CN109117764A - Using the method for color threshold method identification target object region electrical symbol in power monitoring - Google Patents
Using the method for color threshold method identification target object region electrical symbol in power monitoring Download PDFInfo
- Publication number
- CN109117764A CN109117764A CN201810851018.0A CN201810851018A CN109117764A CN 109117764 A CN109117764 A CN 109117764A CN 201810851018 A CN201810851018 A CN 201810851018A CN 109117764 A CN109117764 A CN 109117764A
- Authority
- CN
- China
- Prior art keywords
- image
- color threshold
- color
- target object
- threshold method
- 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
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/50—Context or environment of the image
- G06V20/52—Surveillance or monitoring of activities, e.g. for recognising suspicious objects
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/40—Extraction of image or video features
- G06V10/44—Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/40—Extraction of image or video features
- G06V10/56—Extraction of image or video features relating to colour
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Multimedia (AREA)
- Theoretical Computer Science (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Image Analysis (AREA)
Abstract
A method of target object region electrical symbol being identified using color threshold method in power monitoring, belongs to field of image recognition.It, for indicator light pattern in irregular shape, is identified when carrying out pel identification using color threshold method, obtains a judging result；The recognition result of an equipment running status or equipment present position is obtained according to the judgment result；Then by judgment result displays and recognition result is returned to.Its content that can included according to satisfactory image, the operating status of analytical equipment, the reading for detecting instrument have preferable understanding and understanding ability；It can be used not only for the intellectual analysis to on-site supervision image, can be used for mobile job platform, realize automatic collection, the analysis of image, substitution is accomplished manually the operation such as inspection operation and data record；It can be widely used for the operational management field of the automatic collection of transformer and distribution power station monitoring image, analysis and distribution equipment.
Description
Technical field
The invention belongs to field of image recognition, more particularly to a kind of pumping of the characteristics of image of figure or characteristic for identification
Take method.
Background technique
Based on the considerations of reduce operating cost and save floor occupying area etc., increasingly with unattended operation transformer station
It mostly is used, various video monitoring systems are widely applied.
Since video monitoring can generate a large amount of live video or photograph image, then image processing, interpret or according to institute
Diagram piece is identified, is judged, is had become in the operation monitoring work of electric system necessary.
" visual analysis " technology is a kind of intelligence system, can by vision system (video camera) to locating environment into
The autonomous intellectualized technology observed and analyze of row is an important directions of artificial intelligence technology and machine vision technique development,
Substation inspection, remote centralized control, video image big data analysis and in terms of with boundless application before
Scape.
In power industry, machine vision technique has had some successful stories.Especially in terms of the analysis of infrared image
Have been achieved for some more significant progress.Can be obtained by image analysis technology the Temperature Distribution of insulation fabric part from
And judge whether there is the equipment deficiencies such as insulation decline, overheat；Also have in terms of the line walking of overhead transmission line, instrument board reading non-
Often successfully application.
Sichuan Electric Power company replaces the visual performance of people using computer generation, to substation's important electrical and scene
3-D image perceive, identifies, analyzes, and then the operation conditions of detection system in specific environment, obtains detection knot
Fruit.Wherein mainly realize electric instrument visual identity, the state recognition of visual fracture switch tool, Substation Electric Equipment
Infrared vision on-line checking and substation vision monitoring function.
Hunan University devise it is a kind of based on position to sizing visual spatial attention deicing robot grab line traffic control algorithm, mention
The monocular vision stereoscopic localized for having gone out a kind of class cylindrical body geometrical characteristic and camera imaging model based on power transmission cable is calculated
Method, at the same propose it is a kind of avoid complicated inverse kinematics grab line traffic control strategy, which is by finding
The intersection point of the axis of the working curved surface of mechanical arm clamper end and power transmission cable in space determines cable crawl point and grabs
The position in each joint of line taking Lan Shi robot.Realize the motion control of view-based access control model analysis and processing.
