CN105791758A - Method for automatically reading power meter - Google Patents
Method for automatically reading power meter Download PDFInfo
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- CN105791758A CN105791758A CN201610122889.XA CN201610122889A CN105791758A CN 105791758 A CN105791758 A CN 105791758A CN 201610122889 A CN201610122889 A CN 201610122889A CN 105791758 A CN105791758 A CN 105791758A
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- 238000000034 method Methods 0.000 title claims abstract description 32
- 238000012545 processing Methods 0.000 claims abstract description 54
- 230000005540 biological transmission Effects 0.000 claims description 36
- 238000003379 elimination reaction Methods 0.000 claims description 28
- 239000003595 mist Substances 0.000 claims description 28
- 238000007781 pre-processing Methods 0.000 claims description 25
- 230000008030 elimination Effects 0.000 claims description 24
- 230000008569 process Effects 0.000 claims description 16
- 238000012360 testing method Methods 0.000 claims description 13
- 239000000284 extract Substances 0.000 claims description 8
- 239000000203 mixture Substances 0.000 claims description 4
- 230000003068 static effect Effects 0.000 claims description 4
- 210000000352 storage cell Anatomy 0.000 claims description 4
- XAGFODPZIPBFFR-UHFFFAOYSA-N aluminium Chemical compound [Al] XAGFODPZIPBFFR-UHFFFAOYSA-N 0.000 description 12
- 229910052782 aluminium Inorganic materials 0.000 description 12
- 230000000694 effects Effects 0.000 description 5
- 238000005516 engineering process Methods 0.000 description 4
- 230000006978 adaptation Effects 0.000 description 3
- 238000001914 filtration Methods 0.000 description 3
- 238000003707 image sharpening Methods 0.000 description 3
- 238000012986 modification Methods 0.000 description 3
- 230000004048 modification Effects 0.000 description 3
- 238000010586 diagram Methods 0.000 description 2
- 230000004907 flux Effects 0.000 description 2
- 230000006870 function Effects 0.000 description 2
- XEEYBQQBJWHFJM-UHFFFAOYSA-N Iron Chemical group [Fe] XEEYBQQBJWHFJM-UHFFFAOYSA-N 0.000 description 1
- 230000002411 adverse Effects 0.000 description 1
- 230000015572 biosynthetic process Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 230000007123 defense Effects 0.000 description 1
- 238000009826 distribution Methods 0.000 description 1
- 230000005611 electricity Effects 0.000 description 1
- 238000009499 grossing Methods 0.000 description 1
- 230000002452 interceptive effect Effects 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 238000004804 winding Methods 0.000 description 1
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N7/00—Television systems
- H04N7/18—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast
- H04N7/183—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast for receiving images from a single remote source
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R11/00—Electromechanical arrangements for measuring time integral of electric power or current, e.g. of consumption
- G01R11/02—Constructional details
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- G06T5/73—
Abstract
The present invention relates to a method for automatically reading a power meter. The method comprises the steps of (1) capturing the meter frame of the power meter through a CMOS image sensor, (2) carrying out image processing on the meter frame obtained in the step (1) through a digital signal processor so as to obtain a power meter reading, and (3) storing and displaying the power meter reading obtained in the step (2) through a FLASH memory and an LCD display, wherein the method is implemented by using a power meter automatic reading platform based on CMOS image collection, the platform comprises the CMOS image sensor, the digital signal processor, the LCD display, and the FLASH memory, the CMOS image sensor, the LCD display and the FLASH memory are connected to the digital signal processor. Through the invention, an original cumbersome manual meter reading operation can be replaced, the influences of fog and haze on meter reading is overcome, and the efficiency and accuracy of meter reading are improved.
Description
Technical field
The present invention relates to electric energy meter field, particularly relate to a kind of method electric energy meter being carried out automatic data logging based on cmos image collection.
Background technology
Electric energy meter is measurement electric unit or the instrument of personal electric reading, it is power supply department charge and the important referential data of allotment electric power resource, electric energy meter is large number of simultaneously, and substantially each needs to arrange an electric energy meter by electric unit, and each family resident is also required to be separately provided an electric energy meter.Thus, from the value of electric energy meter and characteristic distributions it can be seen that the reading collection of electric energy meter needs to meet efficient and high-precision requirement simultaneously.
But, all there is intrinsic defect in electric energy meter reading scheme of the prior art: (1), although manual meter reading method can guarantee that the precision gathering reading, however it is necessary that the substantial amounts of cost of labor of consuming, and collecting efficiency is not high, and real-time is not strong；(2) more existing electronic meter reading schemes can only ensure the reading collection under home; owing to much electricity table is placed in open air; under the weather that visibility is relatively low; such as, under foggy days environment; the electric energy meter often causing shooting is image blurring unclear; correspondingly, the error in reading of identification is very big.
Therefore, need a kind of new automatic copying electric meter method, the mode adopting electronic meter reading substitutes original manual metering mode, simultaneously, electronic meter reading mode is carried out upgrading, increase Sharp processing of image function, overcome the foggy days adverse effect to electric energy meter Recognition of Reading such that it is able to meet the efficient and high-precision requirement that electric energy meter reading gathers.
