CN110866903B - Ping-pong ball identification method based on Hough circle transformation technology - Google Patents
Ping-pong ball identification method based on Hough circle transformation technology Download PDFInfo
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0004—Industrial image inspection
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/40—Extraction of image or video features
- G06V10/44—Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components
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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20048—Transform domain processing
- G06T2207/20061—Hough transform
Abstract
The invention discloses a ping-pong ball identification method based on Hough circle transformation technology, which improves identification speed by a gradient Hough transformation method. The method comprises the following steps of 1) carrying out image graying treatment; 2) filtering; 3) extracting edges; 4) marking table tennis balls; 5) special treatment of table tennis identification and setting of relevant parameters. Compared with the prior art, the method and the device can realize real-time identification of the table tennis balls contained in each frame of picture for the pictures read in the camera, and can accurately identify the table tennis balls under complex conditions.
Description
Technical Field
The invention belongs to the technical field of robots, and particularly relates to a table tennis identification method through Hough circle transformation technology.
Background
In order to cooperate with a table tennis ball picking robot to work and realize the function of automatically identifying the table tennis balls by the table tennis ball picking robot, the design of a method capable of identifying and tracking the table tennis balls in continuous images is particularly important. Currently, most algorithms for identifying table tennis are left for a given picture from which table tennis can be marked. The method is easy to be interfered by sundries in the table tennis court with complex background, and the accuracy of identifying the table tennis cannot be ensured under the condition that the picture is slightly torn and noisy.
Aiming at the problems, the invention provides a ping-pong ball identification method based on Hough circle transformation technology, which can be matched with a ping-pong ball picking robot to realize real-time identification of ping-pong balls for videos. The algorithm can eliminate the interference of foreign matters in the table tennis court with a complex background, and still ensure the accuracy of identifying the table tennis balls under the condition that the picture is slightly torn and noisy.
The principle of circle recognition by the Hough transform method is as follows:
assuming that the image acquired by the vision sensor with resolution M x N is f (x, y), the general equation of the circle can be formulated as
(x-a)2+(y-b)2＝r2
Where (a, b) is the center of the circle and r is the radius of the circle. The classical Hough transform converts a circle on an X-Y plane into an a-b-r parameter space, so that all three-dimensional conical surfaces corresponding to points on the same circle in the image space are necessarily intersected at one point in the parameter space, and then whether the result is a circle or not can be judged by voting for the point.
The method has high reliability and is less influenced by noise, deformation and curve discontinuity, but has obvious defects: the occupied memory is large, and the calculated amount is large, so that the real-time circle detection is difficult to meet. Meanwhile, the invention is applied to a mobile robot platform, is limited by hardware conditions and has higher requirement on real-time detection, so the embodiment adopts a gradient Hough transformation method to improve the identification speed.
Disclosure of Invention
In order to realize the function of automatically identifying the table tennis detected by the camera of the table tennis picking robot, the invention provides a table tennis identification method based on the Hough circle transformation technology, and the table tennis which is in the visual field of the camera and meets the constraint condition can be marked on the picture to realize the function of identifying the table tennis.
A ping-pong ball identification method based on the Hough circle transformation technology adopts a gradient Hough transformation method to improve the identification speed. In polar equation
A＝x-r cosθ,B＝y-r sinθ (1)
And representing a circle, wherein x and y are coordinates of a current pixel point, r is a radius, theta is a gradient direction angle, and A and B are possible center coordinates obtained through calculation.
The ping-pong ball identification method based on the Hough transformation technology comprises the following steps:
step 1, image graying treatment
The processor of the robot can continuously obtain images in front through the vision sensor and then preprocess the read-in pictures. And carrying out graying processing on the image by adopting an average value method. Assuming that the three components of the color image are R (x, y), G (x, y), and B (x, y), respectively, after the graying process, the grayscale value Gray (x, y) of the image can be expressed as:
step 2, filtering processing
After graying processing, filtering processing is carried out on the image to inhibit noise, reduce environmental interference and improve the edge definition of the target table tennis. The invention adopts a median filtering mode to sort the data in the template from small to large, and takes the data arranged at the middle position as the final processing result. The median filtered output is:
g(x,y)＝Med{f(x-k,y-l),(k,l)∈W} (3)
where f (x, y) and g (x, y) are the original image and the processed image, respectively, and W is a two-dimensional sliding window, and is generally selected from 3 × 3 and 5 × 5.
