Monitoring area determination method, electronic equipment and computer storage medium

Abstract

The invention relates to the technical field of image calibration, and provides a monitoring area determination method, electronic equipment and a computer storage medium. The method comprises the steps of obtaining a first monitoring image and a first code disc reading corresponding to a first deviation point location when the first deviation point location is located; according to the first code disc reading, the target code disc reading and the target coordinate information, calibration coordinate information corresponding to the first monitoring image is determined, and the calibration coordinate information comprises M calibration coordinate points. According to the multiple calibration images and the target image, multiple similarity values are determined, the first calibration image at least comprises image areas corresponding to N calibration coordinate points, and M is larger than or equal to N. If the second similarity value is greater than a preset threshold value, determining an area where the calibration image corresponding to the second similarity value is located as a monitoring area; and if the first similarity value is smaller than or equal to a preset threshold value, determining that the image area corresponding to the calibration coordinate information is a monitoring area. The reliability and the accuracy of a temperature monitoring result can be improved.

Description

Technical Field

[0001] This application relates to the technical field of image calibration, and particularly to a method for determining a monitoring area, an electronic device, and a computer storage medium. Background Art

[0002] The pan-tilt infrared temperature measurement monitoring technology is a monitoring solution that combines a pan-tilt control system and infrared thermal imaging technology. It can be used to monitor the temperature distribution of a target area, achieving real-time temperature monitoring and remote control of the target area. It has wide applications in the fields of security, industrial monitoring, epidemic prevention and control, and environmental monitoring.

[0003] The monitoring device can monitor multiple monitoring targets through the pan-tilt infrared temperature measurement monitoring technology. Specifically, the monitoring device can preset multiple monitoring points, and multiple monitoring points correspond to multiple encoder angles. Each monitoring point can monitor one monitoring target. The monitoring device can achieve the patrol inspection of multiple monitoring targets through the repositioning of multiple encoder angles.

[0004] However, during the patrol inspection of the monitoring device, due to factors such as limited motor accuracy and strong wind interference in the outdoor environment, there is usually a certain deviation between the encoder angle where the monitoring device is located after repositioning and the encoder angle corresponding to the target monitoring point. The position coordinates of the monitoring target in the monitoring image will change accordingly, and the monitoring results obtained by the monitoring device through the original image position coordinates will also deviate, resulting in false alarms or missed alarms of the temperature monitoring results by the monitoring device. Summary of the Invention

[0005] This application provides a method, device, chip, electronic device, and computer-readable storage medium for determining a monitoring area. It can accurately locate the area where the monitoring target is located, facilitate the temperature monitoring of the monitoring device, and improve the reliability and accuracy of the temperature monitoring results.

[0006] In a first aspect, the present application provides a method for determining a monitoring area, which can be applied to a monitoring device. The monitoring device is used to monitor multiple monitoring targets corresponding to multiple monitoring points. The method includes: when at a first deviation point, obtaining a first monitoring image and a first encoder reading corresponding to the first deviation point. The first deviation point is the point corresponding to the first monitoring point, and the first monitoring point is any one of the multiple monitoring points. According to the first encoder reading, the target encoder reading, and the target coordinate information, determine the calibration coordinate information corresponding to the first monitoring image. The calibration coordinate information includes M calibration coordinate points. The target coordinate information is used to represent the M target coordinate points where the first monitoring target is located in the second monitoring image obtained by the monitoring device when the monitoring device is at the first monitoring point. The first monitoring target is the monitoring target corresponding to the first monitoring point among the multiple monitoring targets. According to multiple calibration images and the target image, determine multiple similarity values. The multiple similarity values correspond one-to-one with the multiple calibration images. The first calibration image includes at least an image area corresponding to N calibration coordinate points. M is greater than or equal to N. The target image is the image area where the M target coordinate points are located in the second monitoring image. The first similarity value is used to represent the similarity between the first calibration image and the target image. The first calibration image is a sub-image of the first monitoring image. The first calibration image is any one of the multiple calibration images. The first similarity value is one of the multiple similarity values corresponding to the first calibration image. If the second similarity value is greater than a preset threshold, determine the area where the calibration image corresponding to the second similarity value is located as the monitoring area. The second similarity value is the maximum value among the multiple similarity values. If the first similarity value is less than or equal to the preset threshold, determine the image area corresponding to the calibration coordinate information as the monitoring area.

[0007] In some embodiments, according to multiple calibration images and the target image, determining multiple similarity values includes: determining multiple calibration images according to the calibration coordinate information. Determine the similarity between the second calibration image and the target image to obtain a third similarity value to determine multiple similarity values. The second calibration image is any one image among the multiple calibration images. The third similarity value is one of the multiple similarity values corresponding to the second calibration image.

[0008] In some embodiments, determining multiple calibration images according to the calibration coordinate information includes: obtaining a preset magnification factor. According to the preset magnification factor and the calibration coordinate information, determine the magnified coordinate information. Determine the sub-image corresponding to the magnified coordinate information in the first monitoring image as the magnified image. According to the magnified image and the target image, determine multiple calibration images. The image size corresponding to each calibration image among the multiple calibration images is the same as the image size corresponding to the target image.

[0009] In some embodiments, the third calibration image and the fourth calibration image are any two different images among a plurality of calibration images. The third calibration image is the image where a plurality of first pixel points in the magnified image are located, and the fourth calibration image is the image where a plurality of second pixel points in the magnified image are located. The plurality of first pixel points and the plurality of second pixel points are not completely the same.

[0010] In some embodiments, determining the similarity between the second calibration image and the target image to obtain a third similarity value includes: performing grayscale processing on the second calibration image to obtain a grayscale image; performing filtering processing on the grayscale image to obtain a filtered image; performing normalization processing on the filtered image to obtain a normalized image; and determining the similarity between the normalized image and the target image to obtain the third similarity value.

[0011] In some embodiments, according to the first encoder reading, the target encoder reading, and the target coordinate information, determining the calibration coordinate information corresponding to the first monitoring image includes: obtaining the target encoder reading; determining a pixel deviation according to the target encoder reading and the first encoder reading, where the pixel deviation is positively correlated with the encoder angle difference between the first angle and the second angle. The first angle is the encoder angle corresponding to the target encoder reading, and the second angle is the encoder angle corresponding to the first encoder reading; obtaining the target coordinate information; and determining the calibration coordinate information according to the pixel deviation and the target coordinate information.

[0012] In some embodiments, before the above method, it further includes: when at the first monitoring position, obtaining a second monitoring image; in response to a received target area division instruction, determining that the sub-image corresponding to the target area division instruction in the second monitoring image is the target image, where the target image is the image where the first monitoring target is located; recording the coordinate information corresponding to the target image in the second monitoring image as the target coordinate information, and recording the encoder reading corresponding to the first monitoring position as the target encoder reading.

