CN111583593A - Dual-band self-adaptive intelligent temperature measurement face recognition method - Google Patents
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Abstract
The utility model provides a two wave band self-adaptation wisdom temperature measurement face identification system, passes through the accurate matching of image fusion technique with visible light image and infrared image to the gauze mask state of wearing optimizes recognition algorithm, but intellectual detection system effective area temperature. When the temperature of a person is found to be abnormal, the alarm can be automatically given. If the person is in the face library, the name of the person is recognized and recorded in an auxiliary mode. The intelligent anti-epidemic monitoring system is an intelligent safety and anti-epidemic monitoring system which integrates a visible light wave band, an infrared wave band, a temperature measuring function, a face detection function, a face recognition function and a face recognition function under the condition of wearing a mask, so that the non-contact, low-error and high-efficiency black body-free ultra-precision body temperature detection application is achieved.
Description
Technical Field
The invention belongs to the field of artificial intelligence, and relates to an intelligent image face recognition and interaction hardware device and software processing intelligent monitoring equipment.
Background
How to use more strict prevention and control measures in a wide range of public places to ensure accurate temperature measurement and improve temperature measurement efficiency and avoid cross infection is effective prevention and control preparation aiming at population flow pressure multiplication. Various infrared thermometers for erection are emerged in the market at present, from thousands of yuan to tens of thousands of yuan, which can mean 'fish dragon mixing', most cheap infrared thermal imager thermometers do not have a face recognition function, the false alarm rate is very high, the thermometers cannot be effectively applied, the error of the thermometers is large, a calibrated temperature precision of +/-0.5 ℃ can actually bring a temperature span of 1 ℃, the body temperature measurement is extremely inaccurate, the view field is very small, the action route of personnel needs to be regulated, and the large-range non-sensible temperature measurement capability cannot be realized. The high-end method is based on an infrared and visible light binocular camera, real-time display of true color images is achieved, simultaneous detection of multiple people is achieved, the recognition error can be within the range of +/-0.5 ℃ to +/-0.3 ℃, however, due to the change of the environment temperature, the temperature measurement result can be changed accordingly, on one hand, the reason is that the infrared thermal imager is too low in cost, the temperature measurement precision is low, the effective temperature measurement position is inaccurate, and on the other hand, due to the fact that the temperature measurement result of the infrared thermal imager can change along with the change of the environment temperature, accurate results cannot be obtained under different temperature environments.
Disclosure of Invention
According to the invention, the visible light image and the infrared image are accurately matched through an image fusion technology, the identification algorithm is optimized according to the wearing state of the mask, the temperature of an effective area can be intelligently detected, the environmental temperature value can be obtained, and the temperature correction value after the environmental temperature is self-adapted is calculated through a formula, so that the accurate values of temperature measurement under different environments can be obtained. When the temperature of a person is found to be abnormal, the alarm can be automatically given. And if the person is successfully matched with the face in the face library, assisting in identifying the name of the person and recording. The intelligent epidemic prevention monitoring system is an intelligent epidemic prevention monitoring system which integrates a visible light wave band, an infrared wave band, a temperature measuring function, a face detection function, a face recognition function and a face recognition function under the condition of wearing a mask.
It is worth mentioning that the adjustment according to the adaptive offset value under different environmental temperatures is innovatively provided, only the parameters required by the calculation formula are obtained by calibrating the machine with a constant temperature object when the machine leaves the factory, and the temperature can be measured with high precision without a black body in use.
A dual-band adaptive intelligent temperature measurement face recognition method comprises the following steps:
the first step is as follows: inputting face image information of known personnel into a database;
the second step is that: the system collects infrared images and visible light images;
the third step: the temperature sensor is used for collecting the ambient temperature, the temperature measurement value is corrected according to the adjustment of the self-adaptive deviation value under different ambient temperatures, and therefore the accurate value of temperature measurement under different environments is obtained
The fourth step: automatically identifying the face contour in the image and judging whether the face contour is a measurable face;
the fifth step: automatically identifying a temperature measurement effective area of a face in an image;
and a sixth step: according to the deviation value, detecting the temperature of the effective temperature measurement area with high precision;
the seventh step: capturing an effective temperature measurement face image in real time;
eighth step: matching the temperature measurement face image with a face database, and taking the best matching face higher than a threshold value as a correct matching result;
the ninth step: outputting and presenting the acquired temperature measurement temperature and matching with the face information in real time;
the tenth step: if the matching is successful, the information of the tested personnel is displayed;
the eleventh step: when the temperature of the effective temperature measurement area is abnormal, the automatic alarm is given;
the twelfth step: and keeping the information of all the tested personnel and the body temperature content to the system.
