CN111553266A - Identification verification method and device and electronic equipment - Google Patents
Identification verification method and device and electronic equipment Download PDFInfo
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Abstract
The embodiment of the disclosure provides an identification verification method, an identification verification device and electronic equipment, belonging to the technical field of image processing, wherein the method comprises the following steps: acquiring an initial image of a preset area; judging whether the target object is in a mask wearing state or not according to the characteristics of the face area in the initial image; if the target object is judged to be in a mask wearing state, judging whether the current temperature of the target object is within a preset temperature range; if the current temperature of the target object is within the preset temperature range, determining that the target object passes the identification verification; and if the target object is in a state of not wearing the mask, or the current temperature of the target object is not in a preset range, determining that the target object is not identified and verified. The scheme disclosed can automatically and accurately screen out the passing identification verification that the wearing mask and the current temperature are normal, does not need to take off the cross infection of the mask so as to be effectively avoided, also reduces the workload of detection personnel and exposes the infection risk, and improves the detection efficiency and the safety in a special period.
Description
Technical Field
The present disclosure relates to the field of image processing technologies, and in particular, to an identification verification method and apparatus, and an electronic device.
Background
In the field of face recognition, a complete face is generally required to be used as a recognized object, so that a person wearing a mask cannot be recognized, and whether the person wears the mask cannot be judged. When the face recognition verification is carried out in the special epidemic situation period, the user can carry out the recognition verification only by taking off the mask, and the risk of cross infection of the user is increased.
Therefore, the existing identification verification scheme has the technical problem that the specific verification requirements cannot be met.
Disclosure of Invention
In view of this, embodiments of the present disclosure provide an identification verification method, an identification verification apparatus, and an electronic device, which at least partially solve the problems in the prior art.
In a first aspect, an embodiment of the present disclosure provides an identification verification method, including:
acquiring an initial image of a preset area, wherein the initial image comprises the characteristics of a face area of a target object;
judging whether the target object is in a mask wearing state or not according to the characteristics of the face area in the initial image;
if the target object is in a mask wearing state, judging whether the current temperature of the target object is within a preset temperature range;
if the current temperature of the target object is within a preset temperature range, determining that the target object passes identification verification;
and if the target object is in a state of not wearing a mask, or the current temperature of the target object is not in the preset range, determining that the target object does not pass the identification verification.
According to a specific implementation manner of the embodiment of the present disclosure, after the step of acquiring the initial image of the preset region, the method further includes:
acquiring a face key point of the target object according to the initial image;
extracting facial feature information of the target object according to the face key points;
searching whether target identity information matched with the facial feature information of the target object exists in a preset identity information base;
if the current temperature of the target object is within a preset temperature range, determining that the target object passes the identification verification, wherein the step comprises the following steps of:
and if the target identity information matched with the facial feature information of the target object is found and the current temperature of the target object is within a preset temperature range, determining that the target object passes identification verification.
According to a specific implementation manner of the embodiment of the present disclosure, the step of determining whether the target object is in a mask wearing state according to the face image in the initial image includes:
judging whether the face key point information contains lip related key points of the target object, wherein the lip related key points comprise at least two of nose key points, mouth key points and chin key points;
if the key points of the face comprise key points related to lips of the target object, judging that the target object is in a mask-not-wearing state;
and if the face key points do not comprise the lip related key points, judging that the target object is in a mask wearing state.
According to a specific implementation manner of the embodiment of the present disclosure, after the step of acquiring the initial image of the preset region, the method further includes:
reading preset type certificate information of the target object;
searching whether target identity information matched with the certificate information of the target object exists in a preset identity information base;
if the current temperature of the target object is within a preset temperature range, determining that the target object passes the identification verification, wherein the step comprises the following steps of:
and if the target identity information matched with the certificate information of the target object is found and the current temperature of the target object is within a preset range, determining that the target object passes the identification verification.
According to a specific implementation manner of the embodiment of the present disclosure, before the step of acquiring the initial image of the preset region, the method further includes:
detecting whether a living object exists in the preset area or not;
and if the living body object exists in the preset area, executing the step of acquiring the initial image of the preset area.
According to a specific implementation manner of the embodiment of the present disclosure, the step of determining whether the current temperature of the target object is within a preset temperature range includes:
prompting that the target object is close to a preset temperature measurement site;
continuously acquiring temperature data of the target object for N times, wherein N is a positive integer;
and screening the highest temperature value in the temperature data for N times as the current temperature of the target object.
