CN113688670A - A method for monitoring the brightness of street lamps based on image recognition technology - Google Patents
A method for monitoring the brightness of street lamps based on image recognition technology Download PDFInfo
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Abstract
The invention belongs to the technical field of street lamp brightness monitoring, and particularly relates to a method for monitoring street lamp brightness based on an image recognition technology, which comprises the following steps: installing an intelligent camera on the urban street lamp, scanning and monitoring street scenes in real time according to the set lighting time point of the street lamp, and judging whether the brightness of the street lamp is normal or not; the cloud server of the urban management command center automatically pushes the identification module to the intelligent cameras installed on the street lamps; when the intelligent camera judges that the street lamp brightness is abnormal, an actual screenshot and an automatic identification result are immediately reported to a cloud server of the urban management command center; and actually comparing the screenshots by the staff of the urban management command center, and informing the urban management team members of field processing when determining an abnormal condition. The intelligent street lamp monitoring system closely surrounds the strategic guidance idea of 'internet +', is provided with the intelligent camera on the street lamp of the city, monitors the street lamp condition in real time, has an algorithm capable of identifying the street lamp abnormal condition, effectively eliminates the additional influence of weather and environment, and correctly identifies the street lamp abnormal condition.
Description
Technical Field
The invention relates to the technical field of street lamp brightness monitoring, in particular to a method for monitoring street lamp brightness based on an image recognition technology.
Background
Along with the continuous development of urbanization construction, the city scale is bigger and bigger, and road street lamp also is the explosive growth, and the task of control street lamp old and dark going out is also more and more heavy, and city street lamp is as municipal works's important constitution, and its accurate management and control and energy-conservation seem more and more important.
At present, two main methods are used for street lamp monitoring tasks, namely, a worker inspects and reports street lamp conditions, and citizens report is relied on. However, the former operation is time-consuming and labor-consuming, and cannot be performed for a long time; the latter can only respond when the citizen finds a problem, which causes the satisfaction of the citizen on the city management work to be reduced.
Therefore, a method for monitoring the brightness of the street lamp based on an image recognition technology is provided to solve the problems.
Disclosure of Invention
The invention aims to solve the defects in the prior art, and provides a method for monitoring the brightness of a street lamp based on an image recognition technology.
In order to achieve the purpose, the invention adopts the following technical scheme:
a method for monitoring street lamp brightness based on an image recognition technology comprises the following steps:
s1, installing an intelligent camera on the urban street lamp, scanning and monitoring street scenes in real time according to the set lighting time point of the street lamp, and judging whether the brightness of the street lamp is normal or not;
s2, automatically pushing an identification module to an intelligent camera installed on each street lamp by the cloud server of the city management command center;
s3, when the intelligent camera judges that the street lamp brightness is abnormal, immediately reporting an actual screenshot and an automatic identification result to a cloud server of the urban management command center;
and S4, actually comparing the screenshots by the staff of the urban management command center, and informing the urban management team members of field processing when determining abnormal conditions.
In the method for monitoring the brightness of the street lamp based on the image recognition technology, the method for feeding back the abnormal brightness of the street lamp in the steps S1 and S2 includes the following steps:
(1) collecting typical pictures of streets under the conditions that the street lamps are extinguished, the brightness is abnormal and the brightness is normal;
(2) marking that the street lamp is off, and the street lamp is a picture with abnormal brightness and a street view picture with normal brightness;
(3) uploading a labeled photo and labeling data to a cloud server of the urban management command center;
(4) the identification module is started, weather can be effectively eliminated, extra articles are mixed, the influence of people is avoided, and the abnormal condition of the street lamp is accurately judged.
In the method for monitoring the street lamp brightness based on the image recognition technology, the recognition module can extract the brightness characteristics of the obtained street lamp real-time image, and the method comprises the following steps:
1) reading in an image;
2) gamma correction of the image;
3) converting the image color space from RGB to XYZ and then from XYZ to Lab;
4) normalizing the image characteristic value;
5) grouping image characteristic values;
6) each pixel point represents a characteristic value by a packet sequence number.