Step 3, adjusting according to the adaptive offset values at different environmental temperatures, obtaining parameters required by a calculation formula only by calibrating the machine with a constant-temperature object when the machine leaves a factory, wherein the parameters T1, T2 and Ti involved in the algorithm formula need to acquire the constant-temperature object B at different environmental temperature values C1, C2 and … Ci before leaving the factory, and the public algorithm is as follows:
setting:
t is the detection temperature; b is the black body temperature, which is a fixed value, such as 36.5 ℃; c is ambient temperature
Then there are:
then when:
Ci＜Cp＜Ci+1
further, the adaptive temperature offset value of step 3 may be calibrated manually.
Furthermore, according to the setting of the user, the related alarm information can be set selectively, including the abnormal body temperature value and the personnel information.
Further, the device for collecting the infrared image and the visible light image in the step 2 is an infrared thermometer and a visible light camera.
Has the advantages that:
the dual-band self-adaptive intelligent temperature measurement face recognition system combines a non-contact infrared camera with an AI technology, intelligently resolves and locks the temperature (forehead) of an effective temperature measurement area of each person, and guarantees accurate and efficient temperature measurement through a self-adaptive deviation value measurement algorithm. The intelligent alarm of abnormal body temperature and the large-range simultaneous temperature measurement of multiple people are realized, the temperature measurement precision can be stabilized within +/-0.2 ℃ by matching the adopted aviation-level thermal infrared imager (without a black body), the optimal temperature measurement distance is 2-6 meters for remote non-contact temperature measurement, the single body temperature detection speed is less than 0.1 second, the face detection speed is less than 0.1 second, and accurate and reliable rapid body temperature screening can be realized by operating a high-precision temperature measurement system device by 1 worker.
The dual-band adaptive intelligent temperature measurement face recognition system aims at the actual requirement of epidemic situation special period on body temperature detection, uses a remote non-sensitive temperature measurement fusion optical technology, combines AI face detection and AI adaptive temperature deviation value adjustment, and achieves non-contact, low-error and high-efficiency black body-free ultra-precision body temperature detection application. Therefore, epidemic prevention and control pain spots caused by the existing handheld temperature detection mode, such as low investigation efficiency, high cross infection probability and the like, can be effectively reduced.
The system can be conveniently deployed in various crowded places such as hospitals, residential areas, institutions, schools, enterprise factories, transportation hubs, business supermarkets and banks, can complete large-range and high-precision body temperature quick screening, is matched with a small amount of rechecks of high-precision temperature measuring equipment, can effectively improve the efficiency, avoids queuing and clustering, and reduces the infection risk.
Description of the drawings:
fig. 1 is a system architecture diagram.
Detailed Description
A dual-band adaptive intelligent temperature measurement face recognition system mainly comprises the following modules, please refer to FIG. 1. The system specifically comprises a system operation host, an infrared thermometer, a visible light camera and a power line.
The system operation host machine is a system software operation carrier, and operates an infrared temperature measurement and visible light fusion algorithm, self-adaptive temperature deviation value measurement, artificial intelligence technology locking temperature measurement effective area, temperature measurement value display function, abnormal body temperature alarm function, face identification matching function, snapshot image storage function and human-computer interaction function.
The infrared thermometer is an infrared image information acquisition end and is also a part for measuring temperature and feeding back a temperature measurement result according to an effective temperature measurement area determined by the system.
The visible light camera is a visible light image information acquisition end and is afraid of face images according to the system.
The power line is a power supply part for the system operation host, the infrared thermometer and the visible light camera.
The user temperature measurement implementation step:
the first step is as follows: a plurality of people wear the mask and enter the temperature measurement area in parallel.
The second step is that: the system implements face recognition non-sensing temperature measurement.
The third step: and (5) giving an alarm in real time for people with abnormal body temperature.
The invention is further illustrated below with reference to specific examples:
the invention at least comprises the following steps:
the first step is as follows: correctly connecting hardware devices and switching on power supply
Specifically, the infrared camera, the visible light camera, the data transmission serial port and the temperature sensor are connected to a system host, the infrared camera and the visible light camera are powered on, and the system host is powered on.
The second step is that: opening system running host and loading system software
Specifically, the automatic operation of the system after the startup can be realized through the startup self-starting and the program self-loading, manual operation intervention is not needed, and the software can be manually started through the software icon on the host.