[0013] In some embodiments, after the above method, it further includes: monitoring the temperature of the monitoring area to obtain a temperature monitoring result.

[0014] In a second aspect, an embodiment of the present application provides a monitoring area determination device. The monitoring area determination device may be a monitoring device, and the monitoring area determination device is used to monitor a plurality of monitoring targets corresponding to a plurality of monitoring positions. The device includes:

[0015] An acquisition module, configured to obtain a first monitoring image and a first encoder reading corresponding to a first deviation position when at the first deviation position. The first deviation position is the position corresponding to the first monitoring position, and the first monitoring position is any one of the plurality of monitoring positions.

[0016] A determination module, configured to determine calibration coordinate information corresponding to a first monitoring image according to a first encoder reading, a target encoder reading, and target coordinate information, where the calibration coordinate information includes M calibration coordinate points, and the target coordinate information is used to represent M target coordinate points where a first monitoring target is located in a second monitoring image obtained by a monitoring device when the monitoring device is at a first monitoring position, and the first monitoring target is a monitoring target corresponding to the first monitoring position among multiple monitoring targets.

[0017] The determination module is further configured to determine multiple similarity values according to multiple calibration images and a target image, where the multiple similarity values correspond to the multiple calibration images one by one, the first calibration image at least includes an image area corresponding to N calibration coordinate points, M is greater than or equal to N, the target image is an image area where M target coordinate points are located in the second monitoring image, the first similarity value is used to represent the similarity between the first calibration image and the target image, the first calibration image is a sub-image of the first monitoring image, the first calibration image is any one of the multiple calibration images, and the first similarity value is one corresponding to the first calibration image among the multiple similarity values.

[0018] The determination module is further configured to, when a second similarity value is greater than a preset threshold, determine that an area where the calibration image corresponding to the second similarity value is located is a monitoring area, and the second similarity value is the maximum value among the multiple similarity values.

[0019] The determination module is further configured to, when the first similarity value is less than or equal to the preset threshold, determine that an image area corresponding to the calibration coordinate information is a monitoring area.

[0020] In a third aspect, the present application provides a chip, which is configured to execute the method in any one of the above first aspects.

[0021] In a fourth aspect, the present application provides an electronic device, including a processor and a memory, where the processor is configured to execute a computer program stored in the memory to implement the method in any one of the above first aspects. Or,

[0022] The electronic device includes the chip in the third aspect.

[0023] In a fifth aspect, an embodiment of the present application provides a computer-readable storage medium, which stores a computer program, and when the computer program is executed by a processor, the method in any one of the above first aspects is implemented.

[0024] In the technical solution provided by this application, when the monitoring device is at the first deviation point, it can obtain the first monitoring image and the first encoder reading corresponding to the first deviation point. The first deviation point is the point corresponding to the first monitoring point, and the first monitoring point is any one of multiple monitoring points. Then, based on the first encoder reading, the target encoder reading, and the target coordinate information, the calibration coordinate information corresponding to the first monitoring image is determined. The calibration coordinate information includes M calibration coordinate points. The target coordinate information is used to represent the M target coordinate points where the first monitoring target is located in the second monitoring image obtained by the monitoring device when the monitoring device is at the first monitoring point. The first monitoring target is the monitoring target corresponding to the first monitoring point among multiple monitoring targets. Next, based on multiple calibration images and the target image, multiple similarity values are determined. The multiple similarity values correspond to the multiple calibration images one by one. The first calibration image includes at least the image area corresponding to N calibration coordinate points. M is greater than or equal to N. The target image is the image area where the M target coordinate points are located in the second monitoring image. The first similarity value is used to represent the similarity between the first calibration image and the target image. The first calibration image is a sub-image of the first monitoring image and is any one of the multiple calibration images. The first similarity value is one of the multiple similarity values corresponding to the first calibration image. If the second similarity value is greater than the preset threshold, it is determined that the area where the calibration image corresponding to the second similarity value is located is the monitoring area, and the second similarity value is the maximum value among the multiple similarity values. If the first similarity value is less than or equal to the preset threshold, it is determined that the image area corresponding to the calibration coordinate information is the monitoring area. The technical solution provided by this application can determine the calibration coordinate information based on the difference between the current encoder reading (the first encoder reading) and the target encoder reading, thereby calculating the similarity between multiple calibration images corresponding to the calibration coordinate information and the target image to obtain multiple similarity values, and determining the monitoring area based on the multiple similarity values. It can accurately locate the area where the monitoring target is located, facilitate the temperature monitoring of the monitoring device, and improve the reliability and accuracy of the temperature monitoring result. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] In order to more clearly illustrate the technical solutions in the embodiments of this application, the following will briefly introduce the drawings required for use in the embodiments or the description of the prior art. Obviously, the following drawings are only some embodiments of this application. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0026] Figure 1 is a schematic structural diagram of a monitoring device provided by an embodiment of this application;

[0027] Figure 2 is a schematic flowchart of a method for determining a monitoring area provided by an embodiment of this application;

[0028] Figure 3 It is a schematic diagram of a target image of a method for determining a monitoring area provided by an embodiment of the present application;

[0029] Figure 4 It is another schematic flowchart of a method for determining a monitoring area provided by an embodiment of the present application;

[0030] Figure 5 It is a schematic diagram of calibration coordinate information of a method for determining a monitoring area provided by an embodiment of the present application;

[0031] Figure 6 It is a schematic diagram of calculating the similarity of a sliding window of a method for determining a monitoring area provided by an embodiment of the present application;

[0032] Figure 7 It is a schematic diagram of a device for determining a monitoring area provided by an embodiment of the present application;

[0033] Figure 8 It is a schematic diagram of an electronic device provided by an embodiment of the present application. Detailed implementation manners

[0034] In the following description, specific details such as specific system architectures and technologies are presented for the purpose of illustration rather than limitation, so as to thoroughly understand the embodiments of the present application. However, those skilled in the art should clearly understand that the present application can also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to avoid unnecessary details from interfering with the description of the present application.

[0035] It should be understood that when used in the specification of the present application and the appended claims, the term "comprising" indicates the presence of the described features, wholes, steps, operations, elements, and / or components, but does not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components, and / or their combinations.

[0036] It should also be understood that the term "and / or" as used in the specification of the present application and the appended claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0037] As used in the specification of the present application and the appended claims, the term "if" can be interpreted as "when", "once", "in response to determining", or "in response to detecting" depending on the context. Similarly, the phrase "if determined" or "if [the described condition or event] is detected" can be interpreted as meaning "once determined", "in response to determining", "once [the described condition or event] is detected", or "in response to detecting [the described condition or event]" depending on the context.

[0038] In addition, in the description of the specification and the appended claims of the present application, terms such as "first", "second", "third", etc. are only used for differential description and should not be construed as indicating or implying relative importance.