In the method for monitoring the brightness of the street lamp based on the image recognition technology, the feature algorithm of the image brightness comprises the following steps:
A. acquiring a neighborhood window: after the original image is converted into a Lab color space, the brightness value of the original image is completely reflected on an L component, a disc area with the radius of R is selected from a first element each time in an L component matrix, the gradient is calculated according to set 4 directions, a small window is drawn in the L component matrix by taking a point of which the gradient is to be solved as the center, and then the elements of the circular area in the small window are weighted, so that each element of the L component of the window matrix is constructed to express the brightness characteristic of the corresponding point of the original image;
B. component partitioning direction matrix: the given direction number is 4, namely the brightness gradient in 4 directions needs to be solved, the disc is divided according to four directions, 8 fan-shaped areas can be obtained, the angle of each fan-shaped area is 4, eight fan-shaped partitions are numbered from 0 to 8, all elements in each partition are assigned to be number values, the partition direction matrix and the window matrix are defined to have the same dimensionality, namely the partition direction matrix is also a square matrix with the row number and the column number both being 2R + 1;
C. constructing a characteristic histogram: after a window matrix to be processed is selected, a neighborhood window and a partition direction matrix are used for carrying out weighted value on the selected area, 8 matrixes of 8 sector partitions in a disc area are compared in a histogram matrix group, each matrix represents the brightness characteristic distribution condition in one sector partition of the window matrix, and each element of the matrix represents the number of times of a brightness level appearing in the sector and is represented by a visual histogram graph;
D. calculating the brightness gradient: when calculating the gradient of a central point in a selected window, dividing a disc outlined by a neighborhood window in the window into two semicircles through the center of the circle, calculating the chi-square distance of the two semicircles, and taking the calculation result as the gradient of the center of the circle on the boundary of the two semicircles.
In the method for monitoring the street lamp brightness based on the image recognition technology, the automatic push recognition module is provided with the timing submodule, and the timing submodule can set the time point of street lamp brightness recognition so as to improve the recognition effectiveness.
In the method for monitoring the street lamp brightness based on the image recognition technology, an information collection library is established in the urban management commanding center cloud server, the brightness signals are put in the library, meanwhile, a time table of the whole street lamp on-off is established, and the abnormal brightness signals are marked.
In the method for monitoring the street lamp brightness based on the image recognition technology, the intelligent camera is provided with a GPS signal module for determining the position, and the urban management command center server can correspondingly acquire the street lamp position at the position with abnormal brightness.
Compared with the prior art, the method for monitoring the street lamp brightness based on the image recognition technology has the advantages that:
1. the invention initiates a technology of fusing internet and artificial intelligence in urban management practice, installs an intelligent camera on an urban street lamp, monitors the street lamp condition in real time, reports the street lamp condition to an urban management command center rapidly when finding abnormality, and the intelligent camera uses an algorithm capable of identifying the street lamp abnormal condition, effectively eliminates the additional influence of weather and environment, and correctly identifies the street lamp abnormal condition.
2. The intelligent street lamp brightness monitoring system can automatically monitor the street lamp brightness in real time, reduces manual input to the maximum extent, does not need to add additional equipment, is low in deployment cost, only needs to install an intelligent camera on the urban street lamp, and does not need additional wiring.
Drawings
Fig. 1 is a schematic flow chart of a method for monitoring street lamp brightness based on an image recognition technology according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be described clearly and completely with reference to the accompanying drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only some embodiments of the present invention, not all embodiments.
Examples
Referring to fig. 1, a method for monitoring street lamp brightness based on image recognition technology includes the following steps:
s1, installing an intelligent camera on the urban street lamp, scanning and monitoring street scenes in real time according to the set lighting time point of the street lamp, and judging whether the brightness of the street lamp is normal or not;
s2, automatically pushing an identification module to an intelligent camera installed on each street lamp by the cloud server of the city management command center;
s3, when the intelligent camera judges that the street lamp brightness is abnormal, immediately reporting an actual screenshot and an automatic identification result to a cloud server of the urban management command center;
and S4, actually comparing the screenshots by the staff of the urban management command center, and informing the urban management team members of field processing when determining abnormal conditions.
The method for feeding back the abnormal street lamp brightness in the steps S1 and S2 comprises the following steps:
(1) collecting typical pictures of streets under the conditions that the street lamps are extinguished, the brightness is abnormal and the brightness is normal;
(2) marking that the street lamp is off, and the street lamp is a picture with abnormal brightness and a street view picture with normal brightness;
(3) uploading a labeled photo and labeling data to a cloud server of the urban management command center;
(4) the identification module is started, weather can be effectively eliminated, extra articles are mixed, the influence of people is avoided, and the abnormal condition of the street lamp is accurately judged.
