CN114332077A - RANSAC-based light dial plate identification method - Google Patents

RANSAC-based light dial plate identification method Download PDF

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CN114332077A
CN114332077A CN202210195989.0A CN202210195989A CN114332077A CN 114332077 A CN114332077 A CN 114332077A CN 202210195989 A CN202210195989 A CN 202210195989A CN 114332077 A CN114332077 A CN 114332077A
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image
circle
straight line
dial
binary edge
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辛建波
徐波
陶可京
李帆
李福德
李志坤
林谋
刘嘉
廖昊爽
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Super High Voltage Branch Of State Grid Jiangxi Electric Power Co ltd
State Grid Corp of China SGCC
Electric Power Research Institute of State Grid Jiangxi Electric Power Co Ltd
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Super High Voltage Branch Of State Grid Jiangxi Electric Power Co ltd
State Grid Corp of China SGCC
Electric Power Research Institute of State Grid Jiangxi Electric Power Co Ltd
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Abstract

The invention belongs to the technical field of image recognition, and discloses a RANSAC-based light-weight dial plate recognition method, which comprises the steps of converting a dial plate inspection image into a gray-scale image, and carrying out median filtering on the gray-scale image to reduce extracted edge pixel points; performing four convolutions by using four Sobel kernels and the gray level image after median filtering to obtain the gray level change of the image in the transverse direction and the longitudinal direction to obtain four binarization edge images, and synthesizing the four binarization edge images into one binarization edge image; removing a straight line formed by the positions of the telegraph poles in the synthesized binary edge map; obtaining a binary edge image after the straight line is deleted; and finally, performing circle fitting by using RANSAC to obtain the specific position of the dial. The method has the characteristics of small operation amount, high accuracy and no need of presetting a template.

Description

RANSAC-based light dial plate identification method
Technical Field
The invention belongs to the technical field of image recognition, and particularly relates to a RANSAC-based light-weight dial plate recognition method.
Background
To acquire the position of the meter, the detection of the shape of the dial is inevitable. Among the many shapes, the most significant for meter detection is the circular shape. To detect circles or ellipses, the most common method is to use hough transform (CHT), which first uses Canny edge detection to obtain edge pixels and then uses the edge pixels to determine the position of the circle. However, hough transform, especially hough ellipse transform, requires a large amount of storage space, has high computational complexity, and has poor accuracy under the conditions of noise in the image and incomplete target shape. In order to solve the problem, researchers at home and abroad propose a plurality of improved methods, such as probabilistic hough transform, Randomized Hough Transform (RHT), fuzzy hough transform and the like. Of these, Lu et al propose an iterative stochastic hough transform (IRHT), which, although yielding good results on noisy complex images, comes at the cost of a large increase in the number of computations. Ayalaamirez et al propose GA-based circle detectors, but this method fails to detect incomplete circles. Dasgupta proposes a circle detector optimized using the bacterial foraging algorithm (BFAOA), but it is not able to detect multiple circles simultaneously as the Ayalaamirez algorithm. In addition, Erik et al propose a Clone Selection Algorithm (CSA), Cuevas et al propose a rapid cycle detection, which can be used for a circle detection method of a Learning Automaton (LA), and the like. Although these algorithms work well in certain scenarios, they are not suitable for performing the task of dial plate recognition. In addition, Canny edge detection is found in the experimental process to generate too many edges, and the least square method has high noise sensitivity and the like.
CN108764257A discloses a multi-view pointer instrument identification method, which includes: collecting images and uploading the images to a computer; positioning an instrument area by utilizing an SSD algorithm; carrying out classification training on the instrument region by using a ResNet34 deep residual neural network, and carrying out primary correction on a sample image according to a classification result; performing secondary positioning of an instrument area on the corrected image by utilizing an SSD algorithm; performing regression training on the secondarily positioned instrument area by using the network, and identifying the position of a pointer on the dial plate; carrying out dial edge detection on the positioned instrument area by using an HED edge detection algorithm; carrying out random sampling according to RANSAC algorithm, and calculating an edge model of a meter dial; correcting the instrument pointer by utilizing the scaling ratio, and calculating an included angle between the instrument pointer and the starting needle; and looking up a database table according to the included angle to obtain the scale of the instrument panel. The method needs to rely on an SSD algorithm for positioning and an HED edge detection algorithm for edge detection, and the calculation amount is large.