According to a specific implementation manner of the embodiment of the present disclosure, before the step of continuously acquiring the temperature data of the target object N times, the method further includes:
collecting coordinates corresponding to the face area of the target object;
judging whether the face area of the target object is overlapped with the preset temperature measuring site or not according to the coordinates corresponding to the face area of the target object;
and if the face area of the target object is superposed with the preset temperature measuring site, continuously acquiring the temperature data of the target object for N times.
According to a specific implementation manner of the embodiment of the present disclosure, before the step of acquiring the initial image of the preset region, the method further includes:
acquiring a basic face image of a registered person in a state that the registered person does not wear a mask;
covering the mask image layer on the face identity image to obtain an upgraded face image;
inputting all basic face images and corresponding upgraded face images into a deep neural network or a basic recognition model for learning training to obtain an upgraded recognition model, and inputting the basic face images and the corresponding upgraded face images into the preset identity information base;
the step of extracting the facial feature information of the target object according to the face key points comprises the following steps:
and extracting facial feature information of the target object by using the upgrading identification model.
In a second aspect, an embodiment of the present disclosure provides an identification verification apparatus, including:
the system comprises an acquisition module, a display module and a processing module, wherein the acquisition module is used for acquiring an initial image of a preset area, and the initial image comprises the characteristics of a face area of a target object;
the first judging module is used for judging whether the target object is in a mask wearing state or not according to the characteristics of the face area in the initial image;
the second judgment module is used for judging whether the current temperature of the target object is within a preset temperature range or not if the target object is judged to be in a mask wearing state;
the determination module is used for determining that the target object passes the identification verification if the current temperature of the target object is within a preset temperature range, and determining that the target object does not pass the identification verification if the target object is in a state that the mask is not worn or the current temperature of the target object is not within the preset range.
In a third aspect, an embodiment of the present disclosure further provides an electronic device, where the electronic device includes:
at least one processor; and the number of the first and second groups,
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of the first aspect or any implementation manner of the first aspect.
In a fourth aspect, the disclosed embodiments also provide a non-transitory computer-readable storage medium storing computer instructions for causing a computer to perform the identification verification method of the first aspect or any implementation manner of the first aspect.
In a fifth aspect, the present disclosure also provides a computer program product, which includes a computer program stored on a non-transitory computer-readable storage medium, the computer program including program instructions, which, when executed by a computer, cause the computer to perform the identification verification method in the foregoing first aspect or any implementation manner of the first aspect.
The scheme is verified in this identification in the embodiment, through set up in the identification verification process and detect earlier to the gauze mask state of wearing to and the scheme that current temperature detected, can select automatically, accurately and wear the gauze mask and the normal personnel of current temperature pass identification verification, and do not wear gauze mask or the unusual user of current temperature value then directly do not pass verification, and like this, the user need not to take off the gauze mask in order to effectively avoid the cross infection that probably exists, has also reduced detection personnel's work load and exposure infection risk, has improved the detection efficiency and the security of special period.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present disclosure, the drawings needed to be used in the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present disclosure, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a schematic flow chart of an identification verification method according to an embodiment of the present disclosure;
fig. 2 to 11 are schematic flow diagrams of various specific implementations of an identification verification method according to an embodiment of the present disclosure;
fig. 12 is a schematic structural diagram of an identification verification apparatus according to an embodiment of the present disclosure;
fig. 13 is a schematic view of an electronic device provided in an embodiment of the present disclosure.
Detailed Description
The embodiments of the present disclosure are described in detail below with reference to the accompanying drawings.
The embodiments of the present disclosure are described below with specific examples, and other advantages and effects of the present disclosure will be readily apparent to those skilled in the art from the disclosure in the specification. It is to be understood that the described embodiments are merely illustrative of some, and not restrictive, of the embodiments of the disclosure. The disclosure may be embodied or carried out in various other specific embodiments, and various modifications and changes may be made in the details within the description without departing from the spirit of the disclosure. It is to be noted that the features in the following embodiments and examples may be combined with each other without conflict. All other embodiments, which can be derived by a person skilled in the art from the embodiments disclosed herein without making any creative effort, shall fall within the protection scope of the present disclosure.
It is noted that various aspects of the embodiments are described below within the scope of the appended claims. It should be apparent that the aspects described herein may be embodied in a wide variety of forms and that any specific structure and/or function described herein is merely illustrative. Based on the disclosure, one skilled in the art should appreciate that one aspect described herein may be implemented independently of any other aspects and that two or more of these aspects may be combined in various ways. For example, an apparatus may be implemented and/or a method practiced using any number of the aspects set forth herein. Additionally, such an apparatus may be implemented and/or such a method may be practiced using other structure and/or functionality in addition to one or more of the aspects set forth herein.
