CN107437244B - Visual detection method for dropping volume of medicinal bag - Google Patents
Visual detection method for dropping volume of medicinal bag Download PDFInfo
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- CN107437244B CN107437244B CN201710469241.4A CN201710469241A CN107437244B CN 107437244 B CN107437244 B CN 107437244B CN 201710469241 A CN201710469241 A CN 201710469241A CN 107437244 B CN107437244 B CN 107437244B
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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
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- G06T7/10—Segmentation; Edge detection
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- G06T2207/20—Special algorithmic details
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Abstract
The invention relates to a visual detection method for the dropping volume of a medicinal bag, which comprises the following steps: s1, establishing an actual value of the liquid level height when the standard volume of the medicinal bagged infusion is obtained; s2, detecting an actual value of the liquid level height of the medicinal bagged infusion to be detected in real time on line; s3, comparing the actual value of the liquid level height of the medicinal bag to be detected in the step S2 with the actual value of the liquid level height with the standard volume established in the step S1, calculating the difference between the actual value and the liquid level height, and generating a report; and S4, rejecting unqualified medicinal bagged drops according to the report. The machine vision detection method is used for detecting the liquid level height of the medicinal bagged dropping liquid instead of the traditional human eye observation and weighing mode, so that whether the volume of the medicinal bagged dropping liquid reaches the standard or not is indirectly detected, the direct contact between a human and a medicine is avoided, the human health is facilitated, and the detection accuracy rate is far higher than that of the traditional detection mode.
Description
Technical Field
The invention relates to the technical field of machine vision detection, in particular to a method for visually detecting the volume of a medicinal bagged infusion.
Background
The regulation of medicine and health is the major importance of national development until now, and is related to the livelihood of people. In the field of medicine, the quality detection of medicinal bagged dripping mainly comprises volume detection and chemical component detection. However, the traditional capacity detection is mainly manual, and comprises a mode of observing and weighing by human eyes, and the detection methods have certain disadvantages due to the contact with medicines, so that the detection methods are not good for human health.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provide the visual detection method for the dropping volume of the medicinal bag, which is beneficial to human health and has high detection accuracy.
In order to achieve the purpose, the technical scheme provided by the invention is as follows: which comprises the following steps:
s1, establishing an actual value of the liquid level height when the standard volume of the medicinal bagged infusion is obtained;
s2, detecting an actual value of the liquid level height of the medicinal bagged infusion to be detected in real time on line;
s3, comparing the actual value of the liquid level height of the medicinal bag to be detected in the step S2 with the actual value of the liquid level height with the standard volume established in the step S1, calculating the difference between the actual value and the liquid level height, and generating a report;
and S4, rejecting unqualified medicinal bagged drops according to the report. And indirectly detecting whether the volume of the medicinal infusion in bags to be detected reaches the standard or not by comparing the detected actual value of the height of the liquid level of the medicinal infusion in bags to be detected with the established actual value of the height of the liquid level in bags with the standard volume.
Further, the step S1 is: selecting a plurality of qualified medicinal bagged drops, calculating the liquid level height of the medicinal bagged drops in the standard capacity, then averaging, and taking the interval of plus or minus 0.1 percent of the average value as a standard value for judging whether the medicinal bagged drops are qualified or not.
Further, the step S2 is a specific step of detecting the actual value of the liquid level height of the to-be-detected medical bagged drip in real time on line, and the specific step is as follows:
s21, acquiring an image of a bagged infusion to be detected by an industrial camera;
s22, calculating the pixel sizes of the length and the width of the medicinal bagged infusion in the image;
s23, extracting a liquid level line formed by connecting a plurality of collinear sub-line sections;
s24, calculating the pixel distance (namely the liquid level height) from a liquid level line formed by connecting a plurality of collinear sub-line sections to the lower bottom edge of the minimum circumscribed rectangle;
and S25, converting the pixel size values of the length and the width of the medicinal bagged infusion solution obtained in the step S22 and the pixel distance values obtained in the step S24 into actual values.
Further, the step S22 is specifically configured to calculate the pixel sizes of the length and width of the medicinal pocket drip in the image as follows:
s221, extracting the edge outline of the medicinal plastic bag;
s222, collecting and operating all edge profiles to obtain a closed profile area;
and S223, solving the minimum external rectangle of the closed outline area to obtain the pixel sizes of the length and the width of the medical bagged infusion.