It is wrong that a set of advanced, intelligent " visual analysis " system can reduce accidental race during practical manual work
The mistakes such as position in storehouse (in transformer and distribution power station, the corresponding building interval for being placed with high-tension apparatus, referred to as position in storehouse), mistakenly entering charged chamber
Accidentally bring risk, for improving operational security, correctness has important role.And various intelligence systems existing at present
" visual analysis " ability of system is very weak, and some of relatively advanced intelligence systems have certain visual analysis ability, but only
It is extremely low that ability can be appreciated and understood according to software analytical equipment state prepared in advance, detection meter reading.
Summary of the invention
Technical problem to be solved by the invention is to provide a kind of electrical cabinet electrical symbol identification side based on OpenCV
Method.It obtains the image for meeting requirement of experiment first with the various preprocess methods in iconology, then similar to appearance
Or close scene and phenomenon carries out classification summary, using threshold value adjust carry out color identification, color identification on the basis of into
Row edge detection etc. identifies work.Its to the color of accurate identification electrical symbol, profile, it is interior have higher feasibility, tentatively
Realize the transformation from manual inspection to machine inspection.
The technical scheme is that providing one kind identifies target object area using color threshold method in power monitoring
The method of domain electrical symbol, including to image preprocessing, linearly put down using gaussian filtering for noise in images to be recognized
Sliding filtering carries out edge detection using Canny operator；It is characterized in that:
Pel identification is carried out to pretreated image, identifies target object region；
When carrying out pel identification, for indicator light pattern in irregular shape, known using color threshold method
Not, a judging result is obtained；
According to the judgment result, it according to preset logical relation, obtains locating for an equipment running status or equipment
The recognition result of position；
Then by judgment result displays and recognition result is returned to.
The indicator light with color that color threshold method described in it is interfered for no background colour, by being in detection image
No there are the color regions of a certain range size, to judge the light on and off state of the indicator light.
Specifically, image is transformed into HSV space by the color threshold method, three ginsengs in the HSV space model
Number is respectively: H-tone, S-saturation degree, V-brightness.
Further, the color threshold method sets the upper and lower threshold value of tri- parameters of HSV first, examines each channel
Pixel value whether in threshold range；If enabling the pixel value in dst image is 255, otherwise in threshold range
Enabling it is 0；Its dst image exported is a width bianry image, and the region for meeting color threshold condition is set as white.
The Key Functions of its color threshold method are inRange (src, lowerb, upperb, dst).
Compared with the prior art, the invention has the advantages that
1, the technical program be based on OpenCV function library, within the scope of camera target object carry out contours extract and
Identification carries information, the content that can included according to satisfactory image, and the operating status of analytical equipment detects instrument
Reading has preferable understanding and understanding ability, and can return in time interpretation result according to scheduled logic rules；
2, the technical program uses a variety of pel recognition methods, can precisely identify color, profile, the content of electrical symbol,
Tentatively realize the transformation from manual inspection to machine inspection；
3, the technical program can be used not only for the intellectual analysis to on-site supervision image, pass through the useful number of image zooming-out
According to and information, identify power equipment and system normal/abnormal state；It can be used for mobile job platform, realize image
Automatic collection, analysis, substitution people complete the operation such as inspection operation and data record；It is a kind of practical, reliable, real-time machine
Device visual analysis system schema.
Detailed description of the invention
Fig. 1 is that machine vision understands model schematic；
Fig. 2 is total algorithm flow diagram of the invention；
Fig. 3 is Canny algorithm flow step schematic diagram of the invention；
Fig. 4 is the original image in pel identification process of the present invention；
Fig. 5 is the image that the present invention obtains after edge detection process；
Fig. 6 (a) is indicator light pattern original image, and the indicator light pattern that Fig. 6 (b) is obtained after color identifies, Fig. 6 (c) is to sentence
Read result；
Fig. 7 (a) is an indicator light pattern original image, and Fig. 7 (b) is color recognition result, and Fig. 7 (c) is canny operator edge
Testing result, Fig. 7 (d) are straight-line detection as a result, Fig. 7 (e) is interpretation result；
Fig. 8 (a) is an electrical pattern original image, and Fig. 8 (b) is canny operator edge detection as a result, Fig. 8 (c) is straight line inspection
Survey result.
