CN111175300A - Real-time observation system for drug resistance generation of bacteria - Google Patents
Real-time observation system for drug resistance generation of bacteria Download PDFInfo
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- CN111175300A CN111175300A CN202010077544.3A CN202010077544A CN111175300A CN 111175300 A CN111175300 A CN 111175300A CN 202010077544 A CN202010077544 A CN 202010077544A CN 111175300 A CN111175300 A CN 111175300A
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- 206010059866 Drug resistance Diseases 0.000 title claims abstract description 31
- 241000894006 Bacteria Species 0.000 title claims abstract description 26
- 238000001514 detection method Methods 0.000 claims abstract description 40
- 239000001963 growth medium Substances 0.000 claims abstract description 40
- 230000001580 bacterial effect Effects 0.000 claims abstract description 22
- 238000004458 analytical method Methods 0.000 claims abstract description 21
- 230000003115 biocidal effect Effects 0.000 claims abstract description 15
- 239000003242 anti bacterial agent Substances 0.000 claims abstract description 10
- 229940088710 antibiotic agent Drugs 0.000 claims abstract description 10
- 230000003068 static effect Effects 0.000 claims description 5
- 241001270131 Agaricus moelleri Species 0.000 claims description 3
- UJKWLAZYSLJTKA-UHFFFAOYSA-N edma Chemical compound O1CCOC2=CC(CC(C)NC)=CC=C21 UJKWLAZYSLJTKA-UHFFFAOYSA-N 0.000 claims description 3
- 238000003672 processing method Methods 0.000 claims description 3
- 238000000034 method Methods 0.000 abstract description 12
- 230000008569 process Effects 0.000 abstract description 9
- 239000011159 matrix material Substances 0.000 description 14
- 238000000605 extraction Methods 0.000 description 6
- 230000008859 change Effects 0.000 description 2
- 230000009467 reduction Effects 0.000 description 2
- 230000011218 segmentation Effects 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 230000009193 crawling Effects 0.000 description 1
- 238000012258 culturing Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 229940079593 drug Drugs 0.000 description 1
- 239000003814 drug Substances 0.000 description 1
- 230000008030 elimination Effects 0.000 description 1
- 238000003379 elimination reaction Methods 0.000 description 1
- 230000002708 enhancing effect Effects 0.000 description 1
- 238000007689 inspection Methods 0.000 description 1
- 230000008439 repair process Effects 0.000 description 1
- 230000035945 sensitivity Effects 0.000 description 1
- 230000000087 stabilizing effect Effects 0.000 description 1
- 230000001629 suppression Effects 0.000 description 1
- 229940043263 traditional drug Drugs 0.000 description 1
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- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/84—Systems specially adapted for particular applications
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Abstract
The invention relates to the technical field of bacteria detection, in particular to a real-time observation system for bacterial drug resistance generation. The culture medium mold comprises a culture medium mold, a detection camera and an analysis computer, wherein a culture tank is arranged at the top of the culture medium mold, position identification grooves are formed in the outer wall of one side of the culture medium mold at equal intervals corresponding to the culture tank, and concentration identification grooves are formed in the outer wall of the other side of the culture medium mold at equal intervals corresponding to the culture tank. In the real-time observation system for the generation of the bacterial drug resistance, the culture tanks are arranged on the culture medium mold, the antibiotic concentration in the culture tanks is distributed in a gradient manner, the adaptability of bacteria to antibiotics can be embodied, the process of the generation of the actual drug resistance of the bacteria can be effectively observed, the growth conditions of the bacteria in the antibiotic culture media with different concentrations can be photographed and recorded in real time by adopting the detection camera, the process of the generation of the bacterial drug resistance can be recorded, and the process of the generation of the bacterial drug resistance can be visually observed and recorded.
Description
Technical Field
The invention relates to the technical field of bacteria detection, in particular to a real-time observation system for bacterial drug resistance generation.
Background
The traditional drug resistance detection means is to inoculate the same strain of bacteria in different culture media (different antibiotic concentrations), after culturing for a certain time, judge the drug resistance of the bacteria to a certain antibiotic by an endpoint observation method, ignore the adaptability of the bacteria to the antibiotic and cannot effectively observe the process of the actual drug resistance of the bacteria.
Disclosure of Invention
The present invention aims to provide a real-time observation system for the generation of bacterial drug resistance, so as to solve the problems in the background art. According to the invention, the bacterial strain is inoculated in the antibiotic culture medium with the lowest concentration gradient, and as time goes on, bacteria capable of resisting high-concentration antibiotic begin to grow in the antibiotic culture medium with high gradient concentration, and the drug-resistant bacterial strain is induced and screened to grow, so that the phenomenon of bacteria crawling can occur.