Disclosure of Invention
In summary, the dial detection requires a computationally inexpensive and efficient algorithm, and the present invention aims to provide a lightweight dial identification method based on RANSAC: firstly, performing median filtering on an image and performing edge detection by using a Sobel core; then, integrating edge pixels by combining dial features; finally, the straight line and fitted dial are removed using a random sample consensus (RANSAC) method.
In order to realize the purpose, the invention adopts the following technical scheme: a RANSAC-based light dial plate identification method comprises the following steps:
step S1, converting the dial plate inspection image into a gray scale image;
step S2, median filtering is carried out on the gray level image;
step S3, performing four convolutions by using four Sobel kernels and the gray level image after median filtering to obtain four binary edge images, and synthesizing the four binary edge images into one binary edge image;
four convolutions with the median filtered gray scale map using four Sobel kernels for obtaining gray scale variations of the image in the lateral and longitudinal directions
Figure 981348DEST_PATH_IMAGE001
Respectively as follows:
Figure 252929DEST_PATH_IMAGE002
Figure 749769DEST_PATH_IMAGE003
taking the pixel average value for the result of each convolution
Figure 601243DEST_PATH_IMAGE004
And will be greater than
Figure 259758DEST_PATH_IMAGE005
The pixel of (1) is set to be 255, and the rest are 0, so that four binary edge images are obtained;
analyzing the gray scale change of each point on the dial plate, and then the upper left point of the dial platep 1And the lower right pointp 4Satisfies the following conditions: the product of the respective lateral gray scale variation and the longitudinal gray scale variation of the dots is greater than 0;
and the upper right pointp 2And the point at the lower leftp 3Satisfies the following conditions: the product of the respective lateral gray scale change and the longitudinal gray scale change of the dots is less than 0;
synthesizing the four binary edge images into a binary edge image;
step S4, removing straight lines in the binary edge image;
because the dial is arranged on the telegraph pole, the dial patrol inspection image not only comprises the dial but also comprises the telegraph pole, the straight line edge where the telegraph pole is located in the combined binary edge image is reserved, and the straight line formed by the position where the telegraph pole is located in the combined binary edge image is removed; a straight line can be defined as:
Figure 753056DEST_PATH_IMAGE006
in the formulak l ，b l Is a constant of a straight line; it can be used at any two points
Figure 522429DEST_PATH_IMAGE007
Figure 168305DEST_PATH_IMAGE008
Expressed as:
Figure 794459DEST_PATH_IMAGE009
Figure 384840DEST_PATH_IMAGE010
applying the formula (6) and the formula (7) to the previous binary edge map, namely determining a straight line by any two white points; for each straight line, calculating the distance between all white points in the binary edge image and the straight line according to the formula (8).
Figure 754641DEST_PATH_IMAGE011
In the formula (I), the compound is shown in the specification,D i is as followsiDot
Figure 707554DEST_PATH_IMAGE012
The distance from the straight line is set to be,counting the parallelogram intervals on both sides of the straight line
Figure 504609DEST_PATH_IMAGE013
The number of the inner white points is the number of the points of any one fitted straight line
Figure 425029DEST_PATH_IMAGE014
Outside the parallelogram interval there are
Figure 598521DEST_PATH_IMAGE015
(ii) a Dot
Figure 671519DEST_PATH_IMAGE014
Within the parallelogram interval sometimes
Figure 983683DEST_PATH_IMAGE016
(ii) a Is provided with
Figure 548657DEST_PATH_IMAGE017
WhereinwAndhwidth and height of the image, respectively; and after all the straight lines are voted, obtaining the straight lines which are 20% of the votes, and deleting points contained in the parallelograms to obtain the binary edge map after the straight lines are deleted.
