CN114120181A - Fire monitoring system and method based on video identification - Google Patents
Fire monitoring system and method based on video identification Download PDFInfo
- Publication number
- CN114120181A CN114120181A CN202111346114.8A CN202111346114A CN114120181A CN 114120181 A CN114120181 A CN 114120181A CN 202111346114 A CN202111346114 A CN 202111346114A CN 114120181 A CN114120181 A CN 114120181A
- Authority
- CN
- China
- Prior art keywords
- image
- information
- module
- fire
- database
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000012544 monitoring process Methods 0.000 title claims abstract description 41
- 238000000034 method Methods 0.000 title claims description 14
- 238000004364 calculation method Methods 0.000 claims abstract description 63
- 238000004891 communication Methods 0.000 claims abstract description 13
- 239000000779 smoke Substances 0.000 claims description 14
- 230000009193 crawling Effects 0.000 claims description 6
- 238000010586 diagram Methods 0.000 claims description 6
- 238000005516 engineering process Methods 0.000 claims description 6
- 238000005259 measurement Methods 0.000 claims description 3
- 238000007781 pre-processing Methods 0.000 claims description 2
- 239000013598 vector Substances 0.000 description 5
- 238000000605 extraction Methods 0.000 description 2
- 239000000463 material Substances 0.000 description 2
- 238000012545 processing Methods 0.000 description 2
- 239000000443 aerosol Substances 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000002485 combustion reaction Methods 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 239000007789 gas Substances 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000002093 peripheral effect Effects 0.000 description 1
- 230000002265 prevention Effects 0.000 description 1
- 238000005070 sampling Methods 0.000 description 1
- 238000013179 statistical model Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B17/00—Fire alarms; Alarms responsive to explosion
- G08B17/12—Actuation by presence of radiation or particles, e.g. of infrared radiation or of ions
- G08B17/125—Actuation by presence of radiation or particles, e.g. of infrared radiation or of ions by using a video camera to detect fire or smoke
-
- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
- G08B21/18—Status alarms
- G08B21/182—Level alarms, e.g. alarms responsive to variables exceeding a threshold
Landscapes
- Business, Economics & Management (AREA)
- Emergency Management (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- Multimedia (AREA)
- Fire-Detection Mechanisms (AREA)
- Alarm Systems (AREA)
Abstract
The invention discloses a fire monitoring system based on video identification, which comprises a recording shooting terminal and an identification computing terminal, wherein the shooting terminal comprises a camera, a sensor assembly, a communication module, a main control device and an integrated circuit, the main control device is respectively connected with the camera, the sensor assembly and the communication module through the integrated circuit, the camera is used for collecting images of monitoring points, the communication module is used for connecting the identification computing terminal and the identification computing terminal through I selection to transmit image information, and the identification computing terminal comprises a collecting module, a storage module, a classification management module and a comparison computing module. According to the invention, through the arrangement of the shooting equipment, when the large changes of the air humidity and the temperature are sensed, the camera is utilized to collect video images of the monitoring point, then the image information is sent to the identification and calculation terminal, the fire images are identified and matched, different early warning prompts are made through comparison, and the fire condition can be conveniently handled by personnel.
Description
Technical Field
The invention belongs to the technical field of fire fighting, and particularly relates to a fire monitoring system based on video identification.
Background
Gases, aerosols, smoke, flames and a lot of heat generated during the combustion process of a fire. The determination of the fire parameters can be used to identify and detect the occurrence of a fire. Fire identification is always an important prevention link in the fire rescue process, and only when the fire is in a controllable state, the fire is effectively controlled, so that the loss can be reduced to the minimum.
The method has the advantages that the flame position can be accurately positioned, but the position of a sampling point is preset and the heat sensor is used, and the flame area is extracted from a video image acquired by a high-speed camera based on color characteristics, such as Healey and Foo in the United kingdom, but the system requires ideal environment and the camera window is manually initialized. A color statistical model is built for an image sequence acquired by a common camera, and a self-adaptive background model is built according to Gaussian distribution of three channels of red, green and blue, so that the method can better perform fire detection. Therefore, the fire monitoring system based on video identification is provided.