In order to achieve the above object, the present invention provides a real-time observation system for bacterial drug resistance generation, which comprises a culture medium mold, a detection camera and an analysis computer, ten culture tanks with equal size are arranged at the top of the culture medium mould, position identification grooves are arranged on the outer wall of one side of the culture medium mould at equal intervals corresponding to the culture tanks, ten position identification grooves are arranged, position display cards for displaying the positions of the culture grooves are sequentially arranged in the position identification grooves from left to right, concentration identification grooves are arranged on the outer wall of the other side of the culture medium mould at equal intervals corresponding to the culture groove, ten concentration identification grooves are arranged, concentration display cards for displaying the concentration of antibiotics in the culture tank are sequentially arranged in the concentration identification grooves from left to right, the detection camera is positioned right above the culture medium die and is fixed on the outer wall of the culture medium die through a connecting plate.
Preferably, two adjacent culture tanks are separated by a slot baffle.
Preferably, a fixing box is installed at the center of one side of the outer wall of the culture medium mold, and a slot matched with the connecting plate in an inserting mode is formed in the fixing box.
Preferably, the bottom of the connecting plate is provided with a thread groove, the outer wall of the fixing box is provided with a through hole, and a fixing bolt in threaded connection with the thread groove is rotatably connected in the through hole.
Preferably, the number of the through holes and the number of the thread grooves are three, and the through holes and the thread grooves are arranged in a triangular disc shape.
Preferably, the detection method comprises the following steps:
s1, adding antibiotics into the corresponding culture tank according to the information of the concentration display card;
s2, inoculating the same strain into culture tanks with different antibiotic concentrations, wherein the culture tanks are connected with each other;
s3, acquiring analog image signals of the culture tank in real time by the detection camera;
s4, converting the analog image signal into an electric signal;
s5, converting the electric signal into a digital signal after amplifying the electric signal;
s6, sending the digital signal to a CPLD for caching through the Ethernet;
s7, inputting the buffered digital signals into the RAM of the analysis computer through an EDMA channel for image processing.
Preferably, an image processing module, a shape detection module and a color detection module are arranged in the analysis computer.
Preferably, the processing method of the image processing module includes the steps of:
s1.1, setting a gray value f (i, j) of an image at a pixel point (i, j), and considering a (2 omega +1) × (2 omega +1) window with the pixel point (i, j) as a center;
s1.2, calculating a threshold value T (i, j) of each pixel point (i, j) in the image;
s1.3, carrying out point-by-point binarization on each pixel point (i, j) in the image by using a b (i, j) value;
s1.4, selecting a static reference frame as a background image;
s1.5, calculating the difference between each pixel of the input person image and the pixel in the corresponding background image.
The formula for calculating the threshold value T (i, j) of each pixel point (i, j) in the image is as follows:
T(i，j)＝0.5×(maxf(i+m，j+n)+minf(i+m，j+n))。
the formula for point-by-point binarization is as follows:
the binarization principle is as follows: storing the value of the gray image by I, setting I to be N × M, expanding the I boundary to an (N +2) × (M +2) extended matrix, first reading the size of the original image I to be N × M, and expanding the gray image I since the elements in I are not all at the center of a 3 × 3 window. First, a matrix (N +2) × (M +2) extended is created, and the pixels enter (I +1, j +1) in the matrix I are I (I, j), and the first row and the last row, the first column and the last column are filled according to the symmetry axis of the row or the column to which the pixels are close. Traversing pixels from enter (2,2) to enter (N +1, M +1), taking the maximum pixel max and the minimum pixel min of a 3 × 3 window taking the current pixel as the center, solving a threshold value t according to a formula t of 0.5 × (max + min), assigning the gray image matrix I to another matrix B so as not to change the currently obtained gray image matrix, traversing the matrix B, comparing the current gray value with t, if the current gray value is greater than the assigned value of t, determining the current gray value as a target pixel class, if the current gray value is greater than the assigned value of t, assigning 0 to the current gray value as a background pixel class, and displaying the obtained binary image B.
Selecting a static reference frame as a background image, carrying out difference between each frame in an image sequence and a reference background, calculating the difference between each pixel of a person input image and the pixel in the corresponding background image, and setting F (i, j) to represent the current frame image and B (i, j) to represent the background image, wherein the algorithm formula of a difference image D (i, j) is as follows: d (i, j) ═ F (i, j) -B (i, j), and the binarized bitmap can be subjected to noise reduction processing.