Step 3. edge extraction
The invention adopts a gradient Hough transformation-based method to find the circle center, and then realizes the extraction of the edge of the table tennis through a Canny algorithm. The step of searching the coordinates of the circle center by gradient Hough transformation comprises the following steps:
3.1 Using gradient formula
And calculating the gradient value of the original image and binarizing the image.
3.2, solving the gradient direction angle theta of the pixel point with the gradient value not being 0 in the image, and then solving the coordinate of the pixel point which is possibly taken as the center of a circle by using the formula (1).
And 3.3, traversing all pixel points with gradient values not being 0 in the image, solving all points which can be the circle center according to the mode of the step 3.2, and voting each point.
3.4 after the whole image is scanned, the point with the highest ticket is the center of the circle to be detected.
Step 4. Table tennis ball marking
For a certain frame of image in which the ping-pong ball is detected, the coordinates and the radius of each circle in the image are marked on the image by taking the upper left corner of the image as an origin and taking each pixel as a unit length. And screening out the table tennis ball closest to the robot according to the physical rules of the near distance and the far distance, and transmitting the x and y coordinates and the radius of the table tennis ball to a processor for collection operation.
Step 5, special treatment of table tennis identification and setting of relevant parameters
5.1 Table tennis ball shielding condition processing method
In practical situations, a plurality of table tennis balls may be shielded from each other, too far away from or too close to the robot, and the like. Therefore, after Hough transformation, parameters such as the minimum distance between two circle centers, the judgment threshold of whether the accumulation plane is a circle, the maximum value and the minimum value of the detected radius of the circle and the like need to be set.
When parameters are adjusted, a black rubber field of 2m by 2m is selected; the width of the ball picking device inlet is 15cm, the maximum resolution of the visual sensor is 640 x 480, the irradiation range is 70 degrees, the irradiation length is 50cm, the range of the distance for identifying the table tennis is 20cm-70cm. in front of the robot, the maximum radius of the table tennis which can be identified is 80 pixels, and the minimum radius of the table tennis is 15 pixels. Since the collection success rate is not high when the ping-pong ball is too far from the robot, in this example, the maximum pixel value and the minimum pixel value of the radius of the detected circle are set to 80 and 30. The place used during the test of this example is black pure color rubber pad, and the reflection of light condition is not serious, and non-table tennis object is not big to detection efficiency's influence, so the accumulation plane is set up to 1 respectively to the decision threshold value whether be the circle, is in a more conventional moderate state. If two table tennis balls are overlapped too much, the situation that the captured table tennis balls cannot be identified by the camera can occur, and under the condition, the radius of the table tennis balls is usually 80 pixels, so that the minimum distance between two circle centers is set to be 120 pixels, the identification effect is not influenced, and the table tennis ball overlapping situation can be well limited.
5.2 parameter setting in operation of table tennis ball picking robot
In order to better match the ball picking device to finish the ball picking action and improve the ball picking efficiency, the position of the table tennis ball entering the ball picking device is required to be as central as possible on the basis, so as to avoid the situation that the table tennis ball is pushed away from the robot due to touching the left edge and the right edge of the ball picking device, which leads to the incapability of picking the table tennis ball. In the example, the entrance of the ball picking device is 15cm, the pixel of the camera is 640 x 480, the irradiation range is 70 degrees, and the irradiation range is larger than the entrance range of the ball picking device; the ball picking range is 20cm to 70cm in front of the robot, the picture irradiated by the real straight line in the camera is trapezoidal, and in order to enable the table tennis ball which is 70cm farthest to be successfully collected, after a plurality of experiments, the collection is finally determined to be carried out when the center of the table tennis ball is positioned between 160 pixels and 480 pixels on the x axis. If the table tennis balls are identified outside the collectable range, the robot is driven to perform corresponding posture adjustment, so that the centers of the table tennis balls enter the collectable range and are collected.