And step S5, performing circle fitting by using RANSAC to obtain the specific position of the dial.
Specifically, in step S1, the three-channel RGB-format dial plate inspection image is converted into a grayscale image using formula (1):
Figure 853736DEST_PATH_IMAGE018
where Y represents the pixel value in the grayscale map and R, G, B is the value of the three color channels of red, green, and blue of the image.
Specifically, in step S2, the calculation formula of the median filtering window is as follows:
Figure 187766DEST_PATH_IMAGE019
wherein size represents the total number of pixels of the image and the window size is
Figure 172295DEST_PATH_IMAGE020
Mod denotes a modulo operation.
Specifically, in step S5, the calculation formula of the circle is:
Figure 21303DEST_PATH_IMAGE021
in the formula (I), the compound is shown in the specification,
Figure 739860DEST_PATH_IMAGE022
as the coordinate of the center of the circle, r is the radius of the circle.
Randomly selecting three points from white points of the binarized edge map after the straight line is deleted
Figure 318609DEST_PATH_IMAGE023
Using them to define a circle, there are:
Figure 97209DEST_PATH_IMAGE024
Figure 246562DEST_PATH_IMAGE025
Figure 768810DEST_PATH_IMAGE026
if it is
Figure 202065DEST_PATH_IMAGE027
If 0, the fitting is considered to fail, and the next circle is directly fitted, if
Figure 286751DEST_PATH_IMAGE028
If not 0, a circle is obtained:
Figure 409428DEST_PATH_IMAGE029
Figure 572556DEST_PATH_IMAGE030
Figure 817592DEST_PATH_IMAGE031
if 1200 points are taken according to this method, 400 circles can be fitted in the best case. The difference between the distance between the white point and the center of the circle in the image and the radius r of the circle is calculated for each circle using the following formulad i ：
Figure 331750DEST_PATH_IMAGE032
It is known whether the point sought is within the circle, wherein whend i If > 0, then point
Figure 71167DEST_PATH_IMAGE033
Outside the circle, e.g.d i ≤0，Then point is reached
Figure 823223DEST_PATH_IMAGE034
Within a circle; and counting the number of white points falling into the circle of each circle, wherein the circle with the largest number of white points falling into the circle is the position of the dial.
Firstly, performing median filtering on an image and performing edge detection by using a Sobel core; then, integrating edge pixels by combining dial features; finally, a random sample consensus (RANSAC) method is used to remove the straight line and fit the dial; the method has the characteristics of small operation amount, high accuracy and no need of presetting a template.
Drawings
FIG. 1 is a flow chart of the present invention.
Detailed Description
In order to make the technical solutions of the present application better understood by those skilled in the art, the technical solutions in the embodiments of the present application will be clearly, completely and specifically described below.
Referring to fig. 1, a method for identifying a lightweight dial based on RANSAC includes the following steps:
and step S1, converting the dial plate inspection image into a gray scale image. Converting a dial plate inspection image in a three-channel RGB format into a gray scale image by using a formula (1):
Figure 504740DEST_PATH_IMAGE035
wherein Y represents the pixel value in the grayscale map, and R, G, B is the values of the three color channels of red, green, and blue of the image;
and step S2, performing median filtering on the gray level map. Carrying out median filtering on the gray level image to reduce the extracted edge pixel points, wherein a calculation formula of a median filtering window is as follows:
Figure 240614DEST_PATH_IMAGE036
wherein size represents the total number of pixels of the image and the window size is
Figure 705094DEST_PATH_IMAGE037
Mod denotes a modulo operation.
