CN113504250B - Peanut aflatoxin detection device and method based on prism type RGB color extraction - Google Patents
Peanut aflatoxin detection device and method based on prism type RGB color extraction Download PDFInfo
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- 241001553178 Arachis glabrata Species 0.000 title claims abstract description 102
- 235000020232 peanut Nutrition 0.000 title claims abstract description 102
- 235000017060 Arachis glabrata Nutrition 0.000 title claims abstract description 76
- 235000010777 Arachis hypogaea Nutrition 0.000 title claims abstract description 76
- 235000018262 Arachis monticola Nutrition 0.000 title claims abstract description 76
- 229930195730 Aflatoxin Natural products 0.000 title claims abstract description 47
- 239000005409 aflatoxin Substances 0.000 title claims abstract description 47
- 238000000605 extraction Methods 0.000 title claims abstract description 41
- XWIYFDMXXLINPU-UHFFFAOYSA-N Aflatoxin G Chemical compound O=C1OCCC2=C1C(=O)OC1=C2C(OC)=CC2=C1C1C=COC1O2 XWIYFDMXXLINPU-UHFFFAOYSA-N 0.000 title claims abstract description 39
- 238000001514 detection method Methods 0.000 title claims abstract description 22
- 238000000034 method Methods 0.000 title claims abstract description 13
- 238000001914 filtration Methods 0.000 claims description 28
- 239000003086 colorant Substances 0.000 claims description 15
- 230000000877 morphologic effect Effects 0.000 claims description 15
- 238000003708 edge detection Methods 0.000 claims description 6
- 230000011218 segmentation Effects 0.000 claims description 6
- 230000008569 process Effects 0.000 claims description 4
- 230000015572 biosynthetic process Effects 0.000 claims description 3
- 230000009977 dual effect Effects 0.000 claims description 3
- 239000011521 glass Substances 0.000 claims description 3
- 238000009499 grossing Methods 0.000 claims description 3
- 230000001629 suppression Effects 0.000 claims description 3
- 238000003786 synthesis reaction Methods 0.000 claims description 3
- 238000005260 corrosion Methods 0.000 claims 1
- 230000007797 corrosion Effects 0.000 claims 1
- 238000006243 chemical reaction Methods 0.000 description 5
- 238000010586 diagram Methods 0.000 description 4
- 238000012986 modification Methods 0.000 description 4
- 230000004048 modification Effects 0.000 description 4
- 230000007547 defect Effects 0.000 description 2
- 230000003628 erosive effect Effects 0.000 description 2
- 241000227425 Pieris rapae crucivora Species 0.000 description 1
- 208000003464 asthenopia Diseases 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 231100000357 carcinogen Toxicity 0.000 description 1
- 239000003183 carcinogenic agent Substances 0.000 description 1
- 230000010339 dilation Effects 0.000 description 1
- 230000036541 health Effects 0.000 description 1
- 230000008520 organization Effects 0.000 description 1
- 231100000614 poison Toxicity 0.000 description 1
- 239000003440 toxic substance Substances 0.000 description 1
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- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
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- 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
- G01N21/01—Arrangements or apparatus for facilitating the optical investigation
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- G—PHYSICS
- 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
- G01N21/01—Arrangements or apparatus for facilitating the optical investigation
- G01N2021/0106—General arrangement of respective parts
- G01N2021/0112—Apparatus in one mechanical, optical or electronic block
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Abstract
The invention discloses a peanut aflatoxin detection device and method based on prismatic RGB color extraction, wherein the device comprises a control box and a computer, the control box and the computer are connected through a control cable, an industrial camera and an ultraviolet lamp light source are arranged in the control box, the industrial camera is connected with the computer, an objective table is also arranged in the control box, the objective table is arranged under the industrial camera, and the two sides of the industrial camera are respectively provided with the ultraviolet lamp light source. According to the invention, the R-G-B color image of the peanut is extracted, and compared with the preset judgment threshold value, whether the peanut is infected with aflatoxin can be detected, so that whether the peanut is infected with aflatoxin can be accurately detected.
Description
Technical Field
The invention belongs to the technical field of machine vision detection, and relates to a peanut aflatoxin detection device and method based on prismatic RGB color extraction.
