CN113536895A - Disc pointer meter identification method - Google Patents
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Abstract
The invention relates to a disc pointer meter identification method. The method comprises the following steps: step 1, moving the inspection robot to a prefabricated point position, and collecting the current meter image in real time. Step 2, performing feature matching on the collected images and corresponding images in the template, and calculating pixel offset difference of the two images; and calculating the horizontal and longitudinal adjusting angles according to the relation between the pixel difference and the adjusting angle under the current focal length, and feeding back to the robot to perform corresponding control and adjustment on the holder. And 3, matching according to the characteristic points between the collected meter image and the corresponding template, then obtaining and calculating a transformation matrix through the corresponding matching points, transforming the collected image, and fitting a disc in the image into a circle through Hough transformation. And 4, unfolding the disc image into a long rectangular image, inputting the long rectangular image into a pointer identification model, and calculating a pointer value. The invention can be applied to various disc pointer meters and has universality.
Description
Technical Field
The invention belongs to the technical field of meter identification based on images, and particularly relates to a disc pointer meter identification method.
Background
Through decades of development, the field of computer vision is rapidly improved, and the computer vision system has superiority in many application scenes. The reading of the pointer instrument equipment of the transformer substation is an important index related to the safety maintenance of the transformer substation equipment, and at present, the image acquisition of the power instrument can be remotely carried out through the inspection robot, and then the reading of the instrument is identified through a related image identification algorithm.
The conventional method for identifying the meter reading based on the inspection robot at present comprises the steps of detecting a disc and a pointer in an image through Hough transformation after a camera on the inspection robot captures a meter image, calculating the degree of an included angle between the pointer and a starting point, and finally converting the reading pointed by the current pointer.
According to the method, Hough transformation is required to be carried out on an original collected image to detect a disc and a pointer, but in an actual situation, due to the limitations of the pose of a cloud deck of the inspection robot and the like, the collected meter image is not a perfect circle; meanwhile, different starting scale marks may exist for different types of disc meters, and the traditional algorithm cannot be used universally.
Disclosure of Invention
The technical problem of the invention is mainly solved by the following technical scheme:
a disc pointer meter identification method is characterized by comprising
Step 1, moving the inspection robot to a prefabricated point position, and collecting the current meter image in real time.
Step 2, performing feature matching on the collected images and corresponding images in the template, and calculating pixel offset difference of the two images; and calculating the horizontal and longitudinal adjusting angles according to the relation between the pixel difference and the adjusting angle under the current focal length, and feeding back to the robot to perform corresponding control and adjustment on the holder.
And 3, matching according to the characteristic points between the collected meter image and the corresponding template, then obtaining and calculating a transformation matrix through the corresponding matching points, transforming the collected image, and fitting a disc in the image into a circle through Hough transformation.
And 4, unfolding the disc image into a long rectangular image.
And 5, inputting the long rectangular image into the pointer identification model, and calculating a pointer value.
In the above method for identifying a disc pointer meter, in step 2, the feature matching is performed based on a template matching algorithm, specifically: the template slides from left to right and from top to bottom on the image to be detected, and the template refers to the image which is collected under the current focal distance and is just opposite to the dial plate;
and when a pixel point is reached, capturing an image with the same size as the template from the source image by taking the pixel point as the top left corner vertex, carrying out pixel comparison operation on the image and the template, and calculating the pixel offset difference R (x, y) of the two images. Let the resulting matrix be R (x, y), the template image matrix be T (x ', y'), and the source image matrix be I (x, y).
In the above method for identifying a disc pointer meter, in step 2, the specific moving mode of the template is as follows: starting from the upper left corner of the source image, moving from left to right and from top to bottom by taking the upper left corner pixel point of the template as a unit each time, and acquiring a pixel offset difference R (x, y) based on the following formula:
in the above identification method for the disc pointer meter, in step 2, the first matching is rough matching, and multiple times of matching are required to ensure the final matching accuracy. And when the pixel offset difference between the two images is smaller than the threshold value, entering the next focal length, acquiring the images again, calculating the pixel offset between the acquired images and the current focal length template based on the template matching algorithm, and feeding back to the robot to adjust the cradle head until obtaining the high-definition image containing the dial plate at the final focal length.