And step S3, performing four convolutions between the four Sobel kernels and the median-filtered gray level image to obtain four binarization edge images, and synthesizing the four binarization edge images into one binarization edge image. Since the classical Canny edge detection algorithm needs to set a binarization threshold, and the edges are refined and connected, two problems are caused: firstly, different threshold parameters need to be proposed for different images, secondly, as few and effective edge information as possible is needed, and edge thinning and connection increase algorithm complexity. Therefore, only the first step of the Canny edge detection algorithm is used, namely four convolutions with the median filtered gray scale map using four Sobel kernels to obtain the gray scale variation of the image in the horizontal and vertical directions
Figure 954066DEST_PATH_IMAGE001
Respectively as follows:
Figure 681851DEST_PATH_IMAGE002
Figure 29655DEST_PATH_IMAGE038
taking the pixel average value for the result of each convolution
Figure 235509DEST_PATH_IMAGE039
And will be greater than
Figure 837522DEST_PATH_IMAGE040
The pixel of (1) is set to be 255, and the rest are 0, so that four binary edge images are obtained; the background in the binary edge image is pure black, lines consisting of white dots formed by dial edges, pointers, dial scales, numbers and telegraph pole edges (or other object edges) are arranged in the binary edge image, and the white dots on the lines have gray level changes due to the use of four Sobel cores for processing.
Analyzing the gray scale change of each point on the dial plate, and then the upper left point of the dial platep 1And the lower right pointp 4Satisfies the following conditions: the product of the respective lateral gray variation and longitudinal gray variation of the dots is greater than 0:
Figure 736208DEST_PATH_IMAGE041
and the upper right pointp 2And the point at the lower leftp 3Satisfies the following conditions: the product of the respective lateral and longitudinal gray scale changes of a dot is less than 0:
Figure 305730DEST_PATH_IMAGE042
in the formula (I), the compound is shown in the specification,S x (p) Is a pointp 1、p 2、p 3Orp 4The lateral gray-scale variation of (a),S y (p) Is a pointp 1、p 2、p 3Orp 4Longitudinal gray scale variation.
Therefore, the previous four binary edge images can be synthesized into one binary edge image according to the characteristic through the above logic; the synthesized binary edge image can remove most noise interference, and only continuous pixels on the dial and the periphery are reserved.
And step S4, removing the straight lines in the binary edge map. Because the dial is generally installed on the telegraph pole, the dial routing inspection image not only comprises the dial but also comprises the telegraph pole, and the straight line edge where the telegraph pole is located in the combined binary edge image is also reserved, because although the algorithm removes the straight lines with deflection angles of 0 and 90 degrees, the rest of the straight lines are not removed. To remove these lines, a RANSAC line fitting method is used. A straight line can be defined as:
Figure 315274DEST_PATH_IMAGE006
in the formulak l ，b l Is a constant of a straight line; it can be used at any two points
Figure 224324DEST_PATH_IMAGE043
Figure 402234DEST_PATH_IMAGE044
Expressed as:
Figure 599997DEST_PATH_IMAGE009
Figure 272287DEST_PATH_IMAGE010
applying the formula (6) and the formula (7) to the previous binary edge map, that is, any two white points (pixel points with the value of 255) can determine a straight line. If 500 white points are randomly chosen, then 250 lines can be fitted. For each straight line, calculating the distance between all white points in the binary edge map and the straight line according to the formula (8).
Figure 239106DEST_PATH_IMAGE011
In the formula (I), the compound is shown in the specification,D i is as followsiDot
Figure 823802DEST_PATH_IMAGE045
The distance between the two parallelograms at the two sides of the straight line can be counted
Figure 508861DEST_PATH_IMAGE046
The number of the inner white points is the number of the points of any one fitted straight line
Figure 984842DEST_PATH_IMAGE047
Outside the parallelogram interval there are
Figure 602905DEST_PATH_IMAGE048
. Dot
Figure 328809DEST_PATH_IMAGE047
Within the parallelogram interval sometimes
Figure 360219DEST_PATH_IMAGE049
. Is provided with
Figure 249677DEST_PATH_IMAGE050
WhereinwAndhrespectively the width and the height of the image. And after all the straight lines are voted, obtaining the straight lines which are 20% of the votes, and deleting points contained in the parallelograms to obtain the binary edge map after the straight lines are deleted.
And step S5, performing circle fitting by using RANSAC to obtain the specific position of the dial.
