CN111783546A - Attendance management system using face recognition and temperature measurement - Google Patents
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Abstract
The invention discloses an attendance management system using face recognition and temperature measurement, which comprises a camera, a face recognition system, an infrared thermometer and a power module, wherein the face recognition system comprises a first model recognition module, a second model recognition module, a comparison image screening module, a third model recognition module, an image classification module, an attendance recording module and an infrared temperature measurement module; the power module comprises a first capacitor, a power supply, a first diode, a first triode, a first inductor, a second capacitor, a second triode, a second resistor, a third resistor, a first resistor, a third triode, a second diode, a fourth resistor, a fourth triode, a fifth resistor, a third diode, a storage battery, a sixth resistor, a seventh resistor, an eighth resistor, a fourth diode, a fifth triode and a voltage output end. The circuit of the invention has the advantages of simple structure, low cost, convenient maintenance and high safety and reliability of the circuit.
Description
Technical Field
The invention relates to the field of attendance management, in particular to an attendance management system using face recognition and temperature measurement.
Background
With the development of society, machine learning algorithms are increasingly applied to our daily lives. The data processing efficiency in various industries can be greatly improved by adopting machine learning. At present, many technical schemes for applying face recognition to an attendance system have appeared, however, in the method in the prior art, the recognition algorithm of attendance is very complex, the data processing amount is large, when the number of company personnel is large, the workload required for comparison is also large, the burden of the attendance system is increased, and the attendance efficiency is reduced. The sample images are screened based on the three-family five-eye proportion, the number of the sample images compared according to the features is reduced, the data processing efficiency is improved, and the attendance checking efficiency is further improved. Through setting up infrared thermometer, acquire attendance personnel's body temperature data according to attendance personnel's position, also recorded attendance personnel's body temperature data when accomplishing the attendance record, accomplished attendance and health monitoring simultaneously. Fig. 1 is a schematic circuit diagram of a power supply part of a conventional attendance management system, and it can be seen from fig. 1 that the power supply part of the conventional attendance management system uses a large number of components and parts, has a complex circuit structure, is high in hardware cost, and is inconvenient to maintain. In addition, because the power supply part of the traditional attendance management system lacks corresponding circuit protection functions, for example: the safety and reliability of the circuit are poor due to the lack of the current-limiting protection function.
Disclosure of Invention
The technical problem to be solved by the present invention is to provide an attendance management system using face recognition and temperature measurement, which has a simple circuit structure, low cost, convenient maintenance, and high circuit safety and reliability, and aims to overcome the above defects of the prior art.
The technical scheme adopted by the invention for solving the technical problems is as follows: the attendance management system comprises a camera, a face recognition system, an infrared thermometer and a power module, wherein the camera, the infrared thermometer and the power module are all connected with the face recognition system;
the first model recognition module is used for acquiring an image of an attendance person shot by a camera and detecting a face region image in the image shot by the camera based on a trained Adaboost classifier;
the second model recognition module is used for acquiring a face region image, detecting a lower base point, a left eye outer hairline point, a right eye outer hairline point, a top center hairline point, two segmentation points of three families and four segmentation points of five eyes in the face image by adopting a trained active shape model, determining a face height range according to the distance between the top center hairline point and the lower base point, determining a face width range according to the distance between the left eye outer hairline point and the right eye outer hairline point, calculating proportion information of the three families according to the two segmentation points of the three families and the face height range, and calculating proportion information of the five eyes according to the four segmentation points of the five eyes and the face width range;
the comparison image screening module is used for screening candidate sample image feature vectors from a preset sample feature library according to the identified ratio information of the three families and the ratio information of the five eyes;