Summary of the invention
In order to solve the problems referred to above, according to an aspect of the present invention, the invention provides a kind of method electric energy meter being carried out automatic data logging based on cmos image collection, comprising:
(1) shoot to obtain bezel, cluster image to the bezel, cluster of electric energy meter by cmos image sensor；
(2) bezel, cluster image step (1) obtained by digital signal processor carries out image procossing, to obtain electric energy meter reading；
(3) the electric energy meter reading respectively step (2) obtained by FLASH memory and LCD display is stored and shows；
Wherein said method utilizes the automatic copying electric meter platform gathered based on cmos image to implement, described platform includes cmos image sensor, digital signal processor, LCD display and FLASH memory, and wherein said cmos image sensor, described LCD display and described FLASH memory are connected with described digital signal processor respectively.
Specifically, described cmos image sensor is for shooting to obtain bezel, cluster image to the bezel, cluster of electric energy meter, described digital signal processor is connected with described cmos image sensor, for described bezel, cluster image is carried out image procossing, to obtain electric energy meter reading, described FLASH memory is connected with described digital signal processor, is used for storing described electric energy meter reading, described LCD display is connected with described digital signal processor, is used for showing described electric energy meter reading.
More specifically, the described automatic copying electric meter platform based on cmos image collection also includes: CSI interface, between cmos image sensor and image-preprocessing device, send image-preprocessing device to for the bezel, cluster image shot by described cmos image sensor；
First parallel port, between described digital signal processor and described LCD display, for by described numeral letter
The electric energy meter reading that number processor obtains sends described LCD display to display；
Second parallel port, between described digital signal processor and described FLASH memory, sends described FLASH memory to store for the electric energy meter reading obtained by described digital signal processor；
Power supply, including solar powered device, accumulator, switching switch and electric pressure converter, described switching switch is connected respectively with described solar powered device and described accumulator, decide whether to be switched to described solar powered device to be powered by described solar powered device according to accumulator dump energy, described electric pressure converter is connected with described switching switch, so that the 5V voltage inputted by switching switch is converted to 3.3V voltage；
Image-preprocessing device, between described CSI interface and described digital signal processor, for receiving described bezel, cluster image, described bezel, cluster image carries out mist elimination process to obtain mist elimination bezel, cluster image, described mist elimination bezel, cluster image is inputted described digital signal processor to carry out image procossing to obtain electric energy meter reading.
More specifically, described image-preprocessing device also includes:
Storage subset, for prestoring sky upper limit gray threshold and sky lower limit gray threshold, described sky upper limit gray threshold and described sky lower limit gray threshold are for isolating the sky areas in image, being additionally operable to prestore presetted pixel value threshold value, described presetted pixel value threshold value value is between 0 to 255；
Haze Concentration Testing subset, is arranged in air, for detecting the haze concentration of electric energy meter position in real time, and determines that intensity removed by haze according to haze concentration, and described haze removes intensity value between 0 to 1；
Region divides subset, connect described CSI interface to receive described bezel, cluster image, described bezel, cluster image carries out gray processing process to obtain gray processing bezel, cluster image, also it is connected with storage subset, by the pixel identification between described sky upper limit gray threshold and described sky lower limit gray threshold of the gray value in described gray processing bezel, cluster image and form gray processing sky sub pattern, it is partitioned into described gray processing sky sub pattern to obtain the non-sky subimage of gray processing from described gray processing bezel, cluster image, the colour non-sky subimage corresponding with described gray processing non-sky subimage is obtained based on described gray processing non-sky subimage position in described bezel, cluster image；
Black channel obtains subset, divides subset with described region and is connected to obtain the non-sky subimage of described colour, for each pixel in the non-sky subimage of described colour, calculates its R, G, B tri-Color Channel pixel value, at described coloured silk
In color non-sky subimage, R, G, the B tri-of all pixels extracts the Color Channel at a minimum Color Channel pixel value place of numerical value in Color Channel pixel value as black channel；
Overall air light value obtains subset, it is connected to obtain presetted pixel value threshold value with described storage subset, divide subset with described region and described black channel obtains subset and is connected respectively to obtain described bezel, cluster image and described black channel, black channel pixel value in described bezel, cluster image is formed set of pixels to be tested be more than or equal to multiple pixels of presetted pixel value threshold value, using the gray value of the pixel in described set of pixels to be tested with maximum gradation value as overall air light value；nullAtmospheric scattering light value obtains subset，Divide subset with described region and described haze Concentration Testing subset is connected respectively，Each pixel to described bezel, cluster image，Extract its R，G，In B tri-Color Channel pixel value, minima is as target pixel value，Use and keep the Gaussian filter EPGF (edge-preservinggaussianfilter) at edge to be filtered described target pixel value processing to obtain filtered target pixel value，Target pixel value is deducted filtered target pixel value to obtain object