5.3 Table tennis identification optimization
In order to ensure the accuracy of detecting the table tennis ball in a complex environment, the picture can be selectively further processed to eliminate the influence caused by the background, such as corrosion, expansion and the like.
The erosion and expansion operations performed on the gray scale map can be expressed by the following equations (4) and (5), respectively:
fob＝min{fx-b(x),x∈D(b)} (4)
fgb＝max{fx+b(x),x∈D(b)} (5)
wherein D (b) the template region of the structural element b.
The purpose of improving the accuracy rate of identifying the table tennis is realized by using opening and closing operations. The operation is a process of corroding and expanding the image, and can be used for eliminating small black points, separating objects at fine points and smoothing the boundary of a larger object without obviously changing the area of the object; the process of expanding and corroding the image by closed operation can be used for eliminating small black holes.
Drawings
FIG. 1 is a flow chart of the method of the present invention
FIG. 2 is a table tennis gray scale diagram
FIG. 3 is a diagram of median filtering after the ping-pong ball is processed by the median filtering
FIG. 4 is a diagram of the edge extraction result of the Canny algorithm
FIG. 5 is a diagram of the effect of modifying the dual threshold
FIG. 6 is an illustration of table tennis ball marking
FIG. 7 shows the result of detection without using the opening/closing operation
FIG. 8 shows the result of detection after the opening/closing operation is used
Detailed Description
A flowchart of a table tennis recognition method based on the Hough transform technology, which is specifically implemented is shown in fig. 1. The method comprises the following steps:
step 1, image graying treatment
In an example of the present invention, the resolution of the vision sensor is 640 x 480 pixels. Through the vision sensor, the processor of the robot can continuously obtain an image in front of the vision sensor, and then preprocess the read-in picture. Firstly, carrying out graying processing on the picture, wherein the graying is carried out by adopting an average value method. Assuming that the three components of the color image are R (x, y), G (x, y), and B (x, y), respectively, after the graying process, the grayscale value Gray (x, y) of the image can be expressed as:
the principle is that the three-component brightness in the color image is averaged to obtain the gray value, that is, in the RGB model, the average value of R, G, B three color values of a pixel point is calculated, and the gray value of the pixel point is represented by the value, so that the color image is converted into a gray image, and a certain amount of calculation is reduced.
Reading an original image of RGB three-color components of a table tennis ball, wherein the color of each pixel point is represented by three values of R (x, y), G (x, y) and B (x, y). The image is grayed to obtain the image 2, and at the moment, the color of each pixel point is only represented by one value Gray (x, y), so that the operation amount of image processing can be reduced.
Step 2, filtering processing
After the graying processing, the light interference in the actual scene is considered, and noise is brought in the processes of shooting, image compression and transmission by the visual sensor, so that the image needs to be filtered, and the purpose is to suppress the noise, reduce the environmental interference and improve the edge definition of the target table tennis ball. The invention adopts a median filtering mode to sort the data in the template from small to large, and takes the data arranged in the middle position as the final processing result. The median filtered output is:
g(x,y)＝Med{f(x-k,y-l),(k,l)∈W} (3)
where f (x, y) and g (x, y) are the original image and the processed image, respectively, W is a two-dimensional sliding window, and is generally selected from 3 × 3 and 5 × 5, and in this example, the sliding window of 3 × 3 is selected for filtering. As can be seen from fig. 3, after the median filtering process, the noise on the image is much less, and the image is much smoother, which is convenient for the next processing.
Step 3. edge extraction
The table tennis ball in the figure can be subjected to edge extraction. In the embodiment of the invention, a gradient Hough transformation-based method is adopted to find the circle center, and the extraction of the table tennis edge is realized through a Canny algorithm. The idea of finding the coordinates of the circle center by gradient Hough transformation is as follows:
3.1 Using gradient formula
And calculating the gradient value of the original image and binarizing the image.
3.2, solving the gradient direction angle theta of the pixel point with the gradient value not being 0 in the image, and then solving the coordinate of the pixel point which is possibly taken as the center of a circle by using the formula (1).