Specific embodiment
The present invention will be further described with reference to the accompanying drawing.
Typical instrument dial plate on substation equipment includes air gauge, oil temperature gauge, thermometer, arrester table and electrically sets
Standby sulphur hexafluoride gas purity used analyzes relevant desk-type digital display instrument, LED alarm lamp and TFT display screen etc..Wherein gas
Pressing table, oil temperature gauge, thermometer, arrester table is pointer instrument, reacts reading by the scale that pointer is directed toward.LED alarm lamp
It is used to refer to the warning message of equipment, position can be distributed in air gauge, oil temperature gauge table dial plate or the viewing area LED.TFT screen display
Content numerous and complicated, including device status information, warning message, multimedia messages for showing etc., the form that information is shown include figure
Mark and text.
OpenCV is the cross-platform computer vision library based on BSD license (open source) distribution, be may operate in
In Linux, Windows, Android and Mac OS operating system.Its lightweight and efficiently --- by a series of C functions and
A small amount of C++ class is constituted, while providing the interface of the language such as Python, Ruby, MATLAB, realizes image procossing and calculating
Many general-purpose algorithms of machine visual aspects.
Fig. 1 is the multilayer fusion representation model figure that machine vision understands model acquisition data, this model is in Andreas
On the basis of the I-SENSE model that Klausner et al. is proposed, improved in conjunction with human eye vision information processing mechanism,
It is one and has gathered numerous data fusion model advantages, general and flexible multi-layer data fusion treatment model.Pass through industry
Camera carries out perception processing to product information, pixel layer, characteristic layer, decision-making level is undergone, from simple to complex, from primary to height
Grade realizes that machine vision understands the task of mould step by step.
In Fig. 2, technical solution of the present invention depends on the electrical cabinet electrical symbol recognition methods based on OpenCV, the knowledge
Other method includes at least the following steps:
1) the positive monitor video of electrical cabinet is obtained using video monitoring system, and monitor video obtained is passed through
Screenshotss extract specified picture, the images to be recognized needed；
2) image preprocessing: linear smoothing filtering is carried out for noise in image using gaussian filtering, is calculated using Canny
Son carries out edge detection；
3) pel identifies: identifying target object region；
4) straight-line detection: using Hough transformation come the rectilinear strip in detection pattern, drafting is detected in original image
Lines；
5) angle calculation: calculating the tilt angle of the lines detected and thus judges whether component is in normal shape
State；
6) by judgment result displays and recognition result is returned to.
In Fig. 3, the Canny algorithm in the technical program can entirely be summarized as three steps: filtering, enhancing, detection.
The technical program is discussed further below:
1.1 image preprocessings:
(1) gaussian filtering
Gaussian filtering (GaussianBlur) is a kind of linear smoothing filtering for noise in image.What noise generated
Error can accumulate transmitting in different operations, to seriously affect the later period application of digital picture.By in gray matrix
Each pixel make the weighted averages of other pixel values in itself and neighborhood, can effectively filter and inhibition is made an uproar
Sound bring influences.
(2) Canny operator edge detection
The algorithm of edge detection is mainly based upon the single order and second dervative of image intensity, by the image of gaussian filtering
Amplitude and the direction of gradient, the convolution operator that Canny algorithm uses can be calculated with the finite difference of single order local derviation are as follows:
Its x to, y to first-order partial derivative matrix, the mathematic(al) representation of gradient magnitude and its gradient direction are as follows:
P [i, j]=(f [i, j+1]-f [i, j]+f [i+1, j+1]-f [i+1, j])/2
Q [i, j]=(f [i, j]-f [i+1, j]+f [i, j+1]-f [i+1, j+1])/2
θ [i, j]=arctan (Q [i, j]/P [i, j])
In Canny algorithm, non-maxima suppression is the important step for carrying out edge detection, i.e. searching pixel part
Gray value corresponding to non-maximum point is set to 0 by maximum value, its ash may be arranged for the local gray level maximum point at edge
Degree is 128.It may include several pseudo-edges in such testing result, therefore Canny algorithm is reduced using dual-threshold voltage
Edge: being connected into profile in high threshold image by the quantity of pseudo-edge, and when reaching the endpoint of profile, which can be disconnected
The point for meeting Low threshold is found in 8 neighborhoods of point, new edge is collected further according to this point, until whole image edge closure is
Only.The setting of upper lower threshold value is most important, directly influences subsequent detection work, the threshold up and down used in the technical program
Value is than being 3:1.