pixel difference，EPGF is used to be filtered object pixel difference processing to obtain filtered target pixel value difference，Filtered target pixel value is deducted filtered target pixel value difference and removes reference value to obtain haze，Haze is removed intensity and is multiplied by haze removal reference value to obtain haze removal threshold value，Take haze and remove the minima in threshold value and target pixel value as comparison reference，Take the atmospheric scattering light value as each pixel of the maximum in comparison reference and 0；Medium transmission rate obtains subset, obtain subset with described overall air light value and described atmospheric scattering light value obtains subset and is connected respectively, by the atmospheric scattering light value of each pixel divided by overall air light value to obtain except value, deduct described except value is to obtain the medium transmission rate of each pixel by 1；nullSharpening Image Acquisition subset，Subset is divided with described region、Described overall air light value obtains subset and described medium transmission rate obtains subset and connects respectively，The medium transmission rate of each pixel is deducted to obtain the first difference by 1，Described first difference is multiplied by overall air light value to obtain product value，The pixel value of each pixel in described bezel, cluster image is deducted described product value to obtain the second difference，By described second difference divided by the medium transmission rate of each pixel to obtain the sharpening pixel value of each pixel，In described bezel, cluster image, the pixel value of each pixel includes the R of each pixel in described bezel, cluster image，G，B tri-Color Channel pixel value，Correspondingly，The sharpening pixel value of each pixel obtained includes the R of each pixel，G，B tri-Color Channel sharpening pixel value，The sharpening pixel value composition mist elimination bezel, cluster image of all pixels；
Wherein, described haze Concentration Testing subset is also built-in with static storage cell, is used for prestoring comparison table, and described comparison table saves haze concentration and the corresponding relation between intensity removed by haze.
Specifically, the bezel, cluster image of described cmos image sensor shooting sends image-preprocessing device to, described bezel, cluster image is carried out mist elimination and processes to obtain mist elimination bezel, cluster image by described image-preprocessing device, it is sequentially carried out image sharpening, self adaptation recursive filtering and OCR identifying processing, to obtain electric energy meter reading after described mist elimination bezel, cluster image is inputted described digital signal processor.
Specifically, in the process, described cmos image sensor is the OV7640 sensor of Omnivision company.
Specifically, in the process, described region divides subset, described black channel obtains subset, described overall air light value obtains subset, described atmospheric scattering light value obtains subset, described medium transmission rate obtains subset and described sharpening Image Acquisition subset is respectively adopted different fpga chips and realizes.
Specifically, in the process, described region divides subset, described black channel obtains subset, described overall air light value obtains subset, described atmospheric scattering light value obtains subset, described medium transmission rate obtains subset and described sharpening Image Acquisition subset is integrated on one piece of circuit board.
Specifically, in the process, described region divides subset, described black channel obtains subset, described overall air light value obtains subset, described atmospheric scattering light value obtains subset, described medium transmission rate obtains subset and described sharpening Image Acquisition subset is integrated in one piece of fpga chip.
According to another aspect of the present invention, present invention also offers a kind of automatic copying electric meter platform gathered based on cmos image, described platform includes digital signal processor, LCD display, FLASH memory and cmos image sensor, described cmos image sensor is for shooting to obtain bezel, cluster image to the bezel, cluster of electric energy meter, described digital signal processor is connected with described cmos image sensor, for described bezel, cluster image is carried out image procossing, to obtain electric energy meter reading, described FLASH memory is connected with described digital signal processor, for storing described electric energy meter reading, described LCD display is connected with described digital signal processor, for showing described electric energy meter reading.
More specifically, in the described automatic copying electric meter platform gathered based on cmos image, also include: CSI interface, between cmos image sensor and image-preprocessing device, send image-preprocessing device to for the bezel, cluster image shot by described cmos image sensor；
First parallel port, between described digital signal processor and described LCD display, sends described LCD display to display for the electric energy meter reading obtained by described digital signal processor；
Second parallel port, between described digital signal processor and described FLASH memory, for by described numeral
The electric energy meter reading that signal processor obtains sends described FLASH memory to store；
Power supply, including solar powered device, accumulator, switching switch and electric pressure converter, described switching switch is connected respectively with described solar powered device and described accumulator, decide whether to be switched to described solar powered device to be powered by described solar powered device according to accumulator dump energy, described electric pressure converter is connected with described switching switch, so that the 5V voltage inputted by switching switch is converted to 3.3V voltage；
Image-preprocessing device, between described CSI interface and described digital signal processor, for receiving described bezel, cluster image, described bezel, cluster image carries out mist elimination process to obtain mist elimination bezel, cluster image, described mist elimination bezel, cluster image is inputted described digital signal processor to carry out image procossing to obtain electric energy meter reading.