[0039] Reference to "one embodiment" or "some embodiments" etc. described in the specification of the present application means that specific features, structures or characteristics described in connection with that embodiment are included in one or more embodiments of the present application. Thus, statements such as "in one embodiment", "in some embodiments", "in other some embodiments", "in still other embodiments" etc. that appear in different places in this specification do not necessarily all refer to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized in another way. The terms "comprise", "include", "have" and their variants all mean "including but not limited to", unless otherwise specifically emphasized in another way.

[0040] A pan-tilt unit is a mechanical device used to support and adjust a camera, sensor or other device, capable of rotating in horizontal and vertical directions, and is widely used in fields such as monitoring, photography, robotics, etc. The core function of the pan-tilt unit is to adjust the pointing of the device by rotation, thereby expanding the monitoring range or achieving dynamic tracking. To ensure the accuracy of the rotation of the pan-tilt unit, a device capable of measuring the rotation angle in real time is usually required, namely an encoder disk. An encoder disk is a device used to measure the rotation angle and is usually used in combination with an encoder. The encoder disk reads the rotation position through optoelectronic or magnetic sensors and outputs digital signals so that the control system can accurately control the rotation angle of the pan-tilt unit. The encoder disk is usually installed on the rotation axis of the pan-tilt unit, capable of reading the rotation angle of the pan-tilt unit in real time and feeding this information back to the pan-tilt unit control system, thereby realizing closed-loop control and ensuring that the pan-tilt unit can accurately reach the preset position.

[0041] In recent years, with the rapid development of infrared temperature measurement technology, the pan-tilt unit infrared temperature measurement and monitoring technology has gradually become an important monitoring solution. This technology combines the rotation control ability of the pan-tilt unit and the infrared temperature measurement technology, and can realize non-contact temperature measurement and monitoring of a large range of areas.

[0042] The monitoring device can realize non-contact temperature measurement of the monitoring target through the pan-tilt unit infrared temperature measurement and monitoring technology.

[0043] Exemplarily, Figure 1 is a schematic structural diagram of a monitoring device provided by an embodiment of the present application. As Figure 1 shown, the monitoring device at least includes a control module, an infrared temperature measurement and imaging module and a pan-tilt unit module, and the pan-tilt unit module includes an encoder disk module.

[0044] The infrared temperature measurement and imaging module is responsible for collecting the temperature information of the target area and generating a thermal imaging image. It can automatically monitor the temperature anomalies (such as supercooled or overheated areas) in the target area and feedback the monitoring results to the control module. The control module is responsible for coordinating and managing the operation of the entire system, including functions such as data processing, instruction issuance, feedback control, and user interaction. Specifically, the control module receives the temperature data sent by the infrared temperature measurement and imaging module, analyzes and processes it; according to user requirements or preset programs, sends rotation instructions to the pan-tilt module to adjust the pointing direction of the infrared temperature measurement and imaging module; at the same time, the control module can also receive the angle feedback from the encoder module for closed-loop control to ensure the accuracy of the pan-tilt rotation. The pan-tilt module can be used to adjust the monitoring direction of the infrared temperature measurement and imaging module, and the encoder module, as a measuring device for the rotation angle of the pan-tilt, can read the rotation angle of the pan-tilt in real time and feedback this information to the control module to ensure that the infrared temperature measurement and imaging module can accurately point to the target area.

[0045] However, due to the limited motor accuracy of the monitoring device and the fact that in the outdoor environment, the pan-tilt module of the monitoring device may be interfered by external factors such as strong winds, there is a certain deviation between the encoder angle where the pan-tilt of the monitoring device is located after repositioning and the encoder angle corresponding to the target monitoring point. This deviation will cause the position coordinates of the monitoring target in the monitoring image to change, and further, when the monitoring device performs temperature monitoring based on the original image position coordinates, the results will deviate. This deviation may cause the monitoring device to give false alarms or miss reporting of temperature monitoring results, affecting the reliability and accuracy of the system.

[0046] In summary, due to factors such as motor accuracy limitations and external environmental interference, the accuracy and stability of the monitoring device are poor.

[0047] In view of this, the embodiments of the present application provide a method for determining a monitoring area, which can accurately locate the area where the monitoring target is located, facilitate the temperature monitoring of the monitoring device, and improve the reliability and accuracy of the temperature monitoring results.

[0048] The technical solution provided by the embodiments of the present application can be applied to monitoring devices such as surveillance cameras and monitoring robots, and the present application does not limit the specific categories of the monitoring devices.

[0049] The method for determining a monitoring area provided by the embodiments of the present application can be divided into two stages. The first stage is the initialization setting stage of the monitoring points, and the second stage is the inspection stage of the monitoring area.

[0050] In the initial setup phase of the monitoring points, the monitoring device can record multiple target encoder readings corresponding to multiple monitoring points one by one, and record multiple target images corresponding to multiple monitoring points one by one. In the embodiment of the present application, taking any one of the multiple monitoring points (the first monitoring point) as an example, the process of the monitoring device determining and recording the target encoder reading and the target image corresponding to the first monitoring point will be described exemplarily. It can be understood that the process of the monitoring device determining and recording the target encoder readings and target images corresponding to other monitoring points has the same or similar calculation principle as the method provided in the embodiment of the present application, and will not be elaborated herein.

[0051] As Figure 2 shown, it is a schematic flowchart of a method for determining a monitoring area provided by an embodiment of the present application. It includes the following steps:

[0052] Step S201: When at the first monitoring point, obtain a second monitoring image.

[0053] In the embodiment of the present application, the user can turn the infrared temperature measurement and imaging module of the monitoring device to the direction corresponding to the monitoring target (i.e., the first monitoring point). When the monitoring device receives the monitoring point determination instruction sent by the user, the monitoring device can obtain the second monitoring image through the infrared temperature measurement and imaging module.

[0054] It can be understood that when the monitoring device is at the first monitoring point, the second monitoring image obtained may include one monitoring target or multiple monitoring targets, which is not limited herein.

[0055] In the embodiment of the present application, the user can input a rotation instruction carrying the target encoder reading to the monitoring device to turn the infrared temperature measurement and imaging module of the monitoring device to the direction corresponding to the monitoring target; or manually turn the infrared temperature measurement and imaging module of the monitoring device to the direction corresponding to the monitoring target, which is not limited herein.

[0056] Step S202: In response to the received target area division instruction, determine that the sub-image corresponding to the target area division instruction in the second monitoring image is the target image, and the target image is the image where the first monitoring target is located.

[0057] In the embodiment of the present application, the monitoring device can perform grayscale processing, filtering processing, and normalization processing on the sub-image corresponding to the target area division instruction in the second monitoring image in sequence to obtain the target image.