3.3 traversing all pixel points with gradient values not being 0 in the image, solving all points which can be the circle center according to the mode of the step 3.2, and voting each point.
3.4 after the whole image is scanned, the point with the highest ticket is the center of the circle to be detected.
As can be seen from fig. 4, after the edge extraction processing is performed by the gradient Hough transform method and the Canny algorithm, the rough contour of the ping-pong ball has been extracted, but the problem of fuzzy and discontinuous boundary also exists. In this example, after a plurality of tests, the high and low dual thresholds in the Canny algorithm are finally set to 100 and 30 respectively, the edge extraction effect is greatly improved as shown in fig. 5.
Step 4. Table tennis ball marking
And when a certain frame image of the ping-pong ball is detected, marking the coordinates and the radius of each circle in the image on the image by taking the upper left corner of the image as an origin and each pixel as a unit length. And finally, screening out the table tennis ball closest to the robot according to the physical rules of the near distance and the far distance, and transmitting the x and y coordinates and the radius of the table tennis ball to a processor for collection operation.
An example of marking a table tennis ball is given in fig. 6. In the figure, the table tennis ball is circled by a circle, and the number on the table tennis ball represents the radius of the table tennis ball. The distance between the table tennis ball at the upper left side and the camera is far, so the radius value is smaller than the table tennis ball at the lower right side, and in actual conditions, the distance between the table tennis ball at the lower right side and the camera is close, and the robot can judge that the table tennis ball is preferentially collected.
Step 5, special treatment of table tennis identification and setting of relevant parameters
5.1 Table tennis ball shielding condition processing method
In practical situations, a plurality of table tennis balls may be shielded from each other, too far away from or too close to the robot, and the like. Therefore, after Hough transformation, parameters such as the minimum distance between two circle centers, the judgment threshold of whether the accumulation plane is a circle, the maximum value and the minimum value of the detected radius of the circle and the like need to be set.
When parameters are adjusted, a black rubber field of 2m by 2m is selected; the width of the ball picking device inlet is 15cm, the maximum resolution of the visual sensor is 640 x 480, the irradiation range is 70 degrees, the irradiation length is 50cm, the range of the distance for identifying the table tennis is 20cm-70cm. in front of the robot, the maximum radius of the table tennis which can be identified is 80 pixels, and the minimum radius of the table tennis is 15 pixels. Since the collection success rate is not high when the ping-pong ball is too far from the robot, in this example, the maximum pixel value and the minimum pixel value of the radius of the detected circle are set to 80 and 30. The place used during the test of this example is black pure color rubber pad, and the reflection of light condition is not serious, and non-table tennis object is not big to detection efficiency's influence, so the accumulation plane is set up to 1 respectively to the decision threshold value whether be the circle, is in a more conventional moderate state. If two table tennis balls are overlapped too much, the situation that the captured table tennis balls cannot be identified by the camera can occur, and under the condition, the radius of the table tennis balls is usually 80 pixels, so that the minimum distance between two circle centers is set to be 120 pixels, the identification effect is not influenced, and the table tennis ball overlapping situation can be well limited.
5.2 parameter setting in operation of table tennis ball picking robot
In order to better match the ball picking device to finish the ball picking action and improve the ball picking efficiency, the position of the table tennis ball entering the ball picking device is required to be as central as possible on the basis, so as to avoid the situation that the table tennis ball is pushed away from the robot due to touching the left edge and the right edge of the ball picking device, which leads to the incapability of picking the table tennis ball. In the example, the entrance of the ball picking device is 15cm, the pixel of the camera is 640 x 480, the irradiation range is 70 degrees, and the irradiation range is larger than the entrance range of the ball picking device; the ball picking range is 20cm to 70cm in front of the robot, the picture irradiated by the real straight line in the camera is trapezoidal, and in order to enable the table tennis ball which is 70cm farthest to be successfully collected, after a plurality of experiments, the collection is finally determined to be carried out when the center of the table tennis ball is positioned between 160 pixels and 480 pixels on the x axis. If the table tennis balls are identified outside the collectable range, the robot is driven to perform corresponding posture adjustment, so that the centers of the table tennis balls enter the collectable range and are collected.