It should be noted that the drawings provided in the following embodiments are only for illustrating the basic idea of the present disclosure, and the drawings only show the components related to the present disclosure rather than the number, shape and size of the components in actual implementation, and the type, amount and ratio of the components in actual implementation may be changed arbitrarily, and the layout of the components may be more complicated.
In addition, in the following description, specific details are provided to facilitate a thorough understanding of the examples. However, it will be understood by those skilled in the art that the aspects may be practiced without these specific details.
The embodiment of the disclosure provides an identification verification method. The identification verification method provided by the present embodiment may be executed by a computing device, which may be implemented as software, or implemented as a combination of software and hardware, and may be integrally provided in a server, a terminal device, or the like.
Referring to fig. 1, a schematic flow chart of an identification verification method according to an embodiment of the present disclosure is shown. As shown in fig. 1, the method mainly comprises the following steps:
s101, acquiring an initial image of a preset area, wherein the initial image comprises the characteristics of a face area of a target object;
the identification verification method provided by the embodiment of the disclosure is applied to identification verification occasions with special requirements, such as identification verification in the fields of channel gates, security inspection and the like during epidemic situations of infectious diseases. In these special periods, automatic detection and result output of the wearing state and temperature of the mask of the person are required in combination with image recognition technology.
In specific implementation, a user to be detected is defined as a target object, and a waiting area entering an identification verification process is defined as a preset area, wherein the preset area is usually an inlet area of a gate channel. The target object enters a preset area, the electronic equipment collects an initial image of the preset area, and the collected initial image comprises the characteristics of a face area of the target object and at least comprises main areas of the mouth, the nose, the eyes and the like of the face of the target object.
S102, judging whether the target object is in a mask wearing state or not according to the characteristics of the face area in the initial image;
after the initial image of the preset area is acquired according to the steps, whether the target object is in a mask wearing state or not can be judged according to the characteristics of the face area in the initial image. If the target object is in a mask wearing state, the lip related area of the target object is a mask with uniform pixel and color characteristics, and original mouth, nose or chin characteristics are covered. The electronic device can judge whether the target object is in a mask wearing state according to the pixel characteristic attribute of the area.
If the target object is in the mask wearing state, executing step S103, and judging whether the current temperature of the target object is within a preset temperature range;
in consideration of the epidemic situation, the body temperature of the user is a direct parameter which can accurately reflect the infection state or the health state of the user, and the detection flow is simple and rapid, so that the process of judging the temperature of the user is added. A preset temperature range is set in the electronic device, for example, the temperature range corresponding to human health is 34.0 to 37.5 ℃. Of course, other temperature ranges may be set according to specific needs, and are not limited.
The electronic device is internally or externally connected with a temperature acquisition device, such as an infrared temperature detector, for acquiring the temperature of a user. And if the electronic equipment judges that the target object is in a mask wearing state according to the steps, continuing to perform the next operation, namely acquiring the current temperature of the target object to judge whether the current temperature is within a preset temperature range.
If the current temperature of the target object is within the preset temperature range, executing step S104, and determining that the target object passes identification and verification;
if the target object is in a state of not wearing a mask, or the current temperature of the target object is not within the preset range, step S105 is executed to determine that the target object fails to pass identification verification.
And if the electronic equipment passes the detection and analysis, the target object is judged to be in a mask wearing state, and the current temperature is within a preset temperature range, the target object is determined to pass the identification verification, and then a gate channel is opened or other subsequent processes corresponding to the identification verification can be executed. Correspondingly, after the electronic equipment detects and analyzes, the target object is judged to be in a state that the mask is not worn, or the current temperature is not within a preset temperature range, the target object is determined not to pass the identification and verification, and accordingly, the gate opening or other corresponding subsequent processes are not executed correspondingly, or the voice alarm prompts a worker to perform special monitoring processing on the target object.
In the embodiment, for saving detection operation, body temperature detection is performed after the target object is determined to be in a mask wearing state, and if the target object is determined to be in a mask not wearing state, it is directly determined that identification verification is not passed. Of course, the detection order of the wearing state and the temperature of the mask may be changed, or both types of detection may be performed simultaneously and then the determination may be made comprehensively according to the result, without limitation.