Due to the Canny operator edge detection category prior art, therefore for letter institute's generation each in above-mentioned formula (1) or (2)
The meaning and unit of table parameter, those skilled in the art, can refer to related statement in pertinent literature or explanation (for example,
" a kind of calculation method of edge detection ", " IEEE mode analysis and machine intelligence journal ", 1986 (6): 67-698 (A
computational approach to edge detection.IEEE Transactions on Pattern
Analysis and Machine Intelligence, 1986 (6): 679-698)), it is not repeated herein.
1.2, pel identifies:
The part category complexity for including in the collected electrical cabinet image of machine inspection is various, carry out image procossing it
Preceding primary work seeks to identify target object region.Pel identification is carried out to pretreated image, identifies target
Object area；
When carrying out pel identification, the technical program is for indicator light pattern in irregular shape, using color threshold method
It is identified, obtains a judging result；
According to the judgment result, it according to preset logical relation, obtains locating for an equipment running status or equipment
The recognition result of position；
Then by judgment result displays and recognition result is returned to.
Color threshold method:
The most significant feature of such pattern is exactly the indicator light (no background colour interference) with color, by detection image
The light on and off state of the indicator light is judged with the presence or absence of the color region of a certain range size.
Image is transformed into HSV space first, three in this model parameter is respectively: H (tone), S (saturation
Degree), V (brightness).
Compared to RGB model, HSV model more meets the mode that people describes and explains color, more natural and intuitive.
Here the Key Functions used are inRange (src, lowerb, upperb, dst), i.e. three ginsengs of setting HSV
Whether several upper lower threshold values examines the pixel value in each channel in threshold range, if it is within range, then enables in dst image
The pixel value is 255, and otherwise enabling it is 0, therefore the dst image exported is a width bianry image, meets color threshold condition
Region be set as white, facilitate subsequent detection work.
Involved equipment running status includes that switch/device corresponding to the pel is in fortune in the technical program
Row state is in dead status, be also possible in live line work state be in power-off stoppage in transit state (for example, certain
Switch corresponding to a pel, transformer or motor, usually using turning on/off to indicate whether it is in energization for signal lamp
Operating status or power-off run-stopping status；In relay protection system, usual turning on/off with some indicator light, to indicate certain
Whether kind of relay protection or interlock condition are put into, etc.).
Involved equipment present position includes that switch/device corresponding to the pel is in the technical program
Line operating status is in position out of service, or be located at maintenance position (for example, switch corresponding to some pel,
Grounding switch or circuit breaker trolley indicate whether it locates usually using the differing tilt angles of the switch on electric cabinet faceplate
In on-state；It is vertical to indicate that in an ON state, 45 ° or 90 ° of inclination indicates that it is in an off state；Circuit breaker trolley exists
Running position must be advanced to just by, which being powered before running, can be carried out power transmission operation, can be pulled it after out of service to power-off and be overhauled
Position, before carrying out grid switching operation, there are the detections of a small truck position of confirmation, judgment step, etc.).
1.3, straight-line detection:
The electrical symbol of common several quasi-representatives on distribution equipment, for the machine for " visual identity ", area
Their maximum foundations are divided to be that the straight line inclination angle in pattern.
The technical program is using Hough transformation come the rectilinear strip in detection pattern, and drafting detects in original image
Lines calculate the tilt angle of these lines and thus judge whether component is in normal condition.