Disclosure of Invention
The invention aims to overcome the problems in the prior art, and provides a fire monitoring system based on video identification.
In order to achieve the technical purpose and achieve the technical effect, the invention is realized by the following technical scheme:
a fire monitoring system based on video identification comprises a recording shooting terminal and an identification computing terminal;
the shooting terminal comprises a camera, a sensor component, a communication module, a main control device and an integrated circuit, wherein the main control device is respectively connected with the camera, the sensor component and the communication module through the integrated circuit;
the identification and calculation terminal comprises an acquisition module, a storage module, a classification management module and a comparison and calculation module, wherein the acquisition module is used for crawling images of fire from the Internet by using a crawler technology and sending image contents to the storage module, the storage module is used for storing and managing acquired massive image information to establish a large database, the classification management module is used for classifying smoke images, open fire images and large fire images in the database, and the comparison and calculation module is used for receiving image information transmitted by the shooting terminal and comparing the image information with image information in the database.
Further, the sensor assembly comprises a temperature sensor and a humidity sensor, wherein the temperature sensor is used for monitoring temperature change of the monitoring point, and the humidity sensor is used for monitoring humidity change of the monitoring point.
Further, the comparison calculation module matches the image information of the shooting terminal with the image information of the smoke in the database, if the comparison calculation module judges that the image information of the shooting terminal is "NO", the comparison calculation module finishes the process of judging that the image information of the shooting terminal is "YES", a first-stage early warning prompt is generated and the image is matched again, the comparison calculation module matches the image information of the shooting terminal with the image of the naked flame in the database, if the comparison calculation module judges that the image information of the shooting terminal is "NO", the comparison calculation module finishes the process of generating a second-stage early warning prompt and the image is matched again, if the comparison calculation module judges that the image information of the shooting terminal is "NO", and if the comparison calculation module judges that the image information of the shooting terminal is "NO", the comparison calculation module finishes the process of the shooting terminal and the image information of the naked flame in the database, and generates a third-stage early warning prompt.
Further, the specific judgment mode is that the image is converted from an RGB image space to an HSV image space, and an HSV color distribution histogram of the monitoring area is established, wherein R, G, B respectively represents three channels of red, green and blue; H. s, V respectively representing hue, saturation and brightness, separating H component from HSV image space, querying color distribution histogram according to H component to obtain flame color probability distribution graph in monitored area, tracking the monitored area by Camshift tracking algorithm according to the flame color probability distribution graph, outputting the centroid position of flame as measurement signal, and sending to Kalman filter, Kalman filterThe an filter determines the position and the size of a search window according to the position of a centroid (namely the central position of the search window), an area for calculating probability distribution is set according to the search window and is fed back to a Camshift tracker as state prediction information, the tracking of a monitoring area in the next image is implemented, the minimum rectangular area surrounding a flame image can be obtained according to the tracking result, i.e. the tracked monitoring area, separates the tracked flame part area from the background of the original image, and the monitored area is preprocessed, such as graying, denoising, binarization, mathematical morphology processing and the like, the flame is segmented from the residual small amount of background, seven Hu moments of flame are extracted according to a calculation formula of the Hu moments as characteristic vectors of the flame, the Hu moments of the segmented monitoring areas are extracted according to the Hu moments, and combining the flame feature vectors into a flame feature vector, wherein the Hu moment is used as a descriptor in the flame feature extraction part. And separating and segmenting the flame according to the tracked result. Calculating the geometrical moment U of the order of (p + q) of the flame by a formulapqWherein U ispqIs a geometric moment of order p + q, xpyqIs a transform kernel, I (x, y) is a pixel value at the binarized image (x, y), and the range of x and y is a flame portion region.