In the above method for identifying a disc pointer meter, in step 3, matching is performed according to feature points between a meter image acquired at a final focal length and a corresponding template, then a transformation matrix is obtained and calculated through the corresponding matching points, the corresponding template refers to a dial image acquired at the final focal length, the acquired dial image is photographed in a forward direction, and after the acquired image is transformed, a disc in the image is fitted into a circle through hough transformation.
In the disk pointer meter identification method, in step 5, the long rectangular image is input into a pointer identification model, the position of the pointer is identified based on a pointer identification algorithm, and the pointer value is calculated according to the proportion of the abscissa of the pointer point in the length of the whole rectangular image.
In the above identification method for a disc pointer meter, the specific calculation method in step 5 is: defining the meter measuring range as range, and finally calculating the pointer numerical digit (tx/width) range according to the proportion of the abscissa (tx) of the pointer point in the length (width) of the whole rectangular image.
Therefore, the invention has the following advantages: 1. the universal disc pointer meter can be suitable for various disc pointer meters and has universality; 2. the pointer is identified by introducing a deep learning method, so that the accuracy and the robustness can be improved to a greater extent. 3. Through disc fitting, the accuracy of the unfolded image is ensured, and the accuracy of the final detection result can be improved; 4. compared with the traditional algorithm, the method not only increases the identification accuracy, but also improves the detection efficiency.
Drawings
FIG. 1 is a schematic flow chart of the algorithm of the present invention;
FIG. 2 is a collected disk pointer meter image;
FIG. 3 is an image after a disk fit;
FIG. 4 is a disk unfolded to a rectangular bar image;
fig. 5 shows the position of the recognition pointer, wherein the red arrow is the recognition result.
Detailed Description
The technical scheme of the invention is further specifically described by the following embodiments and the accompanying drawings.
Example (b):
the traditional identification algorithm for the dial gauges is basically identified by determining the included angle between a pointer and an initial position, different types of dial gauges cannot be used universally, different parameters need to be manually input to achieve the identification algorithm, and inconvenience is increased.
The specific implementation mode of the method provided by the invention is as follows:
the first step is as follows: and moving the inspection robot to a prefabricated point position, and acquiring the current meter image in real time.
The second step is that: the method comprises the steps of performing feature matching on an acquired image and a corresponding image in a template, extracting matching points in the acquired image and the corresponding image in the template by an AKAZE feature matching method, eliminating invalid matching points by a RANSAC algorithm, and calculating the pixel offset difference of the two images based on the template matching algorithm: the template (at the current focal length, the collected image just facing the dial) slides from left to right and from top to bottom on the image to be detected, the template moves from left to right and from top to bottom by taking a pixel point at the upper left corner of the template as a unit every time from the upper left corner of the source image, and when one pixel point is reached, the pixel point is taken as the top left corner vertex to intercept the image with the same size as the template from the source image and carry out pixel comparison operation with the template, and the pixel offset difference R (x, y) of the two images is calculated. Let the resulting matrix be R (x, y), the template image matrix be T (x ', y'), the source image matrix be I (x, y)
And calculating the horizontal and longitudinal adjusting angles according to the relation between the pixel difference and the adjusting angle under the current focal length, and feeding back to the robot to perform corresponding control and adjustment on the holder. The first matching is rough matching, and multiple times of matching are needed to ensure the final matching accuracy. Therefore, when the pixel offset difference between the two images is smaller than the threshold value, the next focal distance is entered, the images are collected again, matching points in the collected images and the corresponding images in the template are extracted through an AKAZE feature matching method, invalid matching points are eliminated through a RANSAC algorithm, the pixel offset between the collected images and the current focal distance template is calculated based on the template matching algorithm, and the pixel offset is fed back to the robot adjusting holder until a high-definition image containing the dial plate under the final focal distance ((three different focal distances in total) is obtained.
The third step: matching according to characteristic points (such as sift and other characteristics) between a meter image acquired to a final focal length and a corresponding template (namely, under the final focal length, the acquired dial image is shot positively), then obtaining and calculating a transformation matrix (E (essential matrix) through the corresponding matching points, wherein the transformation matrix reflects the relation between the representation of image points of a space point P in a camera coordinate system under cameras with different visual angles), transforming the acquired image, and fitting a disc in the image into a circle through Hough transformation.