More specifically, described image-preprocessing device also includes:
Storage subset, for prestoring sky upper limit gray threshold and sky lower limit gray threshold, described sky upper limit gray threshold and described sky lower limit gray threshold are for isolating the sky areas in image, being additionally operable to prestore presetted pixel value threshold value, described presetted pixel value threshold value value is between 0 to 255；
Haze Concentration Testing subset, is arranged in air, for detecting the haze concentration of electric energy meter position in real time, and determines that intensity removed by haze according to haze concentration, and described haze removes intensity value between 0 to 1；
Region divides subset, connect described CSI interface to receive described bezel, cluster image, described bezel, cluster image carries out gray processing process to obtain gray processing bezel, cluster image, also it is connected with storage subset, by the pixel identification between described sky upper limit gray threshold and described sky lower limit gray threshold of the gray value in described gray processing bezel, cluster image and form gray processing sky sub pattern, it is partitioned into described gray processing sky sub pattern to obtain the non-sky subimage of gray processing from described gray processing bezel, cluster image, the colour non-sky subimage corresponding with described gray processing non-sky subimage is obtained based on described gray processing non-sky subimage position in described bezel, cluster image；
Black channel obtains subset, divide subset with described region to be connected to obtain the non-sky subimage of described colour, for each pixel in the non-sky subimage of described colour, calculate its R, G, B tri-Color Channel pixel value, the R of all pixels in described colour non-sky subimage, G, B tri-extracts the Color Channel at a minimum Color Channel pixel value place of numerical value in Color Channel pixel value as black channel；
Overall air light value obtains subset, it is connected to obtain presetted pixel value threshold value with described storage subset, divide subset with described region and described black channel obtains subset and is connected respectively to obtain described bezel, cluster image and described black channel, black channel pixel value in described bezel, cluster image is formed set of pixels to be tested be more than or equal to multiple pixels of presetted pixel value threshold value, using the gray value of the pixel in described set of pixels to be tested with maximum gradation value as overall air light value；
nullAtmospheric scattering light value obtains subset，Divide subset with described region and described haze Concentration Testing subset is connected respectively，Each pixel to described bezel, cluster image，Extract its R，G，In B tri-Color Channel pixel value, minima is as target pixel value，Use and keep the Gaussian filter EPGF (edge-preservinggaussianfilter) at edge to be filtered described target pixel value processing to obtain filtered target pixel value，Target pixel value is deducted filtered target pixel value to obtain object pixel difference，EPGF is used to be filtered object pixel difference processing to obtain filtered target pixel value difference，Filtered target pixel value is deducted filtered target pixel value difference and removes reference value to obtain haze，Haze is removed intensity and is multiplied by haze removal reference value to obtain haze removal threshold value，Take haze and remove the minima in threshold value and target pixel value as comparison reference，Take the atmospheric scattering light value as each pixel of the maximum in comparison reference and 0；
Medium transmission rate obtains subset, obtain subset with described overall air light value and described atmospheric scattering light value obtains subset and is connected respectively, by the atmospheric scattering light value of each pixel divided by overall air light value to obtain except value, deduct described except value is to obtain the medium transmission rate of each pixel by 1；
nullSharpening Image Acquisition subset，Subset is divided with described region、Described overall air light value obtains subset and described medium transmission rate obtains subset and connects respectively，The medium transmission rate of each pixel is deducted to obtain the first difference by 1，Described first difference is multiplied by overall air light value to obtain product value，The pixel value of each pixel in described bezel, cluster image is deducted described product value to obtain the second difference，By described second difference divided by the medium transmission rate of each pixel to obtain the sharpening pixel value of each pixel，In described bezel, cluster image, the pixel value of each pixel includes the R of each pixel in described bezel, cluster image，G，B tri-Color Channel pixel value，Correspondingly，The sharpening pixel value of each pixel obtained includes the R of each pixel，G，B tri-Color Channel sharpening pixel value，The sharpening pixel value composition mist elimination bezel, cluster image of all pixels；
Described mist elimination bezel, cluster image, after receiving described mist elimination bezel, cluster image, is sequentially carried out image sharpening, self adaptation recursive filtering and OCR identifying processing, to obtain electric energy meter reading by described digital signal processor；
Wherein, described haze Concentration Testing subset is also built-in with static storage cell, is used for prestoring comparison table, and described comparison table saves haze concentration and the corresponding relation between intensity removed by haze.
More specifically, in the described automatic copying electric meter platform gathered based on cmos image, described cmos image sensor is the OV7640 sensor of Omnivision company.
More specifically, in the described automatic copying electric meter platform gathered based on cmos image, described region divides subset, described black channel obtains subset, described overall air light value obtains subset, described atmospheric scattering light value obtains subset, described medium transmission rate obtains subset and described sharpening Image Acquisition subset is respectively adopted different fpga chips and realizes.
More specifically, in the described automatic copying electric meter platform gathered based on cmos image, described region divides subset, described black channel obtains subset, described overall air light value obtains subset, described atmospheric scattering light value obtains subset, described medium transmission rate obtains subset and described sharpening Image Acquisition subset is integrated on one piece of circuit board.
More specifically, in the described automatic copying electric meter platform gathered based on cmos image, described region divides subset, described black channel obtains subset, described overall air light value obtains subset, described atmospheric scattering light value obtains subset, described medium transmission rate obtains subset and described sharpening Image Acquisition subset is integrated in one piece of fpga chip.