Further, the zero order moment of the flame is defined as the moment
Is defined as:
further, Upq represents the area of the flame image, the central moment of the flame:
Upq＝∑x∑yI(x，y)
a fire monitoring method based on video identification comprises the following steps:
A. when a sensor of the shooting equipment monitors that the temperature change and the humidity change are large in a short time, a camera acquires images of monitoring points and sends image information to an identification and calculation terminal through a communication module;
B. the system comprises an acquisition module, a storage module, a classification management module and a comparison calculation module, wherein the acquisition module of an identification calculation terminal is used for crawling fire images from the Internet by using a crawler technology and sending image contents to the storage module, the storage module is used for storing and managing acquired massive image information to establish a large database, the classification management module is used for classifying smoke images, open fire images and large fire images in the database, and the comparison calculation module is used for receiving image information transmitted by a shooting terminal and comparing the image information with image information in the database;
C. the comparison calculation module matches the information of the image of the shooting terminal with the information of the image of the smoke in the database, if the information is judged to be NO, the comparison calculation module finishes the step, if the information is judged to be YES, a first-level early warning prompt is generated and the image is matched again, the comparison calculation module matches the information of the image of the shooting terminal with the image of the naked flame in the database, if the information is judged to be NO, the comparison calculation module finishes the step, if the information is judged to be YES, a second-level early warning prompt is generated and the image is matched again, the comparison calculation module matches the information of the image of the shooting terminal with the information of the image of the naked flame in the database, if the information is judged to be NO, the comparison calculation module finishes the step, and if the information is judged to be YES, a third-level early warning prompt is generated.
The invention has the beneficial effects that: this kind of conflagration monitored control system based on video identification, through being provided with shooting equipment, when feeling air humidity and temperature and changing by a wide margin, utilize the camera to carry out video image collection to the monitoring point, send image information for discernment calculation terminal again, discern the matching to conflagration image, make different early warning prompts through the contrast, traditional smoke detector and temperature sensor early warning conflagration have been replaced, carry out the early warning to the conflagration with more accurate mode, classify the rating to the conflagration rank simultaneously, make things convenient for personnel to handle the condition of a fire, reduce the loss.
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 embodiment(s) of the invention and together with the description serve to explain the invention without limiting the invention. In the drawings:
FIG. 1 is a schematic flow diagram of the present invention;
FIG. 2 is a schematic diagram of a comparison calculation module of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In the description of the present invention, it is to be understood that the terms "opening," "upper," "lower," "thickness," "top," "middle," "length," "inner," "peripheral," and the like are used in an orientation or positional relationship that is merely for convenience in describing and simplifying the description, and do not indicate or imply that the referenced component or element must have a particular orientation, be constructed and operated in a particular orientation, and thus should not be considered as limiting the present invention.
As shown in figure 1, a fire monitoring system based on video identification, a shooting terminal comprises a camera, a sensor component, a communication module, a main control device and an integrated circuit, the main control device is respectively connected with the camera, the sensor component and the communication module through the integrated circuit, the camera is used for collecting images of monitoring points, the communication module is used for connecting an identification computing terminal and the identification computing terminal through I's choice to transmit image information, the identification computing terminal comprises a collecting module, a storage module, a classification management module and a comparison computing module, the collecting module is used for crawling fire images from the internet by using a crawler technology and sending image contents to the storage module, the storage module is used for storing and managing the acquired massive image information to establish a large database, the classification management module is used for classifying smoke images, open fire images and large fire images in the database, the comparison calculation module is used for receiving image information transmitted by the shooting terminal and comparing the image information with image information in a database, the sensor assembly comprises a temperature sensor and a humidity sensor, the temperature sensor is used for monitoring temperature change of the monitoring point, and the humidity sensor is used for monitoring humidity change of the monitoring point.