Hough transformation will have the curve of same shape with the transformation between two coordinate spaces in a space
Or straight line is mapped on a point of another coordinate space and forms peak value, so that the problem of detection arbitrary shape, is converted into
Count spike problem.
OpenCV supports three kinds of different Hough transformations, uses function HoughLinesP in the technical program
(contours, lines, rho, theta, threshold, minLineLength, maxLineGap) calls accumulated probability
Hough transformation (PPHT), it is the improvement of standard Hough transformation, and execution efficiency is higher.
Experimental result and analysis:
Based on the above-mentioned thinking solved the problems, such as, technical solution of the present invention using in windows version VS2015 and
OpenCV2.4.13 is tested and is verified.
1, Canny operator edge detection:
Fig. 4 is the original image in pel identification process；
Fig. 5 is the image obtained by Canny operator edge detection；
2, color identifies:
Fig. 6 (a) is indicator light pattern original image, the indicator light pattern that Fig. 6 (b) is obtained after color identifies.
In systems, as long as detecting the pattern of the indicator light, that is, it can determine whether that the indicator light is in " bright " state.
After system detection is to indicator light " bright ", according to logical relation preset in system, that is, correspondence can determine that
Some equipment be in certain specific state (such as certain switchgear be pushed to a specific position or certain switchgear
In some scheduled operating status), then system, that is, exportable corresponding interpretation result.
Fig. 6 (c) is the correspondence interpretation result of output.
3, straight-line detection:
Similar to abovely, Fig. 7 (a) is another indicator light pattern original image, and Fig. 7 (b) is canny operator edge detection knot
Fruit, Fig. 7 (c) are straight-line detection as a result, Fig. 7 (e) is interpretation result.
In straight-line detection, according to testing result, the tilt angle of these lines and thus judgement member can be calculated simultaneously
Whether device is in normal condition.
4, electrical pattern detection:
Fig. 8 (a) is an electrical pattern original image, Fig. 8 (b) is canny operator edge detection result, Fig. 8 (c) is straight line inspection
Survey result.
It similarly, according to testing result, also can be according to straight-line detection as a result, calculating this in electrical pattern detection
Thus the tilt angle of a little lines simultaneously judges operating status locating for the switch representated by it or equipment.
It can be seen that technical solution of the present invention from above-mentioned testing result, realize adopting for all kinds of electrical patterns
The work such as collection, positioning, identification, processing, by judgment result displays and can return.
Due to the centralized operation platform in electric system or on the spot on electrical cabinet, generally according to " bright "/" going out " of indicator light
" vertical "/" inclination " (position being commonly called as) of (state being commonly called as) or far-end operation switch, to indicate various switchgears
Operation whether, therefore use technical solution of the present invention, can be according to the state of indicator light each in the image taken or remote
The position for holding Operation switch, comes whether the corresponding distribution equipment of accurate judgement puts into operation or whether operating status is normal.From
For in this meaning, as long as realizing the automatic collection of the various monitoring images of transformer and distribution power station, analysis, skill through the invention
Art scheme can substitute be accomplished manually the operation such as inspection operation and data record completely.
By the content that technical solution of the present invention can be included according to satisfactory image, the operation of analytical equipment
State, the reading for detecting instrument have preferable understanding and understanding ability, and can be returned in time according to scheduled logic rules
Interpretation result；It uses a variety of pel recognition methods, can precisely identify color, profile, the content of electrical symbol, preliminary to realize
From manual inspection to the transformation of machine inspection；The technical solution can be used not only for the intellectual analysis to on-site supervision image, lead to
Image zooming-out useful data and information are crossed, identify the normal/abnormal state of power equipment and system；It can be used for moving
Job platform, realizes automatic collection, the analysis of image, and substitution is accomplished manually the operation such as inspection operation and data record；It is a kind of
Practical, reliable, real time machine vision understands system schema.
It invention can be widely used in automatic collection, analysis and the operation of distribution equipment of transformer and distribution power station monitoring image
Management domain.
