CN111241896A - Setting request triggering system - Google Patents
Setting request triggering system Download PDFInfo
- Publication number
- CN111241896A CN111241896A CN201910050849.2A CN201910050849A CN111241896A CN 111241896 A CN111241896 A CN 111241896A CN 201910050849 A CN201910050849 A CN 201910050849A CN 111241896 A CN111241896 A CN 111241896A
- Authority
- CN
- China
- Prior art keywords
- image
- pixel point
- minimum value
- noise
- sharpened
- 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.)
- Withdrawn
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/20—Image preprocessing
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/20—Image preprocessing
- G06V10/30—Noise filtering
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Multimedia (AREA)
- Theoretical Computer Science (AREA)
- Image Processing (AREA)
Abstract
The invention relates to a setting request triggering system, comprising: the quantity analysis device is connected with the matching processing device and used for receiving the minimum value filtering image, identifying the number of green plants in the minimum value filtering image based on green plant imaging characteristics, and identifying the number of computers in the minimum value filtering image based on computer imaging characteristics; and the planting request equipment is used for sending out a green planting request when the proportion obtained by dividing the number of the green plants by the number of the computers is less than or equal to a preset proportion threshold value. The setting request triggering system has simple logic and reliable design. The number of the green plants and the number of the computers in the machine room are effectively extracted, and when the proportion obtained by dividing the number of the green plants by the number of the computers is smaller than or equal to a preset proportion threshold value, a green plant planting request is sent, so that the green plant number in the machine room can be adapted to the number of the computers.
Description
Technical Field
The invention relates to the field of computer maintenance, in particular to a setting request triggering system.
Background
The internet has since entered the internet era as it has connected computers around the world. The human world is thoroughly changed by computer networking, people communicate and exchange (OICQ, microblog and the like), share educational resources (document search, distance education and the like), share information (hundredth, Google) and the like through the internet, and particularly, the convenience of using the network by people is greatly improved due to the appearance of a wireless network, and computers will be further developed to the networking aspect in the future.
The artificial intelligence of the computer is a necessary trend for future development. Modern computers have powerful functions and operating speeds, but their intelligence and logic capabilities are still to be improved compared to the human brain. Human beings are continuously exploring how to enable a computer to better reflect human thinking, so that the computer can have human logic thinking judgment capability, can communicate with human beings through thinking, abandons the prior method of running the computer through a coding program and directly sends instructions to the computer.
Disclosure of Invention
The invention aims to provide a setting request triggering system, which comprises: the quantity analysis device is connected with the matching processing device and used for receiving the minimum value filtering image, identifying the number of green plants in the minimum value filtering image based on green plant imaging characteristics, and identifying the number of computers in the minimum value filtering image based on computer imaging characteristics; the planting request equipment is connected with the numerical value analysis equipment and used for sending a green planting request when the proportion obtained by dividing the number of the green plants by the number of the computers is less than or equal to a preset proportion threshold value, otherwise, sending a green planting sufficient request; the panoramic acquisition equipment is arranged in the machine room and used for acquiring panoramic image data of the internal environment of the machine room so as to obtain an internal image of the machine room; the image sharpening device is connected with the panoramic acquisition device and used for receiving the image inside the machine room, equally dividing the image inside the machine room into blocks with the sizes of the corresponding blocks based on the distance between the resolution of the image inside the machine room and a preset resolution threshold, selecting corresponding image sharpening processing with different intensities for each block based on the fuzzy degree of the block to obtain sharpened blocks, and splicing the obtained sharpened blocks to obtain a sharpened image; the first detection device is connected with the image sharpening device and used for receiving the sharpened image, judging noise points of all pixel points in the sharpened image and determining that each pixel point is a noise point or a non-noise point, wherein the first detection device detects various noises in the sharpened image to obtain each noise area in the sharpened image, confirms the pixel points in a certain noise area as the noise points and confirms the pixel points outside the noise areas as the non-noise points; and the second detection device is used for receiving the sharpened image, extracting the resolution of the sharpened image and mapping a preset sliding window with a corresponding size based on the resolution of the sharpened image.