As shown in fig. 2, the comparison calculation module matches the image information of the shooting terminal with the image information of smoke in the database, if the comparison calculation module determines that the image information of the shooting terminal is "NO", the comparison calculation module ends the process, if the comparison calculation module determines that the image information of the shooting terminal is "YES", the first-stage early warning prompt is generated and the image is matched again, the comparison calculation module matches the image information of the shooting terminal with the image of naked flame in the database, if the comparison calculation module determines that the image information of the shooting terminal is "NO", the second-stage early warning prompt is generated and the image is matched again, if the comparison calculation module determines that the image information of the shooting terminal is matched with the image information of the naked flame in the database, the comparison calculation module ends the process, if the comparison calculation module determines that the image information of the shooting terminal is "NO", and the third-stage early warning prompt is generated if the comparison calculation module determines that the image information of the shooting terminal is "YES". The specific judgment mode is that the image is converted from an RGB image space to an HSV image space, and an HSV color distribution histogram of the monitoring area is established, wherein R, G, B respectively represents a red channel, a green channel and a blue channel; H. s, V respectively representing hue, saturation and brightness, separating H component from HSV image space, inquiring the color distribution histogram according to H component to obtain flame color probability distribution diagram in the monitored area, tracking the monitored area by Camshift tracking algorithm according to the flame color probability distribution diagram, outputting the centroid position of the flame as a measuring signal, sending to a Kalman filter, determining the position and size of the searching window according to the centroid position (i.e. the central position of the searching window), setting the area of the calculated probability distribution according to the searching window as state prediction information and feeding back to the Camshift tracker to perform tracking of the monitored area in the next image, obtaining the minimum rectangular area surrounding the flame image according to the tracking result, i.e. the tracked monitored area, separating the tracked flame area from the background of the original image, and preprocessing the monitored area, such as graying, denoising, binarization, mathematical morphology processing and the like, segmenting the flame from the rest of a small amount of background, extracting seven Hu moments of the flame as characteristic vectors of the flame according to a calculation formula of the Hu moments, extracting the Hu moments of the segmented monitored area according to the Hu moments, and combining the Hu moments into flame characteristic vectors, wherein the Hu moments are used as descriptors in the flame characteristic extraction part. And separating and segmenting the flame according to the tracked result, and extracting seven Hu moments of the flame. Through the followingCalculates the (p + q) order geometrical moment U of the flamepqWherein U ispqIs a geometric moment of order p + q, xpyqIs a transform kernel, I (x, y) is a pixel value at the binarized image (x, y), and the range of x and y is a flame portion region.
Zero order moment of flame
Is defined as:
upq denotes the area of the flame image, the central moment of the flame:
Upq＝∑x∑yI(x，y)
a fire monitoring method based on video identification comprises the following steps:
A. when a sensor of the shooting equipment monitors that the temperature change and the humidity change are large in a short time, a camera acquires images of monitoring points and sends image information to an identification and calculation terminal through a communication module;
B. the system comprises an acquisition module, a storage module, a classification management module and a comparison calculation module, wherein the acquisition module of an identification calculation terminal is used for crawling fire images from the Internet by using a crawler technology and sending image contents to the storage module, the storage module is used for storing and managing acquired massive image information to establish a large database, the classification management module is used for classifying smoke images, open fire images and large fire images in the database, and the comparison calculation module is used for receiving image information transmitted by a shooting terminal and comparing the image information with image information in the database;
C. the comparison calculation module matches the information of the image of the shooting terminal with the information of the image of the smoke in the database, if the information is judged to be NO, the comparison calculation module finishes the step, if the information is judged to be YES, a first-level early warning prompt is generated and the image is matched again, the comparison calculation module matches the information of the image of the shooting terminal with the image of the naked flame in the database, if the information is judged to be NO, the comparison calculation module finishes the step, if the information is judged to be YES, a second-level early warning prompt is generated and the image is matched again, the comparison calculation module matches the information of the image of the shooting terminal with the information of the image of the naked flame in the database, if the information is judged to be NO, the comparison calculation module finishes the step, and if the information is judged to be YES, a third-level early warning prompt is generated.
