CN111797909A - Pointer instrument reading method based on machine vision - Google Patents
Pointer instrument reading method based on machine vision Download PDFInfo
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- CN111797909A CN111797909A CN202010571594.7A CN202010571594A CN111797909A CN 111797909 A CN111797909 A CN 111797909A CN 202010571594 A CN202010571594 A CN 202010571594A CN 111797909 A CN111797909 A CN 111797909A
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- 238000004364 calculation method Methods 0.000 claims description 16
- 238000001514 detection method Methods 0.000 claims description 14
- 239000011159 matrix material Substances 0.000 claims description 7
- 238000012937 correction Methods 0.000 claims description 3
- 238000003708 edge detection Methods 0.000 claims description 3
- 238000001914 filtration Methods 0.000 claims description 3
- 238000010586 diagram Methods 0.000 description 2
- 208000003464 asthenopia Diseases 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
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- 238000005286 illumination Methods 0.000 description 1
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/22—Matching criteria, e.g. proximity measures
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration
- G06T5/20—Image enhancement or restoration by the use of local operators
- G06T5/30—Erosion or dilatation, e.g. thinning
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/13—Edge detection
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/136—Segmentation; Edge detection involving thresholding
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/70—Determining position or orientation of objects or cameras
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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
Abstract
The invention relates to a pointer type pressure instrument reading method based on machine vision, which comprises the following steps: acquiring a standard template image of the instrument and an image of the instrument to be read; matching the instrument image to be read with the instrument standard template image by using a matching algorithm to obtain a corrected instrument image to be read; denoising the image of the corrected meter to be read, performing threshold segmentation on the denoised image of the corrected meter to be read to obtain the image of the meter to be read with the background removed, and removing the image of the meter to be readPositioning the position of a dial boundary circle in the background to-be-read instrument image; performing expansion operation on the background-removed instrument image to be read to obtain a pointer image; obtaining the needle point coordinate (x) in the pointer image1,y1) And center coordinates (x)2,y2) (ii) a According to the needle point coordinate (x)1,y1) And center coordinates (x)2,y2) And obtaining the angular position of the pointer, and obtaining the reading of the meter according to the angular position of the pointer. Compared with the prior art, the reading of the meter is more accurate.
Description
Technical Field
The invention relates to the field of image monitoring and processing systems, in particular to a pointer instrument reading method based on machine vision.
Background
In the factory calibration link of the pointer type pressure instrument, the calibration and adjustment of reading errors of the instrument are required. At present, the instrument is pressurized manually, the current reading of the instrument is read out through human eye observation, the numerical value of a high-precision digital instrument is compared, and the error of the instrument to be measured is calculated. The manual method for carrying out factory calibration on the pointer pressure instrument has low efficiency and low accuracy, and is easy to cause visual fatigue and cause errors particularly after long-time continuous interpretation. In addition, the instrument is not screwed in place during fixed installation, a camera for collecting the instrument image does not face the instrument, so that the collecting camera cannot well collect the accurate image of the instrument panel, and the collected instrument image has certain attitude error. How to carry out high-efficient accurate instrument image acquisition and the reading of discernment instrument to the instrument that produces attitude error is the key of guaranteeing that pointer type pressure instrument leaves the factory high-efficient accurate examination.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provide a pointer instrument reading method based on machine vision.
The purpose of the invention can be realized by the following technical scheme:
a machine vision based pointer instrument reading method, the method comprising the steps of:
step S1: acquiring a standard template image of the instrument and an image of the instrument to be read;
step S2: matching the instrument image to be read with the instrument standard template image by using a matching algorithm to obtain a corrected instrument image to be read;
step S3: denoising the corrected to-be-read instrument image, performing threshold segmentation on the denoised corrected to-be-read instrument image to obtain a background-removed to-be-read instrument image, and positioning the position of a dial boundary circle in the background-removed to-be-read instrument image;
step S4: performing expansion operation on the background-removed instrument image to be read to obtain a pointer image;
step S5: obtaining the needle point coordinate (x) in the pointer image1,y1) And center coordinates (x)2,y2)；
Step S6: according to the needle point coordinate (x)1,y1) And center coordinates (x)2,y2) And obtaining the angular position of the pointer, and obtaining the reading of the meter according to the angular position of the pointer.