The invention has at least the following key invention points:
(1) identifying the number of green plants in the customized image based on the green plant imaging characteristics, identifying the number of computers in the customized image based on the computer imaging characteristics, and sending a green plant planting request when the ratio obtained by dividing the number of green plants by the number of computers is less than or equal to a preset ratio threshold value, or otherwise, sending a sufficient green plant planting request;
(2) introducing matching processing equipment to determine the ratio of the salt particle noise amplitude of the reference noise image to the salt particle noise amplitude of the current image, and determining a corresponding minimum value filtering strategy for the current image based on the numerical distribution range of the ratio to ensure the minimum value filtering processing effect;
(3) and determining a data processing mode of each channel of the brightness hue and color difference of the processed pixel points based on a preset sliding window with the corresponding size of the resolution mapping of the high-definition image and based on the value distribution condition of the brightness channel of the pixel points in each direction in the preset sliding window, thereby realizing accurate filtering processing of the image signals.
The setting request triggering system has simple logic and reliable design. The number of the green plants and the number of the computers in the machine room are effectively extracted, and when the proportion obtained by dividing the number of the green plants by the number of the computers is smaller than or equal to a preset proportion threshold value, a green plant planting request is sent, so that the green plant number in the machine room can be adapted to the number of the computers.
Detailed Description
Green plants are short for green ornamental foliage plants, mostly produced in rainforests of tropical regions and subtropical regions, and are generally shade plants. Because of strong negative resistance, the plant can be used as an indoor ornamental plant for indoor planting and maintenance.
Common to green plants are: the epipremnum aureum, Brazilian wood, Pachira macrocarpa, Semiaquilegia lutescens, chlorophytum comosum, green apples, sapphire, dracaena cochinchinensis, sansevieria trifasciata, green giant, green emperor, Heimeiguan and the like are all bred from leaf shapes, leaf colors, plant types and the like.
At present, the dust is more and the radiation volume is big in the general computer lab, for reduce dust and radiation staff's harmful effects in to the computer lab, plant green planting generally and carry out dust-proof and radiation protection and handle, however, the trunk number of planting green planting is according to managers experience random placement, leads to very easily placing too much and leads to green planting extravagant or place the condition that less dust and radiation can't effectively deal with.
In order to overcome the defects, the invention provides a setting request triggering system which can effectively solve the corresponding technical problem.
The following examples are intended to illustrate the invention but are not intended to limit the scope of the invention.
A set request triggering system, comprising:
the quantity analysis device is connected with the matching processing device and used for receiving the minimum value filtering image, identifying the number of green plants in the minimum value filtering image based on green plant imaging characteristics, and identifying the number of computers in the minimum value filtering image based on computer imaging characteristics;
the planting request equipment is connected with the numerical value analysis equipment and used for sending a green planting request when the proportion obtained by dividing the number of the green plants by the number of the computers is less than or equal to a preset proportion threshold value, otherwise, sending a green planting sufficient request;
the panoramic acquisition equipment is arranged in the machine room and used for acquiring panoramic image data of the internal environment of the machine room so as to obtain an internal image of the machine room;
the image sharpening device is connected with the panoramic acquisition device and used for receiving the image inside the machine room, equally dividing the image inside the machine room into blocks with the sizes of the corresponding blocks based on the distance between the resolution of the image inside the machine room and a preset resolution threshold, selecting corresponding image sharpening processing with different intensities for each block based on the fuzzy degree of the block to obtain sharpened blocks, and splicing the obtained sharpened blocks to obtain a sharpened image;
the first detection device is connected with the image sharpening device and used for receiving the sharpened image, judging noise points of all pixel points in the sharpened image and determining that each pixel point is a noise point or a non-noise point, wherein the first detection device detects various noises in the sharpened image to obtain each noise area in the sharpened image, confirms the pixel points in a certain noise area as the noise points and confirms the pixel points outside the noise areas as the non-noise points;
the second detection device is used for receiving the sharpened image, extracting the resolution of the sharpened image and mapping a preset sliding window with a corresponding size based on the resolution of the sharpened image;