5.3 Table tennis identification optimization
In order to ensure the accuracy of detecting the table tennis ball in a complex environment, the picture can be selectively further processed to eliminate the influence caused by the background, such as corrosion, expansion and the like.
The erosion and expansion operations performed on the gray scale map can be expressed by the following equations (4) and (5), respectively:
fob＝min{fx-b(x),x∈D(b)} (4)
fgb＝max{fx+b(x),x∈D(b)} (5)
wherein D (b) the template region of the structural element b.
In this embodiment, the pen user can open and close the pen to achieve the purpose of improving the accuracy of identifying the table tennis. The operation is a process of corroding and expanding the image, and can be used for eliminating small black points, separating objects at fine points and smoothing the boundary of a larger object without obviously changing the area of the object; the process of expanding and corroding the image by closed operation can be used for eliminating small black holes.
Fig. 7 shows the recognition case without using the opening and closing operation. It can be seen that although the ping-pong ball can be identified in a complex environment by the Hough transformation method, many misjudgments also occur at the same time.
Fig. 8 shows the recognition effect after using the open and close operation. It can be seen that all misjudgments are eliminated and the table tennis ball can be still stably recognized, compared to fig. 8. Therefore, when the working environment of the robot is complex, the embodiment eliminates the influence of the complex background on the identification of the table tennis by adding opening and closing operations.
Claims (3)
1. The ping-pong ball identification method based on the Hough circle transformation technology is characterized in that: a gradient Hough transformation method is adopted to improve the identification speed; in polar equation
A＝x-rcosθ,B＝y-rsinθ (1)
Representing a circle, wherein x and y are coordinates of a current pixel point, r is a radius, theta is a gradient direction angle, and A and B are possible coordinates of a circle center obtained through calculation;
the method comprises the following steps:
step 1, image graying treatment
The processor of the robot can continuously obtain images in front through the vision sensor and then preprocess the read-in pictures; performing graying processing on the image by using an average value method, and after graying processing is performed on three components of the color image, namely R (x, y), G (x, y) and B (x, y), the Gray value Gray (x, y) of the image can be represented as follows:
step 2, filtering processing
After graying processing, filtering the image to inhibit noise, reduce environmental interference and improve the edge definition of the target table tennis ball; the invention adopts a median filtering mode to sort the data in the template from small to large, and takes the data arranged at the middle position as the final processing result; the median filtered output is:
g(x,y)＝Med{f(x-k,y-l),(k,l)∈W} (3)
wherein f (x, y) and g (x, y) are respectively an original image and a processed image, and W is a two-dimensional sliding window and is generally selected from 3 × 3 and 5 × 5;
step 3. edge extraction
The invention adopts a method based on gradient Hough transformation to find the circle center, and then extracts the edge of the table tennis through a Canny algorithm; the step of searching the coordinates of the circle center by gradient Hough transformation comprises the following steps:
3.1 Using gradient formula
Calculating the gradient value of the original image, and binarizing the image;
3.2 solving the gradient direction angle theta of a pixel point with gradient value not being 0 in the image, and then solving the coordinate of the pixel point which is possibly as the center of a circle by using the formula (1);
3.3, traversing all pixel points with gradient values not being 0 in the image, solving all points which can be the circle center according to the mode of the step 3.2, and voting each point;
3.4 after the whole image is scanned, the point with the highest ticket is the center of the circle to be detected;
step 4. Table tennis ball marking
For a certain frame of image with the detected ping-pong balls, marking the coordinates and the radius of each circle in the image on the image by taking the upper left corner of the image as an origin and each pixel as a unit length; screening out the table tennis ball closest to the robot according to the physical rules of big and small, transmitting the x and y coordinates and the radius of the table tennis ball to a processor, and performing collection operation;
step 5, special treatment of table tennis identification and setting of relevant parameters
5.1 Table tennis ball shielding condition processing method
After Hough transformation is carried out, the minimum distance between two circle centers, a judgment threshold value of whether an accumulation plane is a circle or not, and the maximum value and the minimum value of the radius of the detected circle need to be set;