In the description herein, references to the description of "one embodiment," "an example," "a specific example" or the like are intended to mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
The foregoing shows and describes the general principles, essential features, and advantages of the invention. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, which are described in the specification and illustrated only to illustrate the principle of the present invention, but that various changes and modifications may be made therein without departing from the spirit and scope of the present invention, which fall within the scope of the invention as claimed.
Claims (5)
1. A fire monitoring system based on video identification is characterized by comprising a recording shooting terminal and an identification computing terminal;
the shooting terminal comprises a camera, a sensor component, a communication module, a main control device and an integrated circuit, wherein the main control device is respectively connected with the camera, the sensor component and the communication module through the integrated circuit;
the identification and calculation terminal comprises an acquisition module, a storage module, a classification management module and a comparison and calculation module, wherein the acquisition module is used for crawling images of fire from the Internet by using a crawler technology and sending image contents to the storage module, the storage module is used for storing and managing acquired massive image information to establish a large database, the classification management module is used for classifying smoke images, open fire images and large fire images in the database, and the comparison and calculation module is used for receiving image information transmitted by the shooting terminal and comparing the image information with image information in the database.
2. The fire monitoring system based on video identification as claimed in claim 1, wherein the sensor assembly comprises a temperature sensor and a humidity sensor, the temperature sensor is used for monitoring temperature change of the monitoring point, and the humidity sensor is used for monitoring humidity change of the monitoring point.
3. The fire monitoring system based on video recognition as recited in claim 1, wherein the comparison calculation module matches the shooting terminal image information with the smoke image information in the database, ends if it is determined as "NO", generates a primary warning prompt if it is determined as "YES", matches the image again, matches the shooting terminal image information with the open fire image in the database, ends if it is determined as "NO", generates a secondary warning prompt if it is determined as "YES", matches the image again, matches the shooting terminal image information with the open fire image information in the database, ends if it is determined as "NO", and generates a tertiary warning prompt if it is determined as "YES".
4. The fire monitoring system based on video identification as claimed in claim 1, wherein the contrast calculation module converts the image from RGB image space to HSV image space, establishes HSV color distribution histogram of the monitored area, wherein R, G, B represents red, green and blue channels, H, S, V represents hue, saturation and brightness, separates H component from HSV image space, queries the color distribution histogram according to H component, obtains flame color probability distribution diagram in the monitored area, tracks the monitored area by using Camshift tracking algorithm according to the flame color probability distribution diagram, outputs the centroid position of the flame as a measurement signal, sends the measurement signal to Kalman filter, determines the position and size of the search window according to the centroid position, and feeds back the area of the probability distribution calculated according to the search window setting as state prediction information to the Camshift tracker, and obtaining a tracked monitoring area surrounding the flame image according to the tracking result, separating the tracked flame part area from the original image background, preprocessing the monitoring area, and performing operation matching comparison in a mathematical form.
5. The fire monitoring method based on video identification as claimed in claim 1, wherein the method comprises the following steps: .