[0058] The user can frame the area where the monitoring target is located in the second monitoring image as the target area (i.e., send a target area division instruction to the monitoring device). When the monitoring device receives the target area division instruction sent by the user, it can determine that the sub-image corresponding to the target area division instruction in the second monitoring image is the target image.

[0059] It is understandable that the target image may include one monitoring target or multiple monitoring targets, and this application does not make any limitations here. In the embodiments of this application, taking the target image including one monitoring target as an example, the technical solutions provided by the embodiments of this application will be described exemplarily.

[0060] For example, Figure 3 is a schematic diagram of the target image of a method for determining a monitoring area provided by an embodiment of this application. As Figure 3 shown in (a) in the figure, it is a schematic diagram of the second monitoring image including the target area. As Figure 3 shown in (b) in the figure, it is a schematic diagram of the target image.

[0061] Step S203: Record the coordinate information corresponding to the target image in the second monitoring image as the target coordinate information, and record the encoder reading corresponding to the first monitoring point as the target encoder reading.

[0062] In the embodiments of this application, after the monitoring device determines the target image corresponding to the first monitoring point, it can determine the target coordinate information according to the coordinate information corresponding to the target image in the second monitoring image.

[0063] If the target area selected by the user is a rectangle, the monitoring device can represent the target area through two coordinate points. For example, continuing to refer to Figure 3 , the monitoring device can represent the target area through coordinate point A(8, 16) and coordinate point B(4, 8). That is, the size of the target area is 4×8. Among the M coordinate points corresponding to the target coordinate information, the minimum abscissa value of each coordinate point is 4, and the maximum abscissa value is 8; the minimum ordinate value of each coordinate point is 8, and the maximum ordinate value is 16.

[0064] If the target area selected by the user is not a rectangle, such as a triangle, a rhombus or a trapezoid, etc., the monitoring device can represent the target area through M coordinate points, which will not be elaborated in this application.

[0065] The encoder reading corresponding to the encoder module of the current monitoring device is the target encoder reading corresponding to the first monitoring point.

[0066] The monitoring device can obtain the target encoder readings, target coordinate information and target images corresponding to other monitoring points among multiple monitoring points one by one through the technical solutions provided in steps S201 to S203, which will not be elaborated in this application.

[0067] During the inspection stage of the monitoring area, the monitoring device can inspect multiple monitoring points one by one, determine the area where the monitoring target actually is in the monitoring image as the monitoring area, and perform real-time temperature monitoring and remote control on the monitoring area.

[0068] Figure 4 Another flowchart of a method for determining a monitoring area provided by an embodiment of the present application. As Figure 4 shown, the monitoring device can determine the monitoring area through the following method.

[0069] Step S401: When at the first deviation point, obtain the first monitoring image and the first encoder disk reading corresponding to the first deviation point. The first deviation point is the point corresponding to the first monitoring point, and the first monitoring point is any one of multiple monitoring points.

[0070] In the embodiment of the present application, the monitoring device can be used to monitor multiple monitoring targets corresponding to multiple monitoring points. It can be understood that one monitoring point can correspond to one monitoring target or multiple monitoring targets, and the present application does not make any limitations here.

[0071] After the monitoring device enables the monitoring area calibration mode, during the process of patrolling multiple monitoring points, each time a monitoring point is patrolled, the current monitoring point can be determined as the deviation point, and the monitoring area corresponding to the current monitoring point is calibrated.

[0072] It should be understood that if the first encoder disk reading corresponding to the first deviation point is different from the target encoder disk reading corresponding to the first monitoring point, that is, there is a deviation in the encoder disk angle, the monitoring device can determine the monitoring area where the monitoring target is located in the first monitoring image through the technical solution provided by the embodiment of the present application, and perform temperature monitoring and remote control on the monitoring area. If the first encoder disk reading corresponding to the first deviation point is the same as the target encoder disk reading corresponding to the first monitoring point, that is, there is no deviation (the deviation is 0) in the encoder disk angle, the monitoring device can also perform temperature monitoring and remote control on the monitoring area where the monitoring target is located through the technical solution provided by the embodiment of the present application.

[0073] Step S402: Determine the calibration coordinate information corresponding to the first monitoring image according to the first encoder disk reading, the target encoder disk reading, and the target coordinate information. The calibration coordinate information includes M calibration coordinate points. The target coordinate information is used to represent the M target coordinate points where the first monitoring target is located in the second monitoring image obtained by the monitoring device when the monitoring device is at the first monitoring point. The first monitoring target is the monitoring target corresponding to the first monitoring point among multiple monitoring targets.

[0074] In the embodiment of the present application, the method for the monitoring device to determine the calibration coordinate information corresponding to the first monitoring image according to the first encoder disk reading, the target encoder disk reading, and the target coordinate information may include:

[0075] Step A1: Obtain the target encoder disk reading. <##

[0076] In the embodiments of the present application, the target encoder reading is the encoder reading corresponding to the encoder module when the monitoring device is at the first monitoring point.

[0077] Step A2: Determine the pixel deviation according to the target encoder reading and the first encoder reading. The pixel deviation is positively correlated with the encoder angle difference between the first angle and the second angle. The first angle is the encoder angle corresponding to the target encoder reading, and the second angle is the encoder angle corresponding to the first encoder reading.

[0078] In the embodiments of the present application, the pixel deviation is the image pixel deviation caused by the encoder angle difference. The formula for calculating the offset of the pixel deviation determined by the monitoring device according to the target encoder reading and the first encoder reading can be:

[0079] where, represents the encoder angle difference between the first angle and the second angle, P represents the resolution of the infrared temperature measurement imaging module (i.e., the camera), and FOV represents the field of view angle corresponding to the infrared temperature measurement imaging module.

[0080] Step A3: Obtain the target coordinate information.

[0081] In the embodiments of the present application, the target coordinate information is the coordinate information corresponding to the target image determined by the monitoring device through steps S202 and S203 in the corresponding embodiments described above in the second monitoring image. Figure 2 In the corresponding embodiments, the coordinate information corresponding to the target image determined by the monitoring device through steps S202 and S203.

[0082] Step A4: Determine the calibration coordinate information according to the pixel deviation and the target coordinate information.

[0083] For example, Figure 5 is a schematic diagram of the calibration coordinate information of a monitoring area determination method provided by the embodiments of the present application. If the pixel deviation is 5 pixel points of horizontal deviation and -3 pixel points of vertical deviation. The target area selected by the user is a rectangle, and the area corresponding to the target coordinate information is Figure 5 The coordinate points A(8, 16) and coordinate point B(4, 8) in represent the target area, that is, area 1. Then the area corresponding to the calibration coordinate information in the first monitoring image is Figure 5 The coordinate points C(13, 13) and coordinate point D(9, 5) in represent the target area, that is, area 2.

[0084] Step S403: Determine a plurality of similarity values according to a plurality of calibration images and a target image. The plurality of similarity values correspond to the plurality of calibration images one by one. The first calibration image includes at least an image region corresponding to N calibration coordinate points, M is greater than or equal to N. The target image is an image region where M target coordinate points are located in the second monitoring image. The first similarity value is used to characterize the similarity between the first calibration image and the target image. The first calibration image is a sub-image of the first monitoring image, and the first calibration image is any one of the plurality of calibration images. The first similarity value is one corresponding to the first calibration image among the plurality of similarity values.

[0085] In the embodiments of the present application, the method for the monitoring device to determine a plurality of similarity values according to a plurality of calibration images and a target image may include the following steps:

[0086] Step B1: Determine a plurality of calibration images according to calibration coordinate information.

[0087] Step B1-1: Obtain a preset magnification factor.

[0088] In the embodiments of the present application, the monitoring device may determine the specific value of the preset method coefficient according to the actual application scenario (such as factors such as the degree of strong wind interference and the degree of motor precision deviation). It can be understood that the higher the degree of strong wind interference and / or the degree of motor precision deviation, the greater the gap between the target encoder reading and the first encoder reading, and the greater the encoder angle difference between the first angle and the second angle, and the greater the preset magnification factor. For example, the preset magnification factor is 1.15, 1.25, or 1.5. Conversely, the lower the degree of strong wind interference and / or the degree of motor precision deviation, the smaller the gap between the target encoder reading and the first encoder reading, and the smaller the encoder angle difference between the first angle and the second angle, and the smaller the preset magnification factor. For example, the preset magnification factor is 2, 2.25, or 2.5.

[0089] Step B1-2: Determine magnified coordinate information according to the preset magnification factor and calibration coordinate information.

[0090] The monitoring device may perform a magnification process on the calibration coordinate information according to the preset magnification factor to obtain magnified coordinate information.

[0091] For example, continue to refer to Figure 5 , when the preset magnification factor is 2, the region corresponding to the magnified coordinate information in the first monitoring image is Figure 5 where the coordinate point E(15, 17) and the coordinate point F(7, 1) in represent the target region, that is, region 3.

[0092] Step B1-3: Determine the sub-image corresponding to the magnified coordinate information in the first monitoring image as the magnified image.

[0093] For example, continue to refer to Figure 5, the image region where Region 3 is located in the first monitoring image is the magnified image.

[0094] Step B1-4: Determine a plurality of calibration images according to the magnified image and the target image, and the image size corresponding to each calibration image in the plurality of calibration images is the same as the image size corresponding to the target image.

[0095] Continue to refer to Figure 5 , it should be understood that the closer N is to M, the higher the overlap degree between the calibration image and Region 2. When N is equal to M, it means that the calibration image is the image corresponding to Region 2; the closer N is to 0, the lower the overlap degree between the calibration image and Region 2. When N is 0, it means that the calibration image and Region 2 do not overlap at all.

[0096] In the embodiment of the present application, the monitoring device can calculate the sliding window similarity between the target image and the magnified image based on the sliding window similarity calculation principle to obtain a similarity matrix (i.e., a plurality of similarity values). It should be understood that during the process of the monitoring device calculating the sliding window similarity between the target image and the magnified image, it is actually calculating the similarity between the target image and a plurality of sub-images (i.e., a plurality of calibration images) in different pixel regions of the magnified image.

[0097] For example, Figure 6 is a schematic diagram of the sliding window similarity calculation of a monitoring area determination method provided by an embodiment of the present application. As Figure 6 shown, the change range of the plurality of abscissas corresponding to the magnified image is the change range corresponding to the plurality of vertical lines on the magnified image, and the change range of the plurality of ordinates corresponding to the magnified image is the change range corresponding to the plurality of horizontal lines on the magnified image.

[0098] It should be understood that any two calibration images in the plurality of calibration images do not completely have the same corresponding pixel points in the magnified image. That is, the third calibration image and the fourth calibration image are any two different images in the plurality of calibration images. The third calibration image is the image where a plurality of first pixel points are located in the magnified image, and the fourth calibration image is the image where a plurality of second pixel points are located in the magnified image. The plurality of first pixel points and the plurality of second pixel points are not completely the same.

[0099] For example, continue to refer to Figure 6 , the third calibration image can be calibration image 1, and the fourth calibration image can be calibration image 2. The pixel points corresponding to calibration image 1 and the pixel points corresponding to calibration image 2 are not completely the same.

[0100] Step B2: Determine the similarity between the second calibration image and the target image to obtain a third similarity value to determine a plurality of similarity values. The second calibration image is any one image in the plurality of calibration images, and the third similarity value is one corresponding to the second calibration image among the plurality of similarity values.

[0101] In the embodiments of the present application, the monitoring device may perform grayscale processing on the second calibration image to obtain a grayscale image; then perform filtering processing on the grayscale image to obtain a filtered image; finally perform normalization processing on the filtered image to obtain a normalized image; and determine the similarity between the normalized image and the target image to obtain a third similarity value.

[0102] In the embodiments of the present application, based on the sliding window similarity calculation principle, the monitoring device performs sliding window similarity calculation on the target image and the enlarged image. The calculation formula for obtaining the similarity matrix (i.e., multiple similarity values) can be:

[0103]

[0104] Among them, R(x, y) represents the coordinates corresponding to the coordinate point with the smallest abscissa and ordinate in the image to be calibrated. It can be understood that if the size of the enlarged image is 8×16, and the coordinate point with the smallest abscissa and ordinate in the enlarged image is regarded as (0, 0), then among the multiple calibration images, the coordinates corresponding to the coordinate points with the smallest abscissa and ordinate can be: (0, 0), (0, 1), (0, 2), (0, 3), (0, 4), (0, 5), (0, 6), (0, 7), (0, 8), (1, 0), (1, 1), (1, 2), (1, 3), (1, 4), (1, 5), (1, 6), (1, 7), (1, 8), (2, 0), (2, 1), (2, 2), (2, 3), (2, 4), (2, 5), (2, 6), (2, 7), (2, 8), (3, 0), (3, 1), (3, 2), (3, 3), (3, 4), (3, 5), (3, 6), (3, 7), (3, 8), (4, 0), (4, 1), (4, 2), (4, 3), (4, 4), (4, 5), (4, 6), (4, 7), (4, 8). That is, the value range of the coordinate point with the smallest abscissa is [0, 4], and the value range of the coordinate point with the smallest ordinate is [0, 8].

[0105] T(x', y') represents the pixel value corresponding to each pixel point (x', y') in the target image. It can be understood that if the size of the target image is 4×8, and the coordinate point with the smallest abscissa and ordinate in the target image is regarded as (0, 0), then the value range of the coordinate point with the smallest abscissa in the target image is [0, 4), and the value range of the coordinate point with the smallest ordinate is [0, 8).