The fourth step: the disk image is expanded to a long rectangular image.
The fifth step: inputting the long strip rectangular image into a pointer identification model, identifying the position of a pointer based on a pointer identification algorithm, and calculating the pointer value according to the proportion of the abscissa of the pointer point in the length of the whole rectangular image. (assuming that the measuring range of the meter is range, and finally, calculating the numerical value (tx/width) range of the pointer according to the proportion of the abscissa (tx) of the pointer point in the length (width) of the whole rectangular image.)
The specific embodiments described herein are merely illustrative of the spirit of the invention. Various modifications or additions may be made to the described embodiments or alternatives may be employed by those skilled in the art without departing from the spirit or ambit of the invention as defined in the appended claims.
Claims (7)
1. A disc pointer meter identification method is characterized by comprising
Step 1, moving the inspection robot to a prefabricated point position, and collecting a current meter image in real time;
step 2, performing feature matching on the collected image and the corresponding image in the template, extracting matching points in the collected image and the corresponding image in the template by an AKAZE feature matching method, eliminating invalid matching points by a RANSAC algorithm, and calculating a pixel offset difference of the two images; calculating the horizontal and longitudinal adjusting angles according to the relation between the pixel difference and the adjusting angle under the current focal length, and feeding back to the robot to perform corresponding control adjustment on the holder;
step 3, matching according to the collected characteristic points between the meter image and the corresponding template, then obtaining and calculating a transformation matrix through the corresponding matching points, transforming the collected image, and fitting a disc in the image into a circle through Hough transformation;
step 4, unfolding the disc image into a long rectangular image;
and 5, inputting the long rectangular image into the pointer identification model, and calculating a pointer value.
2. The disc pointer meter identification method according to claim 1, wherein in step 2, feature matching is performed based on a template matching algorithm, specifically: sliding a template from left to right and from top to bottom on an image to be detected, wherein the template refers to an image which is collected under the current focal length and is just opposite to a dial plate;
when a pixel point is reached, an image with the same size as the template is intercepted from a source image by taking the pixel point as the top left corner, and the image and the template are subjected to pixel comparison operation, and the pixel offset difference R (x, y) of the two images is calculated; let the resulting matrix be R (x, y), the template image matrix be T (x ', y'), and the source image matrix be I (x, y).
3. The method for identifying a disc pointer meter according to claim 1, wherein in the step 2, the specific moving mode of the template is as follows: starting from the upper left corner of the source image, moving from left to right and from top to bottom by taking the upper left corner pixel point of the template as a unit each time, and acquiring a pixel offset difference R (x, y) based on the following formula:
4. the disc pointer meter identification method according to claim 1, wherein in step 2, the first matching is a rough matching, and multiple matching is required to ensure the final matching accuracy; and therefore, when the pixel offset difference between the two images is smaller than the threshold value, entering the next focal length, acquiring the images again, extracting matching points in the acquired images and the corresponding images in the template by using an AKAZE characteristic matching method, eliminating invalid matching points by using a RANSAC algorithm, calculating the pixel offset between the acquired images and the current focal length template based on the template matching algorithm, and feeding back to the robot adjusting holder until obtaining a high-definition image containing the dial plate at the final focal length.
5. The method for identifying a disc pointer meter according to claim 1, wherein in the step 3, matching is performed according to feature points between the meter image acquired at the final focal length and a corresponding template, then a transformation matrix is obtained and calculated through the corresponding matching points, the corresponding template refers to a captured dial image which is photographed in the positive direction under the final focal length, and after the captured image is transformed, a disc in the image is fitted into a circle through Hough transformation.
6. The method of claim 1, wherein in step 5, the long rectangular image is input into a pointer recognition model (as shown in the following figure), the position of the pointer is recognized based on a pointer recognition algorithm, and the pointer value is calculated according to the proportion of the abscissa of the pointer point to the length of the whole rectangular image.
7. The disc pointer meter identification method according to claim 1, wherein the specific calculation method in step 5 is: defining the meter measuring range as range, and finally calculating the pointer numerical digit (tx/width) range according to the proportion of the abscissa (tx) of the pointer point in the length (width) of the whole rectangular image.
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