Background
Aflatoxin is defined by the world health organization cancer research institute as a class of naturally occurring carcinogens, which are extremely toxic substances. Peanut is one of crops which is most easy to infect aflatoxin, and accurate detection of whether the peanut is infected with aflatoxin is a problem to be solved.
At present, the existing peanut aflatoxin detection mainly adopts artificial naked eyes for detection, and the peanuts are randomly extracted by the artificial eyes to detect whether the peanuts are mildewed or not, only the mildewed and rotted peanuts can be detected, but also a small amount of aflatoxin-infected peanuts can not be detected, so that the accuracy is low; because the workers are easy to generate visual fatigue after working for a long time, the problematic peanuts are easy to sort out by mistake, and the consumer is easy to influence the credit of the merchant. In addition, the existing technology for detecting peanut mildew based on machine vision mainly adopts a white light LED light source to irradiate peanuts, gray values of different areas are analyzed through gray images of the peanuts, whether the peanuts are mildewed or not is judged in a contrasting mode, when the peanuts are infected with a small amount of aflatoxin, the gray images of the peanuts extracted under irradiation of a common white light LED light source are not different from the gray images of the normal peanuts, and a traditional CCD linear array industrial camera cannot image the slightly changed colors in a high quality mode, so that the peanuts infected with a small amount of aflatoxin cannot be detected.
Disclosure of Invention
In order to solve the problems, the technical scheme of the invention is as follows: the peanut aflatoxin detection device based on the prism type RGB color extraction comprises a control box and a computer, wherein the control box and the computer are connected through a control cable, an industrial camera and an ultraviolet lamp light source are arranged in the control box, the industrial camera is connected with the computer, an objective table is further arranged in the control box, the objective table is arranged under the industrial camera, and the ultraviolet lamp light sources are respectively arranged at two sides of the industrial camera;
the control box is a black box body which is opaque in photographing, an opening is formed in the side face of the control box, and peanuts are placed on the objective table through the opening;
The industrial camera is a prismatic industrial R-G-B area array scanning camera;
The control cable comprises a GigE gigabit network port digital connecting wire for controlling the industrial camera to be connected with the computer and a control cable for controlling the ultraviolet lamp light source to be connected with the computer;
the computer receives the image data of the peanuts collected by the industrial camera, processes and analyzes the image data, and determines whether the peanuts are infected with aflatoxin.
Preferably, the ultraviolet lamp light source comprises a lamp panel, and an ultraviolet lamp tube is inlaid on the lamp panel through a groove arranged on the lamp panel.
Preferably, the stage is a glass sheet with both sides frosted.
Based on the above purpose, the invention also provides a peanut aflatoxin detection method based on the prism type RGB color extraction, which adopts the peanut aflatoxin detection device based on the prism type RGB color extraction, and comprises the following steps:
S10, after a peanut aflatoxin detection device based on prismatic RGB color extraction is built, an ultraviolet light source is turned on, and an industrial camera collects color RGB images of peanuts;
s20, the industrial camera sends the acquired color RGB image of the peanut to a computer for filtering treatment, and then the background segmentation is carried out on the treated image to obtain an image with the background removed;
And S30, extracting R, G, B colors of the images with the background removed in the S20, judging the similar colors of the aflatoxins on each peanut, and judging that the peanut is infected by the aflatoxins if the colors exceed a set threshold value.
Preferably, in the filtering process in S20, wiener filtering is adopted, and the local mean value of each pixel point is:
the variance of each pixel is:
The wiener filter estimation formula is:
Wherein S represents a local neighborhood of MxN of each pixel point in the image; δ 2 represents the noise variance, which can be replaced by the average of all local estimated variances.
Preferably, the step of performing background segmentation on the peanut color RGB image after the filtering in S20 includes the following steps:
S21, edge extraction, namely processing the peanut color RGB image subjected to the filtering processing by adopting a Canny edge detection operator and extracting edges to obtain a peanut edge extraction image;
s22, morphological filtering is carried out on the peanut edge extracted image, and image noise is removed by adopting morphological filtering, so that a peanut image after morphological filtering treatment is obtained;
S23, image filling and marking, namely marking the occupied area of the peanut in the image by adopting a scanning line seed filling method on the peanut area in the peanut image after morphological filtering treatment to obtain a marked peanut image;
S24, image synthesis, namely taking the marked peanut image as a mask, performing AND operation on the mask and R, G, B of the source image respectively to obtain a bit and operated R, G, B image, and combining the bit and operated R, G, B image to obtain a background segmented image.