Above-mentioned identification verification scheme in this embodiment of this disclosure detects earlier to the gauze mask wearing state through addding in identification verification process to and current temperature detection's scheme, can select automatically, accurately to wear the gauze mask and the normal personnel of current temperature pass identification verification, and does not wear gauze mask or the unusual user of current temperature value then directly not pass verification, and like this, the user need not to take off the gauze mask in order effectively to avoid the cross infection that probably exists, has also reduced measurement personnel's work load and exposure infection risk, has improved the detection efficiency and the security of special period.
In order to further improve the identification and verification capability, a process of identity verification according to the facial features is added. According to a specific implementation manner of the embodiment of the present disclosure, after the step of acquiring the initial image of the preset region, the method further includes:
acquiring a face key point of the target object according to the initial image;
extracting facial feature information of the target object according to the face key points;
searching whether target identity information matched with the facial feature information of the target object exists in a preset identity information base;
if the current temperature of the target object is within a preset temperature range, determining that the target object passes the identification verification, wherein the step comprises the following steps of:
and if the target identity information matched with the facial feature information of the target object is found and the current temperature of the target object is within a preset temperature range, determining that the target object passes identification verification.
In specific implementation, after acquiring an initial image of a preset region, the electronic device acquires face key points of a target object, such as eye key points, nose key points, eyebrow key points, mouth key points, ear key points, and the like, according to the initial image. After the electronic device acquires all or part of the key points, facial feature information of the target object, such as eye features, iris information, facial contour features and the like, is extracted according to pixel pigment channel values or other attribute values of the key points, and the extracted facial feature information of the target object is used for a subsequent identification process of the target object.
A preset identity information base is configured in the electronic equipment, and the preset identity information base comprises identity information of a plurality of registered persons, such as face feature information, certificate information and the like. After extracting the facial feature information of the target object, the electronic equipment searches for matching in a preset identity information base to find whether personnel identity information matched with the facial feature information of the target object exists or not, the found identity information is defined as target identity information, and the target identity information can be determined as the identity information of the target object.
If the target identity information matched with the facial feature information of the target object is found, and the target object passes the previous mask wearing state detection and temperature detection, the target object can be determined to pass the identification verification. It should be noted that the sequence of the identity information matching, the mask wearing state detection and the temperature detection may be properly adjusted without limitation. The embodiment adds the process of matching the facial feature information of the target object to be detected with the identity information in the identity information base of the registered personnel, is suitable for the identity information verification and safety passing verification requirements of the registered people such as companies and groups, and further improves the efficiency of identification verification.
Further, according to a specific implementation manner of the embodiment of the present disclosure, the step of determining whether the target object is in a mask wearing state according to the face image in the initial image may further include:
judging whether the face key point information contains lip related key points of the target object, wherein the lip related key points comprise at least two of nose key points, mouth key points and chin key points;
if the key points of the face comprise key points related to lips of the target object, judging that the target object is in a mask-not-wearing state;
and if the face key points do not comprise the lip related key points, judging that the target object is in a mask wearing state.
The present embodiment further defines a specific implementation of the mask wearing state. Considering that when a user wears the mask, the lip area of the user is in a shielding state, the mouth, the nose or the chin is usually shielded by the mask, and whether the user wears the mask is judged according to the detection state of the key point associated with the lip area.
After all face key points of the target object are obtained according to the steps, whether all face key points contain lip related key points, namely at least two of nose key points, mouth key points and chin key points is judged. If the key points of the face comprise key points related to the lips of the target object, it indicates that the lip area of the target object is not blocked, and it can be determined that the target object is in a state of not wearing a mask. If the detected face key points do not include the key points related to the lips of the target object, the fact that the lip area of the target object is blocked is indicated, and the target object can be judged to be in a mask wearing state.
Therefore, the mask wearing state of the user is judged according to the acquirable state of the key points in the lip region, the calculation is simple and accurate, and the detection efficiency is high.
In addition, according to another specific implementation manner of the embodiment of the present disclosure, after the step of acquiring the initial image of the preset region, the method may further include:
reading preset type certificate information of the target object;
searching whether target identity information matched with the certificate information of the target object exists in a preset identity information base;
if the current temperature of the target object is within a preset temperature range, determining that the target object passes the identification verification, wherein the step comprises the following steps of:
and if the target identity information matched with the certificate information of the target object is found and the current temperature of the target object is within a preset range, determining that the target object passes the identification verification.
According to the embodiment, the process of verifying the certificate information of the user is added. The preset identity information base configured in the electronic equipment contains identity information of registered personnel, and the identity information also comprises certificate information, such as identity card information or work card information. The electronic equipment collects the certificate information through recognition reading or photographing, and then matches the collected certificate information with the identity information in a preset identity information base to determine the identity information of the target object.