The formula for the circle is:
Figure 66455DEST_PATH_IMAGE021
in the formula (I), the compound is shown in the specification,
Figure 117587DEST_PATH_IMAGE051
as the coordinate of the center of the circle, r is the radius of the circle.
Randomly selecting three points from white points of the binarized edge map after the straight line is deleted
Figure 636293DEST_PATH_IMAGE052
Using them to define a circle, there are:
Figure 329443DEST_PATH_IMAGE024
Figure 499262DEST_PATH_IMAGE025
Figure 49192DEST_PATH_IMAGE026
if it is
Figure 930560DEST_PATH_IMAGE053
If 0, the fitting is considered to fail, and the next circle is directly fitted, if
Figure 936880DEST_PATH_IMAGE028
If not 0, a circle is obtained:
Figure 736339DEST_PATH_IMAGE029
Figure 105004DEST_PATH_IMAGE030
Figure 999011DEST_PATH_IMAGE031
if 1200 points are taken according to this method, 400 circles can be fitted in the best case. The difference between the distance between the white point and the center of the circle in the image and the radius r of the circle is calculated for each circle using the following formulad i ：
Figure 503941DEST_PATH_IMAGE032
It is known whether the point sought is within the circle, wherein whend i If > 0, then point
Figure 964049DEST_PATH_IMAGE054
Outside the circle, e.g.d i ≤0，Then point is reached
Figure 820009DEST_PATH_IMAGE055
Within a circle; and counting the number of white points falling into the circle of each circle, wherein the circle with the largest number of white points falling into the circle is the position of the dial.
And (3) comparative analysis: the dial plate inspection image collected by the robot is used for carrying out experiments. There are 118 dial patrol images containing dials of different backgrounds, sizes and orientations. The table 1 shows the comparison result of the proposed algorithm with the hough circle and several classical template matching algorithms, the calculation amount is small, the accuracy rate is high, no template needs to be preset, and the method is a light-weight and convenient dial plate identification method.
Figure 517707DEST_PATH_IMAGE056
The foregoing has outlined rather broadly the principles and embodiments of the present invention so that the present disclosure may be better understood with reference to the accompanying drawings, which are included to illustrate and describe the principles and features of the invention.

Claims (4)

1. A RANSAC-based light dial plate identification method is characterized by comprising the following steps:
step S1, converting the dial plate inspection image into a gray scale image;
step S2, median filtering is carried out on the gray level image;
step S3, performing four convolutions by using four Sobel kernels and the gray level image after median filtering to obtain four binary edge images, and synthesizing the four binary edge images into one binary edge image;
performing four convolutions with the median-filtered gray scale map by using four Sobel kernels to obtain the gray scale change of the image in the transverse direction and the longitudinal direction, wherein the four Sobel kernels are respectively:
Figure 143707DEST_PATH_IMAGE001
Figure 431469DEST_PATH_IMAGE002
taking the pixel average value for the result of each convolution
Figure 614189DEST_PATH_IMAGE003
And will be greater than
Figure 862768DEST_PATH_IMAGE004
The pixel of (1) is set to be 255, and the rest are 0, so that four binary edge images are obtained;
analyzing the gray scale change of each point on the dial plate, and then the upper left point of the dial platep 1And the lower right pointp 4Satisfies the following conditions: the product of the respective lateral gray scale variation and the longitudinal gray scale variation of the dots is greater than 0;
and the upper right pointp 2And the point at the lower leftp 3Satisfies the following conditions: the product of the respective lateral gray scale change and the longitudinal gray scale change of the dots is less than 0;
synthesizing the four binary edge images into a binary edge image;
step S4, removing straight lines in the binary edge image;
because the dial is arranged on the telegraph pole, the dial patrol inspection image not only comprises the dial but also comprises the telegraph pole, the straight line edge where the telegraph pole is located in the combined binary edge image is reserved, and the straight line formed by the position where the telegraph pole is located in the combined binary edge image is removed; the straight line is defined as:
Figure 602185DEST_PATH_IMAGE005
in the formulak l ，b l Is a constant of a straight line; using a straight line with two arbitrary points
Figure 619819DEST_PATH_IMAGE006
Figure 301336DEST_PATH_IMAGE007
Expressed as:
Figure 37211DEST_PATH_IMAGE008
Figure 78854DEST_PATH_IMAGE009
applying the formula (6) and the formula (7) to the binary edge map, namely determining a straight line by any two white points; for each straight line, calculating the distance between all white points in the binary edge image and the straight line according to the formula (8):
Figure 950995DEST_PATH_IMAGE010
in the formula (I), the compound is shown in the specification,D i is as followsiDot
Figure 537834DEST_PATH_IMAGE011
The distance between the two parallelograms at the two sides of the straight line is counted
Figure 761005DEST_PATH_IMAGE012
The number of the inner white points is the number of the points of any one fitted straight line
Figure 842225DEST_PATH_IMAGE013
Outside the parallelogram interval there are
Figure 631189DEST_PATH_IMAGE014
(ii) a Dot
Figure 529875DEST_PATH_IMAGE013
Within the parallelogram interval sometimes
Figure 99397DEST_PATH_IMAGE015
(ii) a Is provided with
Figure 843362DEST_PATH_IMAGE016
WhereinwAndhwidth and height of the image, respectively; after all straight lines are voted, straight lines which are 20% of the number of votes are obtained, points contained in a parallelogram of the straight lines are deleted, and a binary edge map after the straight lines are deleted is obtained;
and step S5, performing circle fitting by using RANSAC to obtain the specific position of the dial.
2. The RANSAC-based lightweight dial plate recognition method according to claim 1, wherein the three-channel RGB-format dial plate patrol inspection image is converted into a gray scale image using formula (1) in step S1:
Figure 320787DEST_PATH_IMAGE017
where Y represents the pixel value in the grayscale map and R, G, B is the value of the three color channels of red, green, and blue of the image.
3. The RANSAC-based lightweight dial identification method according to claim 1, wherein in step S2, the gray-scale map is median-filtered to reduce the extracted edge pixels, and the calculation formula of the median-filtered window is as follows:
Figure 124795DEST_PATH_IMAGE018
wherein size represents the total number of pixels of the image and the window size is
Figure 119295DEST_PATH_IMAGE019
Mod denotes a modulo operation.
4. The RANSAC-based lightweight dial identification method according to claim 1, wherein in step S5, the calculation formula of the circle is:
Figure 791585DEST_PATH_IMAGE020
in the formula (I), the compound is shown in the specification,
Figure 758404DEST_PATH_IMAGE021
as the coordinate of the center of the circle, r is the radius of the circle;
randomly selecting three points from white points of the binarized edge map after the straight line is deleted
Figure 874259DEST_PATH_IMAGE022
Using them to define a circle, there are:
Figure 28160DEST_PATH_IMAGE023
Figure 504140DEST_PATH_IMAGE024
Figure 325466DEST_PATH_IMAGE025
if it is
Figure 110757DEST_PATH_IMAGE026
If 0, the fitting is considered to fail, and the next circle is directly fitted, if
Figure 17533DEST_PATH_IMAGE026
If not 0, a circle is obtained:
Figure 703729DEST_PATH_IMAGE027
Figure 769774DEST_PATH_IMAGE028
Figure 352065DEST_PATH_IMAGE029
the difference between the distance between the white point and the center of the circle in the image and the radius r of the circle is calculated for each circle using the following formulad i ：
Figure 621504DEST_PATH_IMAGE030
Determining whether the point is within the circle, e.g.d i If > 0, then point
Figure 314653DEST_PATH_IMAGE031
Outside the circle, e.g.d i ≤0，Then point is reached
Figure 704046DEST_PATH_IMAGE032
Within a circle; and counting the number of white points falling into the circle of each circle, wherein the circle with the largest number of white points falling into the circle is the position of the dial.
CN202210195989.0A 2022-03-02 2022-03-02 RANSAC-based light dial plate identification method Pending CN114332077A (en)

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Application publication date: 20220412