In step S2, the feature matching algorithm of the GMS grid mobile statistical strategy is used to match the to-be-read meter image with the standard meter template image, and the process includes:
step S21: detecting characteristic points and a calculation descriptor of the instrument standard template image and the instrument image to be read;
step S22: respectively matching the characteristic points and the calculation descriptors of the instrument standard template image with the characteristic points and the calculation descriptors of the instrument image to be read through a BF violence matching algorithm;
step S23: respectively dividing the instrument standard template image and the instrument image to be read into a plurality of grids, reserving correctly matched characteristic points, and calculating to obtain a projection matrix between the instrument standard template image and the instrument image to be read;
step S24: and obtaining an image of the instrument to be read by correction according to the projection matrix.
And the number of the correctly matched feature points is larger than a threshold value.
In the step S3, the meter image to be read is corrected by denoising using median filtering.
In the step S3, an OTSU threshold segmentation algorithm is used to perform threshold segmentation on the denoised corrected meter-to-be-read image.
After the background-removed to-be-read instrument image is obtained in the step S3, edge detection is performed on the background-removed to-be-read instrument image by using a Canny operator, circle detection is performed by using a hough transform algorithm to obtain a dial boundary circle, and the position of the dial boundary circle is located in the background-removed to-be-read instrument image.
The process of obtaining the needle point coordinates in the pointer image in step S5 includes:
step S51: obtaining a pointer position predicted value;
step S52: searching a pointer edge lateral line around a pointer position predicted value of the pointer image;
step S53: and obtaining the coordinate of the needle point by utilizing the edge lateral line.
The step S6 is based on the needle point coordinate (x)1,y1) And center coordinates (x)2,y2) The calculation formula for obtaining the angular position theta of the pointer is as follows:
in step S6, the calculation formula of obtaining the meter reading N according to the angle position of the pointer is as follows:
where θ is the angular position of the pointer, θ0Is the minimum angular position of the instrument, thetamaxFor maximum angular position of the instrument, N0Is the minimum value of the meter reading, NmaxIs the maximum value of the meter reading.
The instrument standard template image and the instrument image to be read are shot by an industrial camera.
Compared with the prior art, the invention has the following advantages:
(1) the attitude of the measured instrument is corrected by using the template matching algorithm, so that the measurement error caused by the attitude error of the instrument is reduced, and the identification precision of the algorithm is improved.
(2) By using a feature matching algorithm of a GMS grid mobile statistical strategy, the feature point pairs which are accurately matched are reserved, the projection matrix between the meter to be read and the standard template meter is accurately calculated, and the reading error of the meter is reduced.
(3) After the dial boundary circle is identified, the effective area is determined, elements which influence the identification of the pointer, such as the meter frame, the dial and the like, can be deleted, and the calculation cost of the pointer edge lateral line detection is reduced.
(4) According to the particularity of the pointer instrument detection, the pointer edge lateral line detection is carried out in a certain pressure range (namely around the pointer position predicted value), instead of carrying out the straight line detection on the whole image, so that the speed of the pointer edge lateral line detection is greatly reduced, and the algorithm running speed is improved.
Drawings
FIG. 1 is a flow chart of the present invention;
FIG. 2 is a standard template image of the meter of the present invention;
FIG. 3 is a graph of the matching results of the present invention;
FIG. 4 is a graph of OTSU threshold segmentation in accordance with the present invention;
FIG. 5 is a dial boundary circle detection diagram of the present invention;
FIG. 6 is a pointer image of the present invention;
FIG. 7 is a pointer edge siding detection diagram of the present invention;
fig. 8 is a conversion chart of the pointer angle position-meter reading of the present invention.