Method electric energy meter being carried out automatic data logging based on cmos image collection of the present invention and the automatic copying electric meter platform gathered based on cmos image, utilize high-precision acquisition technology and image processing techniques, ensure the high efficiency of data acquisition, determine the haze influence factor to image according to atmospheric attenuation model simultaneously, and the electric energy meter image gathered under foggy days is carried out the process of mist elimination hazeization, obtain electric energy meter image clearly, thus ensureing the accuracy that reading gathers.
Accompanying drawing explanation
Below with reference to accompanying drawing, embodiment of the present invention are described, wherein:
Fig. 1 is the block diagram of the automatic copying electric meter platform gathered based on cmos image illustrated according to an embodiment of the present invention.
Detailed description of the invention
Below with reference to accompanying drawings the embodiment based on the automatic copying electric meter platform of cmos image collection of the present invention is described in detail.
Electric energy can convert various energy to.As: convert heat energy to by electric furnace, convert mechanical energy to by motor, convert luminous energy etc. to by electric light.And the ammeter recording this electric energy is electric energy meter.
The operation principle of electric energy meter is as follows: when electric energy meter is accessed circuit-under-test, and current coil and just have alternating current to flow through in potential winding, the two alternating current produces the magnetic flux of alternation respectively in their iron core；Alternating flux, through aluminum dish, induces eddy current in aluminum dish；Eddy current is subject to again the effect of power in magnetic field, so that aluminum dish obtains torque (actively moment) and rotates.The power of load consumption is more big, more big by the electric current of current coil, and the eddy current induced in aluminum dish is also more big, makes the moment that aluminum dish rotates more big.Namely the size of torque is directly proportional with the power of load consumption.Power is more big, and torque is also more big, and aluminum dish rotates also more fast.When aluminum dish rotates, being subject to again the effect of the braking moment that permanent magnet produces, braking moment is with actively moment is in opposite direction；The size of braking moment is directly proportional to the rotating speed of aluminum dish, and aluminum dish rotates more fast, and braking moment is also more big.When active moment reaches temporary equilibrium with braking moment, aluminum dish is by uniform rotation.The electric energy that load consumes is directly proportional to the revolution of aluminum dish.When aluminum dish rotates, drive enumerator, the electric energy consumed is indicated.Here it is the simple procedure of electric energy meter work.
Owing to electric energy meter has widely distributed, and the correctness of electric energy meter reading is extremely important.Therefore, the collection of electric energy meter reading should be quickly accurate again.But electric energy meter reading acquisition platform of the prior art cannot meet this 2 requirements simultaneously.For this, the present invention has built a kind of automatic copying electric meter platform gathered based on cmos image, efficient requirement is met by image acquisition and processing technology targetedly, processed by mist elimination hazeization and realize also carrying out under vile weather the collection of high-precision electric energy meter reading, thus meeting the setting requirement of power supply department.
Fig. 1 is the block diagram of the automatic copying electric meter platform gathered based on cmos image illustrated according to an embodiment of the present invention, described platform includes digital signal processor 1, LCD display 4, FLASH memory 3 and cmos image sensor 2, described cmos image sensor 2 is for shooting to obtain bezel, cluster image to the bezel, cluster of electric energy meter, described digital signal processor 1 is connected with described cmos image sensor 2, for described bezel, cluster image is carried out image procossing, to obtain electric energy meter reading, described FLASH memory 3 is connected with described digital signal processor 1, for storing described electric energy meter reading, described LCD display 4 is connected with described digital signal processor 1, for showing described electric energy meter reading.
Then, continue the concrete structure based on the automatic copying electric meter platform of cmos image collection of the present invention is further detailed.
Described platform also includes: CSI interface, between cmos image sensor 2 and image-preprocessing device, for sending the bezel, cluster image that described cmos image sensor 2 shoots to image-preprocessing device.
Described platform also includes: the first parallel port, between described digital signal processor 1 and described LCD display 4, for sending the electric energy meter reading that described digital signal processor 1 obtains to described LCD display 4 to display.
Described platform also includes: the second parallel port, between described digital signal processor 1 and described FLASH memory 3, for sending the electric energy meter reading that described digital signal processor 1 obtains to described FLASH memory 3 to store.
Described platform also includes: power supply, including solar powered device, accumulator, switching switch and electric pressure converter, described switching switch is connected respectively with described solar powered device and described accumulator, decide whether to be switched to described solar powered device to be powered by described solar powered device according to accumulator dump energy, described electric pressure converter is connected with described switching switch, so that the 5V voltage inputted by switching switch is converted to 3.3V voltage.
Described platform also includes: image-preprocessing device, between described CSI interface and described digital signal processor 1, for receiving described bezel, cluster image, described bezel, cluster image carries out mist elimination process to obtain mist elimination bezel, cluster image, described mist elimination bezel, cluster image is inputted described digital signal processor 1 to carry out image procossing to obtain electric energy meter reading.
Described image-preprocessing device also includes: storage subset, is used for prestoring sky upper limit gray threshold and sky
Empty lower limit gray threshold, described sky upper limit gray threshold and described sky lower limit gray threshold, for isolating the sky areas in image, are additionally operable to prestore presetted pixel value threshold value, and described presetted pixel value threshold value value is between 0 to 255.
Described image-preprocessing device also includes: haze Concentration Testing subset, is arranged in air, for detecting the haze concentration of electric energy meter position in real time, and determines that intensity removed by haze according to haze concentration, and described haze removes intensity value between 0 to 1.
Described image-preprocessing device also includes: region divides subset, connect described CSI interface to receive described bezel, cluster image, described bezel, cluster image carries out gray processing process to obtain gray processing bezel, cluster image, also it is connected with storage subset, by the pixel identification between described sky upper limit gray threshold and described sky lower limit gray threshold of the gray value in described gray processing bezel, cluster image and form gray processing sky sub pattern, it is partitioned into described gray processing sky sub pattern to obtain the non-sky subimage of gray processing from described gray processing bezel, cluster image, the colour non-sky subimage corresponding with described gray processing non-sky subimage is obtained based on described gray processing non-sky subimage position in described bezel, cluster image.
Described image-preprocessing device also includes: black channel obtains subset, divide subset with described region to be connected to obtain the non-sky subimage of described colour, for each pixel in the non-sky subimage of described colour, calculate its R, G, B tri-Color Channel pixel value, the R of all pixels in described colour non-sky subimage, G, B tri-extracts the Color Channel at a minimum Color Channel pixel value place of numerical value in Color Channel pixel value as black channel.
Described image-preprocessing device also includes: overall air light value obtains subset, it is connected to obtain presetted pixel value threshold value with described storage subset, divide subset with described region and described black channel obtains subset and is connected respectively to obtain described bezel, cluster image and described black channel, black channel pixel value in described bezel, cluster image is formed set of pixels to be tested be more than or equal to multiple pixels of presetted pixel value threshold value, using the gray value of the pixel in described set of pixels to be tested with maximum gradation value as overall air light value.
nullDescribed image-preprocessing device also includes: atmospheric scattering light value obtains subset，Divide subset with described region and described haze Concentration Testing subset is connected respectively，Each pixel to described bezel, cluster image，Extract its R，G，In B tri-Color Channel pixel value, minima is as target pixel value，Use and keep the Gaussian filter EPGF (edge-preservinggaussianfilter) at edge to be filtered described target pixel value processing to obtain filtered target pixel value，Target pixel value is deducted filtered target pixel value to obtain object pixel difference，EPGF is used to be filtered object pixel difference processing to obtain filtered target pixel value difference，Filtered target pixel value is deducted filtered target pixel value difference and removes reference value to obtain haze，Haze is removed intensity and is multiplied by haze removal reference value to obtain haze removal threshold value，Take haze and remove the minima in threshold value and target pixel value as comparison reference，Take the atmospheric scattering light value as each pixel of the maximum in comparison reference and 0.
Described image-preprocessing device also includes: medium transmission rate obtains subset, obtains subset with described overall air light value and described atmospheric scattering light value obtains subset and is connected respectively, by the atmospheric scattering light value of each pixel divided by entirety
Air light value, to obtain except value, deducts described except value is to obtain the medium transmission rate of each pixel by 1.
nullDescribed image-preprocessing device also includes: sharpening Image Acquisition subset，Subset is divided with described region、Described overall air light value obtains subset and described medium transmission rate obtains subset and connects respectively，The medium transmission rate of each pixel is deducted to obtain the first difference by 1，Described first difference is multiplied by overall air light value to obtain product value，The pixel value of each pixel in described bezel, cluster image is deducted described product value to obtain the second difference，By described second difference divided by the medium transmission rate of each pixel to obtain the sharpening pixel value of each pixel，In described bezel, cluster image, the pixel value of each pixel includes the R of each pixel in described bezel, cluster image，G，B tri-Color Channel pixel value，Correspondingly，The sharpening pixel value of each pixel obtained includes the R of each pixel，G，B tri-Color Channel sharpening pixel value，The sharpening pixel value composition mist elimination bezel, cluster image of all pixels.
Described mist elimination bezel, cluster image, after receiving described mist elimination bezel, cluster image, is sequentially carried out image sharpening, self adaptation recursive filtering and OCR identifying processing, to obtain electric energy meter reading by described digital signal processor 1.
Wherein, described haze Concentration Testing subset is also built-in with static storage cell, is used for prestoring comparison table, and described comparison table saves haze concentration and the corresponding relation between intensity removed by haze.
More specifically, in the described automatic copying electric meter platform gathered based on cmos image, described cmos image sensor is the OV7640 sensor of Omnivision company.
Wherein, in described platform, described region divides subset, described black channel obtains subset, described overall air light value obtains subset, described atmospheric scattering light value obtains subset, described medium transmission rate obtains subset and described sharpening Image Acquisition subset can be respectively adopted different fpga chips and realize；Or described region divides subset, described black channel obtains subset, described overall air light value obtains subset, described atmospheric scattering light value obtains subset, described medium transmission rate obtains subset and described sharpening Image Acquisition subset can be integrated on one piece of circuit board；Alternatively, described region divides subset, described black channel obtains subset, described overall air light value obtains subset, described atmospheric scattering light value obtains subset, described medium transmission rate obtains subset and described sharpening Image Acquisition subset can be integrated in one piece of fpga chip.
It addition, haze image can process equipment by a series of images realizes the mist elimination haze of image, to obtain the image of sharpening, improve the visibility of image.These image processing equipments perform different image processing functions respectively, based on the principle that haze is formed, reach to remove the effect of haze.The sharpening of haze image processes all has great using value for dual-use field, and military domain includes military and national defense, remote sensing navigation etc., and civil area includes road monitoring, target following and automatic Pilot etc..
The process that haze image is formed can be described by atmospheric attenuation process, relation between haze image and real image and sharpening image can be stated by the medium transmission rate of overall air light value and each pixel, namely when known haze image, medium transmission rate according to overall air light value and each pixel, it is possible to solve sharpening image.
nullThere are some means effectively and through verifying in the solving of medium transmission rate for overall air light value and each pixel，Such as，Medium transmission rate for each pixel，Need to obtain the atmospheric scattering light value of overall air light value and each pixel，And the atmospheric scattering light value of each pixel can obtain each pixel pixel value in haze image is performed twice at the Gaussian smoothing filter keeping edge，Therebetween，The intensity that haze is removed is adjustable，And entirety air light value can (the black channel value namely making some pixels in haze image be non-normally low by obtaining the black channel of haze image，Black channel is R，G，One in B tri-Color Channel)，In haze image，The pixel finding gray value maximum in multiple pixels bigger than normal by finding black channel pixel value obtains，It is about to search out、The gray value of the pixel that gray value is maximum is as overall air light value，Participate in the sharpening of each pixel in haze image to process.Relation between concrete haze image and real image and sharpening image, and the relation between parameters can referring to above content.
By the discussion to haze image formation basic theory, build the relation between haze image and sharpening image, this relation is represented by multiple parameters, subsequently by the multiple parameter values obtained and haze image and the higher image of reducible acquisition definition, some statistical means and empirical means has been used due to the acquisition of parameter, therefore the image that described definition is higher can not be fully equivalent to real image, but there is considerable degree of mist elimination haze effect, provide effective guarantee for the every field operation under haze weather.
It addition, parallel port and parallel interface, refer to adopt parallel transmission mode to transmit the interface standard of data.From a simplest parallel data register or special purpose interface IC chip such as 8255,6820 etc., to more complicated SCSI or IDE parallel interface, kind has tens of kinds.
The interface features of one parallel interface can be been described by from two aspects: the width of the data channel 1, transmitted in a parallel fashion, also referred to as the figure place of interface transmission；2, for coordinating the additional interface control line of parallel data transmission or claiming the characteristic of interactive signal.The width of data from 1-128 position or wider, can be most commonly used that 8, can pass through interface and once transmit 8 data bit.At the LPT interface that the parallel interface that computer realm is the most frequently used is known as.
Adopt the automatic copying electric meter platform gathered based on cmos image of the present invention, for existing electric energy meter reading ineffective systems and would be likely to occur, at vile weather, the technical problem that precision is not high, by adopting image acquisition and image processing techniques targetedly, substitute manual metering mode, improve meter reading efficiency, simultaneously, add the image preprocess apparatus based on atmospheric attenuation model and realize the process of mist elimination hazeization, reduce haze on the impact of quality of image of checking meter, it is to avoid it is disturbed that electric energy meter reading gathers data.
Although it is understood that the present invention discloses as above with preferred embodiment, but above-described embodiment is not limited to the present invention.For any those of ordinary skill in the art, without departing under technical solution of the present invention ambit, all may utilize the technology contents of the disclosure above and technical solution of the present invention is made many possible variations and modification, or be revised as the Equivalent embodiments of equivalent variations.Therefore, every content without departing from technical solution of the present invention, the technical spirit of the foundation present invention, to any simple modification made for any of the above embodiments, equivalent variations and modification, all still falls within the scope of technical solution of the present invention protection.