Preferably, the shape detection module adopts a contour analysis algorithm, after a binary image obtained by the contour analysis algorithm through threshold segmentation is subjected to defect repair, contour extraction is required to obtain a two-dimensional contour of a target in the image, in this embodiment, a method of hollowing out interior points is adopted to perform contour extraction processing on the binary image, the principle is that if a background color is black and the target color is white, if a pixel point in an original image is white and 8 adjacent points thereof are white, the point can be determined to be an interior point, the point is deleted, that is, the interior points are hollowed out, and the algorithm comprises the following steps:
s2.1, if the gray scale interval of the image f (x, y) is [ Zmin,Zmax]；
S2.2, setting a threshold value Z in the intervaltAnd Z ismin<Zt<Zmax；
S2.3, enabling all gray values in the image to be less than or equal to ZtAll the pixels of (2) have a gray scale of 0 greater than ZtThe new grayscales of the pixels of (1) are all;
s2.4, constructing an output binary image f by threshold segmentationt(x,y)，
In the binary image, assuming that the gray value of the background pixel is 0, the gray value of the product pixel is 1, and the extraction rule of the boundary contour is as follows:
1) if the central pixel value is 0, the central pixel value is uniformly reserved no matter what the values of the other adjacent 8 pixels are;
2) if the central pixel value is 1 and the other adjacent 8 pixel values are all 1, changing the central pixel value to 0;
3) except the above case, the center pixel value is all changed to 1.
Preferably, the formula of the color detection module is as follows:
Gray＝0.3×R+0.59×G+0.11XB。
compared with the prior art, the invention has the beneficial effects that:
1. in the real-time observation system for the generation of the drug resistance of the bacteria, ten adjacent culture tanks are arranged on a culture medium mould, the concentration of antibiotics in the culture tanks is in gradient distribution, the same strain of bacteria is inoculated in different culture tanks, the adaptability of the bacteria to the antibiotics can be reflected, and the process of the generation of the actual drug resistance of the bacteria can be effectively observed.
2. In the real-time observation system for the generation of the bacterial drug resistance, a detection camera is adopted to shoot and record the growth conditions of bacteria in antibiotic culture media with different concentrations in real time, the process of the generation of the bacterial drug resistance is recorded, and the process of the generation of the bacterial drug resistance can be visually observed and recorded.
Drawings
FIG. 1 is a schematic view of the overall structure of the present invention;
FIG. 2 is a schematic view of a side structure of a culture medium mold according to the present invention;
FIG. 3 is another schematic view of the structure of the culture medium mold according to the present invention;
FIG. 4 is a schematic structural view of a fixing case according to the present invention;
FIG. 5 is a schematic view of a detecting camera according to the present invention;
FIG. 6 is a schematic view of the connection structure of the inspection camera and the analysis computer according to the present invention;
FIG. 7 is a schematic view of the overall flow structure of the present invention;
FIG. 8 is a block diagram of an analysis computer according to the present invention;
FIG. 9 is a flow chart of an image processing module according to the present invention;
FIG. 10 is a flow chart of a shape detection module according to the present invention.
The various reference numbers in the figures mean:
1. a culture medium mold; 11. a culture tank; 12. a concentration identification groove; 13. a concentration display card; 14. a position identification slot; 15. a position display card; 16. a clamp groove baffle;
17. a fixing box; 171. a slot; 172. a through hole; 173. fixing the bolt;
2. detecting a camera; 21. a connecting plate; 22. a thread groove;
3. an analysis computer; 31. an image processing module; 32. a shape detection module; 33. and a color detection module.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1-10, the present invention provides a technical solution:
the invention provides a real-time observation system for bacterial drug resistance generation, which comprises a culture medium mould 1, a detection camera 2 and an analysis computer 3, wherein ten culture tanks 11 with the same size are formed in the top of the culture medium mould 1, so that antibiotics with unequal concentrations can be conveniently placed in the culture tanks 11, the ten culture tanks 11 with the same size are adjacently arranged, the same strain of bacteria is inoculated in different culture tanks 11, the adaptability of the bacteria to the antibiotics can be reflected, and the process of generating the actual drug resistance of the bacteria can be effectively observed.