Claims (5)
1. a kind of method that target object region electrical symbol is identified using color threshold method in power monitoring, including to image
Pretreatment carries out linear smoothing filtering for noise in images to be recognized using gaussian filtering, carries out edge using Canny operator
Detection；It is characterized in that:
Pel identification is carried out to pretreated image, identifies target object region；
When carrying out pel identification, for indicator light pattern in irregular shape, is identified, obtained using color threshold method
One judging result；
According to the judgment result, according to preset logical relation, an equipment running status or equipment present position are obtained
Recognition result；
Then by judgment result displays and recognition result is returned to.
2. described in accordance with the claim 1 identify target object region electrical symbol using color threshold method in power monitoring
Method, it is characterized in that the indicator light with color that the color threshold method is interfered for no background colour, by detection image
With the presence or absence of the color region of a certain range size, to judge the light on and off state of the indicator light.
3. according to claim 2 using color threshold method identification target object region electrical symbol in power monitoring
Method, it is characterized in that image is transformed into HSV space by the color threshold method, three parameters in the HSV space model
It is respectively: H-tone, S-saturation degree, V-brightness.
4. described in accordance with the claim 3 identify target object region electrical symbol using color threshold method in power monitoring
Method examines the picture in each channel it is characterized in that the color threshold method sets the upper and lower threshold value of tri- parameters of HSV first
Whether element value is in threshold range；If enabling the pixel value in dst image is 255 in threshold range, it is otherwise enabled to be
0；Its dst image exported is a width bianry image, and the region for meeting color threshold condition is set as white.
5. according to claim 4 using color threshold method identification target object region electrical symbol in power monitoring
Method, it is characterized in that the Key Functions of the color threshold method are inRange (src, lowerb, upperb, dst).
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810851018.0A CN109117764A (en) | 2018-07-29 | 2018-07-29 | Using the method for color threshold method identification target object region electrical symbol in power monitoring |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810851018.0A CN109117764A (en) | 2018-07-29 | 2018-07-29 | Using the method for color threshold method identification target object region electrical symbol in power monitoring |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN109117764A true CN109117764A (en) | 2019-01-01 |
Family
ID=64863575
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201810851018.0A Pending CN109117764A (en) | 2018-07-29 | 2018-07-29 | Using the method for color threshold method identification target object region electrical symbol in power monitoring |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109117764A (en) |
Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110062202A (en) * | 2019-03-12 | 2019-07-26 | 国网浙江省电力有限公司杭州供电公司 | A kind of power system information acquisition radio alarm method based on image recognition |
| CN110082620A (en) * | 2019-05-05 | 2019-08-02 | 北京云迹科技有限公司 | A kind of charging pile working state detecting method and device |
| CN110119680A (en) * | 2019-04-03 | 2019-08-13 | 上海工程技术大学 | A kind of electrical cabinet wiring automatic errordetecting system based on image recognition |
| CN110774055A (en) * | 2019-10-10 | 2020-02-11 | 华中科技大学 | Cutter breakage monitoring method and system based on image edge detection |
| CN111698468A (en) * | 2020-05-14 | 2020-09-22 | 中国电力工程顾问集团西南电力设计院有限公司 | Method for automatically monitoring three-dimensional scene based on power transmission line |
| CN113345036A (en) * | 2021-05-24 | 2021-09-03 | 广西电网有限责任公司电力科学研究院 | HSV (hue, saturation, value) feature transformation based indicator lamp state identification method |