Further, in the step S221, a canny operator is used to extract the edge contour of the pharmaceutical plastic bag.
Furthermore, in step S23, a preprocessing based on the dropping image is required before the extracting line, and the preprocessing includes: and (3) inverting the dropping original pixel, then differentiating the dropping original pixel and the inverted image, and performing local threshold segmentation based on edge detection on the differentiated image.
Furthermore, in the actual image processing, the extracted liquid level line is often divided into sub-line segments with different lengths and different directions instead of being continuous, so that the liquid level line is fitted by adopting a line segment clustering method; the specific steps of extracting the liquid level line formed by connecting a plurality of collinear sub-line segments in the step S23 are as follows:
s231, communicating the sub-line sections;
s232, setting parameters, selecting sub-line segments with proper lengths, and removing the sub-line segments with smaller lengths;
s233, calculating the number and direction angles of the selected sub-line segments;
s234, setting the collinearity, and deleting the sub-line segments which are not on one straight line by using the collinearity measurement;
and S235, connecting the collinear sub-line segments under screening to serve as liquid level lines, and extracting.
Further, the step S24 is to calculate the pixel distance (i.e., the liquid level height) from the liquid level line formed by connecting the plurality of collinear sub-line segments to the bottom edge of the minimum circumscribed rectangle, and includes the following specific steps:
s241, solving a union set of a plurality of collinear sub line segments forming the liquid level line;
s242, selecting and collecting the longest two collinear sub-line sections;
S243. respectively calculating the distances d from the two sub-line segments selected in the step S242 to the lower bottom edge of the minimum external rectangle of the medical plastic bag1And d2Get d1And d2To obtain the desired pixel distance d.
Further, the specific step of converting the pixel value into the actual value in step S25 is as follows:
s251, calibrating a camera to obtain internal parameter, external parameter and distortion coefficient parameters of the camera;
s252, calculating a linear relation between an actual value and a pixel value according to the camera parameters;
and S253, converting the values of the length and the width of the pixels of the medical infusion bag to be detected and the value of the pixel distance from the liquid level line to the lower bottom edge of the minimum circumscribed rectangle into actual values.
Compared with the prior art, the principle and the advantages of the scheme are as follows:
replace traditional people's eye to observe and the liquid level height that the mode detected medicinal infusion in bags with weighing through machine vision detection to indirectly detect out whether up to standard the capacity of medicinal infusion in bags, avoid people direct and medicine contact, do benefit to the health, detect the rate of accuracy moreover and be higher than traditional detection mode far away.
Drawings
FIG. 1 is a flow chart of a method for visually inspecting the drip volume of a medicinal bag according to an embodiment of the present invention;
fig. 2 is a diagram of an experimental effect of a visual detection method for the drop volume of a medicinal bag in an embodiment of the invention.
Detailed Description
The invention will be further illustrated with reference to specific examples:
referring to fig. 1-2, the method for visually inspecting the volume of a drip in a bag for medicine according to the present embodiment includes the following steps:
s1, establishing an actual value of the liquid level height when the standard volume of the medicinal bagged infusion is set:
selecting 1000 qualified medicinal bagged drops, calculating the liquid level height, averaging, and taking the interval of plus or minus 0.1% of the average value as a standard value for judging whether the medicinal bagged drops are qualified.
S2, detecting the actual value of the liquid level height of the medicinal bagged drip to be detected in real time on line, and specifically comprising the following steps:
s21, acquiring an image of a bagged infusion to be detected by an industrial camera;
s22, calculating the pixel sizes of the length and the width of the medicinal bagged infusion in the image:
firstly, extracting the edges of the bagged infusion by using a canny operator, then, collecting and operating all the edge outlines to obtain a closed outline area, then, obtaining a minimum circumscribed rectangle for the closed outline area, obtaining characteristic points of the minimum circumscribed rectangle, namely the upper left corner and the lower right corner, respectively marking as (Row1, Column1) and (Row2, Column2), subtracting two rows to obtain the width of the rectangle, and subtracting two columns to obtain the length of the rectangle, thereby obtaining the size of the pixels of the length and the width of the medicinal bagged infusion.