the first processing device is connected with the second detection device and used for acquiring the preset sliding window and performing the following processing on each pixel point in the sharpened image: taking each pixel point in the sharpened image as an object pixel point, determining each pixel point in a preset sliding window taking the object pixel point as a centroid in the sharpened image as each pixel point to be evaluated, calculating the mean square error of the brightness channel values of each pixel point to be evaluated after the object pixel point is eliminated in the horizontal direction taking the object pixel point as the center in the preset sliding window, calculating the mean square error of the brightness channel values of each pixel point to be evaluated after the object pixel point is eliminated in the vertical direction taking the object pixel point as the center in the preset sliding window, calculating the mean square error of the brightness channel values of each pixel point to be evaluated after the object pixel point is eliminated in the main diagonal direction taking the object pixel point as the center in the preset sliding window, and calculating the mean square error of the brightness channel values of each pixel point to be evaluated after the object pixel point is eliminated in the auxiliary diagonal direction taking the object pixel point as the center in the preset sliding window Obtaining the minimum value of the four mean square deviations of the brightness channel values of the pixel points to be evaluated;
the second processing device is connected with the first processing device and is used for carrying out the following processing on each pixel point in the sharpened image: taking each pixel point in the sharpened image as an object pixel point, taking the mean value of the brightness channel values of all to-be-evaluated pixel points after the object pixel point is eliminated in the direction corresponding to the minimum value obtained by the first processing device as the processed brightness channel value of the object pixel point, taking the mean value of the hue channel values of all to-be-evaluated pixel points after the object pixel point is eliminated in the direction corresponding to the minimum value as the processed hue channel value of the object pixel point, and taking the mean value of the color difference channel values of all to-be-evaluated pixel points after the object pixel point is eliminated in the direction corresponding to the minimum value as the processed color difference channel value of the object pixel point;
the first output device is connected with the second processing device and is used for acquiring a signal output image corresponding to the sharpened image based on the processed brightness channel value, the processed hue channel value and the processed color difference channel value of each pixel point in the sharpened image;
the numerical value extraction device comprises a built-in DDR memory and is used for pre-storing a reference noise image, wherein the salt particle noise amplitude of each area in the reference noise image exceeds the limit;
the numerical extraction device is further configured to be connected to the first output device, receive the signal output image, perform an analysis on the signal output image based on the respective Y component values of the respective constituent pixels to determine a salt particle noise amplitude of the signal output image, and perform an analysis on the reference noise image based on the respective Y component values of the respective constituent pixels to determine a salt particle noise amplitude of the reference noise image;
and the matching processing device is connected with the numerical extraction device and used for receiving the salt particle noise amplitude of the signal output image and the salt particle noise amplitude of the reference noise image, determining the ratio of the salt particle noise amplitude of the reference noise image to the salt particle noise amplitude of the signal output image, and determining a corresponding minimum value filtering strategy for the signal output image based on the numerical distribution range of the ratio.
Next, a specific configuration of the setting request triggering system of the present invention will be further described.
The setting request triggers the system:
in the matching processing apparatus, the determined corresponding minimum value filtering policy for the signal output image is a multiple minimum value filtering mode when the numerical value of the ratio is distributed between 0-0.25, the determined corresponding minimum value filtering policy for the signal output image is a double minimum value filtering mode when the numerical value of the ratio is distributed between 0.25-0.75, the determined corresponding minimum value filtering policy for the signal output image is a single minimum value filtering mode when the numerical value of the ratio is distributed between 0.75-1, and the minimum value filtering processing is not performed on the signal output image when the numerical value of the ratio is greater than or equal to 1.
The setting request triggers the system:
in the matching processing device, after determining a corresponding minimum value filtering strategy for the signal output image, corresponding minimum value filtering processing is performed on the signal output image by using a corresponding minimum value filtering strategy to obtain a minimum value filtered image.