| CN113762192A (en) * | 2021-09-15 | 2021-12-07 | 南方电网数字电网研究院有限公司 | Equipment detection method and device based on gateway and container technology and gateway equipment |
| CN113837110A (en) * | 2021-09-27 | 2021-12-24 | 广东纬德信息科技股份有限公司 | Centralized monitoring and alarming method and system for running state of power grid station equipment |
| CN115861304A (en) * | 2023-02-20 | 2023-03-28 | 江苏金恒信息科技股份有限公司 | Method and system for detecting steel strip-shaped structure based on image processing |
| CN116189089A (en) * | 2023-02-14 | 2023-05-30 | 深圳市巨龙创视科技有限公司 | Intelligent video monitoring method and system |
Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103543277A (en) * | 2013-09-13 | 2014-01-29 | 中国科学院苏州生物医学工程技术研究所 | Blood type result recognition algorithm based on grey level analysis and type recognition |
| CN104298354A (en) * | 2014-10-11 | 2015-01-21 | 河海大学 | Man-machine interaction gesture recognition method |
| US20150213326A1 (en) * | 2014-01-28 | 2015-07-30 | Ncr Corporation | Methods and Apparatus for Item Identification Using Brightness Compensation |
| CN104952066A (en) * | 2015-05-11 | 2015-09-30 | 国网安徽省电力公司芜湖供电公司 | Method for identifying phase signboards of power transmission lines on basis of HSV (hue, saturation and value) color spaces |
| CN106250902A (en) * | 2016-07-29 | 2016-12-21 | 武汉大学 | Power system on off state detection method based on characteristics of image template matching |
| CN106570865A (en) * | 2016-11-08 | 2017-04-19 | 国家电网公司 | Digital-image-processing-based switch state detecting system of power equipment |
| CN106650696A (en) * | 2016-12-30 | 2017-05-10 | 山东大学 | Handwritten electrical element identification method based on singular value decomposition |
| CN107081765A (en) * | 2017-03-29 | 2017-08-22 | 国网上海市电力公司 | A kind of substation inspection robot autonomous classification method and a kind of inspecting robot |
| US20170249840A1 (en) * | 2016-02-29 | 2017-08-31 | Analog Devices Glibal | Visual vehicle parking occupancy sensor |
-
2018
- 2018-07-29 CN CN201810851018.0A patent/CN109117764A/en active Pending
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103543277A (en) * | 2013-09-13 | 2014-01-29 | 中国科学院苏州生物医学工程技术研究所 | Blood type result recognition algorithm based on grey level analysis and type recognition |
| US20150213326A1 (en) * | 2014-01-28 | 2015-07-30 | Ncr Corporation | Methods and Apparatus for Item Identification Using Brightness Compensation |
| CN104298354A (en) * | 2014-10-11 | 2015-01-21 | 河海大学 | Man-machine interaction gesture recognition method |
| CN104952066A (en) * | 2015-05-11 | 2015-09-30 | 国网安徽省电力公司芜湖供电公司 | Method for identifying phase signboards of power transmission lines on basis of HSV (hue, saturation and value) color spaces |
| US20170249840A1 (en) * | 2016-02-29 | 2017-08-31 | Analog Devices Glibal | Visual vehicle parking occupancy sensor |
| CN106250902A (en) * | 2016-07-29 | 2016-12-21 | 武汉大学 | Power system on off state detection method based on characteristics of image template matching |
| CN106570865A (en) * | 2016-11-08 | 2017-04-19 | 国家电网公司 | Digital-image-processing-based switch state detecting system of power equipment |
| CN106650696A (en) * | 2016-12-30 | 2017-05-10 | 山东大学 | Handwritten electrical element identification method based on singular value decomposition |
| CN107081765A (en) * | 2017-03-29 | 2017-08-22 | 国网上海市电力公司 | A kind of substation inspection robot autonomous classification method and a kind of inspecting robot |
Non-Patent Citations (2)
| Title |
|---|
| 侯宾等: "基于OpenCV的目标物体颜色及轮廓的识别方法", 《现代电子技术》 * |
| 快乐成长吧: "inRange()函数、cvtColor()函数、createTrackbar()函数", 《CSDN》 * |
Cited By (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110062202A (en) * | 2019-03-12 | 2019-07-26 | 国网浙江省电力有限公司杭州供电公司 | A kind of power system information acquisition radio alarm method based on image recognition |
| CN110119680A (en) * | 2019-04-03 | 2019-08-13 | 上海工程技术大学 | A kind of electrical cabinet wiring automatic errordetecting system based on image recognition |
| CN110119680B (en) * | 2019-04-03 | 2023-08-01 | 上海工程技术大学 | Automatic error checking system of regulator cubicle wiring based on image recognition |
| CN110082620A (en) * | 2019-05-05 | 2019-08-02 | 北京云迹科技有限公司 | A kind of charging pile working state detecting method and device |