The intelligent street lamp is low in deployment cost without adding extra equipment, and only the intelligent camera is required to be installed on the street lamp of the city, so that extra wiring is not required.
Further, the identification module can extract the brightness characteristics of the obtained street lamp real-time image, and the method comprises the following steps:
1) reading in an image;
2) gamma correction of the image;
3) converting the image color space from RGB to XYZ and then from XYZ to Lab;
4) normalizing the image characteristic value;
5) grouping image characteristic values;
6) each pixel point represents a characteristic value by a packet sequence number.
Further, the characteristic algorithm of the image brightness comprises the following steps:
A. acquiring a neighborhood window: after the original image is converted into a Lab color space, the brightness value of the original image is completely reflected on an L component, a disc area with the radius of R is selected from a first element each time in an L component matrix, the gradient is calculated according to set 4 directions, a small window is drawn in the L component matrix by taking a point of which the gradient is to be solved as the center, and then the elements of the circular area in the small window are weighted, so that each element of the L component of the window matrix is constructed to express the brightness characteristic of the corresponding point of the original image;
B. component partitioning direction matrix: the given direction number is 4, namely the brightness gradient in 4 directions needs to be solved, the disc is divided according to four directions, 8 fan-shaped areas can be obtained, the angle of each fan-shaped area is 4, eight fan-shaped partitions are numbered from 0 to 8, all elements in each partition are assigned to be number values, the partition direction matrix and the window matrix are defined to have the same dimensionality, namely the partition direction matrix is also a square matrix with the row number and the column number both being 2R + 1;
C. constructing a characteristic histogram: after a window matrix to be processed is selected, a neighborhood window and a partition direction matrix are used for carrying out weighted value on the selected area, 8 matrixes of 8 sector partitions in a disc area are compared in a histogram matrix group, each matrix represents the brightness characteristic distribution condition in one sector partition of the window matrix, and each element of the matrix represents the number of times of a brightness level appearing in the sector and is represented by a visual histogram graph;
D. calculating the brightness gradient: when calculating the gradient of a central point in a selected window, dividing a disc outlined by a neighborhood window in the window into two semicircles through the center of the circle, calculating the chi-square distance of the two semicircles, and taking the calculation result as the gradient of the center of the circle on the boundary of the two semicircles.
By adopting the characteristic algorithm of the image brightness, the signal acquisition can be carried out on the brightness change of the street lamp in real time and accurately, and once the brightness of the street lamp is abnormal, the abnormal brightness can be timely identified and transmitted to a cloud server of a city management command center, so that the city management part can be conveniently and timely processed.
Wherein, the automatic pushing identification module is provided with a timing submodule which can set the time point of street lamp brightness identification so as to improve the identification effectiveness, an information collection library is established in a cloud server of an urban management command center, the brightness signal is put in the library, and a time table of the whole street lamp on-off is established at the same time, for the abnormal brightness signal mark, a GPS signal module for determining the position is arranged at the intelligent camera, and the urban management command center server can correspondingly acquire the street lamp position at the abnormal brightness position, the invention can automatically monitor the street lamp brightness in real time, reduce the manual input to the maximum extent, the identification speed is high, the response speed can reach the second level, the adaptability is high, and the method can be applied to the weather such as overcast and rainy days, ice and snow days and the like, and can also be normally used under the viaduct, the tunnel culvert and other environments.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art should be considered to be within the technical scope of the present invention, and equivalent alternatives or modifications according to the technical solution and the inventive concept of the present invention should be covered by the scope of the present invention.
Claims (7)
1. A method for monitoring street lamp brightness based on an image recognition technology is characterized by comprising the following steps:
s1, installing an intelligent camera on the urban street lamp, scanning and monitoring street scenes in real time according to the set lighting time point of the street lamp, and judging whether the brightness of the street lamp is normal or not;
s2, automatically pushing an identification module to an intelligent camera installed on each street lamp by the cloud server of the city management command center;
s3, when the intelligent camera judges that the street lamp brightness is abnormal, immediately reporting an actual screenshot and an automatic identification result to a cloud server of the urban management command center;
and S4, actually comparing the screenshots by the staff of the urban management command center, and informing the urban management team members of field processing when determining abnormal conditions.