If the target identity information matched with the certificate information of the target object is found, and the target object passes the previous mask wearing state detection and temperature detection, the target object can be determined to pass the identification verification. It should be noted that the sequence of certificate matching, mask wearing state detection and temperature detection may be properly adjusted, or the accuracy of identification and verification may be further enhanced by combining the above-mentioned facial features and certificate verification, without limitation.
According to a specific implementation manner of the embodiment of the present disclosure, before the step of acquiring the initial image of the preset region, the method further includes:
detecting whether a living object exists in the preset area or not;
and if the living body object exists in the preset area, executing the step of acquiring the initial image of the preset area.
In the present embodiment, before performing all the identification verification operations, the living body object is detected in the preset area, and for example, an infrared detection device is used to detect whether a living body enters the preset area. The electronic equipment can continuously and periodically acquire whether a living body object exists in the preset area, the subsequent initial image acquisition and identification verification process can be carried out only when the living body exists in the preset area, and if the living body does not exist in the preset area, the electronic equipment continues to detect whether the living body object exists in the preset area until the living body object exists in the preset area. Therefore, unnecessary calculation work of image acquisition and identification verification can be effectively reduced.
In another specific implementation manner of the embodiment of the present disclosure, the step of determining whether the current temperature of the target object is within a preset temperature range may include:
prompting that the target object is close to a preset temperature measurement site;
continuously acquiring temperature data of the target object for N times, wherein N is a positive integer;
and screening the highest temperature value in the temperature data for N times as the current temperature of the target object.
Further, before the step of continuously acquiring temperature data of the target object N times, the method further includes:
collecting coordinates corresponding to the face area of the target object;
judging whether the face area of the target object is overlapped with the preset temperature measuring site or not according to the coordinates corresponding to the face area of the target object;
and if the face area of the target object is superposed with the preset temperature measuring site, continuously acquiring the temperature data of the target object for N times.
The best face temperature measurement position is preferably utilized to improve the temperature measurement accuracy. The method for acquiring the optimal face temperature measurement position comprises the following steps: fixing the relative positions of a camera and a thermodetector of the face recognition equipment; after repeated manual testing is carried out to obtain the optimal temperature measurement position, calculating the coordinate of the face in the camera picture, and setting the coordinate as the optimal face temperature measurement position; when the overlapping rate of the human face in the picture of the camera and the optimal temperature measurement position is larger than a certain threshold value in the using process, the temperature measurement is started again. When the infrared thermal imaging thermometer is used, if high-temperature objects such as a vacuum cup, an incandescent lamp and the like appear in an infrared thermal imaging picture, the temperature measurement effect can be influenced, and the influence of non-human high-temperature objects on temperature measurement can be reduced in a key area temperature fitting mode. The specific method comprises the following steps: fixing the relative positions of a camera and a thermodetector of the face recognition equipment; finding a position mapping relation between a camera picture of the face recognition equipment and an infrared thermal imaging picture; in the actual use process, according to the position coordinates obtained by the face recognition equipment, only the maximum temperature value in the corresponding area in the infrared thermal imaging picture is obtained, but not the maximum temperature value in the whole picture.
Before the formal identification verification process is carried out, a training process of the identification verification model can be further included. According to a specific implementation manner of the embodiment of the present disclosure, before the step of acquiring the initial image of the preset region, the method may further include:
acquiring a basic face image of a registered person in a state that the registered person does not wear a mask;
covering the mask image layer on the face identity image to obtain an upgraded face image;
inputting all basic face images and corresponding upgraded face images into a deep neural network or a basic recognition model for learning training to obtain an upgraded recognition model, and inputting the basic face images and the corresponding upgraded face images into the preset identity information base;
the step of extracting the facial feature information of the target object according to the face key points comprises the following steps:
and extracting facial feature information of the target object by using the upgrading identification model.
During the concrete implementation, after collecting a large amount of gauze mask data sets, retrain original basic recognition model M1 or degree of depth neural network, can obtain the upgrading recognition model M2 of having strengthened gauze mask discernment ability, can make the differentiation to whether the personnel correctly wear the gauze mask, can carry out face identification to wearing gauze mask personnel simultaneously. In the face recognition apparatus using M1 or M2 as a recognition model, a feature library L is obtained by performing feature registration using a user's normal photograph, i.e., a photograph of a person who is not wearing a mask.