The setting request triggers the system:
the matching processing equipment further comprises a minimum value filtering unit, an amplitude obtaining unit and an amplitude comparing unit, wherein the minimum value filtering unit, the amplitude obtaining unit and the amplitude comparing unit share the same clock generator.
The setting request triggers the system:
in the second detection device, the larger the resolution of the sharpened image is, the larger the radial length of the mapped preset sliding window is.
The setting request triggers the system:
in the image sharpening device, the closer the resolution of the image inside the computer room is to the preset resolution threshold, the larger corresponding blocks into which the image inside the computer room is equally divided are.
The setting request triggers the system:
in the image sharpening device, for each block, the greater the degree of blurring of the block, the greater the intensity of the selected image sharpening process.
The setting request triggers the system:
the first processing device includes a data receiving unit, a horizontal direction evaluation unit, a vertical direction evaluation unit, a main diagonal direction evaluation unit, a sub diagonal direction evaluation unit, and a data output unit.
The setting request triggers the system:
the main diagonal direction is a direction from the lower left corner of the preset sliding window to the upper right corner of the preset sliding window, and the auxiliary diagonal direction is a direction from the lower right corner of the preset sliding window to the upper left corner of the preset sliding window.
In addition, DDR Double Data Rate SDRAM. Strictly speaking, DDR shall be referred to as DDR SDRAM, which is an abbreviation of Synchronous Dynamic Random access memory, and is commonly referred to as DDR. DDR SDRAM, however, is an abbreviation for Double Data Rate SDRAM, meaning Double-Rate synchronous dynamic random access memory. DDR memory is developed on the basis of SDRAM memory, and SDRAM production system is still used, so for memory manufacturers, DDR memory production can be realized only by slightly improving equipment for manufacturing common SDRAM, and cost can be effectively reduced. Double Data Rate: compared with the traditional single data rate, the DDR technology realizes two read/write operations in one clock cycle, namely, the read/write operations are respectively executed once on the rising edge and the falling edge of the clock.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention.
Claims (9)
1. A system for setting request triggering, comprising:
the quantity analysis device is connected with the matching processing device and used for receiving the minimum value filtering image, identifying the number of green plants in the minimum value filtering image based on green plant imaging characteristics, and identifying the number of computers in the minimum value filtering image based on computer imaging characteristics;
the planting request equipment is connected with the numerical value analysis equipment and used for sending a green planting request when the proportion obtained by dividing the number of the green plants by the number of the computers is less than or equal to a preset proportion threshold value, otherwise, sending a green planting sufficient request;
the panoramic acquisition equipment is arranged in the machine room and used for acquiring panoramic image data of the internal environment of the machine room so as to obtain an internal image of the machine room;
the image sharpening device is connected with the panoramic acquisition device and used for receiving the image inside the machine room, equally dividing the image inside the machine room into blocks with the sizes of the corresponding blocks based on the distance between the resolution of the image inside the machine room and a preset resolution threshold, selecting corresponding image sharpening processing with different intensities for each block based on the fuzzy degree of the block to obtain sharpened blocks, and splicing the obtained sharpened blocks to obtain a sharpened image;
the first detection device is connected with the image sharpening device and used for receiving the sharpened image, judging noise points of all pixel points in the sharpened image and determining that each pixel point is a noise point or a non-noise point, wherein the first detection device detects various noises in the sharpened image to obtain each noise area in the sharpened image, confirms the pixel points in a certain noise area as the noise points and confirms the pixel points outside the noise areas as the non-noise points;
the second detection device is used for receiving the sharpened image, extracting the resolution of the sharpened image and mapping a preset sliding window with a corresponding size based on the resolution of the sharpened image;
