CN111339997B - Fire point area determination method and device, storage medium and electronic device - Google Patents
Fire point area determination method and device, storage medium and electronic device Download PDFInfo
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Abstract
The invention provides a method and a device for determining a fire area, a storage medium and an electronic device, wherein the method comprises the following steps: acquiring an image frame sequence acquired by image shooting equipment and temperature distribution information corresponding to each frame of image in the image frame sequence; determining a first area in the image frame sequence according to the temperature distribution information, wherein the temperature in the first area is greater than or equal to a first preset threshold value; taking the image frame sequence as the input of a target detection algorithm, and acquiring a second area output by the target detection algorithm; a fire area is determined from the first area and the second area. The invention solves the problem of lower accuracy of the fire monitoring method, thereby achieving the effect of improving the accuracy of fire monitoring.
Description
Technical Field
The invention relates to the field of video monitoring, in particular to a method and a device for determining a fire area, a storage medium and an electronic device.
Background
Fire is a man-made disaster or natural disaster with strong destructive power, strong burst and great difficulty in putting out the fire. In the field, such as forests, plains, fields and the like, the phenomenon that the ignition point spreads and loses control to form a fire disaster is frequently and frequently found and alarmed every year. Therefore, the fire point in the field is found in time, and the fire early warning alarm is triggered in time, so that firefighters can take measures in time to extinguish the fire point, and the fire-fighting equipment is very important for field fire prevention and forest fire prevention work.
Currently, a traditional field fire monitoring method is mainly used for monitoring whether a fire exists or not through manual inspection or whether a fire happens or not through video monitoring. The manual inspection has certain hysteresis, and the fire is required to reach a certain degree to be found. The current video monitoring method mainly uses a visible light camera to shoot images, and determines whether fire disaster occurs or not according to image information. But the images taken by the visible light camera are vulnerable to weather. If the weather and environment with low visibility such as fog, haze, dust emission and the like can greatly reduce the penetrating power of visible light, a visible light camera can not clearly acquire a smoke and fire image of a region to be detected, so that alarm leakage is caused.
Therefore, aiming at the problem of lower accuracy of the fire monitoring method in the related technology, no effective solution exists at present.
Disclosure of Invention
The embodiment of the invention provides a method and a device for determining a fire area, a storage medium and an electronic device, which are used for at least solving the problem of lower accuracy of a fire monitoring method in the related technology.
According to an embodiment of the present invention, there is provided a method of determining a fire area, including: acquiring an image frame sequence acquired by image shooting equipment and temperature distribution information corresponding to each frame of image in the image frame sequence; determining a first area in the image frame sequence according to the temperature distribution information, wherein the temperature in the first area is greater than or equal to a first preset threshold value; taking the image frame sequence as the input of a target detection algorithm, and acquiring a second area output by the target detection algorithm; and determining a fire point area according to the first area and the second area.
Optionally, determining the first region in the image frame sequence according to the temperature distribution information includes: performing binarization processing on a temperature distribution matrix of each frame of image in the image frame sequence to obtain a first distribution matrix, wherein the temperature distribution information comprises the temperature distribution matrix; and carrying out connected domain marking processing on the first distribution matrix to obtain the first region.
Optionally, taking the image frame sequence as an input of a target detection algorithm, obtaining a second region output by the target detection algorithm includes: inputting the image frame sequence into the target detection algorithm, wherein the target detection algorithm is trained through machine learning using a plurality of sets of training data, wherein each set of data in the plurality of sets of training data comprises: a sequence of image frames; and acquiring the second area output by the target detection algorithm and a target object category positioned in the second area.
Optionally, determining a fire area according to the first area and the second area includes: determining that the intersection of the first region and the second region is a third region, and the union of the first region and the second region is a fourth region; and determining the fire point area according to the third area and the fourth area.
Optionally, determining the fire area according to the third area and the fourth area includes: determining a region area ratio of the third region to the fourth region; and under the condition that the area ratio of the first area is smaller than or equal to a second preset threshold value, determining the first area as the fire point area.