The above embodiments describe various embodiments of the identification verification method, and will be explained below with reference to specific implementations. The electronic equipment collects an initial image when a living body object is detected, and can extract the features of the human face to obtain features F, namely the overall features when the human face is in a wearing state. The electronic equipment can respectively carry out mask detection, living body detection, identification detection and temperature detection, and the detection results are formed into four judgment conditions which are respectively marked as C1, C2, C3 and C4. The four detection sequences and switches can be configured according to actual conditions.
The mask detection judges whether the mask is worn correctly by a detection target. If the face wears the mask normally, recording C1 as TRUE; if the mask is not worn or not worn correctly, if the nose or mouth is not covered by the mask, the mask is judged to fail to be detected, and C1 is recorded as FALSE.
The living body detection judges whether the detection target is a living body, if the human face passes the living body judgment, C2 is recorded as TURE, otherwise, the detection target is recorded as FALSE.
And identifying, detecting and judging whether the facial features with similarity scores exceeding a threshold score with F exist in the feature library L, if so, recording C3 as TURE, otherwise, recording as FALSE. According to the temperature detection, according to different temperature measurement modes such as forehead temperature and wrist temperature, the face recognition device prompts a user to approach a temperature measurement point in a proper mode, the temperature measurement modules circularly measure the temperature at intervals of certain time T (different according to different types of temperature measurement modules), and after N times of temperature reading, body temperature judgment is carried out. And if the maximum value of the temperature in the N times of reading is in a reasonable body temperature range, judging that the body temperature is normal, and recording C4 as TRUE, otherwise, recording as FALSE.
In different cases, the various detection decisions can be combined in different forms, adapting different actual scenarios in different modes, for example:
1. face comparison and temperature measurement:
as shown in fig. 2, the human face + thermometry mode, i.e. live body detection, identification detection (i.e. facial feature detection and identity information matching, the same below), and temperature detection are performed in parallel, and if C2& C3& C4 is TRUE, the identification is passed;
as shown in fig. 3, in the face and mask mode, mask detection is performed first, and then recognition detection and living body detection are performed in parallel, and if C1& C2& C3 is TRUE, recognition is passed;
as shown in fig. 4, in the face recognition + mask + body temperature detection mode, mask detection and body temperature detection are performed in parallel, and after passing the mask detection, recognition detection and living body detection are performed, and if C1& C2& C3& C4 is TRUE, the recognition is passed;
as shown in fig. 5, the human face is identified first, then the temperature is measured, and finally the identification result is processed, and all the detections are processed in series;
as shown in fig. 6, mask detection is performed first, face recognition is performed, temperature measurement is performed, the recognition result is processed, and all detection is processed serially.
2. Card swiping and temperature measurement:
as shown in fig. 7, card swiping comparison is performed first, temperature measurement is performed, and the identification result is processed and processed in series;
3. comparing the testimony with the certificate and measuring the temperature:
as shown in fig. 7, the device is externally connected with an identity card reader, detects identity card information, performs temperature measurement while performing people-card comparison, and finally processes the total result;
referring to fig. 8, the device is externally connected with an identity card reader, detects the identity card information, measures the temperature after the people and the card are successfully compared, and finally processes the total result.
Depending on the configuration, the actually generated decision modes include, but are not limited to, the above.
As shown in fig. 10, the optimal face thermometry position can be used to improve the accuracy of thermometry. The method for acquiring the optimal face temperature measurement position comprises the following steps: fixing the relative positions of a camera and a thermodetector of the face recognition equipment; after repeated manual testing is carried out to obtain the optimal temperature measurement position, calculating the coordinate of the face in the camera picture, and setting the coordinate as the optimal face temperature measurement position; when the overlapping rate of the human face in the picture of the camera and the optimal temperature measurement position is larger than a certain threshold value in the using process, the temperature measurement is started again.
As shown in fig. 11, when the infrared thermal imaging thermometer is used, if high-temperature objects such as a thermos cup and an incandescent lamp appear in an infrared thermal imaging picture, the temperature measurement effect is affected, and the influence of non-human high-temperature objects on temperature measurement can be reduced by means of key region temperature fitting. The specific method comprises the following steps: fixing the relative positions of a camera and a thermodetector of the face recognition equipment; finding a position mapping relation between a camera picture of the face recognition equipment and an infrared thermal imaging picture; in the actual use process, according to the position coordinates obtained by the face recognition equipment, only the maximum temperature value in the corresponding area in the infrared thermal imaging picture is obtained, but not the maximum temperature value in the whole picture.