the first processing device is connected with the second detection device and used for acquiring the preset sliding window and performing the following processing on each pixel point in the sharpened image: taking each pixel point in the sharpened image as an object pixel point, determining each pixel point in a preset sliding window taking the object pixel point as a centroid in the sharpened image as each pixel point to be evaluated, calculating the mean square error of the brightness channel values of each pixel point to be evaluated after the object pixel point is eliminated in the horizontal direction taking the object pixel point as the center in the preset sliding window, calculating the mean square error of the brightness channel values of each pixel point to be evaluated after the object pixel point is eliminated in the vertical direction taking the object pixel point as the center in the preset sliding window, calculating the mean square error of the brightness channel values of each pixel point to be evaluated after the object pixel point is eliminated in the main diagonal direction taking the object pixel point as the center in the preset sliding window, and calculating the mean square error of the brightness channel values of each pixel point to be evaluated after the object pixel point is eliminated in the auxiliary diagonal direction taking the object pixel point as the center in the preset sliding window Obtaining the minimum value of the four mean square deviations of the brightness channel values of the pixel points to be evaluated;
the second processing device is connected with the first processing device and is used for carrying out the following processing on each pixel point in the sharpened image: taking each pixel point in the sharpened image as an object pixel point, taking the mean value of the brightness channel values of all to-be-evaluated pixel points after the object pixel point is eliminated in the direction corresponding to the minimum value obtained by the first processing device as the processed brightness channel value of the object pixel point, taking the mean value of the hue channel values of all to-be-evaluated pixel points after the object pixel point is eliminated in the direction corresponding to the minimum value as the processed hue channel value of the object pixel point, and taking the mean value of the color difference channel values of all to-be-evaluated pixel points after the object pixel point is eliminated in the direction corresponding to the minimum value as the processed color difference channel value of the object pixel point;
the first output device is connected with the second processing device and is used for acquiring a signal output image corresponding to the sharpened image based on the processed brightness channel value, the processed hue channel value and the processed color difference channel value of each pixel point in the sharpened image;
the numerical value extraction device comprises a built-in DDR memory and is used for pre-storing a reference noise image, wherein the salt particle noise amplitude of each area in the reference noise image exceeds the limit;
the numerical extraction device is further configured to be connected to the first output device, receive the signal output image, perform an analysis on the signal output image based on the respective Y component values of the respective constituent pixels to determine a salt particle noise amplitude of the signal output image, and perform an analysis on the reference noise image based on the respective Y component values of the respective constituent pixels to determine a salt particle noise amplitude of the reference noise image;
and the matching processing device is connected with the numerical extraction device and used for receiving the salt particle noise amplitude of the signal output image and the salt particle noise amplitude of the reference noise image, determining the ratio of the salt particle noise amplitude of the reference noise image to the salt particle noise amplitude of the signal output image, and determining a corresponding minimum value filtering strategy for the signal output image based on the numerical distribution range of the ratio.
2. The system for setting request triggering as claimed in claim 1, wherein:
in the matching processing apparatus, the determined corresponding minimum value filtering policy for the signal output image is a multiple minimum value filtering mode when the numerical value of the ratio is distributed between 0-0.25, the determined corresponding minimum value filtering policy for the signal output image is a double minimum value filtering mode when the numerical value of the ratio is distributed between 0.25-0.75, the determined corresponding minimum value filtering policy for the signal output image is a single minimum value filtering mode when the numerical value of the ratio is distributed between 0.75-1, and the minimum value filtering processing is not performed on the signal output image when the numerical value of the ratio is greater than or equal to 1.
3. The system for setting request triggering as claimed in claim 2, wherein:
in the matching processing device, after determining a corresponding minimum value filtering strategy for the signal output image, corresponding minimum value filtering processing is performed on the signal output image by using a corresponding minimum value filtering strategy to obtain a minimum value filtered image.
4. The setting request triggering system as claimed in claim 3, wherein:
the matching processing equipment further comprises a minimum value filtering unit, an amplitude obtaining unit and an amplitude comparing unit, wherein the minimum value filtering unit, the amplitude obtaining unit and the amplitude comparing unit share the same clock generator.
5. The system for setting request triggering as claimed in claim 4, wherein:
in the second detection device, the larger the resolution of the sharpened image is, the larger the radial length of the mapped preset sliding window is.