| CN110082620B (en) * | 2019-05-05 | 2021-09-24 | 北京云迹科技有限公司 | Charging pile working state detection method and device |
| CN110774055A (en) * | 2019-10-10 | 2020-02-11 | 华中科技大学 | Cutter breakage monitoring method and system based on image edge detection |
| CN111698468A (en) * | 2020-05-14 | 2020-09-22 | 中国电力工程顾问集团西南电力设计院有限公司 | Method for automatically monitoring three-dimensional scene based on power transmission line |
| CN113345036A (en) * | 2021-05-24 | 2021-09-03 | 广西电网有限责任公司电力科学研究院 | HSV (hue, saturation, value) feature transformation based indicator lamp state identification method |
| CN113762192A (en) * | 2021-09-15 | 2021-12-07 | 南方电网数字电网研究院有限公司 | Equipment detection method and device based on gateway and container technology and gateway equipment |
| CN113837110A (en) * | 2021-09-27 | 2021-12-24 | 广东纬德信息科技股份有限公司 | Centralized monitoring and alarming method and system for running state of power grid station equipment |
| CN116189089A (en) * | 2023-02-14 | 2023-05-30 | 深圳市巨龙创视科技有限公司 | Intelligent video monitoring method and system |
| CN115861304A (en) * | 2023-02-20 | 2023-03-28 | 江苏金恒信息科技股份有限公司 | Method and system for detecting steel strip-shaped structure based on image processing |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109117764A (en) | Using the method for color threshold method identification target object region electrical symbol in power monitoring | |
| CN109271844A (en) | Electrical cabinet electrical symbol recognition methods based on OpenCV | |
| CN109409395A (en) | Using the method for template matching method identification target object region electrical symbol in power monitoring | |
| CN109308447A (en) | The method of equipment operating parameter and operating status is automatically extracted in remote monitoriong of electric power | |
| CN109271872B (en) | Device and method for judging on-off state and diagnosing fault of high-voltage isolating switch | |
| CN109063764A (en) | A kind of judgment method of disconnecting switch closing operation in place based on machine vision | |
| CN109308448A (en) | A method of it prevents from becoming distribution maloperation using image processing techniques | |
| CN109063634A (en) | Using the method for hough-circle transform identification target object region electrical symbol in power monitoring | |
| CN107133592B (en) | Human body target feature detection algorithm for power substation by fusing infrared thermal imaging and visible light imaging technologies | |
| CN107067595B (en) | State identification method and device of indicator light and electronic equipment | |
| CN104282011A (en) | Method and device for detecting interference stripes in video images | |
| CN109740507A (en) | A kind of method of transformer equipment abnormality sensing | |
| CN110008937B (en) | Switch cabinet running state management monitoring system and method and computing equipment | |
| CN110348380A (en) | A kind of visualization grounding switch state video recognition system and method | |
| CN111639568A (en) | Navigation patrol method for intelligent robot of transformer substation | |
| CN112017173A (en) | Power equipment defect detection method based on target detection network and structured positioning | |
| CN106650735B (en) | A kind of LED character automatic positioning recognition methods | |
| CN109345787A (en) | A kind of anti-outer damage monitoring and alarming system of the transmission line of electricity based on intelligent image identification technology | |
| CN110247328A (en) | Position judging method based on image recognition in switchgear | |
| CN112532927A (en) | Intelligent safety management and control system for construction site | |
| CN112001332A (en) | Method, system, medium, equipment and application for monitoring working state of isolating switch | |
| CN115294352A (en) | Intelligent switch cabinet state identification system and method based on image identification | |
| CN112085654B (en) | Configurable analog screen recognition system | |
| CN114549822A (en) | Disconnecting switch closing state detection method based on preset position camera | |
| CN109687576B (en) | Visual discrimination inspection method for states of power equipment of converter station |
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 | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20190101 |