In correspondence with the above method embodiment, referring to fig. 12, the disclosed embodiment further provides an identification verification apparatus 120, including:
an acquisition module 1201, configured to acquire an initial image of a preset region, where the initial image includes features of a face region of a target object;
a first judging module 1202, configured to judge whether the target object is in a mask wearing state according to a feature of a face region in the initial image;
a second determining module 1203, configured to determine whether a current temperature of the target object is within a preset temperature range if it is determined that the target object is in a mask wearing state;
a determining module 1204, configured to determine that the target object passes the identification verification if the current temperature of the target object is within a preset temperature range, and determine that the target object does not pass the identification verification if the target object is in a state where the mask is not worn or if the current temperature of the target object is not within the preset range.
The apparatus shown in fig. 12 may correspondingly execute the content in the above method embodiment, and details of the part not described in detail in this embodiment refer to the content described in the above method embodiment, which is not described again here.
Referring to fig. 13, an embodiment of the present disclosure also provides an electronic device 130, including:
at least one processor; and the number of the first and second groups,
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of identification verification of the preceding method embodiments.
The disclosed embodiments also provide a non-transitory computer-readable storage medium storing computer instructions for causing the computer to perform the identification verification method in the aforementioned method embodiments.
The disclosed embodiments also provide a computer program product comprising a computer program stored on a non-transitory computer readable storage medium, the computer program comprising program instructions which, when executed by a computer, cause the computer to perform the identification verification method in the aforementioned method embodiments.
Referring now to FIG. 13, a block diagram of an electronic device 130 suitable for use in implementing embodiments of the present disclosure is shown. The electronic devices in the embodiments of the present disclosure may include, but are not limited to, mobile terminals such as mobile phones, notebook computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), in-vehicle terminals (e.g., car navigation terminals), and the like, and fixed terminals such as digital TVs, desktop computers, and the like. The electronic device shown in fig. 13 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present disclosure.
As shown in fig. 13, the electronic device 130 may include a processing means (e.g., a central processing unit, a graphics processor, etc.) 1301 that may perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM)1302 or a program loaded from a storage device 1308 into a Random Access Memory (RAM) 1303. In the RAM 1303, various programs and data necessary for the operation of the electronic apparatus 130 are also stored. The processing device 1301, the ROM 1302, and the RAM 1303 are connected to each other via a bus 1304. An input/output (I/O) interface 1305 is also connected to bus 1304.
Generally, the following devices may be connected to the I/O interface 1305: input devices 1306 including, for example, touch screens, touch pads, keyboards, mice, image sensors, microphones, accelerometers, gyroscopes, and the like; an output device 1307 including, for example, a Liquid Crystal Display (LCD), speaker, vibrator, etc.; storage devices 1308 including, for example, magnetic tape, hard disk, etc.; and a communication device 1309. The communication means 1309 may allow the electronic device 130 to communicate wirelessly or by wire with other devices to exchange data. While the figures illustrate an electronic device 130 having various means, it is to be understood that not all illustrated means are required to be implemented or provided. More or fewer devices may alternatively be implemented or provided.
In particular, according to an embodiment of the present disclosure, the processes described above with reference to the flowcharts may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method illustrated in the flow chart. In such embodiments, the computer program may be downloaded and installed from a network via the communication means 1309, or installed from the storage device 1308, or installed from the ROM 1302. The computer program, when executed by the processing apparatus 1301, performs the functions defined in the methods of the embodiments of the present disclosure.
It should be noted that the computer readable medium in the present disclosure can be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present disclosure, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In contrast, in the present disclosure, a computer readable signal medium may comprise a propagated data signal with computer readable program code embodied therein, either in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: electrical wires, optical cables, RF (radio frequency), etc., or any suitable combination of the foregoing.
The computer readable medium may be embodied in the electronic device; or may exist separately without being assembled into the electronic device.
The computer readable medium carries one or more programs which, when executed by the electronic device, enable the electronic device to implement the schemes provided by the method embodiments.
Alternatively, the computer readable medium carries one or more programs, which when executed by the electronic device, enable the electronic device to implement the schemes provided by the method embodiments.
Computer program code for carrying out operations for aspects of the present disclosure may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + +, and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units described in the embodiments of the present disclosure may be implemented by software or hardware. Where the name of a unit does not in some cases constitute a limitation of the unit itself, for example, the first retrieving unit may also be described as a "unit for retrieving at least two internet protocol addresses".
It should be understood that portions of the present disclosure may be implemented in hardware, software, firmware, or a combination thereof.
The above description is only for the specific embodiments of the present disclosure, but the scope of the present disclosure is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present disclosure should be covered within the scope of the present disclosure. Therefore, the protection scope of the present disclosure shall be subject to the protection scope of the claims.