In this embodiment, the outer wall of one side of culture medium mould 1 corresponds culture tank 11 department equidistant position sign groove 14 that is provided with, position sign groove 14 is provided with ten, position sign inslot 14 that sets gradually from the left side right side and be used for showing the position of culture tank 11 shows card 15, it has marked "left 1", "left 2", "left 3", "left 4", "left 5", "right 4", "right 3", "right 2", "right 1" in proper order on the display card 15 that sets up from the left side right side, be convenient for show the position of every culture tank 11.
Further, the other side outer wall of culture medium mould 1 corresponds culture tank 11 department equidistant concentration sign groove 12 that is provided with, concentration sign groove 12 is provided with ten, concentration sign inslot 12 that sets gradually from the left side to the right side sets up the concentration display card 13 that is used for showing antibiotic concentration in culture tank 11, concentration display card 13 that sets gradually from the left side to the right side is gone up "0 doubly", "2 times", "10 times", "100 times", "1000 times", "100 times", "10 times", "2 times", "0 times", be convenient for sign the concentration of antibiotic in every culture tank 11, and concentration is the gradient distribution, can fully reflect the bacterium situation of growing in different concentration antibiotic culture medium.
Specifically, the detection camera 2 is positioned right above the culture medium mould 1, the detection camera 2 is fixed on the outer wall of the culture medium mould 1 through a connecting plate 21, the detection camera 2 adopts a CCD image sensor, specifically, the detection camera 2 can adopt a RJ2421AB0PB chip produced by SHARP company of Japan as a 1/4type solid-state type photosensitive diode structure color area array CCD image sensor, the effective pixel number is 320k (512H Q582V), the pixel size reaches 7.2 Mum 4.7 Mum, two output modes of common and mirror image are provided, the CCD comprises a Mg, G, Cy and Ye color compensation filter, an output amplifier and an exposure suppression structure are arranged in the CCD, an electronic shutter is variable in the range of 1/50-1/10000s, the sensitivity is 720mV, the elimination ratio is-105 dB, the main characteristics are that the fixed noise and the dragging are low, the embedding and the image distortion are avoided, the output signal is of PAL standard, the resolution can reach 330Horizontal TVlines, and the detection requirement is met.
It should be noted that two adjacent culture tanks 11 are separated by a slot baffle 16, so that different culture tanks 11 can be distinguished when the detection camera 2 detects the culture tanks.
In addition, the fixed box 17 is installed at the center position of the outer wall side of the culture medium mold 1, the slot 171 which is matched with the connecting plate 21 in an inserting mode is formed in the fixed box 17, and the connecting plate 21 can be positioned at the outer wall side of the culture medium mold 1 by inserting the connecting plate 21 into the slot 171.
In addition, the bottom of the connecting plate 21 is provided with a thread groove 22, the outer wall of the fixing box 17 is provided with a through hole 172, a fixing bolt 173 in threaded connection with the thread groove 22 is rotatably connected in the through hole 172, and after the connecting plate 21 is inserted into the slot 171 of the fixing box 17, the fixing bolt 173 is inserted into the through hole 172 and screwed into the thread groove 22, so that the fixing of the connecting plate 21 is completed.
It should be noted that three through holes 172 and three screw grooves 22 are provided, and the through holes 172 and the screw grooves 22 are arranged in a triangular disc, so that the fixing bolts 173 are screwed into the screw grooves 22 to form a triangular stable structure, thereby further enhancing the stabilizing effect of the connecting plate 21.
It is worth to be noted that the culture tank 11 is a chromogenic culture medium prepared according to different bacteria, and when bacteria grow, the color of the culture tank 11 changes, so that the process of generating the drug resistance of the bacteria can be visually observed and recorded.
In this embodiment, the detection method includes the following steps:
s1, adding antibiotics into the corresponding culture tank 11 according to the information of the concentration display card 13;
s2, inoculating the same strain into culture tanks 11 which are connected with each other and have different antibiotic concentrations;
s3, the detection camera 2 collects the analog image signal of the culture tank 11 in real time;
s4, converting the analog image signal into an electric signal;
s5, converting the electric signal into a digital signal after amplifying the electric signal;
s6, sending the digital signal to a CPLD for caching through the Ethernet;
s7, inputting the buffered digital signals into the RAM of the analysis computer 3 through an EDMA channel for image processing.
In this embodiment, the detection camera 2 and the analysis computer 3 realize data transmission through ethernet, so that image data acquired by the detection camera 2 can be transmitted to the analysis computer 3 for analysis.