The third step: operating system running host initialization data
Specifically, software initializes, assigns variables to default values, sets controls to default states, sets relevant contents to be used to ready states, and loads AI models and algorithms required by functions such as face detection.
The fourth step: starting the system, loading data information and infrared and visible light cameras
Specifically, the system acquires related images to a system interface for display through data interaction with an infrared camera and a visible light camera, and loads configuration data, wherein the configuration data comprises basic system information such as camera names, video stream addresses, initial temperature deviation values, over-temperature alarm threshold values, face identification sensitivity, data serial port positions and the like.
The fifth step: temperature measurement interface of system operation host display system
Specifically, the infrared camera starts to collect the field temperature, the visible light camera starts to collect the field image, the related image is output to a software interface after the fusion and calibration of the system, and the interaction with the user is carried out on the system interface through keys and prompt characters, so that the user can carry out the operations of control, calibration, recording, deletion and the like.
And a sixth step: the system automatically runs an offset value measuring program according to the ambient temperature to determine the offset value
Specifically, the temperature sensor is placed in the air, the system acquires the temperature of the current environment from the temperature sensor in real time, the correction quantity of the detected temperature value is determined according to the temperature characteristic curve of the infrared thermometer and the current temperature, and the software output data is the corrected value of the detected temperature, so that the error of the infrared thermometer generated along with the temperature change is corrected.
According to the adjustment of the self-adaptive offset values under different environmental temperatures, the parameters needed by a calculation formula are obtained only by calibrating a machine with a constant-temperature object when the machine leaves a factory, the parameters T1, T2 and Ti involved in the algorithm formula need to acquire the constant-temperature object B under different environmental temperature values C1, C2 and … Ci before leaving the factory, and the public algorithm is as follows:
setting:
t is the detection temperature; b is the black body temperature, which is a fixed value, such as 36.5 ℃; c is ambient temperature
Then there are:
then when:
Ci＜Cp＜Ci+1
the seventh step: when the system finds the face characteristics of the environment, the effective temperature measurement area is automatically identified for temperature measurement
Specifically, the visible light camera preferentially collects environmental information and captures a face image, the system runs the host to perform identification operation, an effective temperature measurement area is determined, the infrared thermometer is controlled to accurately measure the temperature of the effective temperature measurement area, data are fed back to the running host, and the running host displays the face captured image and a temperature measurement result on a system interface in a matching mode.
Eighth step: and (4) simultaneously starting the face recognition function, and if the recognized face features are matched with the face data in the database, displaying the photos in the face database by an interface to represent that the matching is successful.
Specifically, specific face data can be recognized by comparing the current face features with the pre-stored face features, once a matched face is recognized, the system software can perform feedback through preset actions, such as setting welcome words of specific personnel, checking the face, marking and reminding special personnel, and the like.
The ninth step: when the temperature measurement result exceeds the set value in the system, the system gives an alarm in the mode of interface display of a pop-up window, acousto-optic effect and the like.
The tenth step: and after the system gives an alarm, the visible light image captured by the person with abnormal body temperature is marked and displayed.
Further, the user can view this information on the system interface.
The eleventh step: go back to the seventh step
The system operation host can be a desktop computer, a notebook computer, an integrated all-in-one machine and the like, but needs a mouse keyboard or touch screen mode to carry out man-machine interaction operation, and the host can support system software operation. The infrared temperature measuring instrument can be equipment with various brands and models, but different equipment can cause temperature measurement identification accuracy difference. The visible light camera can be equipment of various brands and models, but different equipment can cause different recognition accuracy of effective temperature measurement areas and different face recognition accuracy.
It will be further appreciated by those of skill in the art that the elements and algorithm steps of the examples described in connection with the embodiments disclosed herein may be embodied in a combination of electronic hardware, computer software, or combinations of both, the components and steps of the examples having been described in a functional general sense in the foregoing description for clarity of explanation of interchangeability of hardware and software. The functional specific data representation depends on the specific hardware application and design constraints of the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied in hardware, a software module executed by a processor, or a combination thereof, or may be embodied in a mobile phone. A software module may reside in Random Access Memory (RAM), memory, Read Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, or any other form of storage medium known in the art.
In the description herein, references to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, a schematic representation of the above terms does not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Moreover, various embodiments or examples and features of various embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention, and that variations, modifications, substitutions and alterations can be made to the above embodiments by those of ordinary skill in the art within the scope of the present invention.
The above-described embodiments of the present invention should not be construed as limiting the scope of the present invention. Any other corresponding changes and modifications made according to the technical idea of the present invention should be included in the protection scope of the claims of the present invention.