Claims (10)
1. An identification verification method, comprising:
acquiring an initial image of a preset area, wherein the initial image comprises the characteristics of a face area of a target object;
judging whether the target object is in a mask wearing state or not according to the characteristics of the face area in the initial image;
if the target object is in a mask wearing state, judging whether the current temperature of the target object is within a preset temperature range;
if the current temperature of the target object is within a preset temperature range, determining that the target object passes identification verification;
and if the target object is in a state of not wearing a mask, or the current temperature of the target object is not in the preset range, determining that the target object does not pass the identification verification.
2. The method of claim 1, wherein after the step of acquiring an initial image of the preset area, the method further comprises:
acquiring a face key point of the target object according to the initial image;
extracting facial feature information of the target object according to the face key points;
searching whether target identity information matched with the facial feature information of the target object exists in a preset identity information base;
if the current temperature of the target object is within a preset temperature range, determining that the target object passes the identification verification, wherein the step comprises the following steps of:
and if the target identity information matched with the facial feature information of the target object is found and the current temperature of the target object is within a preset temperature range, determining that the target object passes identification verification.
3. The method according to claim 2, wherein the step of determining whether the target object is in a mask wearing state based on the face image in the initial image comprises:
judging whether the face key point information contains lip related key points of the target object, wherein the lip related key points comprise at least two of nose key points, mouth key points and chin key points;
if the key points of the face comprise key points related to lips of the target object, judging that the target object is in a mask-not-wearing state;
and if the face key points do not comprise the lip related key points, judging that the target object is in a mask wearing state.
4. The method of claim 2, wherein after the step of acquiring an initial image of the preset area, the method further comprises:
reading preset type certificate information of the target object;
searching whether target identity information matched with the certificate information of the target object exists in a preset identity information base;
if the current temperature of the target object is within a preset temperature range, determining that the target object passes the identification verification, wherein the step comprises the following steps of:
and if the target identity information matched with the certificate information of the target object is found and the current temperature of the target object is within a preset range, determining that the target object passes the identification verification.
5. The method of claim 4, wherein the step of acquiring an initial image of the preset area is preceded by the method further comprising:
detecting whether a living object exists in the preset area or not;
and if the living body object exists in the preset area, executing the step of acquiring the initial image of the preset area.
6. The method according to any one of claims 1 to 5, wherein the step of determining whether the current temperature of the target object is within a preset temperature range comprises:
prompting that the target object is close to a preset temperature measurement site;
continuously acquiring temperature data of the target object for N times, wherein N is a positive integer;
and screening the highest temperature value in the temperature data for N times as the current temperature of the target object.
7. The method of claim 6, wherein prior to the step of acquiring temperature data of the target object N times in succession, the method further comprises:
collecting coordinates corresponding to the face area of the target object;
judging whether the face area of the target object is overlapped with the preset temperature measuring site or not according to the coordinates corresponding to the face area of the target object;
and if the face area of the target object is superposed with the preset temperature measuring site, continuously acquiring the temperature data of the target object for N times.
8. The method of claim 1, wherein the step of acquiring an initial image of the preset area is preceded by the method further comprising:
acquiring a basic face image of a registered person in a state that the registered person does not wear a mask;
covering the mask image layer on the face identity image to obtain an upgraded face image;
inputting all basic face images and corresponding upgraded face images into a deep neural network or a basic recognition model for learning training to obtain an upgraded recognition model, and inputting the basic face images and the corresponding upgraded face images into the preset identity information base;
the step of extracting the facial feature information of the target object according to the face key points comprises the following steps:
and extracting facial feature information of the target object by using the upgrading identification model.
9. An identification verification apparatus, comprising:
the system comprises an acquisition module, a display module and a processing module, wherein the acquisition module is used for acquiring an initial image of a preset area, and the initial image comprises the characteristics of a face area of a target object;
the first judging module is used for judging whether the target object is in a mask wearing state or not according to the characteristics of the face area in the initial image;
the second judgment module is used for judging whether the current temperature of the target object is within a preset temperature range or not if the target object is judged to be in a mask wearing state;
the determination module is used for determining that the target object passes the identification verification if the current temperature of the target object is within a preset temperature range, and determining that the target object does not pass the identification verification if the target object is in a state that the mask is not worn or the current temperature of the target object is not within the preset range.
10. An electronic device, characterized in that the electronic device comprises:
at least one processor; and the number of the first and second groups,
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the identification verification method of any one of the preceding claims 1-8.
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