Claims (1)
1. the method based on cmos image collection, electric energy meter being carried out automatic data logging, comprising:
(1) shoot to obtain bezel, cluster image to the bezel, cluster of electric energy meter by cmos image sensor；
(2) bezel, cluster image step (1) obtained by digital signal processor carries out image procossing, to obtain electric energy meter reading；
(3) the electric energy meter reading respectively step (2) obtained by FLASH memory and LCD display is stored and shows；
Described method utilizes the automatic copying electric meter platform gathered based on cmos image to implement, described platform includes cmos image sensor, digital signal processor, LCD display and FLASH memory, and wherein said cmos image sensor, described LCD display and described FLASH memory are connected with described digital signal processor respectively；
Described automatic copying electric meter platform also includes:
CSI interface, between cmos image sensor and image-preprocessing device, sends image-preprocessing device to for the bezel, cluster image shot by described cmos image sensor；
First parallel port, between described digital signal processor and described LCD display, sends described LCD display to display for the electric energy meter reading obtained by described digital signal processor；
Second parallel port, between described digital signal processor and described FLASH memory, sends described FLASH memory to store for the electric energy meter reading obtained by described digital signal processor；
Power supply, including solar powered device, accumulator, switching switch and electric pressure converter, described switching switch is connected respectively with described solar powered device and described accumulator, decide whether to be switched to described solar powered device to be powered by described solar powered device according to accumulator dump energy, described electric pressure converter is connected with described switching switch, so that the 5V voltage inputted by switching switch is converted to 3.3V voltage；
Image-preprocessing device, between described CSI interface and described digital signal processor, for receiving described bezel, cluster image, described bezel, cluster image carries out mist elimination process to obtain mist elimination bezel, cluster image, described mist elimination bezel, cluster image is inputted described digital signal processor to carry out image procossing to obtain electric energy meter reading；
Described image-preprocessing device also includes:
Storage subset, for prestoring sky upper limit gray threshold and sky lower limit gray threshold, described sky upper limit gray threshold and described sky lower limit gray threshold are for isolating the sky areas in image, being additionally operable to prestore presetted pixel value threshold value, described presetted pixel value threshold value value is between 0 to 255；
Haze Concentration Testing subset, is arranged in air, for detecting the haze concentration of electric energy meter position in real time, and determines that intensity removed by haze according to haze concentration, and described haze removes intensity value between 0 to 1；
Region divides subset, connect described CSI interface to receive described bezel, cluster image, described bezel, cluster image carries out gray processing process to obtain gray processing bezel, cluster image, also it is connected with storage subset, by the pixel identification between described sky upper limit gray threshold and described sky lower limit gray threshold of the gray value in described gray processing bezel, cluster image and form gray processing sky sub pattern, it is partitioned into described gray processing sky sub pattern to obtain the non-sky subimage of gray processing from described gray processing bezel, cluster image, the colour non-sky subimage corresponding with described gray processing non-sky subimage is obtained based on described gray processing non-sky subimage position in described bezel, cluster image；
Black channel obtains subset, divide subset with described region to be connected to obtain the non-sky subimage of described colour, for each pixel in the non-sky subimage of described colour, calculate its R, G, B tri-Color Channel pixel value, the R of all pixels in described colour non-sky subimage, G, B tri-extracts the Color Channel at a minimum Color Channel pixel value place of numerical value in Color Channel pixel value as black channel；
Overall air light value obtains subset, it is connected to obtain presetted pixel value threshold value with described storage subset, divide subset with described region and described black channel obtains subset and is connected respectively to obtain described bezel, cluster image and described black channel, black channel pixel value in described bezel, cluster image is formed set of pixels to be tested be more than or equal to multiple pixels of presetted pixel value threshold value, using the gray value of the pixel in described set of pixels to be tested with maximum gradation value as overall air light value；
nullAtmospheric scattering light value obtains subset，Divide subset with described region and described haze Concentration Testing subset is connected respectively，Each pixel to described bezel, cluster image，Extract its R，G，In B tri-Color Channel pixel value, minima is as target pixel value，Use and keep the Gaussian filter EPGF at edge to be filtered described target pixel value processing to obtain filtered target pixel value，Target pixel value is deducted filtered target pixel value to obtain object pixel difference，EPGF is used to be filtered object pixel difference processing to obtain filtered target pixel value difference，Filtered target pixel value is deducted filtered target pixel value difference and removes reference value to obtain haze，Haze is removed intensity and is multiplied by haze removal reference value to obtain haze removal threshold value，Take haze and remove the minima in threshold value and target pixel value as comparison reference，Take the atmospheric scattering light value as each pixel of the maximum in comparison reference and 0；
Medium transmission rate obtains subset, obtain subset with described overall air light value and described atmospheric scattering light value obtains subset and is connected respectively, by the atmospheric scattering light value of each pixel divided by overall air light value to obtain except value, deduct described except value is to obtain the medium transmission rate of each pixel by 1；
nullSharpening Image Acquisition subset，Subset is divided with described region、Described overall air light value obtains subset and described medium transmission rate obtains subset and connects respectively，The medium transmission rate of each pixel is deducted to obtain the first difference by 1，Described first difference is multiplied by overall air light value to obtain product value，The pixel value of each pixel in described bezel, cluster image is deducted described product value to obtain the second difference，By described second difference divided by the medium transmission rate of each pixel to obtain the sharpening pixel value of each pixel，In described bezel, cluster image, the pixel value of each pixel includes the R of each pixel in described bezel, cluster image，G，B tri-Color Channel pixel value，Correspondingly，The sharpening pixel value of each pixel obtained includes the R of each pixel，G，B tri-Color Channel sharpening pixel value，The sharpening pixel value composition mist elimination bezel, cluster image of all pixels；
Wherein, described haze Concentration Testing subset is also built-in with static storage cell, is used for prestoring comparison table, and described comparison table saves haze concentration and the corresponding relation between intensity removed by haze；
Described cmos image sensor is the OV7640 sensor of Omnivision company.
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Effective date of registration: 20201215 Address after: 236600 Maji village committee, Maji Township, Taihe County, Fuyang City, Anhui Province Applicant after: Tian Chaoyi Address before: 213000 Jinling North Road, Xinbei District, Changzhou, Jiangsu, China, Hohai University Applicant before: Zhou Jie |
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