S23, extracting a liquid level line formed by connecting a plurality of collinear sub-line sections, and comprising the following steps:
s231, communicating the sub-line sections;
s232, setting parameters, selecting sub-line segments with proper lengths, and removing the sub-line segments with smaller lengths;
s233, calculating the number and direction angles of the selected sub-line segments;
s234, setting the collinearity, and deleting the sub-line segments which are not on one straight line by using the collinearity measurement:
the threshold for co-linearity was set to 1. If the direction angle difference of the two sub-line segments exceeds 1 degree, the two sub-line segments are judged not to be on the same straight line, and the two sub-line segments are removed. The collinearity calculation formula is:
wherein f is the average length of the two line segments, c is the distance between the nearest pair of endpoints, a is the included angle between the two line segments, b is the average value of the included angles between the midpoint connecting line of the two line segments and the line segment, and Td,Ta,TbIs a normalized threshold parameter. T can be obtained by multiple experimentsd＝3～5,Ta＝π/36～π/18，TbWhen pi/18-pi/9, the collinear line segment is fittedThe optimal effect is achieved;
and S235, connecting the collinear sub-line segments under screening to serve as liquid level lines, and extracting.
S24, calculating the pixel distance (namely the liquid level height) from the liquid level line formed by connecting a plurality of collinear sub-line sections to the lower bottom edge of the minimum circumscribed rectangle, and comprising the following steps:
s241, solving a union set of a plurality of collinear sub line segments forming the liquid level line;
s242, selecting and collecting the longest two collinear sub-line sections;
s243, respectively calculating the distance d from the two sub-line segments selected in the step S242 to the bottom edge of the minimum external rectangle of the medicinal plastic bag1And d2Get d1And d2To obtain the required pixel distance d, the formula is:
s25, converting the values of the length and width pixel sizes of the medicinal bagged infusion solution obtained in the step S22 and the values of the pixel distance obtained in the step S24 into actual values:
s251, calibrating the camera to obtain parameters (f) of internal parameter, external parameter and distortion coefficient of the camerax，fy，u0，v0)；
Wherein (x, y) is a two-dimensional coordinate in the image coordinate system, (x)c，yc，zc) Coordinates of a camera three-dimensional coordinate system taking a camera projection center as an origin;
s252, calculating a linear relation between the actual value and the pixel value according to the camera parameters:
wherein, (u, v) are world coordinates;
s253, combining the values of the length l and the width w of the pixels of the medical infusion bag to be detected and the value of the pixel distance d from the liquid level line to the lower bottom edge of the minimum external rectangle, converting the pixel value into an actual value:
wherein, L, W and D are the values of physical actual size, length, width and liquid level line height of the corresponding drop respectively.
S3, comparing the actual value of the liquid level height of the medicinal bag to be detected in the step S2 with the actual value of the liquid level height with the standard volume established in the step S1, calculating the difference between the actual value and the liquid level height, and generating a report.
S4, rejecting unqualified medicinal bagged drops:
the detected actual value of the liquid level height of the medicinal bagged dropping to be detected is compared with the established actual value of the liquid level height in the standard capacity, whether the capacity of the medicinal bagged dropping to be detected reaches the standard or not is indirectly detected, and unqualified medicinal bagged dropping is removed according to a report.
Replace traditional people's eye to observe and the liquid level height that the mode detected medicinal infusion in bags with weighing through machine vision detection to indirectly detect out whether up to standard the capacity of medicinal infusion in bags, avoid people direct and medicine contact, do benefit to the health, detect the rate of accuracy moreover and be higher than traditional detection mode far away.
The above-mentioned embodiments are merely preferred embodiments of the present invention, and the scope of the present invention is not limited thereto, so that variations based on the shape and principle of the present invention should be covered within the scope of the present invention.