6. The setting request triggering system as claimed in claim 5, wherein:
in the image sharpening device, the closer the resolution of the image inside the computer room is to the preset resolution threshold, the larger corresponding blocks into which the image inside the computer room is equally divided are.
7. The system for setting request triggering as claimed in claim 6, wherein:
in the image sharpening device, for each block, the greater the degree of blurring of the block, the greater the intensity of the selected image sharpening process.
8. The set request triggering system as recited in claim 7, wherein:
the first processing device includes a data receiving unit, a horizontal direction evaluation unit, a vertical direction evaluation unit, a main diagonal direction evaluation unit, a sub diagonal direction evaluation unit, and a data output unit.
9. The set request triggering system as recited in claim 8, wherein:
the main diagonal direction is a direction from the lower left corner of the preset sliding window to the upper right corner of the preset sliding window, and the auxiliary diagonal direction is a direction from the lower right corner of the preset sliding window to the upper left corner of the preset sliding window.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910050849.2A CN111241896A (en) | 2019-01-20 | 2019-01-20 | Setting request triggering system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910050849.2A CN111241896A (en) | 2019-01-20 | 2019-01-20 | Setting request triggering system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN111241896A true CN111241896A (en) | 2020-06-05 |
Family
ID=70869281
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910050849.2A Withdrawn CN111241896A (en) | 2019-01-20 | 2019-01-20 | Setting request triggering system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111241896A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113688778A (en) * | 2021-09-05 | 2021-11-23 | 江阴市浩华新型复合材料有限公司 | Action triggering platform and method based on mean square error identification |
-
2019
- 2019-01-20 CN CN201910050849.2A patent/CN111241896A/en not_active Withdrawn
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113688778A (en) * | 2021-09-05 | 2021-11-23 | 江阴市浩华新型复合材料有限公司 | Action triggering platform and method based on mean square error identification |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US20200410212A1 (en) | Fast side-face interference resistant face detection method | |
| CN108323204A (en) | A kind of method and intelligent terminal of detection face flaw point | |
| CN106296666A (en) | A kind of coloured image goes shadow method and application | |
| CN108510451B (en) | Method for reconstructing license plate based on double-layer convolutional neural network | |
| CN108198147A (en) | A kind of method based on the multi-source image fusion denoising for differentiating dictionary learning | |
| JP2021531571A (en) | Certificate image extraction method and terminal equipment | |
| CN112115979B (en) | Fusion method and device of infrared image and visible image | |
| CN109377499A (en) | A kind of Pixel-level method for segmenting objects and device | |
| CN105741244A (en) | Method for removing shadows and halos under weak light through indoor polling robot | |
| CN108711160B (en) | Target segmentation method based on HSI (high speed input/output) enhanced model | |
| CN106971399A (en) | Image-mosaics detection method and device | |
| CN110986889A (en) | High-voltage substation panoramic monitoring method based on remote sensing image technology | |
| US9940543B2 (en) | Control of computer vision pre-processing based on image matching using structural similarity | |
| CN106599891A (en) | Remote sensing image region-of-interest rapid extraction method based on scale phase spectrum saliency | |
| Wang et al. | An efficient method for image dehazing | |
| CN105719254A (en) | Image denoising method and system | |
| CN111241896A (en) | Setting request triggering system | |
| CN106920266A (en) | The Background Generation Method and device of identifying code | |
| CN110827355B (en) | Moving target rapid positioning method and system based on video image coordinates | |
| CN111462034A (en) | Method for triggering setting request | |
| CN111667509A (en) | Method and system for automatically tracking moving target under condition that target is similar to background color | |
| CN116704316A (en) | Substation oil leakage detection method, system and medium based on shadow image reconstruction | |
| CN116128766A (en) | Improved Retinex-Net-based infrared image enhancement method for power equipment | |
| CN104700416A (en) | Image segmentation threshold determination method based on visual analysis | |
| Park et al. | Applying enhanced confusion line color transform using color segmentation for mobile applications |
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 | ||
| WW01 | Invention patent application withdrawn after publication | ||
| WW01 | Invention patent application withdrawn after publication |
Application publication date: 20200605 |