the third model recognition module is used for extracting a feature vector of a face region image to be recognized by adopting a trained feature recognition model;
the image classification module is used for calculating Euclidean distances between feature vectors of alternative sample images and feature vectors of a face region image to be recognized, selecting the minimum Euclidean distance obtained through calculation, judging whether the minimum Euclidean distance is smaller than a preset threshold value, if yes, taking the sample image corresponding to the minimum Euclidean distance as the closest sample image, and determining the identity corresponding to the face region image to be recognized according to the identity label of the closest sample image;
the attendance recording module is used for determining the attendance position of an attendance person according to the position of a camera for shooting images when the image classification module identifies the identity corresponding to the face region image, and recording the identity identification information, the current time and the attendance position of the attendance person as attendance records;
the infrared temperature measurement module is used for searching an infrared thermometer closest to the attendance checking position of an attendance checking person when an attendance checking record is newly added to the attendance checking record module, controlling the closest infrared thermometer to measure the body temperature of the attendance checking person, and adding measured body temperature data into the corresponding attendance checking record;
the power supply module comprises a first capacitor, a power supply, a first diode, a first triode, a first inductor, a second capacitor, a second triode, a second resistor, a third resistor, a first resistor, a third triode, a second diode, a fourth resistor, a fourth triode, a fifth resistor, a third diode, a storage battery, a sixth resistor, a seventh resistor, an eighth resistor, a fourth diode, a fifth triode and a voltage output end, wherein one end of the first capacitor is respectively connected with the power supply, the cathode of the first diode, one end of the first resistor, the anode of the second diode, one end of the fifth resistor and one end of the sixth resistor, the anode of the first diode is respectively connected with one end of the first inductor, one end of the second capacitor and the collector of the first triode, the base of the first triode is connected with the collector of the second triode, an emitting electrode of the second triode is respectively connected with the other end of the first inductor, one end of the second resistor and a collector of the fourth triode, the other end of the second resistor is respectively connected with one end of the third resistor, the other end of the first resistor and a base electrode of the third triode, a collector of the third triode is respectively connected with a cathode of the second diode, one end of the fourth resistor and a base electrode of the fourth triode, an emitting electrode of the fourth triode is respectively connected with a cathode of the third diode and an anode of the storage battery, an anode of the third diode is respectively connected with the other end of the fifth resistor and one end of the seventh resistor, the other end of the seventh resistor is respectively connected with one end of the eighth resistor and a base electrode of the fifth triode, and a collector of the fifth triode is connected with a cathode of the fourth diode, the other end of the sixth resistor is connected with the anode of the fourth diode and one end of the voltage output end respectively, and the other end of the first capacitor is connected with the emitting electrode of the first triode, the other end of the third resistor, the emitting electrode of the third triode, the negative electrode of the storage battery, the other end of the eighth resistor, the emitting electrode of the fifth triode and the other end of the voltage output end respectively.
In the attendance management system using face recognition and temperature measurement, the type of the fourth diode is S-822T.
In the attendance management system using face recognition and temperature measurement, the power supply module further comprises a ninth resistor, one end of the ninth resistor is connected with the emitter of the third triode, and the other end of the ninth resistor is connected with the other end of the third resistor.
In the attendance management system using face recognition and temperature measurement, the resistance value of the ninth resistor is 26k omega.
In the attendance management system using face recognition and temperature measurement, the first triode is an NPN type triode.
In the attendance management system using face recognition and temperature measurement, the second triode is a PNP triode.
In the attendance management system using face recognition and temperature measurement, the third triode is an NPN type triode.
In the attendance management system using face recognition and temperature measurement, the fourth triode is a PNP triode.
In the attendance management system using face recognition and temperature measurement, the fifth triode is an NPN-type triode.
The attendance management system using face recognition and temperature measurement has the following beneficial effects: the face recognition system comprises a first model recognition module, a second model recognition module, a comparison image screening module, a third model recognition module, an image classification module, an attendance recording module and an infrared temperature measurement module, the power supply module comprises a first capacitor, a power supply, a first diode, a first triode, a first inductor, a second capacitor, a second triode, a second resistor, a third resistor, a first resistor, a third triode, a second diode, a fourth resistor, a fourth triode, a fifth resistor, a third diode, a storage battery, a sixth resistor, a seventh resistor, an eighth resistor, a fourth diode, a fifth triode and a voltage output end, the power supply module uses fewer components compared with the power supply part of the traditional attendance management system, and saves some components, therefore, the hardware cost can be reduced, and in addition, the fourth diode is used for current limiting protection, so that the circuit structure is simpler, the cost is lower, the maintenance is convenient, and the safety and the reliability of the circuit are higher.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a schematic circuit diagram of a power supply part of a conventional attendance management system;
fig. 2 is a schematic structural diagram of an embodiment of an attendance management system using face recognition and temperature measurement according to the present invention;
fig. 3 is a schematic circuit diagram of the power supply module in the embodiment.
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 only a part of the embodiments of the present invention, and not all of the embodiments. 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.
In the embodiment of the attendance management system using face recognition and temperature measurement, the structural schematic diagram of the attendance management system using face recognition and temperature measurement is shown in fig. 2. In fig. 2, this attendance management system using face recognition and temperature measurement includes camera 1, face recognition system 2, infrared thermometer 3 and power module 4, wherein, camera 1, infrared thermometer 3 and power module 4 all are connected with face recognition system 2, face recognition system 2 includes first model identification module 21, second model identification module 22, compare image screening module 23, third model identification module 24, image classification module 25, attendance record module 26 and infrared temperature measurement module 27, infrared thermometer 3 is connected with infrared temperature measurement module 27, power module 4 is connected with infrared temperature measurement module 27.
The first model recognition module 21 is configured to acquire an image of an attendance checking person shot by a camera, and detect a face region image in the image shot by the camera based on a trained Adaboost classifier.
The second model recognition module 22 is configured to obtain a face region image, detect a chin top, a left eye outer hairline point, a right eye outer hairline point, a top center hairline point, two segmentation points of three genres, and four segmentation points of five eyes in the face image by using a trained active shape model, determine a face height range according to a distance between the top center hairline point and the chin top, determine a face width range according to a distance between the left eye outer hairline point and the right eye outer hairline point, calculate proportion information of the three genres according to the two segmentation points of the three genres and the face height range, and calculate proportion information of the five eyes according to the four segmentation points of the five eyes and the face width range.
The comparison image screening module 23 is configured to screen candidate sample image feature vectors from a preset sample feature library according to the identified ratio information of the three families and the ratio information of the five eyes.
The third model recognition module 24 is configured to extract a feature vector of the face region image to be recognized by using the trained feature recognition model.
The image classification module 25 is configured to calculate euclidean distances between feature vectors of candidate sample images and feature vectors of a face region image to be recognized, select a minimum computed euclidean distance, determine whether the minimum euclidean distance is smaller than a preset threshold, if so, take a sample image corresponding to the minimum euclidean distance as a closest sample image, and determine an identity corresponding to the face region image to be recognized according to an identity tag of the closest sample image.
The attendance recording module 26 is configured to determine an attendance position of the attendance person according to a position of a camera that captures the image when the image classification module identifies the identity corresponding to the face region image, and record the identity identification information, the current time, and the attendance position of the attendance person as an attendance record.
The infrared temperature measurement module 27 is configured to, when an attendance record is newly added to the attendance record module, search for an infrared thermometer closest to an attendance position of an attendance person, control the closest infrared thermometer to measure a body temperature of the attendance person, and add measured body temperature data to a corresponding attendance record.
Fig. 3 is a schematic circuit diagram of a power module in this embodiment, in fig. 3, the power module 4 includes a first capacitor C1, a power source VCC, a first diode D1, a first transistor Q1, a first inductor L1, a second capacitor C2, a second transistor Q2, a second resistor R2, a third resistor R3, a first resistor R1, a third transistor Q3, a second diode D2, a fourth resistor R4, a fourth transistor Q4, a fifth resistor R5, a third diode D3, a battery E, a sixth resistor R6, a seventh resistor R6, an eighth resistor R6, a fourth diode D6, a fifth transistor Q6, and a voltage output terminal Vo, wherein one end of the first capacitor C6 is respectively connected to the power source VCC, a cathode of the first diode D6, one end of the first resistor R6, an anode of the second diode D6, an anode of the first resistor R6, one end of the sixth resistor R6, and an anode of the first inductor L6, and an anode of the first resistor R6 are respectively connected to the anode 6 of the first inductor L6, and an anode of the first resistor R6, One end of a second capacitor C2 is connected with a collector of a first triode Q1, a base of a first triode Q1 is connected with a collector of a second triode Q2, an emitter of a second triode Q2 is respectively connected with the other end of a first inductor L1, one end of a second resistor R2 and a collector of a fourth triode Q4, the other end of a second resistor R2 is respectively connected with one end of a third resistor R3, the other end of a first resistor R1 and a base of a third triode Q3, a collector of a third triode Q3 is respectively connected with a cathode of a second diode D2, one end of a fourth resistor R4 and a base of a fourth triode Q4, an emitter of a fourth triode Q4 is respectively connected with a cathode of a third diode D3 and an anode of a storage battery E3, an anode of a third diode D23 is respectively connected with the other end of a fifth resistor R5 and one end of a seventh resistor R7, the other end of a seventh resistor R7 is respectively connected with a base of an eighth resistor 8 and a base of a fifth triode Q5, the collector of the fifth triode Q5 is connected to the cathode of the fourth diode D4, the other end of the sixth resistor R6 is connected to the anode of the fourth diode D4 and one end of the voltage output Vo, respectively, the other end of the first capacitor C1 is connected to the emitter of the first triode Q1, the other end of the third resistor R3, the emitter of the third triode Q3, the cathode of the battery E, the other end of the eighth resistor R8, the emitter of the fifth triode Q5 and the other end of the voltage output Vo, respectively.
This power module 4 compares with traditional attendance management system's in fig. 1 power supply part, and the components and parts that it used are less, and circuit structure is comparatively simple, and convenient the maintenance owing to saved some components and parts, can reduce the hardware cost like this, and in addition, fourth diode D4 is current limiting diode for carry out current-limiting protection to fifth triode Q5's collector current. The current limiting protection principle is as follows: when the collector current of the fifth triode Q5 is large, the collector current of the fifth triode Q5 can be reduced by the fourth diode D4 to keep the fifth triode Q5 in a normal working state, and the device in the circuit is not burnt out due to the large current, so that the safety and reliability of the circuit are high. It should be noted that in the present embodiment, the fourth diode D4 has a model number of S-822T. Of course, in practical applications, other types of diodes with the same function may be used as the fourth diode D4.
The working principle of the power module 4 is as follows: charging the battery E. If the battery being charged is not fully charged. The voltage between the anode of the third diode D3 and the cathode of the battery E is also low due to the low terminal voltage, so that the voltage division on the loop of the seventh resistor R7 and the eighth resistor R8 is lower than the bias voltage of the fifth transistor Q5, and thus the fifth transistor Q5 is turned off, and the power voltage is directly applied to the voltage output Vo through the sixth resistor R6. In addition, the power supply supplies power to the emergency switching function circuit of the third triode Q3 and the fourth triode Q4 through the first resistor R1 and the second diode D2, and the first resistor R1 makes the third triode Q3 biased to be on, but at this time, the electric potential value on the base of the fourth triode Q4 is higher than the emitter thereof, so that the fourth triode Q4 is also in the off state. Once the utility power is cut off, the third transistor Q3 is still turned on during the short-term discharge of the original storage voltage of the first capacitor C1, so the electric quantity of the rechargeable battery immediately turns on the e-C electrode of the fourth transistor Q4 due to the bias current generated by the e-b electrode of the fourth transistor Q4 and the C-e electrode loop of the third transistor Q3. Thus, the battery E is immediately powered by the first transistor Q1-the second transistor Q2 through the E-c terminal of the fourth transistor Q4. The first transistor Q1-the second transistor Q2 are a simple self-feedback self-oscillating circuit, and the oscillating current passes through the first inductor Ll and generates a high self-induced electromotive force at its two ends as the supply voltage of the driving voltage output Vo. If the commercial power is recovered, the circuit recovers the initial working state: automatically changing the main power supply state of the commercial power; the battery E is also switched into a charged state to replenish the charge.
In this embodiment, the first transistor Q1 is an NPN transistor, the second transistor Q2 is a PNP transistor, the third transistor Q3 is an NPN transistor, the fourth transistor Q4 is a PNP transistor, and the fifth transistor Q5 is an NPN transistor. Certainly, in practical applications, the first transistor Q1, the third transistor Q3, and the fifth transistor Q5 may also be PNP transistors, and the second transistor Q2 and the fourth transistor Q4 may also be NPN transistors, but the circuit structure may also be changed accordingly.
In this embodiment, the power module 4 further includes a ninth resistor R9, one end of the ninth resistor R9 is connected to the emitter of the third transistor Q3, and the other end of the ninth resistor R9 is connected to the other end of the third resistor R3. The ninth resistor R9 is a current limiting resistor, and is used for current limiting protection of the emitter current of the third transistor Q3. The current limiting protection principle is as follows: when the emitter current of the third triode Q3 is large, the ninth resistor R9 can reduce the emitter current of the third triode Q3 to keep the third triode Q3 in a normal operating state, so that the elements in the circuit are not burned out due to too large current, and the safety and reliability of the circuit are further enhanced. It should be noted that, in the present embodiment, the resistance of the ninth resistor R9 is 26k Ω. Of course, in practical applications, the resistance of the ninth resistor R9 may be increased or decreased according to specific situations.
In a word, in this embodiment, compared with the power supply part of the traditional attendance management system, the power module 4 has fewer used components, simpler circuit structure and convenient maintenance, and can reduce the hardware cost due to the saving of some components. In addition, the power module 4 is provided with a current-limiting diode, so that the safety and the reliability of the circuit are high.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.
Claims (9)
1. An attendance management system using face recognition and temperature measurement is characterized by comprising a camera, a face recognition system, an infrared thermometer and a power module, wherein the camera, the infrared thermometer and the power module are all connected with the face recognition system;
the first model recognition module is used for acquiring an image of an attendance person shot by a camera and detecting a face region image in the image shot by the camera based on a trained Adaboost classifier;
the second model recognition module is used for acquiring a face region image, detecting a lower base point, a left eye outer hairline point, a right eye outer hairline point, a top center hairline point, two segmentation points of three families and four segmentation points of five eyes in the face image by adopting a trained active shape model, determining a face height range according to the distance between the top center hairline point and the lower base point, determining a face width range according to the distance between the left eye outer hairline point and the right eye outer hairline point, calculating proportion information of the three families according to the two segmentation points of the three families and the face height range, and calculating proportion information of the five eyes according to the four segmentation points of the five eyes and the face width range;
the comparison image screening module is used for screening candidate sample image feature vectors from a preset sample feature library according to the identified ratio information of the three families and the ratio information of the five eyes;
the third model recognition module is used for extracting a feature vector of a face region image to be recognized by adopting a trained feature recognition model;
the image classification module is used for calculating Euclidean distances between feature vectors of alternative sample images and feature vectors of a face region image to be recognized, selecting the minimum Euclidean distance obtained through calculation, judging whether the minimum Euclidean distance is smaller than a preset threshold value, if yes, taking the sample image corresponding to the minimum Euclidean distance as the closest sample image, and determining the identity corresponding to the face region image to be recognized according to the identity label of the closest sample image;
the attendance recording module is used for determining the attendance position of an attendance person according to the position of a camera for shooting images when the image classification module identifies the identity corresponding to the face region image, and recording the identity identification information, the current time and the attendance position of the attendance person as attendance records;
the infrared temperature measurement module is used for searching an infrared thermometer closest to the attendance checking position of an attendance checking person when an attendance checking record is newly added to the attendance checking record module, controlling the closest infrared thermometer to measure the body temperature of the attendance checking person, and adding measured body temperature data into the corresponding attendance checking record;