Claims (7)
1. A visual detection method for the dropping volume of a medicinal bag is characterized in that: the method comprises the following steps:
s1, establishing an actual value of the liquid level height when the standard volume of the medicinal bagged infusion is obtained;
s2, detecting an actual value of the liquid level height of the medicinal bagged infusion to be detected in real time on line;
s3, comparing the actual value of the liquid level height of the medicinal bag to be detected in the step S2 with the actual value of the liquid level height with the standard volume established in the step S1, calculating the difference between the actual value and the liquid level height, and generating a report;
s4, rejecting unqualified medicinal bagged drops according to the report;
the step S2 is used for detecting the actual value of the liquid level height of the bagged infusion to be detected in real time on line, and comprises the following specific steps:
s21, acquiring an image of a bagged infusion to be detected by an industrial camera;
s22, calculating the pixel sizes of the length and the width of the medicinal bagged infusion in the image;
s23, extracting a liquid level line formed by connecting a plurality of collinear sub-line sections;
s24, calculating the pixel distance from a liquid level line formed by connecting a plurality of collinear sub-line segments to the lower bottom edge of the minimum circumscribed rectangle;
s25, converting the pixel size values of the length and the width of the medicinal bagged infusion solution obtained in the step S22 and the pixel distance values obtained in the step S24 into actual values;
the specific steps of extracting the liquid level line formed by connecting a plurality of collinear sub-line segments in the step S23 are as follows:
s231, communicating the sub-line sections;
s232, setting parameters, selecting sub-line segments with proper lengths, and removing the sub-line segments with smaller lengths;
s233, calculating the number and direction angles of the selected sub-line segments;
s234, setting the collinearity, and deleting the sub-line segments which are not on one straight line by using the collinearity measurement:
setting a threshold value of the co-linearity as 1 degree; if the direction angle difference of the two sub-line segments exceeds 1 degree, judging that the two sub-line segments are not on the same straight line, and rejecting; the collinearity calculation formula is:
wherein f is the average length of the two line segments, c is the distance between the nearest pair of endpoints, a is the included angle between the two line segments, b is the average value of the included angles between the midpoint connecting line of the two line segments and the line segment, and Td,Ta,TbIs a normalized threshold parameter;
and S235, connecting the collinear sub-line segments under screening to serve as liquid level lines, and extracting.
2. A method of visually inspecting the volume of a drop of a pharmaceutical bag according to claim 1, wherein: the step of step S1 is: selecting a plurality of qualified medicinal bagged drops, calculating the liquid level height of the medicinal bagged drops in the standard capacity, then averaging, and taking the interval of plus or minus 0.1 percent of the average value as a standard value for judging whether the medicinal bagged drops are qualified or not.
3. A method of visually inspecting the volume of a drop of a pharmaceutical bag according to claim 1, wherein: the specific steps of calculating the pixel sizes of the length and width of the medicinal bagged drops in the image in the step S22 are as follows:
s221, extracting the edge outline of the medicinal plastic bag;
s222, collecting and operating all edge profiles to obtain a closed profile area;
and S223, solving the minimum external rectangle of the closed outline area to obtain the pixel sizes of the length and the width of the medical bagged infusion.
4. A method of visually inspecting the volume of a drop of a pharmaceutical bag according to claim 3, wherein: and step S221, extracting the edge contour of the medicinal plastic bag by using a canny operator.
5. A method of visually inspecting the volume of a drop of a pharmaceutical bag according to claim 1, wherein: in step S23, a preprocessing based on the dropping image is required before the extracting solution line, and the preprocessing includes: and (3) inverting the dropping original pixel, then differentiating the dropping original pixel and the inverted image, and performing local threshold segmentation based on edge detection on the differentiated image.
6. A method of visually inspecting the volume of a drop of a pharmaceutical bag according to claim 1, wherein: the step S24 is to calculate the pixel distance from the liquid level line formed by connecting a plurality of collinear sub-line segments to the lower bottom edge of the minimum circumscribed rectangle, and the specific steps are as follows:
s241, solving a union set of a plurality of collinear sub line segments forming the liquid level line;
s242, selecting and collecting the longest two collinear sub-line sections;
s243, respectively calculating the distance d from the two sub-line segments selected in the step S242 to the bottom edge of the minimum external rectangle of the medicinal plastic bag1And d2Get d1And d2To obtain the desired pixel distance d.
7. A method of visually inspecting the volume of a drop of a pharmaceutical bag according to claim 1, wherein: the specific steps of converting the pixel value into the actual value in step S25 are as follows:
s251, calibrating a camera to obtain internal parameter, external parameter and distortion coefficient parameters of the camera;
s252, calculating a linear relation between an actual value and a pixel value according to the camera parameters;
and S253, converting the values of the length and the width of the pixels of the medical infusion bag to be detected and the value of the pixel distance from the liquid level line to the lower bottom edge of the minimum circumscribed rectangle into actual values.
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| CN114067102B (en) * | 2021-11-17 | 2023-04-07 | 中国矿业大学 | Liquid level detection control method in mechanical arm liquid pouring task based on target detection |
| CN115457067B (en) * | 2022-11-09 | 2023-04-07 | 乐比(广州)健康产业有限公司 | Nose-clearing and refreshing medicine liquid level detection method |
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