[0106] represents the average pixel value of the target image.

[0107] I(x + x', y + y') represents the pixel value corresponding to each pixel point (x + x', y + y') in the image to be calibrated. represents the average pixel value of the image to be calibrated.

[0108] Based on the sliding window similarity calculation principle, the monitoring device traverses each value point in the value range of (x', y') and (x, y) in sequence, and a similarity matrix (multiple similarity values) can be obtained.

[0109] Step S404: If the second similarity value is greater than the preset threshold, determine the area of the calibrated image corresponding to the second similarity value as the monitoring area, and the second similarity value is the maximum value among the multiple similarity values.

[0110] It can be understood that the closer the similarity value is to 1, the more similar the calibrated image corresponding to the similarity value is to the target image; the closer the similarity value is to 0, the less similar the calibrated image corresponding to the similarity value is to the target image. If the similarity value is 1, it means that the calibrated image corresponding to the similarity value completely matches the target image.

[0111] The preset threshold can be 0.95, 0.9, 0.85, 0.8, etc., and the specific value of the preset threshold is not limited in this application.

[0112] Step S405: If the first similarity value is less than or equal to the preset threshold, determine the image area corresponding to the calibration coordinate information as the monitoring area.

[0113] It can be understood that if there is no similarity value greater than the preset threshold among the multiple similarity values, it indicates that the probability that the monitoring target is not completely in the image area where the magnified image is located is relatively high, and the monitoring device can determine the image area corresponding to the calibration coordinate information as the monitoring area.

[0114] In some embodiments, if the first similarity value is less than or equal to the preset threshold, the monitoring device can also increase the preset magnification factor to obtain a larger magnified image range, and calculate the similarity value between the magnified image and the target image. This can avoid the calculation result deviation caused by the monitoring target not being completely in the image area where the magnified image is located, improve the accuracy of the calculation result, and thus improve the reliability of the temperature monitoring result.

[0115] After the monitoring device increases the preset magnification factor, the method for determining multiple calibrated images can refer to the method provided in the above steps B1-1 to B1-4, and this application will not elaborate here.

[0116] In the technical solution provided by the embodiments of the present application, when the monitoring device is at the first deviation point, it can obtain the first monitoring image and the first encoder reading corresponding to the first deviation point. The first deviation point is the point corresponding to the first monitoring point, and the first monitoring point is any one of multiple monitoring points. Then, according to the first encoder reading, the target encoder reading, and the target coordinate information, the calibration coordinate information corresponding to the first monitoring image is determined. The calibration coordinate information includes M calibration coordinate points. The target coordinate information is used to represent the M target coordinate points where the first monitoring target is located in the second monitoring image obtained by the monitoring device when the monitoring device is at the first monitoring point. The first monitoring target is the monitoring target corresponding to the first monitoring point among multiple monitoring targets. Then, according to multiple calibration images and the target image, multiple similarity values are determined. The multiple similarity values correspond to the multiple calibration images one by one. The first calibration image includes at least an image area corresponding to N calibration coordinate points. M is greater than or equal to N. The target image is the image area where the M target coordinate points are located in the second monitoring image. The first similarity value is used to represent the similarity between the first calibration image and the target image. The first calibration image is a sub-image of the first monitoring image. The first calibration image is any one of the multiple calibration images. The first similarity value is one of the multiple similarity values corresponding to the first calibration image. If the second similarity value is greater than the preset threshold, it is determined that the area where the calibration image corresponding to the second similarity value is located is the monitoring area, and the second similarity value is the maximum value among the multiple similarity values. If the first similarity value is less than or equal to the preset threshold, it is determined that the image area corresponding to the calibration coordinate information is the monitoring area. The technical solution provided by the embodiments of the present application can determine the calibration coordinate information according to the difference between the current encoder reading (the first encoder reading) and the target encoder reading, thereby calculating the similarity between the multiple calibration images corresponding to the calibration coordinate information and the target image to obtain multiple similarity values, and determining the monitoring area according to the multiple similarity values. It can accurately locate the area where the monitoring target is located, facilitate the monitoring device to perform temperature monitoring, and improve the reliability and accuracy of the temperature monitoring result.

[0117] In some embodiments, after the monitoring device determines the monitoring area, it can perform temperature monitoring on the monitoring area to obtain a temperature monitoring result and output the temperature monitoring result, which can avoid false alarms or missed alarms of the temperature monitoring result by the monitoring device.

[0118] It should be understood that, on the premise of no logical conflict, the above-mentioned various application embodiments can be combined and implemented with each other to meet the actual application requirements. The specific embodiments or implementation schemes obtained after these combinations still fall within the protection scope of the present application.

[0119] Corresponding to the monitoring area determination method in the above embodiments, an embodiment of the present application provides a monitoring area determination device 70, which can be a monitoring device. The monitoring area determination device 70 is used to monitor multiple monitoring targets corresponding to multiple monitoring points, and can be implemented by software, hardware, or a combination of both to become part or all of a computer device, and is used to execute the steps in the monitoring area determination method in the above embodiments.

[0120] Figure 7 FIG. shows a schematic structural diagram of a monitoring area determination device provided by an embodiment of the present application. For the sake of convenience of description, only the parts related to the embodiments of the present application are shown.

[0121] Referring to Figure 7 , the monitoring area determination device 70 includes an acquisition module 710 and a determination module 720.

[0122] The acquisition module 710 is configured to obtain a first monitoring image and a first encoder reading corresponding to a first deviation point when at the first deviation point. The first deviation point is the point corresponding to the first monitoring point, and the first monitoring point is any one of the multiple monitoring points.

[0123] The determination module 720 is configured to determine calibration coordinate information corresponding to the first monitoring image according to the first encoder reading, the target encoder reading, and the target coordinate information. The calibration coordinate information includes M calibration coordinate points. The target coordinate information is used to represent the M target coordinate points where the first monitoring target is located in the second monitoring image obtained by the monitoring device when the monitoring device is at the first monitoring point. The first monitoring target is the monitoring target corresponding to the first monitoring point among the multiple monitoring targets.

[0124] The determination module 720 is further configured to determine multiple similarity values according to multiple calibration images and the target image. The multiple similarity values correspond to the multiple calibration images one by one. The first calibration image includes at least an image area corresponding to N calibration coordinate points, M is greater than or equal to N. The target image is the image area where the M target coordinate points are located in the second monitoring image. The first similarity value is used to represent the similarity between the first calibration image and the target image. The first calibration image is a sub-image of the first monitoring image, the first calibration image is any one of the multiple calibration images, and the first similarity value is one corresponding to the first calibration image among the multiple similarity values.

[0125] The determination module 720 is further configured to determine the area where the calibration image corresponding to the second similarity value is located as the monitoring area when the second similarity value is greater than the preset threshold. The second similarity value is the maximum value among the multiple similarity values.

[0126] The determination module 720 is further configured to determine the image area corresponding to the calibration coordinate information as the monitoring area when the first similarity value is less than or equal to the preset threshold.

[0127] In some embodiments, the determining module 720 is specifically configured to: determine a plurality of calibration images according to the calibration coordinate information. Determine the similarity between the second calibration image and the target image to obtain a third similarity value, so as to determine a plurality of similarity values, where the second calibration image is any one of the plurality of calibration images, and the third similarity value is one corresponding to the second calibration image among the plurality of similarity values.

[0128] In some embodiments, the determining module 720 is specifically configured to: obtain a preset magnification factor. Determine the magnified coordinate information according to the preset magnification factor and the calibration coordinate information. Determine the sub-image corresponding to the magnified coordinate information in the first monitoring image as the magnified image. Determine a plurality of calibration images according to the magnified image and the target image, and the image size corresponding to each calibration image among the plurality of calibration images is the same as the image size corresponding to the target image.

[0129] In some embodiments, the third calibration image and the fourth calibration image are any two different images among the plurality of calibration images. The third calibration image is the image where a plurality of first pixel points are located in the magnified image, and the fourth calibration image is the image where a plurality of second pixel points are located in the magnified image, and the plurality of first pixel points and the plurality of second pixel points are not completely the same.

[0130] In some embodiments, the determining module 720 is specifically configured to: perform grayscale processing on the second calibration image to obtain a grayscale image. Perform filtering processing on the grayscale image to obtain a filtered image. Perform normalization processing on the filtered image to obtain a normalized image. Determine the similarity between the normalized image and the target image to obtain a third similarity value.

[0131] In some embodiments, the determining module 720 is specifically configured to: obtain the target encoder reading. Determine the pixel deviation according to the target encoder reading and the first encoder reading, and the pixel deviation is positively correlated with the encoder angle difference between the first angle and the second angle. The first angle is the encoder angle corresponding to the target encoder reading, and the second angle is the encoder angle corresponding to the first encoder reading. Obtain the target coordinate information. Determine the calibration coordinate information according to the pixel deviation and the target coordinate information.

[0132] In some embodiments, the determining module 720 is further configured to: when at the first monitoring position, obtain a second monitoring image. In response to the received target area division instruction, determine that the sub-image corresponding to the target area division instruction in the second monitoring image is the target image, and the target image is the image where the first monitoring target is located. Record the coordinate information corresponding to the target image in the second monitoring image as the target coordinate information, and record the encoder reading corresponding to the first monitoring position as the target encoder reading.

[0133] In some embodiments, the determining module 720 is further configured to: monitor the temperature of the monitoring area to obtain a temperature monitoring result.

[0134] It should be noted that for the information interaction, execution process, etc. between the above-mentioned devices / units, since they are based on the same inventive concept as the method embodiments of the present application, for their specific functions and the technical effects brought about, reference may be specifically made to the method embodiment part, and details will not be elaborated herein.

[0135] It should be understood that the magnitudes of the sequence numbers of the steps in the above embodiments do not mean the order of execution is prior or posterior. The order of execution of each process should be determined according to its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present application.

[0136] Based on the same inventive concept, an embodiment of the present application further provides an electronic device.

[0137] Figure 8 is a schematic structural diagram of the electronic device provided by the embodiment of the present application. As Figure 8 shown, the electronic device 80 of this embodiment includes: at least one processor 810 ( Figure 8 only one is shown in the figure), a memory 820, and a communication module 840. A computer program 830 that may run on the processor 810 is stored in the memory 820. When the processor 810 executes the computer program 830, it implements the steps in the above-mentioned method embodiment for determining the monitoring area, such as Figure 2 the steps S201 to S203 or the steps S401 to S405 shown in the figure. Alternatively, when the processor 810 executes the computer program 830, it implements the functions of each module / unit in the above-mentioned device embodiments, such as Figure 7 the functions of the modules 710 to 720 shown in the figure. The communication module 840 may be a separate communication unit for communicating with an external server or a terminal device.

[0138] The electronic device 80 may include, but is not limited to: a processor 810 and a memory 820. Those skilled in the art can understand that Figure 8 merely examples of the electronic device 80 do not constitute a limitation to the electronic device 80, and it may include more or fewer components than shown in the figure, or combine certain components, or different components. For example, the electronic device 80 may further include an input and sending device, a network access device, a bus, etc.

[0139] The processor 810 may be a Central Processing Unit (CPU), or may also be other general-purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field-Programmable Gate Arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0140] In some embodiments, the memory 820 may be an internal storage unit of the electronic device 80, such as the hard disk or memory of the electronic device 80. The memory 820 may also be an external storage device of the electronic device 80, such as a plug-in hard disk equipped on the electronic device 80, a Smart Media Card (SMC), a Secure Digital (SD) card, a Flash Card, etc. The memory 820 may also include both the internal storage unit of the electronic device 80 and the external storage device. The memory 820 is used to store an operating system, application programs, a BootLoader, data, and other programs, such as the program code of the computer program 830. The memory 820 may also be used to temporarily store data that has been sent or will be sent.

[0141] In addition, those skilled in the art can clearly understand that, for the convenience and brevity of description, only the above-mentioned division of each functional unit and module is used as an example for illustration. In practical applications, the above-mentioned functions can be allocated to different functional units and modules according to needs, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. In each embodiment of the present application, each functional unit may be integrated in one processing unit, or each unit may exist physically alone, or two or more units may be integrated in one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of a software functional unit.

[0142] The embodiments of the present application provide a computer-readable storage medium. The computer-readable storage medium stores a computer program. When the computer program runs on an electronic device, the electronic device is enabled to execute the steps in the above-mentioned method embodiments.

[0143] An embodiment of the present application provides a chip, which includes a processor and a memory. A computer program is stored in the memory, and when the computer program is executed by the processor, the steps in the above-mentioned method embodiments are implemented.

[0144] An embodiment of the present application provides a computer program product. When the computer program product runs on an electronic device, the electronic device is enabled to execute the steps in the above-mentioned method embodiments.

[0145] It should be understood that the processor mentioned in the embodiments of the present application may be a central processing unit (CPU), or may also be other general-purpose processors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor, or the processor may also be any conventional processor, etc.

[0146] It should also be understood that the memory mentioned in the embodiments of the present application may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memories. Among them, the non-volatile memory may be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory may be a random access memory (RAM), which is used as an external cache. By way of example but not limitation, many forms of RAM are available, such as static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchlink dynamic random access memory (SLDRAM), and direct rambus random access memory (DR RAM).

[0147] Those skilled in the art can clearly understand that, for the convenience and brevity of description, only the above division of each functional unit and module is used as an example. In actual applications, the above functions can be allocated to different functional units and modules according to needs, that is, the internal structure of the device is divided into different functional units or modules to complete all or part of the functions described above. Each functional unit and module in the embodiment can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above integrated unit can be implemented in the form of hardware or in the form of a software functional unit. In addition, the specific names of each functional unit and module are only for the convenience of distinguishing from each other, and do not limit the protection scope of the present application. The specific working process of the units and modules in the above system can refer to the corresponding process in the foregoing method embodiments, and will not be described in detail here.

[0148] In the above embodiments, the descriptions of the respective embodiments have their own emphases. For parts not described in detail or recorded in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0149] Those of ordinary skill in the art can realize that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be implemented by electronic hardware or a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of this application.

[0150] In the embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the system embodiments described above are merely illustrative. For example, the division of the modules or units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed mutual coupling, direct coupling, or communication connection can be through some interfaces. The indirect coupling or communication connection of the devices or units can be in an electrical, mechanical, or other form.

[0151] The units described as separate components may or may not be physically separated. The components displayed as units may or may not be physical units, that is, they can be located in one place or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0152] In addition, the functional units in each embodiment of this application can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above integrated units can be implemented in the form of hardware or in the form of software functional units.

[0153] When the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, to implement all or part of the processes in the above-described embodiment methods of this application, a computer program can be used to instruct relevant hardware to complete. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by a processor, the steps of the above-described various method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in the form of source code, object code, executable file, or some intermediate form, etc. The computer-readable medium can at least include: any entity or device that can carry the computer program code to a large-screen device, a recording medium, a computer memory, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), an electrical carrier signal, a telecommunications signal, and a software distribution medium. For example, a USB flash drive, a mobile hard disk, a magnetic disk, or an optical disc, etc. In some jurisdictions, according to legislation and patent practice, the computer-readable medium cannot be an electrical carrier signal and a telecommunications signal.

[0154] Finally, it should be noted that: The above is only the specific implementation manner of this application, but the protection scope of this application is not limited thereto. Any changes or substitutions within the technical scope disclosed in this application should be covered by the protection scope of this application. Therefore, the protection scope of this application should be subject to the protection scope of the claims.

Claims

1. A method for determining a monitoring area, characterized in that, Applied to a monitoring device for monitoring multiple monitoring targets corresponding to multiple monitoring points, the method includes: When at a first deviation point, obtain a first monitoring image and a first encoder reading corresponding to the first deviation point, where the first deviation point is the point corresponding to a first monitoring point, and the first monitoring point is any one of the multiple monitoring points; According to the first encoder reading, a target encoder reading, and target coordinate information, determine calibration coordinate information corresponding to the first monitoring image. The calibration coordinate information includes M calibration coordinate points. The target coordinate information is used to represent M target coordinate points where a first monitoring target is located in a second monitoring image obtained by the monitoring device when the monitoring device is at the first monitoring point. The first monitoring target is the monitoring target corresponding to the first monitoring point among the multiple monitoring targets; Determine multiple similarity values according to multiple calibration images and a target image. The multiple similarity values correspond one by one to the multiple calibration images. A first calibration image includes at least an image region corresponding to N calibration coordinate points, M is greater than or equal to N. The target image is the image region where the M target coordinate points are located in the second monitoring image. A first similarity value is used to represent the similarity between the first calibration image and the target image. The first calibration image is a sub-image of the first monitoring image and is any one of the multiple calibration images. The first similarity value is one of the multiple similarity values corresponding to the first calibration image; If a second similarity value is greater than a preset threshold, determine the region where the calibration image corresponding to the second similarity value is located as the monitoring region, where the second similarity value is the maximum value among the multiple similarity values; If the first similarity value is less than or equal to the preset threshold, determine the image region corresponding to the calibration coordinate information as the monitoring region.

2. The method for determining a monitoring area according to claim 1, wherein The determining multiple similarity values according to multiple calibration images and a target image includes: Determine the multiple calibration images according to the calibration coordinate information; Determine the similarity between a second calibration image and the target image to obtain a third similarity value to determine the multiple similarity values. The second calibration image is any one image among the multiple calibration images, and the third similarity value is one of the multiple similarity values corresponding to the second calibration image.

3. The monitoring area determination method according to claim 2, characterized in that The determining the multiple calibration images according to the calibration coordinate information includes: Obtain a preset magnification factor; Determine magnified coordinate information according to the preset magnification factor and the calibration coordinate information; Determine the sub-image corresponding to the magnified coordinate information in the first monitoring image as the magnified image; Determine the multiple calibration images according to the magnified image and the target image. The image size corresponding to each calibration image among the multiple calibration images is the same as the image size corresponding to the target image.

4. The method for determining a monitoring area according to claim 3, wherein The third calibration image and the fourth calibration image are any two different images among the multiple calibration images. The third calibration image is the image where multiple first pixel points in the enlarged image are located, and the fourth calibration image is the image where multiple second pixel points in the enlarged image are located. The multiple first pixel points and the multiple second pixel points are not completely the same.

5. The method for determining a monitoring area according to claim 2, wherein Determining the similarity between the second calibration image and the target image to obtain a third similarity value includes: Performing grayscale processing on the second calibration image to obtain a grayscale image; Performing filtering processing on the grayscale image to obtain a filtered image; Performing normalization processing on the filtered image to obtain a normalized image; Determining the similarity between the normalized image and the target image to obtain the third similarity value.

6. The method for determining a monitoring area according to claim 1, wherein The determining the calibration coordinate information corresponding to the first monitoring image according to the first encoder reading, the target encoder reading, and the target coordinate information includes: Obtaining the target encoder reading; Determining a pixel deviation according to the target encoder reading and the first encoder reading. The pixel deviation is positively correlated with the encoder angle difference between the first angle and the second angle. The first angle is the encoder angle corresponding to the target encoder reading, and the second angle is the encoder angle corresponding to the first encoder reading; Obtaining the target coordinate information; Determining the calibration coordinate information according to the pixel deviation and the target coordinate information.

7. The method for determining a monitoring area according to claim 1, wherein Before the method, it further includes: When at the first monitoring position, obtaining the second monitoring image; In response to the received target area division instruction, determining that the sub-image corresponding to the target area division instruction in the second monitoring image is the target image. The target image is the image where the first monitoring target is located; Recording the coordinate information corresponding to the target image in the second monitoring image as the target coordinate information, and recording the encoder reading corresponding to the first monitoring position as the target encoder reading.

8. The method for determining a monitoring area according to any one of claims 1 to 7, characterized in that, After the method, it further includes: Performing temperature monitoring on the monitoring area to obtain a temperature monitoring result.

9. An electronic device, characterized in that, It includes a processor and a memory. The processor is used to execute the computer program stored in the memory to implement the monitoring area determination method described in any one of claims 1-8 above.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the monitoring area determination method described in any one of claims 1-8 above.

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