CN104573702A - Method for automatically identifying sulfur hexafluoride pressure instrument image - Google Patents
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- CN104573702A CN104573702A CN201410705151.7A CN201410705151A CN104573702A CN 104573702 A CN104573702 A CN 104573702A CN 201410705151 A CN201410705151 A CN 201410705151A CN 104573702 A CN104573702 A CN 104573702A
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- 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
- G06V10/28—Quantising the image, e.g. histogram thresholding for discrimination between background and foreground patterns
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
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- 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
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V2201/00—Indexing scheme relating to image or video recognition or understanding
- G06V2201/02—Recognising information on displays, dials, clocks
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Abstract
The invention discloses a method for automatically identifying a sulfur hexafluoride pressure instrument image. The method comprises the following steps: an image obtained through instrument video monitoring is pretreated and converted into a gray image; the OTSU is utilized to find a proper threshold value of the image, a target pointer in the instrument image is distinguished from a disc background; sobel operator edge detection is performed on the gray image, and then Hough Transform is utilized to obtain the coordinate and radius of a central point of a circular area of the image; according to the features of the instrument image, the reference point position and the reference terminal point coordinate of a dial plate are obtained; according to the obtained coordinate parameters, the deflection included angel of the pointer is calculated, and the pointer read is calculated by combining the reference point position of the dial plate to realize the automatic identification of instrument image read. According to the invention, the pointer read of the instrument can be accurately and rapidly identified, a template image database is not needed to be established in advance, which is remarkably different from other image identification technologies, and automatic read identification of the image pointer of the sulfur hexafluoride pressure instrument can be realized through feature separation and identification of the image.
Description
Technical field
The present invention relates to a kind of electric system Instrument image automatic identifying method, specifically relate to the application of a kind of computer image processing technology in GIS sulfur hexafluoride manometer image automatic identification field.
Background technology
In power transmission and transformation system, sulfur hexafluoride gas is as a kind of important insulating medium, usually be used in high pressure, middle pressure sulfur hexafluoride loading switch, in the electrical equipments such as combined electrical cabinet (GIS), and monitored by the pressure of tensimeter to insulating medium sulfur hexafluoride, to guarantee the insulation safety of equipment.
At present, most meter reading is all by manually going on-the-spot reading collection, or gathers image and pass computing machine by installing fixing camera back and carry out artificial reading again.Above-mentioned data acquisition modes needs a large amount of duty personnel constantly at instrument and computing machine advance line item, add handling cost and the human resources consumption in power station, and high voltage generating station also has certain danger, need during data acquisition to carry out limiting to safe distance, thus reduce work efficiency.If automatically identified quickly and accurately GIS sulfur hexafluoride manometer by computer pattern recognition, important effect will be had to reduction power station operating cost, raising reliability undoubtedly.
Computer image processing technology has a wide range of applications in engineering field particularly high voltage power transmission field.By adopting image instrument automatic identification technology, the various problems existed can well be solved in human meter's identifying, improving the precision and efficiency that identify, reducing the management maintenance cost of transformer station.At present, knowing method for distinguishing for Instrument image has multiple, but the method for carrying out pattern-recognition for this particular meter of sulfur hexafluoride tensimeter is little, therefore studies a kind of sulfur hexafluoride Instrument image pointer reading mode identification technology and there is very large practical value.
Summary of the invention
For the deficiency of the existence of the problem mentioned in background technology and existing research method, be difficult to meet the needs of sulfur hexafluoride tensimeter image automatic identification reading in practical application, the present invention proposes a kind of automatic distinguishing method for image for sulfur hexafluoride manometer.
A kind of sulfur hexafluoride manometer automatic distinguishing method for image, it is characterized in that, described method comprises following concrete implementation step:
A. first obtain field instrument pointer image by instrument video monitoring equipment, and pass image back computing machine;
B. gray processing process is carried out to the coloured image passed back and be converted into gray level image;
C. the image after gray processing first adopts morphologic opening operation to carry out image expansion, then is carried out gray inversion and gray scale Refinement operation;
D. image binaryzation process, specifically comprises:
1) read in pretreated gray level image and be designated as matrix I, round values in matrix I is converted into floating point values, obtains image array J;
2) adopt maximum class methods to find suitable gray threshold: note g is the segmentation threshold of display foreground and image background, prospect is counted and is accounted for image scaled and be
p, average gray is
u; Background is counted and is accounted for image scaled and be
q, average gray is
w, then the overall average gray scale of image is:
;
3) variance of prospect and background image:
, work as variance
gtime maximum, can think that now prospect and background reach maximum difference, are suitable gray threshold;
4) gray threshold in integrating step D, image array J binary conversion treatment, is optimized image by differencing algorithm, is finally carrying out medium filtering process to this image.