Furthermore, the analyzing computer 3 adopts TMS320DM642 model DSP of TI company as an algorithm implementation platform for image processing, and adopts XC95144 of Xilinx company as a time sequence distribution control device for image acquisition, so that SDRAM is expanded on the basis of the hardware to realize image storage, and real-time image processing is realized.
Specifically, the analysis computer 3 is provided therein with an image processing module 31, a shape detection module 32, and a color detection module 33.
Further, the processing method of the image processing module 31 includes the steps of:
s1.1, setting a gray value f (i, j) of an image at a pixel point (i, j), and considering a (2 omega +1) × (2 omega +1) window with the pixel point (i, j) as a center;
s1.2, calculating a threshold value T (i, j) of each pixel point (i, j) in the image;
s1.3, carrying out point-by-point binarization on each pixel point (i, j) in the image by using a b (i, j) value;
s1.4, selecting a static reference frame as a background image;
s1.5, calculating the difference between each pixel of the input person image and the pixel in the corresponding background image.
The formula for calculating the threshold value T (i, j) of each pixel point (i, j) in the image is as follows:
T(i，j)＝0.5×(maxf(i+m，j+n)+minf(i+m，j+n))。
the formula for point-by-point binarization is as follows:
it should be noted that the binarization principle is as follows: storing the value of the gray image by I, setting I to be N × M, expanding the I boundary to an (N +2) × (M +2) extended matrix, first reading the size of the original image I to be N × M, and expanding the gray image I since the elements in I are not all at the center of a 3 × 3 window. First, a matrix (N +2) × (M +2) extended is created, and the pixels enter (I +1, j +1) in the matrix I are I (I, j), and the first row and the last row, the first column and the last column are filled according to the symmetry axis of the row or the column to which the pixels are close. Traversing pixels from enter (2,2) to enter (N +1, M +1), taking the maximum pixel max and the minimum pixel min of a 3 × 3 window taking the current pixel as the center, solving a threshold value t according to a formula t of 0.5 × (max + min), assigning the gray image matrix I to another matrix B so as not to change the currently obtained gray image matrix, traversing the matrix B, comparing the current gray value with t, if the current gray value is greater than the assigned value of t, determining the current gray value as a target pixel class, if the current gray value is greater than the assigned value of t, assigning 0 to the current gray value as a background pixel class, and displaying the obtained binary image B.
Specifically, a static reference frame is selected as a background image, each frame in an image sequence is differentiated from a reference background, the difference between each pixel of a person-input image and the pixel in the corresponding background image is calculated, F (i, j) is set to represent the current frame image, B (i, j) is set to represent the background image, and the algorithm formula of a differential image D (i, j) is as follows: d (i, j) ═ F (i, j) -B (i, j), and the binarized bitmap can be subjected to noise reduction processing.
In addition, the shape detection module 32 adopts a contour analysis algorithm, after the binary image obtained by the contour analysis algorithm through threshold segmentation is repaired, contour extraction is needed to obtain a two-dimensional contour of the target in the image, in this embodiment, a method of hollowing out interior points is adopted to perform contour extraction processing on the binary image, the principle is that, assuming that the background color is black and the target color is white, if a pixel point in the original image is white and 8 adjacent points thereof are white, the point can be determined to be an interior point, the point is deleted, that is, the interior points are hollowed out, and the algorithm comprises the following steps:
s2.1, if the gray scale interval of the image f (x, y) is [ Zmin,Zmax)；
S2.2, setting a threshold value Z in the intervaltAnd Z ismin<Zt<Zmax；
S2.3, enabling all gray values in the image to be less than or equal to ZtAll the pixels of (2) have a gray scale of 0 greater than ZtThe new grayscales of the pixels of (1) are all;
s2.4, constructing an output binary image f by threshold segmentationt(x,y)，
Further, in the binary image, assuming that the gray value of the background pixel is 0, the gray value of the product pixel is 1, and the extraction rule of the boundary contour is as follows:
1) if the central pixel value is 0, the central pixel value is uniformly reserved no matter what the values of the other adjacent 8 pixels are;
2) if the central pixel value is 1 and the other adjacent 8 pixel values are all 1, changing the central pixel value to 0;
3) except the above case, the center pixel value is all changed to 1.
It is worth noting that the formula of the color detection module 33 is as follows:
Gray＝0.3×R+0.59×G+0.11×B。
the foregoing shows and describes the general principles, essential features, and advantages of the invention. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, and the preferred embodiments of the present invention are described in the above embodiments and the description, and are not intended to limit the present invention. The scope of the invention is defined by the appended claims and equivalents thereof.