5.2 parameter setting in operation of table tennis ball picking robot
In the example, the entrance of the ball picking device is 15cm, the pixel of the camera is 640 x 480, the irradiation range is 70 degrees, and the irradiation range is larger than the entrance range of the ball picking device; the ball picking range is 20cm to 70cm in front of the robot, the picture irradiated by the real straight line in the camera is trapezoidal, and in order to enable the table tennis ball which is 70cm farthest to be successfully collected, after a plurality of experiments, the collection is finally determined to be carried out when the circle center of the table tennis ball is positioned between 160 pixels and 480 pixels on the x axis; if the table tennis ball is identified outside the collectable range, driving the robot to perform corresponding posture adjustment, so that the center of the table tennis ball enters the collectable range and is collected;
5.3 Table tennis identification optimization
Selectively carrying out corrosion and expansion operations on the picture to eliminate the influence caused by the background;
the erosion and expansion operations performed on the gray scale map can be expressed by the following equations (4) and (5), respectively:
wherein, D (b) the template region of the structural element b;
the purpose of improving the accuracy rate of identifying the table tennis is realized by using opening and closing operations; the operation is a process of firstly corroding and then expanding the image, and is used for eliminating small black points, separating objects at fine points and smoothing the boundary of a larger object without obviously changing the area of the object; the closed operation is used for eliminating small black holes in the process of expanding the image firstly and then corroding the image.
2. The ping-pong ball identification method based on the Hough circle transformation technology as claimed in claim 1, wherein: in the step 5.1, a black rubber field of 2m by 2m is selected when parameters are adjusted; the width of the ball picking device inlet is 15cm, the maximum resolution of the visual sensor is 640 x 480, the irradiation width is 70 degrees, the irradiation length is 50cm, the distance range for identifying the table tennis is 20cm-70cm. in front of the robot, the maximum radius of the table tennis which can be identified is 80 pixels, and the minimum radius of the table tennis is 15 pixels; setting maximum and minimum pixel values of the radius of the detected circle to 80 and 30; the judgment threshold values of whether the accumulation plane is round or not are respectively set to be 1, and the accumulation plane is in a more conventional moderate state; when two table tennis balls are overlapped too much and the captured table tennis balls cannot be identified by the camera, the minimum distance between two circle centers is set to be 120 pixels according to the radius of the table tennis balls which is usually 80 pixels.
3. The ping-pong ball identification method based on the Hough circle transformation technology as claimed in claim 1, wherein: in the step 5.2, the position of the table tennis ball entering the ball picking device is as central as possible, so that the situation that the table tennis ball cannot be picked due to being pushed away from the robot when touching the left edge and the right edge of the ball picking device is avoided, the ball picking action is better finished, and the ball picking efficiency is improved; the entrance of the ball picking device is 15cm, the pixel of the camera is 640 x 480, the irradiation range is 70 degrees, and the irradiation range is larger than the entrance range of the ball picking device; the ball picking range is 20cm to 70cm in front of the robot, the picture irradiated by the real straight line in the camera is trapezoidal, and the center of a table tennis ball is collected when the center of the table tennis ball is positioned between 160 pixels and 480 pixels on the x axis, so that the table tennis ball at the farthest position of 70cm can be successfully collected; if the table tennis balls are identified outside the collectable range, the robot is driven to perform corresponding posture adjustment, so that the centers of the table tennis balls enter the collectable range and are collected.
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| CN106600580B (en) * | 2016-11-30 | 2020-01-21 | 浙江大学 | Hough transform-based power line anomaly identification method and system |
| CN108921176B (en) * | 2018-06-22 | 2020-07-10 | 河海大学常州校区 | Pointer instrument positioning and identifying method based on machine vision |
| CN109035258B (en) * | 2018-07-20 | 2021-08-13 | 北京工业大学 | Image segmentation method based on directed cross genetic algorithm and two-dimensional maximum entropy threshold segmentation algorithm |
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