A. When a sensor of the shooting equipment monitors that the temperature change and the humidity change are large in a short time, a camera acquires images of monitoring points and sends image information to an identification and calculation terminal through a communication module;
B. the system comprises an acquisition module, a storage module, a classification management module and a comparison calculation module, wherein the acquisition module of an identification calculation terminal is used for crawling fire images from the Internet by using a crawler technology and sending image contents to the storage module, the storage module is used for storing and managing acquired massive image information to establish a large database, the classification management module is used for classifying smoke images, open fire images and large fire images in the database, and the comparison calculation module is used for receiving image information transmitted by a shooting terminal and comparing the image information with image information in the database;
C. the comparison calculation module matches the information of the image of the shooting terminal with the information of the image of the smoke in the database, if the information is judged to be NO, the comparison calculation module finishes the step, if the information is judged to be YES, a first-level early warning prompt is generated and the image is matched again, the comparison calculation module matches the information of the image of the shooting terminal with the image of the naked flame in the database, if the information is judged to be NO, the comparison calculation module finishes the step, if the information is judged to be YES, a second-level early warning prompt is generated and the image is matched again, the comparison calculation module matches the information of the image of the shooting terminal with the information of the image of the naked flame in the database, if the information is judged to be NO, the comparison calculation module finishes the step, and if the information is judged to be YES, a third-level early warning prompt is generated.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111346114.8A CN114120181A (en) | 2021-11-15 | 2021-11-15 | Fire monitoring system and method based on video identification |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111346114.8A CN114120181A (en) | 2021-11-15 | 2021-11-15 | Fire monitoring system and method based on video identification |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN114120181A true CN114120181A (en) | 2022-03-01 |
Family
ID=80396109
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111346114.8A Pending CN114120181A (en) | 2021-11-15 | 2021-11-15 | Fire monitoring system and method based on video identification |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114120181A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115359615A (en) * | 2022-08-15 | 2022-11-18 | 北京飞讯数码科技有限公司 | Indoor fire alarm early warning method, system, device, equipment and medium |
| CN115437293A (en) * | 2022-09-27 | 2022-12-06 | 爱景节能科技（上海）有限公司 | Air compressor machine remote monitering system |
-
2021
- 2021-11-15 CN CN202111346114.8A patent/CN114120181A/en active Pending
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115359615A (en) * | 2022-08-15 | 2022-11-18 | 北京飞讯数码科技有限公司 | Indoor fire alarm early warning method, system, device, equipment and medium |
| CN115359615B (en) * | 2022-08-15 | 2023-08-04 | 北京飞讯数码科技有限公司 | Indoor fire alarm early warning method, system, device, equipment and medium |
| CN115437293A (en) * | 2022-09-27 | 2022-12-06 | 爱景节能科技（上海）有限公司 | Air compressor machine remote monitering system |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN115691026B (en) | Intelligent early warning monitoring management method for forest fire prevention | |
| CN110516609B (en) | Fire disaster video detection and early warning method based on image multi-feature fusion | |
| CN108416968B (en) | Fire early warning method and device | |
| CN112069975B (en) | Comprehensive flame detection method based on ultraviolet, infrared and vision | |
| CN114120181A (en) | Fire monitoring system and method based on video identification | |
| US9495754B2 (en) | Person clothing feature extraction device, person search device, and processing method thereof | |
| Zhao et al. | SVM based forest fire detection using static and dynamic features | |
| US7876229B2 (en) | Flare monitoring | |
| CN110675588B (en) | Forest fire detection device and method | |
| CN108898069B (en) | Video flame detection method based on multi-classifier fusion | |
| Ap-Apid | An algorithm for nudity detection | |
| CN114885119A (en) | Intelligent monitoring alarm system and method based on computer vision | |
| CN106815567B (en) | Flame detection method and device based on video | |
| Celik et al. | Computer vision based fire detection in color images | |
| JP5155250B2 (en) | Object detection device | |
| CN112418102A (en) | Smoke and fire detection method and device, smoke and fire detection system and electronic equipment | |
| CN112070072B (en) | Prefabricated cabin fire control system based on image recognition and control method thereof | |
| CN113657250A (en) | Flame detection method and system based on monitoring video | |
| Li et al. | Research on forest fire image recognition algorithm based on color feature statistics | |
| US11610386B2 (en) | Electronic device for identifying and tracking at least one target, associated electronic system, method and computer program | |
| Chen et al. | Research of fire detection method based on multi-sensor data fusion | |
| Yuan et al. | Vision based fire detection using mixture Gaussian model | |
| CN112052912A (en) | Intelligent flame combustion state identification method for fire-fighting robot | |
| CN112101232A (en) | Flame detection method based on multiple classifiers | |
| Vijaylaxmi et al. | Fire detection using YCbCr color model |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |