whether the continuous heart rate signal is in a preset range of the heart rate signal of the living person;
if the continuous heart rate signal is within a preset range of the heart rate signal of the living person, determining that the detection result of the rPPG heartbeat detection is yes;
and if the continuous heart rate signal is not in the preset range of the heart rate signal of the living person, determining whether the detection result of the rPPG heartbeat detection is negative.
4. The express delivery pickup method based on iris recognition according to claim 1, further comprising:
when receiving a delivery request, acquiring a receiver in the delivery request;
if the recipient has registered an account and reserves iris features, extracting the iris features of the recipient from an iris database to a feature library of the express cabinet;
and deleting the iris characteristics corresponding to the receiver from the characteristic library after the express corresponding to the delivery request is taken away.
5. The express delivery pickup method based on iris recognition according to any claim 1 to 4, before responding to the pickup request and opening the express delivery window corresponding to the compared reserved iris features on the express delivery cabinet, further comprising:
acquiring contrast similarity between the reserved iris features with consistent contrast and the first iris features;
if the contrast similarity exceeds a preset threshold value, executing the step of responding to the pickup request and opening an express window corresponding to the reserved iris features with consistent contrast on the express cabinet;
if the contrast similarity does not exceed a preset threshold, extracting a first face feature in the face image;
comparing the first face features with reserved target face features, wherein the target face features refer to face features of users reserved with iris features and consistent in comparison;
if the comparison is not consistent, rejecting the pickup request;
and if the comparison is consistent, executing the steps of responding to the pickup request and opening an express window corresponding to the reserved iris characteristics on the express cabinet consistent with the comparison.
6. The utility model provides an express delivery pickup device based on iris discernment which characterized in that includes:
the camera starting module is used for starting a camera with an iris function on the express cabinet when receiving a pickup request;
the living body detection module is used for carrying out living body detection on personnel positioned in front of the express delivery cabinet through the camera to obtain a living body detection result;
the first request rejection module is used for rejecting the pickup request if the living body detection result is a non-living body;
the iris feature extraction module is used for acquiring a face image of the person through the camera if the living body detection result is a living body, and extracting iris features in the face image to obtain first iris features;
the iris comparison module is used for comparing the first iris characteristic with the reserved iris characteristics in the characteristic library;
the request response module is used for responding the pickup request if the reserved iris features with consistent comparison exist, and opening an express window corresponding to the reserved iris features with consistent comparison on the express cabinet;
the living body detecting module includes:
the eye image acquisition unit is used for acquiring eye images of people in front of the express delivery cabinet in real time through the camera;
the eye tracking unit is used for analyzing the eye images by using an eye tracking technology, determining the current eye position of the person in real time, and updating and displaying the current eye position on a display screen of the express delivery cabinet in real time by using a preset first mark;
the guiding unit is used for guiding the person to move the catch of eyes so that the preset first mark moves to a preset specified position;
the eye image acquisition unit is used for acquiring the current eye image of the person when the preset first mark moves to a preset specified position;
the judging unit is used for judging whether the collected eye images and the preset designated position meet the preset matching requirement or not through a pre-trained static point location model;
a first determination unit configured to determine that the living body detection result is a living body if the determination result of the determination unit is yes;
a second determination unit configured to determine that the living body detection result is a non-living body if the determination result of the determination unit is negative.
7. The device for taking express delivery based on iris recognition according to claim 6, further comprising:
the human face image acquisition module is used for acquiring a plurality of human face images of the personnel through the camera;
the heartbeat detection module is used for carrying out rPPG heartbeat detection on the plurality of face images;
and the first triggering module is used for executing the step of determining that the living body detection result is the living body if the detection result of the heartbeat detection module is positive.
And the non-living body determining module is used for determining that the living body detection result is a non-living body if the detection result of the heartbeat detecting module is negative.
8. The express delivery pickup device based on iris recognition of claim 7, wherein the heartbeat detection module comprises:
the regional image intercepting unit is used for respectively intercepting regional images of a preset ROI (region of interest) from the plurality of face images;
the spatial mean value calculation unit is used for calculating the spatial mean value of the color RGB of each intercepted area image;
the signal processing unit is used for processing each space mean value by applying a preset signal processing method to obtain components which respectively correspond to the plurality of face images and contain heart rate information;
the heart rate signal processing unit is used for processing each component by adopting fast Fourier transform to obtain heart rate signals corresponding to the plurality of face images;
the heart rate signal integration unit is used for integrating the heart rate signals according to the acquisition sequence of the plurality of face images to obtain continuous heart rate signals of the person in a continuous acquisition time period;
the heart rate judging unit is used for judging whether the continuous heart rate signal is in a preset range of the heart rate signal of the living person;
a first determining unit, configured to determine that a detection result of rPPG heartbeat detection is yes if a determination result of the heart rate determining unit is yes;
and the second determining unit is used for determining whether the detection result of the rPPG heartbeat detection is negative if the judgment result of the heart rate judging unit is negative.
9. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the method for express delivery based on iris recognition according to any one of claims 1 to 5 when executing the computer program.
10. A computer-readable storage medium storing a computer program, wherein the computer program is executed by a processor to implement the method for picking up express delivery based on iris recognition according to any one of claims 1 to 5.
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