Claims (5)
1. A dual-band adaptive intelligent temperature measurement face recognition method is characterized by comprising the following steps: the method comprises the following steps:
the first step is as follows: inputting face image information of known personnel into a database;
the second step is that: the system collects infrared images and visible light images;
the third step: the temperature sensor is used for collecting the ambient temperature, the temperature measurement value is corrected according to the adjustment of the self-adaptive deviation value under different ambient temperatures, and therefore the accurate value of temperature measurement under different environments is obtained
The fourth step: automatically identifying the face contour in the image and judging whether the face contour is a measurable face;
the fifth step: automatically identifying a temperature measurement effective area of a face in an image;
and a sixth step: according to the deviation value, detecting the temperature of the effective temperature measurement area with high precision;
the seventh step: capturing an effective temperature measurement face image in real time;
eighth step: matching the temperature measurement face image with a face database, and taking the best matching face higher than a threshold value as a correct matching result;
the ninth step: outputting and presenting the acquired temperature measurement temperature and matching with the face information in real time;
the tenth step: if the matching is successful, the information of the tested personnel is displayed;
the eleventh step: when the temperature of the effective temperature measurement area is abnormal, the automatic alarm is given;
the twelfth step: and keeping the information of all the tested personnel and the body temperature content to the system.
2. The method of claim 1, wherein the method comprises the following steps: step 3, adjusting according to the adaptive offset values at different environmental temperatures, obtaining parameters required by a calculation formula only by calibrating the machine with a constant-temperature object when the machine leaves a factory, wherein the parameters T1, T2 and Ti involved in the algorithm formula need to acquire the constant-temperature object B at different environmental temperature values C1, C2 and … Ci before leaving the factory, and the public algorithm is as follows:
setting:
t is the detection temperature; b is the black body temperature, which is a fixed value, such as 36.5 ℃; c is ambient temperature
Then there are:
then when:
Ci＜Cp＜Ci+1
3. the method of claim 1, wherein the method comprises the following steps: step 3 the adaptive temperature offset value may be manually calibrated.
4. The method of claim 1, wherein the method comprises the following steps: furthermore, according to the setting of the user, the related alarm information can be set selectively, and the related alarm information comprises the abnormal body temperature value and the personnel information.
5. The method of claim 1, wherein the method comprises the following steps: and 2, acquiring the infrared image and the visible light image by using an infrared thermometer and a visible light camera.
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| CN111915686A (en) * | 2020-09-18 | 2020-11-10 | 深圳市商汤科技有限公司 | Calibration method and device and temperature measurement face recognition device |
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| CN112380938A (en) * | 2020-11-04 | 2021-02-19 | 浙江大华技术股份有限公司 | Face recognition and temperature measurement method, device, equipment and medium |
| CN112461374A (en) * | 2020-11-13 | 2021-03-09 | 上海优加利健康管理有限公司 | Infrared temperature measuring equipment |
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Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2000217788A (en) * | 1999-02-01 | 2000-08-08 | Matsushita Electric Ind Co Ltd | Radiation thermometer |
| CN201352153Y (en) * | 2008-09-03 | 2009-11-25 | 袁剑敏 | Non-contact infrared thermometer for human body and object surface |
| CN104215335A (en) * | 2014-09-29 | 2014-12-17 | 中国计量学院 | Wireless infrared temperature measuring device |
| CN106289532A (en) * | 2016-08-05 | 2017-01-04 | 西安西拓电气股份有限公司 | The temperature extracting method of a kind of thermal-induced imagery and device |
| CN107591207A (en) * | 2017-08-24 | 2018-01-16 | 深圳市华盛昌科技实业股份有限公司 | A kind of epidemic situation investigation method, apparatus, system and equipment |
| CN109916517A (en) * | 2017-12-12 | 2019-06-21 | 纬创资通股份有限公司 | Thermal imagery processing system and method |
| CN110411570A (en) * | 2019-06-28 | 2019-11-05 | 武汉高德智感科技有限公司 | Infrared human body temperature screening method based on human testing and human body tracking technology |
-
2020
- 2020-05-06 CN CN202010374803.9A patent/CN111583593A/en active Pending
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2000217788A (en) * | 1999-02-01 | 2000-08-08 | Matsushita Electric Ind Co Ltd | Radiation thermometer |
| CN201352153Y (en) * | 2008-09-03 | 2009-11-25 | 袁剑敏 | Non-contact infrared thermometer for human body and object surface |
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