Claims (10)
1. The utility model provides a real-time observation system of bacterium drug resistance production, includes culture medium mould (1), detects camera (2) and analysis computer (3), its characterized in that: ten culture tanks (11) with equal size are arranged at the top of the culture medium mold (1), position identification grooves (14) are arranged on the outer wall of one side of the culture medium mold (1) at equal intervals corresponding to the positions of the culture tanks (11), ten position identification grooves (14) are arranged, position display cards (15) for displaying the positions of the culture tanks (11) are sequentially arranged in the position identification grooves (14) arranged from left to right, concentration identification grooves (12) are arranged on the outer wall of the other side of the culture medium mold (1) at equal intervals corresponding to the positions of the culture tanks (11), ten concentration identification grooves (12) are arranged, concentration display cards (13) for displaying the concentration of antibiotics in the culture tanks (11) are sequentially arranged in the concentration identification grooves (12) arranged from left to right, and the detection camera (2) is positioned right above the culture medium mold (1), the detection camera (2) is fixed on the outer wall of the culture medium mould (1) through a connecting plate (21).
2. The system for real-time observation of bacterial drug resistance generation according to claim 1, wherein: two adjacent culture tanks (11) are separated by a clamping groove baffle plate (16).
3. The system for real-time observation of bacterial drug resistance generation according to claim 1, wherein: the culture medium mould (1) is characterized in that a fixing box (17) is installed at the center of one side of the outer wall of the culture medium mould (1), and a slot (171) which is in plug-in fit with the connecting plate (21) is formed in the fixing box (17).
4. The system for real-time observation of bacterial drug resistance generation according to claim 3, wherein: thread groove (22) have been seted up to the bottom of connecting plate (21), through-hole (172) have been seted up to the outer wall of fixed box (17), through-hole (172) internal rotation is connected with fixing bolt (173) with thread groove (22) threaded connection.
5. The system for real-time observation of bacterial drug resistance generation according to claim 4, wherein: the through holes (172) and the thread grooves (22) are three, and the through holes (172) and the thread grooves (22) are arranged in a triangular disc shape.
6. The system for real-time observation of bacterial drug resistance generation according to claim 1, wherein the detection method comprises the following steps:
s1, adding antibiotics into the corresponding culture tank (11) according to the information of the concentration display card (13);
s2, inoculating the same strain into culture tanks (11) which are connected with each other and have different antibiotic concentrations;
s3, acquiring a simulated image signal of the culture tank (11) in real time by the detection camera (2);
s4, converting the analog image signal into an electric signal;
s5, converting the electric signal into a digital signal after amplifying the electric signal;
s6, sending the digital signal to a CPLD for caching through the Ethernet;
s7, inputting the buffered digital signals into the RAM of the analysis computer (3) through an EDMA channel for image processing.
7. The system for real-time observation of bacterial drug resistance generation according to claim 6, wherein: an image processing module (31), a shape detection module (32) and a color detection module (33) are arranged in the analysis computer (3).
8. The system for real-time observation of bacterial drug resistance generation according to claim 7, wherein: the processing method of the image processing module (31) comprises the following steps:
s1.1, setting a gray value f (i, j) of an image at a pixel point (i, j), and considering a (2 omega +1) × (2 omega +1) window with the pixel point (i, j) as a center;
s1.2, calculating a threshold value T (i, j) of each pixel point (i, j) in the image;
s1.3, carrying out point-by-point binarization on each pixel point (i, j) in the image by using a b (i, j) value;
s1.4, selecting a static reference frame as a background image;
s1.5, calculating the difference between each pixel of the input person image and the pixel in the corresponding background image.
9. The system for real-time observation of bacterial drug resistance generation according to claim 7, wherein: the shape detection module (32) adopts a profile analysis algorithm, and the algorithm comprises the following steps:
s2.1, if the gray scale interval of the image f (x, y) is [ Zmin,Zmax]；
S2.2, setting a threshold value Z in the intervaltAnd Z ismin<Zt<Zmax；
S2.3, enabling all gray values in the image to be less than or equal to ZtAll the pixels of (2) have a gray scale of 0 greater than ZtThe new grayscales of the pixels of (1) are all;
s2.4, constructing an output binary image f by threshold segmentationt(x,y)，
10. The system for real-time observation of bacterial drug resistance generation according to claim 7, wherein: the formula of the color detection module (33) is as follows:
Gray＝0.3×R+0.59×G+0.11×B。
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Cited By (2)
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Application publication date: 20200519 |