2. The method for monitoring the brightness of the street lamp based on the image recognition technology as claimed in claim 1, wherein the abnormal street lamp brightness feedback method in the steps S1 and S2 comprises the following steps:
(1) collecting typical pictures of streets under the conditions that the street lamps are extinguished, the brightness is abnormal and the brightness is normal;
(2) marking that the street lamp is off, and the street lamp is a picture with abnormal brightness and a street view picture with normal brightness;
(3) uploading a labeled photo and labeling data to a cloud server of the urban management command center;
(4) the identification module is started, weather can be effectively eliminated, extra articles are mixed, the influence of people is avoided, and the abnormal condition of the street lamp is accurately judged.
3. The method for monitoring the brightness of the street lamp based on the image recognition technology as claimed in claim 2, wherein the recognition module can extract the brightness characteristics of the obtained real-time image of the street lamp, and the method comprises the following steps:
1) reading in an image;
2) gamma correction of the image;
3) converting the image color space from RGB to XYZ and then from XYZ to Lab;
4) normalizing the image characteristic value;
5) grouping image characteristic values;
6) each pixel point represents a characteristic value by a packet sequence number.
4. The method for monitoring the brightness of the street lamp based on the image recognition technology as claimed in claim 3, wherein the characteristic algorithm of the image brightness comprises the following steps:
A. acquiring a neighborhood window: after the original image is converted into a Lab color space, the brightness value of the original image is completely presented on an L component, a disc area with the radius of R is selected from a first element every time in a matrix of the L component, the gradient is calculated according to set 4 directions, a small window is drawn in the L component matrix by taking a point of which the gradient is to be solved as the center, and then the elements of the circular area in the small window are weighted, so that each element of the L component of the window matrix is constructed to embody the brightness characteristic of the corresponding point of the original image;
B. component partitioning direction matrix: the given direction number is 4, namely the brightness gradient in 4 directions needs to be solved, the disc is divided according to four directions, 8 fan-shaped areas can be obtained, the angle of each fan-shaped area is 4, eight fan-shaped partitions are numbered from 0 to 8, all elements in each partition are assigned as number values, a partition direction matrix and a window matrix are defined to have the same dimensionality, namely, the partition direction matrix is also a square matrix with the row number and the column number both being 2R + 1;
C. constructing a characteristic histogram: after a window matrix to be processed is selected, a neighborhood window and a partition direction matrix are used for carrying out pair on the selected area weighted value, 8 matrixes which are compared with 8 sector partitions in a disc area are arranged in a histogram matrix group, each matrix represents the brightness characteristic distribution condition in one sector partition of the window matrix, and each element of the matrix represents the number of times of a brightness level appearing in the sector and is represented by a visual histogram graph;
D. calculating the brightness gradient: when calculating the gradient of a central point in a selected window, dividing a disc outlined by a neighborhood window in the window into two semicircles through the center of the circle, calculating the chi-square distance of the two semicircles, and taking the calculation result as the gradient of the center of the circle on the boundary of the two semicircles.
5. The method for monitoring the brightness of the street lamp based on the image recognition technology as claimed in claim 1, wherein a timing sub-module is disposed in the automatic push recognition module, and the timing sub-module can set a time point of the street lamp brightness recognition so as to improve recognition effectiveness.
6. The method for monitoring the brightness of the street lamp based on the image recognition technology as claimed in claim 1, wherein an information collection library is established in the cloud server of the urban management command center, the brightness signals are put into the library, and meanwhile, a time table of the whole turn-on and turn-off of the street lamp is established to mark abnormal brightness signals.
7. The method for monitoring the brightness of the street lamp based on the image recognition technology as claimed in claim 1, wherein a GPS signal module for determining the position is disposed at the intelligent camera, and the server of the city management command center can correspondingly acquire the street lamp position at the position with abnormal brightness.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117759909A (en) * | 2023-12-26 | 2024-03-26 | 江苏华美照明科技有限公司 | Light control consumption reduction type energy-saving street lamp for smart city |
| CN118474975A (en) * | 2024-05-14 | 2024-08-09 | 杭州一目倾诚网络科技有限公司 | A lighting intelligent control management system |
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