Optionally, after determining the fire area, the method further comprises: and sending alarm information.
According to another embodiment of the present invention, there is provided a fire area determining apparatus including: a first acquisition module for acquiring an image frame sequence acquired by an image capturing device and temperature distribution information corresponding to each frame of image in the image frame sequence; a first determining module, configured to determine a first area in the image frame sequence according to the temperature distribution information, where a temperature in the first area is greater than or equal to a first preset threshold; the second acquisition module is used for taking the image frame sequence as the input of a target detection algorithm and acquiring a second region output by the target detection algorithm; and the second determining module is used for determining a fire point area according to the first area and the second area.
Optionally, the first determining module includes: the first processing unit is used for carrying out binarization processing on the temperature distribution matrix of each frame of image in the image frame sequence to obtain a first distribution matrix, wherein the temperature distribution information comprises the temperature distribution matrix; and the second processing unit is used for carrying out connected domain marking processing on the first distribution matrix to obtain the first region.
According to a further embodiment of the invention, there is also provided a storage medium having stored therein a computer program, wherein the computer program is arranged to perform the steps of any of the method embodiments described above when run.
According to a further embodiment of the invention, there is also provided an electronic device comprising a memory having stored therein a computer program and a processor arranged to run the computer program to perform the steps of any of the method embodiments described above.
By the invention, the image frame sequence acquired by the image shooting equipment and the temperature distribution information corresponding to each frame of image in the image frame sequence are acquired; determining a first area in the image frame sequence according to the temperature distribution information, wherein the temperature in the first area is greater than or equal to a first preset threshold value; taking the image frame sequence as the input of a target detection algorithm, and acquiring a second area output by the target detection algorithm; a fire area is determined from the first area and the second area. Therefore, the problem of lower accuracy of the fire monitoring method can be solved, and the effect of improving the accuracy of fire monitoring is achieved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiments of the invention and together with the description serve to explain the invention and do not constitute a limitation on the invention. In the drawings:
fig. 1 is a block diagram of a hardware structure of a mobile terminal according to a fire area determining method according to an embodiment of the present invention;
FIG. 2 is a flow chart of a method of determining a fire area according to an embodiment of the invention;
FIG. 3 is a schematic diagram I of a method of determining a fire area according to an alternative embodiment of the invention;
FIG. 4 is a second schematic diagram of a method of determining a fire area according to an alternative embodiment of the present invention;
FIG. 5 is a schematic diagram III of a method of determining a fire area according to an alternative embodiment of the invention;
FIG. 6 is a schematic diagram IV of a method of determining a fire area according to an alternative embodiment of the invention;
FIG. 7 is a schematic diagram five of a method of determining a fire area according to an alternative embodiment of the invention;
fig. 8 is a block diagram of a fire area determination apparatus according to an embodiment of the present invention.
Detailed Description
The invention will be described in detail hereinafter with reference to the drawings in conjunction with embodiments. It should be noted that, in the case of no conflict, the embodiments and features in the embodiments may be combined with each other.
It should be noted that the terms "first," "second," and the like in the description and the claims of the present invention and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order.
The method embodiment provided in the first embodiment of the present application may be executed in a mobile terminal, a computer terminal or a similar computing device. Taking the mobile terminal as an example, fig. 1 is a block diagram of a hardware structure of the mobile terminal according to a method for determining a fire area according to an embodiment of the present invention. As shown in fig. 1, the mobile terminal may include one or more (only one is shown in fig. 1) processors 102 (the processors 102 may include, but are not limited to, a microprocessor MCU or a processing device such as a programmable logic device FPGA) and a memory 104 for storing data, and optionally, a transmission device 106 for communication functions and an input-output device 108. It will be appreciated by those skilled in the art that the structure shown in fig. 1 is merely illustrative and not limiting of the structure of the mobile terminal described above. For example, the mobile terminal may also include more or fewer components than shown in fig. 1, or have a different configuration than shown in fig. 1.
The memory 104 may be used to store a computer program, for example, a software program of application software and a module, such as a computer program corresponding to a method for determining a fire area in an embodiment of the present invention, and the processor 102 executes the computer program stored in the memory 104 to perform various functional applications and data processing, that is, to implement the above-described method. Memory 104 may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 104 may further include memory remotely located relative to the processor 102, which may be connected to the mobile terminal via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The transmission device 106 is used to receive or transmit data via a network. Specific examples of the network described above may include a wireless network provided by a communication provider of the mobile terminal. In one example, the transmission device 106 includes a network adapter (Network Interface Controller, simply referred to as NIC) that can connect to other network devices through a base station to communicate with the internet. In one example, the transmission device 106 may be a Radio Frequency (RF) module, which is configured to communicate with the internet wirelessly.
In this embodiment, a method for determining a fire area operating on the mobile terminal is provided, and fig. 2 is a flowchart of a method for determining a fire area according to an embodiment of the present invention, as shown in fig. 2, where the flowchart includes the following steps:
step S202, acquiring an image frame sequence acquired by image shooting equipment and temperature distribution information corresponding to each frame of image in the image frame sequence;
the image shooting device can be an infrared thermal imaging camera, the infrared thermal imaging camera can acquire video images of a monitoring area and a thermal imaging spectrogram in real time, the thermal imaging spectrogram comprises temperature detection data of the video images, and temperature distribution information of each frame of image can be reflected through the thermal imaging spectrogram.
Step S204, determining a first area in the image frame sequence according to the temperature distribution information, wherein the temperature in the first area is greater than or equal to a first preset threshold;
the first preset threshold value can be determined according to practical situations, and the area exceeding the first preset threshold value is used as a high-temperature area of the suspicious fire point.
Step S206, taking the image frame sequence as the input of a target detection algorithm, and acquiring a second area output by the target detection algorithm;
the high-temperature area is not necessarily a fire area completely because of being influenced by environmental factors, such as people, motor vehicles, non-motor vehicles, animals, street lamps and the like, and interference of other environmental factors can be eliminated through a target detection algorithm, so that accuracy of a monitoring result is improved.
And step S208, determining a fire area according to the first area and the second area.
By the above steps, since the image frame sequence acquired by the image capturing apparatus and the temperature distribution information corresponding to each frame image in the image frame sequence are acquired; determining a first area in the image frame sequence according to the temperature distribution information, wherein the temperature in the first area is greater than or equal to a first preset threshold value; taking the image frame sequence as the input of a target detection algorithm, and acquiring a second area output by the target detection algorithm; a fire area is determined from the first area and the second area. Therefore, the problem of lower accuracy of the fire monitoring method can be solved, and the effect of improving the accuracy of fire monitoring is achieved.
Alternatively, the execution subject of the above steps may be a terminal or the like, but is not limited thereto.
As an alternative embodiment, determining the first region in the image frame sequence according to the temperature distribution information includes: performing binarization processing on a temperature distribution matrix of each frame of image in the image frame sequence to obtain a first distribution matrix, wherein the temperature distribution information comprises the temperature distribution matrix; and carrying out connected domain marking processing on the first distribution matrix to obtain the first region. In this embodiment, the following steps may be performed by the high temperature detection module:
step 1: and acquiring a video image sequence of each monitoring point thermal imaging camera in the field and a corresponding temperature distribution matrix sequence in real time. The image sequence can be white heat, black heat, amber, jade and other pseudo colors, and if the thermal imaging camera is a double-spectrum camera, the video image sequence can also be a visible light image;
step 2: processing each frame of image in the image frame sequence in the following way: taking the image I as an example, the temperature distribution matrix corresponding to the image I is T, and the temperature T is taken as a threshold value to perform binarization processing, where the value of T can be adjusted according to actual situations, and specifically, the method may be as follows: 100 ℃, 80 ℃, 60 ℃ and the like to obtain a binarized temperature distribution matrix Tbin ij ：
Where M and N are the matrix width and length of the temperature matrix T, or the length and width of the thermal imaging image I, respectively.
Step 3: for the binarized temperature distribution matrix Tbin ij And executing a connected domain marking algorithm to obtain marking frames (id, tx1, ty1, tx2, ty 2) of the binarized high-temperature region, wherein (Tx 1, ty 1) and (Tx 2, ty 2) are respectively the upper left corner coordinates and the lower right corner coordinates of the marking frames, and id is the marking frame number. Wherein the determined mark frame (id, tx1, ty1, tx2, ty 2) of the high temperature region is the first region. Fig. 3 is a schematic diagram of the first area in the present embodiment. By the method, the high-temperature area at the position can be marked, and the suspicious high-temperature area in the monitoring range is determined.
As an alternative embodiment, taking the image frame sequence as an input of a target detection algorithm, acquiring the second region output by the target detection algorithm includes: inputting the image frame sequence into the target detection algorithm, wherein the target detection algorithm is trained through machine learning using a plurality of sets of training data, wherein each set of data in the plurality of sets of training data comprises: a sequence of image frames; and acquiring the second area output by the target detection algorithm and a target object category positioned in the second area. In this embodiment, the following steps may be performed by the high temperature detection module:
step 1: and inputting the video image sequence shot by the thermal imaging camera into a thermal imaging image target detection module for thermal imaging image target detection. The thermal imaging image target detection algorithm is a pre-trained deep convolutional neural network, and detection categories include but are not limited to: human, motor vehicle, non-motor vehicle, animal, street lamp, etc. Thermal imaging image target detection algorithms include, but are not limited to: R-CNN, R-FCN, SSD, YOLO series and other target detection algorithms.
Step 2: and executing the thermal imaging image target detection algorithm on the thermal imaging image frame I corresponding to the temperature distribution matrix T in the high-temperature region detection module to obtain each detected target and corresponding coordinates (class, ix1, iy1, ix2, iy 2) in the thermal imaging image. Wherein (Ix 1, iy 1) and (Ix 2, iy 2) are the upper left and lower right pixel coordinates of the object, respectively, and class is the detected class. The second region is constituted by (Ix 1, iy 1) and (Ix 2, iy 2), and is schematically shown in fig. 4 as a second region detected by the target detection algorithm.
As an alternative embodiment, determining a fire area from the first area and the second area comprises: determining that the intersection of the first region and the second region is a third region, and the union of the first region and the second region is a fourth region; and determining the fire point area according to the third area and the fourth area. In this embodiment, as shown in fig. 5, a third area schematic diagram is formed by the intersection of the first area and the second area; as shown in fig. 6, a fourth region is schematically shown which is formed by the union of the first region and the second region.
As an alternative embodiment, determining the fire area according to the third area and the fourth area includes: determining a region area ratio of the third region to the fourth region; and under the condition that the area ratio of the first area is smaller than or equal to a second preset threshold value, determining the first area as the fire point area. In the present embodiment, the high temperature region marking frames (id, tx1, ty1, tx2, ty 2) and the detection frames (class, ix1, iy1, ix2, iy 2) of the thermal imaging target detection algorithm are subjected to the overlap degree calculation. The proposed overlap degree calculation method adopts a cross ratio IoU calculation method, and the calculation flow is as follows: calculating an intersection overlap of the mark frame and the detection frame:
overlap＝(min(Tx 2 ,Ix 2 )-max(Tx 1 ,Ix 1 ))×(min(Ty 2 ,Iy 2 )-max(Ty 1 ,Iy 1 ))
calculating union of the mark frame and the detection frame:
union＝w 1 ×h 1 +w 2 ×h 2 -overlap
wherein w is 1 ＝Tx 2 -Tx 1 ，h 1 ＝Ty 2 -Ty 1 ，w 2 ＝Ix 2 -Ix 1 ，h 2 ＝Iy 2 -Iy 1 。
Calculating the cross ratio IoU:
when IoU is more than or equal to iou_thresh, the high Wen Biaoji frame corresponding to the id can be judged to be a negative sample, and the high temperature region is excluded from suspicious fires.
When IoU < iou_thresh, judging that the id corresponds to a high-temperature mark frame as a positive sample, namely that the area is a suspicious fire point, and timely triggering alarm output. Specifically, the second preset threshold iou_thresh may be specific to the actual situation, and may be, for example: 0.2, 0.3, 0.5, etc.
As an alternative embodiment, after determining the fire area, the method further comprises: and sending alarm information. In this embodiment, a flowchart of an overall scheme according to an embodiment of the present invention is shown in fig. 7. The embodiment is based on a computer vision and deep learning method, utilizes an infrared thermal imaging camera to monitor suspicious heat sources in the field environment such as forests, plains and the like in real time, and can timely and accurately discover suspicious fire points in a suspicious manner and output an alarm. The infrared spectrum thermal imaging camera has strong environment anti-interference capability, and can monitor suspicious heat sources in real time under the condition of low visibility; can find and alarm in time before the open fire appears, avoid the fire occurrence; the negative sample is generated by utilizing the target detection algorithm, so that non-fire heat sources of motor vehicles, pedestrians, non-motor vehicles, field animals and the like can be eliminated, and the alarm accuracy is improved.
From the description of the above embodiments, it will be clear to a person skilled in the art that the method according to the above embodiments may be implemented by means of software plus the necessary general hardware platform, but of course also by means of hardware, but in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art in the form of a software product stored in a storage medium (e.g. ROM/RAM, magnetic disk, optical disk) comprising instructions for causing a terminal device (which may be a mobile phone, a computer, a server, or a network device, etc.) to perform the method according to the embodiments of the present invention.
The embodiment also provides a device for determining a fire area, which is used for implementing the foregoing embodiments and preferred embodiments, and is not described in detail. As used below, the term "module" may be a combination of software and/or hardware that implements a predetermined function. While the means described in the following embodiments are preferably implemented in software, implementation in hardware, or a combination of software and hardware, is also possible and contemplated.
Fig. 8 is a block diagram of a fire area determining apparatus according to an embodiment of the present invention, as shown in fig. 8, including: a first acquisition module 82 for acquiring a sequence of image frames acquired by an image capturing apparatus, and temperature distribution information corresponding to each frame of image in the sequence of image frames; a first determining module 84, configured to determine a first area in the image frame sequence according to the temperature distribution information, where a temperature in the first area is greater than or equal to a first preset threshold; a second obtaining module 86, configured to obtain a second region output by the target detection algorithm with the image frame sequence as an input of the target detection algorithm; a second determination module 88 for determining a fire area based on the first area and the second area.
As an alternative embodiment, the first determining module includes: the first processing unit is used for carrying out binarization processing on the temperature distribution matrix of each frame of image in the image frame sequence to obtain a first distribution matrix, wherein the temperature distribution information comprises the temperature distribution matrix; and the second processing unit is used for carrying out connected domain marking processing on the first distribution matrix to obtain the first region.
As an alternative embodiment, the second obtaining module includes: an input unit, configured to input the image frame sequence to the target detection algorithm, where the target detection algorithm is trained by machine learning using a plurality of sets of training data, where each set of data in the plurality of sets of training data includes: a sequence of image frames; and the acquisition unit is used for acquiring the second area output by the target detection algorithm and the target object category positioned in the second area.
As an alternative embodiment, the second determining module is further configured to determine the fire area from the first area and the second area by: determining that the intersection of the first region and the second region is a third region, and the union of the first region and the second region is a fourth region; and determining the fire point area according to the third area and the fourth area.
As an alternative embodiment, the second determining module is further configured to determine the fire area according to the third area and the fourth area by: determining a region area ratio of the third region to the fourth region; and under the condition that the area ratio of the first area is smaller than or equal to a second preset threshold value, determining the first area as the fire point area.
As an alternative embodiment, the apparatus is further configured to, after determining the fire area, further comprise: and sending alarm information.
It should be noted that each of the above modules may be implemented by software or hardware, and for the latter, it may be implemented by, but not limited to: the modules are all located in the same processor; alternatively, the above modules may be located in different processors in any combination.
An embodiment of the invention also provides a storage medium having a computer program stored therein, wherein the computer program is arranged to perform the steps of any of the method embodiments described above when run.
Alternatively, in the present embodiment, the above-described storage medium may be configured to store a computer program for performing the steps of:
s1, acquiring an image frame sequence acquired by image shooting equipment and temperature distribution information corresponding to each frame of image in the image frame sequence;
s2, determining a first area in the image frame sequence according to the temperature distribution information, wherein the temperature in the first area is greater than or equal to a first preset threshold value;
s3, taking the image frame sequence as the input of a target detection algorithm, and acquiring a second area output by the target detection algorithm;
and S4, determining a fire point area according to the first area and the second area.
Alternatively, in the present embodiment, the storage medium may include, but is not limited to: a usb disk, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), a removable hard disk, a magnetic disk, or an optical disk, or other various media capable of storing a computer program.
An embodiment of the invention also provides an electronic device comprising a memory having stored therein a computer program and a processor arranged to run the computer program to perform the steps of any of the method embodiments described above.
Optionally, the electronic apparatus may further include a transmission device and an input/output device, where the transmission device is connected to the processor, and the input/output device is connected to the processor.
Alternatively, in the present embodiment, the above-described processor may be configured to execute the following steps by a computer program:
s1, acquiring an image frame sequence acquired by image shooting equipment and temperature distribution information corresponding to each frame of image in the image frame sequence;
s2, determining a first area in the image frame sequence according to the temperature distribution information, wherein the temperature in the first area is greater than or equal to a first preset threshold value;
s3, taking the image frame sequence as the input of a target detection algorithm, and acquiring a second area output by the target detection algorithm;
and S4, determining a fire point area according to the first area and the second area.
Alternatively, specific examples in this embodiment may refer to examples described in the foregoing embodiments and optional implementations, and this embodiment is not described herein.
It will be appreciated by those skilled in the art that the modules or steps of the invention described above may be implemented in a general purpose computing device, they may be concentrated on a single computing device, or distributed across a network of computing devices, they may alternatively be implemented in program code executable by computing devices, so that they may be stored in a memory device for execution by computing devices, and in some cases, the steps shown or described may be performed in a different order than that shown or described, or they may be separately fabricated into individual integrated circuit modules, or multiple modules or steps within them may be fabricated into a single integrated circuit module for implementation. Thus, the present invention is not limited to any specific combination of hardware and software.
The above description is only of the preferred embodiments of the present invention and is not intended to limit the present invention, but various modifications and variations can be made to the present invention by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the principle of the present invention should be included in the protection scope of the present invention.
Claims (8)
1. A method of determining a fire area, comprising:
acquiring an image frame sequence acquired by image shooting equipment and temperature distribution information corresponding to each frame of image in the image frame sequence;
determining a first area in the image frame sequence according to the temperature distribution information, wherein the temperature in the first area is greater than or equal to a first preset threshold value;
taking the image frame sequence as the input of a target detection algorithm, and acquiring a second region output by the target detection algorithm, wherein the second region is a region containing a target object;
determining a fire area according to the first area and the second area;
wherein determining a fire area from the first area and the second area comprises: determining that the intersection of the first region and the second region is a third region, and the union of the first region and the second region is a fourth region; determining a region area ratio of the third region to the fourth region; and under the condition that the area ratio of the first area is smaller than or equal to a second preset threshold value, determining the first area as the fire point area.
2. The method of claim 1, wherein determining a first region in the sequence of image frames from the temperature distribution information comprises:
performing binarization processing on a temperature distribution matrix of each frame of image in the image frame sequence to obtain a first distribution matrix, wherein the temperature distribution information comprises the temperature distribution matrix;
and carrying out connected domain marking processing on the first distribution matrix to obtain the first region.
3. The method of claim 1, wherein taking the sequence of image frames as input to a target detection algorithm, obtaining a second region output by the target detection algorithm, comprises:
inputting the image frame sequence into the target detection algorithm, wherein the target detection algorithm is trained through machine learning using a plurality of sets of training data, wherein each set of data in the plurality of sets of training data comprises: a sequence of image frames;
and acquiring the second area output by the target detection algorithm and a target object category positioned in the second area.
4. A method according to any one of claims 1 to 3, wherein after determining the fire area, the method further comprises:
and sending alarm information.
5. A fire area determination apparatus, comprising:
a first acquisition module for acquiring an image frame sequence acquired by an image capturing device and temperature distribution information corresponding to each frame of image in the image frame sequence;
a first determining module, configured to determine a first area in the image frame sequence according to the temperature distribution information, where a temperature in the first area is greater than or equal to a first preset threshold;
the second acquisition module is used for taking the image frame sequence as the input of a target detection algorithm and acquiring a second region output by the target detection algorithm, wherein the second region is a region containing a target object;
the second determining module is used for determining a fire point area according to the first area and the second area;
the second determining module is further configured to determine a fire area according to the first area and the second area by: determining that the intersection of the first region and the second region is a third region, and the union of the first region and the second region is a fourth region; determining a region area ratio of the third region to the fourth region; and under the condition that the area ratio of the first area is smaller than or equal to a second preset threshold value, determining the first area as the fire point area.
6. The apparatus of claim 5, further comprising the first determination module comprising:
the first processing unit is used for carrying out binarization processing on the temperature distribution matrix of each frame of image in the image frame sequence to obtain a first distribution matrix, wherein the temperature distribution information comprises the temperature distribution matrix;
and the second processing unit is used for carrying out connected domain marking processing on the first distribution matrix to obtain the first region.
7. A storage medium having a computer program stored therein, wherein the computer program is arranged to perform the method of any of claims 1 to 4 when run.
8. An electronic device comprising a memory and a processor, characterized in that the memory has stored therein a computer program, the processor being arranged to run the computer program to perform the method of any of the claims 1 to 4.
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| CN112347874A (en) * | 2020-10-26 | 2021-02-09 | 创泽智能机器人集团股份有限公司 | Fire detection method, device, equipment and storage medium |
| CN112362164B (en) * | 2020-11-10 | 2022-01-18 | 广东电网有限责任公司 | Temperature monitoring method and device of equipment, electronic equipment and storage medium |
| CN113205178B (en) * | 2021-04-27 | 2021-11-30 | 特斯联科技集团有限公司 | Artificial intelligent infrared image sensing system and method |
| CN113192038B (en) * | 2021-05-07 | 2022-08-19 | 北京科技大学 | Method for recognizing and monitoring abnormal smoke and fire in existing flame environment based on deep learning |
| CN113343859A (en) * | 2021-06-10 | 2021-09-03 | 浙江大华技术股份有限公司 | Smoking behavior detection method and device, storage medium and electronic device |
| CN113536918B (en) * | 2021-06-10 | 2024-04-16 | 浙江华感科技有限公司 | Firework detection method, system, electronic device and storage medium |
| CN113298025A (en) * | 2021-06-11 | 2021-08-24 | 浙江华消科技有限公司 | Target object determination method and device, storage medium and electronic device |
| CN115862296B (en) * | 2023-02-14 | 2023-06-06 | 山东铁路投资控股集团有限公司 | Fire risk early warning method, system, equipment and medium for railway construction site |
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