Detailed Description
The invention is described in detail below with reference to the figures and specific embodiments. The present embodiment is implemented on the premise of the technical solution of the present invention, and a detailed implementation manner and a specific operation process are given, but the scope of the present invention is not limited to the following embodiments.
Examples
The embodiment provides a pointer type pressure instrument reading method based on machine vision, as shown in fig. 1, comprising the following steps:
(1) placing a standard instrument on a plane, polishing the instrument by using an annular low-angle light source, and acquiring an instrument standard template image by using an industrial camera, wherein the instrument standard template image is shown in figure 2; placing the meter to be read in the same illumination environment as the standard meter, and acquiring the image of the meter to be read by using an industrial camera;
(2) the template matching is carried out by using a feature matching algorithm of a GMS grid motion statistical strategy, and the flow is as follows:
a. detecting characteristic points and a calculation descriptor of the instrument standard template image and the instrument image to be read;
b. respectively matching the characteristic points and the calculation descriptors of the instrument standard template image with the characteristic points and the calculation descriptors of the instrument image to be read through a BF violence matching algorithm;
c. respectively dividing the instrument standard template image and the instrument image to be read into a plurality of grids;
d. calculating the number of correct matching points near the feature points matched by the BF violent matching algorithm, comparing the number with a set threshold value, judging whether the feature points are correctly matched or not, reserving the correctly matched feature points, and removing the incorrectly matched feature points, wherein the figure is shown in figure 3;
e. selecting 4 pairs of correctly matched characteristic points to obtain a quaternion linear equation, calculating to obtain a projection matrix between the standard template image of the instrument and the image of the instrument to be read, and correcting the posture of the image of the instrument to be read through the projection matrix to obtain a corrected image of the instrument to be read;
(3) performing median filtering on the image of the meter to be read for correction, and removing noise interference; performing threshold segmentation on the image of the meter to be read by using an OTSU threshold segmentation algorithm, and removing the background of the instrument panel as shown in FIG. 4; and (3) performing edge detection on the background-removed instrument image to be read by using a Canny operator, then performing circle detection by using a Hough transform algorithm, starting detection from a circle with the largest radius to obtain a dial boundary circle, and positioning the position of the dial boundary circle, as shown in fig. 5.
(4) The background-removed cross-shaped area expansion of the meter image to be read, where the dial boundary circle is located, is performed by 7 × 7, various interference straight lines in the instrument panel are removed, and only the pointer image is retained, as shown in fig. 6.
(5) The method comprises the steps of detecting a pointer edge side line, wherein the pointer edge side line detection has certain particularity, the current reading of a pointer is provided by a standard controllable pressure generator, a pressure generation scheme is provided according to the type of the meter, and the current pointer position of the meter to be read is close to the provided pressure value. The pointer edge lateral line detection is carried out according to the prior knowledge, and the specific steps are as follows:
a. obtaining a predicted value of the current pointer position according to the current pressure value provided by a standard controllable pressure generator, wherein if the predicted value is 17MPa, the error requirement of the instrument is within 1MPa, and pointer edge lateral line detection is carried out on the instrument pointer within the range of 16-18 MPa;
b. if the pointer edge siding is not found in the current interval, expanding the range to the interval of 15-16 MPa and 18-19 MPa to search the pointer edge siding, as shown in FIG. 7;
c. after the side line of the pointer edge is found, the coordinate (x) of the needle point is obtained1,y1) And center coordinates (x)2,y2)；
(6) According to the needle point coordinate (x)1,y1) And center coordinates (x)2,y2) The angular position of the pointer is obtained and the meter reading is obtained based on the angular position of the pointer, as shown in fig. 8.
According to the needle point coordinate (x)1,y1) And center coordinates (x)2,y2) The calculation formula for obtaining the angular position theta of the pointer is as follows:
the calculation formula for obtaining the meter reading N according to the angular position of the pointer is as follows:
where θ is the angular position of the pointer, θ0Is the minimum angular position of the instrument, thetamaxFor maximum angular position of the instrument, N0Is the minimum value of the meter reading, NmaxFor reading of metersA maximum value.
Claims (10)
1. A pointer instrument reading method based on machine vision is characterized by comprising the following steps:
step S1: acquiring a standard template image of the instrument and an image of the instrument to be read;
step S2: matching the instrument image to be read with the instrument standard template image by using a matching algorithm to obtain a corrected instrument image to be read;
step S3: denoising the corrected to-be-read instrument image, performing threshold segmentation on the denoised corrected to-be-read instrument image to obtain a background-removed to-be-read instrument image, and positioning the position of a dial boundary circle in the background-removed to-be-read instrument image;
step S4: performing expansion operation on the background-removed instrument image to be read to obtain a pointer image;
step S5: obtaining the needle point coordinate (x) in the pointer image1,y1) And center coordinates (x)2,y2)；
Step S6: according to the needle point coordinate (x)1,y1) And center coordinates (x)2,y2) And obtaining the angular position of the pointer, and obtaining the reading of the meter according to the angular position of the pointer.
2. The machine vision-based pointer instrument reading method of claim 1, wherein the step S2 matches the instrument image to be read with the standard template image of the instrument by using a feature matching algorithm of a GMS grid moving statistical strategy, and the process includes:
step S21: detecting characteristic points and a calculation descriptor of the instrument standard template image and the instrument image to be read;
step S22: respectively matching the characteristic points and the calculation descriptors of the instrument standard template image with the characteristic points and the calculation descriptors of the instrument image to be read through a BF violence matching algorithm;
step S23: respectively dividing the instrument standard template image and the instrument image to be read into a plurality of grids, reserving correctly matched characteristic points, and calculating to obtain a projection matrix between the instrument standard template image and the instrument image to be read;
step S24: and obtaining an image of the instrument to be read by correction according to the projection matrix.
3. The machine vision-based pointer instrument reading method of claim 2, wherein the correctly matched feature points are feature points with the number of the surrounding correctly matched points larger than a threshold value.
4. The machine-vision-based pointer instrument reading method as claimed in claim 1, wherein the step S3 is implemented by denoising the corrected meter-to-be-read image by using median filtering.
5. The machine-vision-based pointer instrument reading method of claim 1, wherein in step S3, the corrected denoised image of the reading instrument to be read is subjected to threshold segmentation by using OTSU threshold segmentation algorithm.
6. The machine vision-based pointer instrument reading method of claim 1, wherein after the background-removed image of the meter to be read is obtained in step S3, edge detection is performed on the background-removed image of the meter to be read by using a Canny operator, circle detection is performed by using a hough transform algorithm to obtain a dial boundary circle, and a position of the dial boundary circle is located in the background-removed image of the meter to be read.
7. The machine vision-based pointer instrument reading method of claim 1, wherein the step S5 of obtaining the coordinates of the needle tip in the pointer image comprises:
step S51: obtaining a pointer position predicted value;
step S52: searching a pointer edge lateral line around a pointer position predicted value of the pointer image;
step S53: and obtaining the coordinate of the needle point by utilizing the edge lateral line.
8. The machine vision-based pointer instrument reading method of claim 1, wherein the step S6 is performed according to the needle point coordinate (x)1,y1) And center coordinates (x)2,y2) The calculation formula for obtaining the angular position theta of the pointer is as follows:
9. the machine-vision-based pointer instrument reading method of claim 1, wherein the calculation formula of obtaining the instrument reading N according to the angular position of the pointer in the step S6 is as follows:
where θ is the angular position of the pointer, θ0Is the minimum angular position of the instrument, thetamaxFor maximum angular position of the instrument, N0Is the minimum value of the meter reading, NmaxIs the maximum value of the meter reading.
10. The machine vision-based pointer instrument reading method as claimed in claim 1, characterized in that the instrument standard template image and the instrument image to be read are captured by an industrial camera.
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