the power supply module comprises a first capacitor, a power supply, a first diode, a first triode, a first inductor, a second capacitor, a second triode, a second resistor, a third resistor, a first resistor, a third triode, a second diode, a fourth resistor, a fourth triode, a fifth resistor, a third diode, a storage battery, a sixth resistor, a seventh resistor, an eighth resistor, a fourth diode, a fifth triode and a voltage output end, wherein one end of the first capacitor is respectively connected with the power supply, the cathode of the first diode, one end of the first resistor, the anode of the second diode, one end of the fifth resistor and one end of the sixth resistor, the anode of the first diode is respectively connected with one end of the first inductor, one end of the second capacitor and the collector of the first triode, the base of the first triode is connected with the collector of the second triode, an emitting electrode of the second triode is respectively connected with the other end of the first inductor, one end of the second resistor and a collector of the fourth triode, the other end of the second resistor is respectively connected with one end of the third resistor, the other end of the first resistor and a base electrode of the third triode, a collector of the third triode is respectively connected with a cathode of the second diode, one end of the fourth resistor and a base electrode of the fourth triode, an emitting electrode of the fourth triode is respectively connected with a cathode of the third diode and an anode of the storage battery, an anode of the third diode is respectively connected with the other end of the fifth resistor and one end of the seventh resistor, the other end of the seventh resistor is respectively connected with one end of the eighth resistor and a base electrode of the fifth triode, and a collector of the fifth triode is connected with a cathode of the fourth diode, the other end of the sixth resistor is connected with the anode of the fourth diode and one end of the voltage output end respectively, and the other end of the first capacitor is connected with the emitting electrode of the first triode, the other end of the third resistor, the emitting electrode of the third triode, the negative electrode of the storage battery, the other end of the eighth resistor, the emitting electrode of the fifth triode and the other end of the voltage output end respectively.
2. The attendance management system using face recognition and temperature measurement as claimed in claim 1, wherein the fourth diode has a model of S-822T.
3. The attendance management system using face recognition and temperature measurement as claimed in claim 2, wherein the power module further comprises a ninth resistor, one end of the ninth resistor is connected to an emitter of the third transistor, and the other end of the ninth resistor is connected to the other end of the third resistor.
4. The attendance management system using face recognition and temperature measurement according to claim 3, wherein the resistance of the ninth resistor is 26k Ω.
5. The attendance management system using face recognition and temperature measurement according to any one of claims 1 to 4, wherein the first transistor is an NPN transistor.
6. The attendance management system using face recognition and temperature measurement according to any one of claims 1 to 4, wherein the second transistor is a PNP type transistor.
7. The attendance management system using face recognition and temperature measurement according to any one of claims 1 to 4, wherein the third transistor is an NPN transistor.
8. The attendance management system using face recognition and temperature measurement according to any one of claims 1 to 4, wherein the fourth transistor is a PNP type transistor.
9. The attendance management system using face recognition and temperature measurement according to any one of claims 1 to 4, wherein the fifth transistor is an NPN transistor.
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| Application Number | Priority Date | Filing Date | Title |
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| CN202010498255.0A CN111783546A (en) | 2020-06-04 | 2020-06-04 | Attendance management system using face recognition and temperature measurement |
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| CN202010498255.0A CN111783546A (en) | 2020-06-04 | 2020-06-04 | Attendance management system using face recognition and temperature measurement |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112378521A (en) * | 2020-11-13 | 2021-02-19 | 深圳市科瑞康实业有限公司 | Temperature measuring system |
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2020
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112378521A (en) * | 2020-11-13 | 2021-02-19 | 深圳市科瑞康实业有限公司 | Temperature measuring system |
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Application publication date: 20201016 |