E. sobel operator edge detection is adopted to gray level image simultaneously, obtain the edge of Instrument image pointer profile and image index dial.
F. carry out Hough transformation to image array J, correspond to parameter space (X, Y, P) from image space, the convergence point being exceeded threshold value by search obtains Instrument image central coordinate of circle
and radius
r, for certain in matrix J a bit (x, y), if in the center of circle be
with radius be
rcircle on, then its correspondence parameter space meet:
, wherein
, adopt Hough transformation to detect instrument pie chart picture, central point and edge accurately can be found.
G. extract the coordinate of reference point according to the feature of round meter scale starting point and terminal, this algorithm selects final position to be reference point.
H. reading is calculated according to the image central coordinate of circle obtained in step F and step G, reference terminal point coordinate and pointer coordinate.
The present invention is a kind of sulfur hexafluoride manometer automatic distinguishing method for image, the present invention is not need to set up template image data storehouse in advance relative to the advantage of other image recognition technologys, automatically reading is identified by sulfur hexafluoride manometer image cursor can be realized to the character separation of image with identification, greatly facilitate the remote monitoring of work of transformer substation personnel to power equipment running status, improve work efficiency, reduce the operation expense of transformer station, there is very high engineering practical value.
Accompanying drawing explanation
Fig. 1 is a kind of sulfur hexafluoride manometer automatic distinguishing method for image process flow diagram provided by the invention;
Fig. 2 is image binaryzation processing flow chart of the present invention;
Fig. 3 the present invention is directed to the image recognition processes and result that sulfur hexafluoride manometer specifically implements.
Embodiment
Below in conjunction with accompanying drawing, to the specific operation process that sulfur hexafluoride manometer identifies.
A. Image Acquisition: instrument monitoring equipment obtains current Instrument image, passes computing machine back by transmission equipment.
B. greyscale transformation is carried out, as shown in Fig. 3 (a) to the image obtained.
C. binary conversion treatment being carried out to gray level image, by differencing algorithm, image is optimized, finally carrying out medium filtering process to this image, obtaining Fig. 3 (b).
D. again expansion process, gray inversion and image thinning are carried out to image, finally adopt Hough matrixing to demonstrate position and the scale end pointer position of gauge pointer point, as Fig. 3 (c) and 3(d) in cross represent the position of current pointer and scale terminal.
E. based on sobel operator, rim detection is carried out to the gray level image in step B, carry out Hough transformation simultaneously, obtain Instrument image home position and radius, as shown in Fig. 3 (e).
F. according to Instrument image feature-set terminal reading be
v, according to the central coordinate of circle obtained
, radius
r, pointer coordinate
and terminal point coordinate
, adopt the angle between triangle cosine law calculating pointer position and terminal point coordinate
for:
wherein
,
;
G. the total indicator reading of final Instrument image identification is:
,
for the angle between meter dial origin-to-destination.
These are only the concrete implementation and operation of the best of the present invention; but protection scope of the present invention is not limited thereto; any those of ordinary skill in the art allow to carry out changing or revising in the technical scope of announcement in the present invention, all should be encompassed within protection scope of the present invention.Therefore, scope of patent protection of the present invention should be defined by the claims.
Claims (6)
1. a sulfur hexafluoride manometer automatic distinguishing method for image, is characterized in that, comprises the following steps:
A. obtained the image of whole instrument by instrument monitoring camera, pre-service is carried out to the image obtained simultaneously;
B. image binaryzation process: find image suitable threshold value based on method between maximum kind, object pointer in Instrument image and disk background are distinguished, by differencing algorithm, the image obtained is optimized, finally medium filtering process is being carried out to this image;
C. adopt sobel operator to carry out rim detection to the image result of processing of step A, utilize Hough transformation to obtain center point coordinate and the radius of instrument inner circular region image;
D. analyze characteristics of image, obtain the coordinate of dial plate reference point locations and pointer terminal;
E. according to the parameter of the acquisition of step C and D, calculate needle deflection angle, and calculate pointer registration in conjunction with dial plate reference point locations, realize the automatic identification of Instrument image.
2. require described a kind of sulfur hexafluoride manometer automatic distinguishing method for image according to right 1, it is characterized in that, described preprocessing process is:
A. first gray processing process is carried out to the whole Instrument image that instrument monitoring camera obtains;
B. morphologic opening operation is adopted to carry out image expansion, gray inversion and gray scale Refinement operation to the image after gray processing.
3. require described a kind of sulfur hexafluoride manometer automatic distinguishing method for image according to right 1, it is characterized in that, image binaryzation process described in step B, specifically comprises:
A. read in pretreated gray level image to matrix I, round values in matrix I is converted into floating point values, obtains image array J;
B. maximum class methods principle: note
gfor the segmentation threshold of display foreground and image background, prospect is counted and is accounted for image scaled and be
p, average gray is
u; Background is counted and is accounted for image scaled and be
q, average gray is
w, then the overall average gray scale of image is:
; The variance of prospect and background image:
, work as variance
gtime maximum, can think that now prospect and background reach maximum difference, are suitable gray threshold;
C. the gray threshold in integrating step B, image array J binary conversion treatment, is optimized image by differencing algorithm, is finally carrying out medium filtering process to this image.
4. require described a kind of sulfur hexafluoride manometer automatic distinguishing method for image according to right 1, it is characterized in that, specifically comprise described in step C:
A. adopt sobel operator to carry out rim detection to gray level image and obtain image array J(x, y);
B. to image array J(x, y) carry out Hough transformation, correspond to parameter space (X, Y, P) from image space, the convergence point being exceeded threshold value by search obtains Instrument image central coordinate of circle
and radius
r.
5. require described a kind of sulfur hexafluoride manometer automatic distinguishing method for image according to right 1, it is characterized in that, specifically comprise described in step D:
A. extract the coordinate of reference point according to the feature of round meter scale starting point and terminal, this algorithm selects final position to be reference point;
B, to the gray level image matrix I of steps A in claim 2, first obtains size [m, the n]=size (I) of its ranks pixel, according to the feature in final position, will be less than
be greater than
the pixel of scope is set to I(x, y)=1, the coordinate adopting Hough matrixing to obtain final position
;
C. according to the feature of pointer position, will be less than equally
rbe greater than
the pixel of scope is set to I(x, y)=1, the coordinate of pointer position is being obtained in conjunction with Hough matrixing
(
).
6. require described a kind of sulfur hexafluoride manometer automatic distinguishing method for image according to right 1, it is characterized in that, described in step e, computed image total indicator reading specifically comprises:
A. reading is calculated according to the image central coordinate of circle obtained in right 5 and right 4, reference terminal point coordinate and pointer coordinate;
B. based on the triangle cosine law, the angle between pointer and terminal point coordinate
for:
wherein
,
,
;
C. the pointer angle calculated according to step B finally can obtain the total indicator reading of image.
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Cited By (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104994334A (en) * | 2015-06-09 | 2015-10-21 | 海南电网有限责任公司 | Automatic substation monitoring method based on real-time video |
| CN106446903A (en) * | 2016-09-20 | 2017-02-22 | 山东省计量科学研究院 | Recognition method for position of wave-band switch of instrument |
| CN106570948A (en) * | 2016-11-01 | 2017-04-19 | 东南大学 | Transformer substation intelligent meter reading system provided with portable device |
| CN106908189A (en) * | 2017-02-14 | 2017-06-30 | 中国航天空气动力技术研究院 | A kind of differential pressure high precision measurement method |
| CN107038049A (en) * | 2017-04-25 | 2017-08-11 | 航天科技控股集团股份有限公司 | A kind of adaptive download system of automobile instrument aging procedure and method based on graphic correlation pattern |
| CN107122210A (en) * | 2017-04-25 | 2017-09-01 | 航天科技控股集团股份有限公司 | A kind of adaptive download system of automobile instrument program and method based on graphic correlation pattern |
| CN107133623A (en) * | 2017-05-11 | 2017-09-05 | 安徽慧视金瞳科技有限公司 | A kind of pointer position accurate detecting method positioned based on background subtraction and the center of circle |
| CN107256379A (en) * | 2017-05-05 | 2017-10-17 | 深圳市科迈爱康科技有限公司 | Information collecting method, mobile terminal and storage medium based on image recognition |
| CN109063637A (en) * | 2018-07-30 | 2018-12-21 | 安徽慧视金瞳科技有限公司 | A kind of instrument piecemeal scale detection method |
| CN109858474A (en) * | 2019-01-08 | 2019-06-07 | 北京全路通信信号研究设计院集团有限公司 | A kind of detection of transformer oil surface temperature controller and recognition methods |
| CN109993154A (en) * | 2019-04-19 | 2019-07-09 | 山东大学 | The lithium sulfur type instrument intelligent identification Method of substation's simple pointer formula |
| CN109992011A (en) * | 2019-04-23 | 2019-07-09 | 广东电网有限责任公司 | A kind of secondary alignment methods, device and the equipment of inspection machine user tripod head |
| CN110121054A (en) * | 2018-02-07 | 2019-08-13 | 中国石油化工股份有限公司 | A kind of petrochemical equipment cruising inspection system based on video analysis |
| CN112749598A (en) * | 2019-10-31 | 2021-05-04 | 中移物联网有限公司 | Information processing method, terminal and data platform of pointer type meter |
| CN113639836A (en) * | 2021-08-11 | 2021-11-12 | 国网河北省电力有限公司电力科学研究院 | Online measuring system for weight of sulfur hexafluoride gas in electrical equipment |
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| CN104994334A (en) * | 2015-06-09 | 2015-10-21 | 海南电网有限责任公司 | Automatic substation monitoring method based on real-time video |
| CN106446903A (en) * | 2016-09-20 | 2017-02-22 | 山东省计量科学研究院 | Recognition method for position of wave-band switch of instrument |
| CN106446903B (en) * | 2016-09-20 | 2019-04-23 | 山东省计量科学研究院 | A kind of instrument band switch location recognition method |
| CN106570948A (en) * | 2016-11-01 | 2017-04-19 | 东南大学 | Transformer substation intelligent meter reading system provided with portable device |
| CN106908189B (en) * | 2017-02-14 | 2019-03-26 | 中国航天空气动力技术研究院 | A kind of differential pressure high precision measurement method |
| CN106908189A (en) * | 2017-02-14 | 2017-06-30 | 中国航天空气动力技术研究院 | A kind of differential pressure high precision measurement method |
| CN107122210A (en) * | 2017-04-25 | 2017-09-01 | 航天科技控股集团股份有限公司 | A kind of adaptive download system of automobile instrument program and method based on graphic correlation pattern |
| CN107038049A (en) * | 2017-04-25 | 2017-08-11 | 航天科技控股集团股份有限公司 | A kind of adaptive download system of automobile instrument aging procedure and method based on graphic correlation pattern |
| CN107256379B (en) * | 2017-05-05 | 2021-06-22 | 深圳市科迈爱康科技有限公司 | Information acquisition method based on image recognition, mobile terminal and storage medium |
| CN107256379A (en) * | 2017-05-05 | 2017-10-17 | 深圳市科迈爱康科技有限公司 | Information collecting method, mobile terminal and storage medium based on image recognition |
| CN107133623B (en) * | 2017-05-11 | 2020-03-24 | 安徽慧视金瞳科技有限公司 | Pointer position accurate detection method based on background difference and circle center positioning |
| CN107133623A (en) * | 2017-05-11 | 2017-09-05 | 安徽慧视金瞳科技有限公司 | A kind of pointer position accurate detecting method positioned based on background subtraction and the center of circle |
| CN110121054A (en) * | 2018-02-07 | 2019-08-13 | 中国石油化工股份有限公司 | A kind of petrochemical equipment cruising inspection system based on video analysis |
| CN109063637A (en) * | 2018-07-30 | 2018-12-21 | 安徽慧视金瞳科技有限公司 | A kind of instrument piecemeal scale detection method |
| CN109858474A (en) * | 2019-01-08 | 2019-06-07 | 北京全路通信信号研究设计院集团有限公司 | A kind of detection of transformer oil surface temperature controller and recognition methods |
| CN109993154A (en) * | 2019-04-19 | 2019-07-09 | 山东大学 | The lithium sulfur type instrument intelligent identification Method of substation's simple pointer formula |
| CN109993154B (en) * | 2019-04-19 | 2020-02-07 | 山东大学 | Intelligent identification method for single-pointer sulfur hexafluoride instrument of transformer substation |
| CN109992011A (en) * | 2019-04-23 | 2019-07-09 | 广东电网有限责任公司 | A kind of secondary alignment methods, device and the equipment of inspection machine user tripod head |
| CN112749598A (en) * | 2019-10-31 | 2021-05-04 | 中移物联网有限公司 | Information processing method, terminal and data platform of pointer type meter |
| CN113639836A (en) * | 2021-08-11 | 2021-11-12 | 国网河北省电力有限公司电力科学研究院 | Online measuring system for weight of sulfur hexafluoride gas in electrical equipment |
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