Preferably, the processing and extracting the edge by using the Canny edge detection operator comprises the following steps:
s211, smoothing the image by using a Gaussian filter;
s212, calculating a gradient amplitude image and a gradient angle image;
S213, applying non-maximum suppression to the gradient magnitude image;
s214, edges are detected and connected using dual thresholding and connectivity.
Preferably, the morphological filtering in S22 includes expansion, erosion, open operation and closed operation.
Preferably, when the image is subjected to R, G, B color extraction in S30, the following discriminant rule is adopted for the R, G, B three colors: and judging that a certain pixel point is a certain color according to the fact that the difference value between a certain color component and the other two color components in R, G, B is larger than a set value, and controlling the color of the judging condition by setting a judging threshold value.
Preferably, in S30, the threshold is a value for determining R, G, B a color area of the image after color extraction, and if the value exceeds the set range of the value, it is determined that the peanut is infected with aflatoxin.
Compared with the prior art, the invention has the following beneficial effects:
According to the invention, an ultraviolet lamp light source is adopted, and if peanut is infected with aflatoxin, a specific fluorescent reaction can occur under the irradiation of the light source; the invention adopts a prism type industrial R-G-B area array scanning camera, and the camera is provided with three CMOS sensors, each sensor is responsible for one color, and compared with a single CMOS sensor, the prism type industrial R-G-B area array scanning camera is more sensitive to the color and can provide better color fidelity and spatial resolution; when peanut image acquisition is carried out, an ultraviolet lamp light source is turned on, the computer controls an industrial camera to trigger synchronously, the industrial camera sends images of peanuts under the irradiation of the ultraviolet lamp light source to the computer, and as aflatoxin can generate fluorescent reaction under the irradiation of the ultraviolet lamp, the peanuts infected by aflatoxin can generate the fluorescent reaction as well, and the fluorescent reaction can not occur in normal occurrence of the peanut which is not infected by aflatoxin. The R-G-B color image of the peanut is extracted by the computer, and compared with a preset judgment threshold value, whether the peanut is infected with aflatoxin can be detected, so that whether the peanut is infected with aflatoxin is accurately detected.
Drawings
Fig. 1 is a schematic diagram of the overall structure of a peanut aflatoxin detection device based on prismatic RGB color extraction according to an embodiment of the present invention;
fig. 2 is a schematic diagram of an internal structure of a control box in a peanut aflatoxin detection device based on prismatic RGB color extraction according to an embodiment of the present invention;
Fig. 3 is a schematic structural diagram of an ultraviolet light source in a peanut aflatoxin detection device based on prismatic RGB color extraction according to an embodiment of the present invention;
fig. 4 is a flowchart of a method for detecting peanut aflatoxin based on prismatic RGB color extraction according to an embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present invention more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
On the contrary, the invention is intended to cover any alternatives, modifications, equivalents, and variations as may be included within the spirit and scope of the invention as defined by the appended claims. Further, in the following detailed description of the present invention, certain specific details are set forth in order to provide a better understanding of the present invention. The present invention will be fully understood by those skilled in the art without the details described herein.
Aiming at the defects existing in the prior art, the applicant carries out intensive research on the structure of the traditional broadband high-efficiency power amplifier in the prior art, and the applicant discovers in the research that the traditional broadband high-efficiency power amplifier in the prior art has the advantages of relatively single mode, relatively complex structure, relatively large implementation difficulty, relatively large whole circuit size and relatively high cost.
In order to overcome the defects of the prior art, referring to fig. 1-3, a structural block diagram of a peanut aflatoxin detection device based on prismatic RGB color extraction is shown, a computer 1 and a control box 2 are shown, an industrial camera 5 is arranged in the control box 1, the industrial camera 5 is connected with the computer 1, an objective table 8 is arranged right below the industrial camera in the control box 2, and ultraviolet lamp light sources 6 and 7 and a control cable 4 for connecting the computer and the control box are respectively arranged on two sides of the industrial camera 5 in the control box 2.
The control box 2 is a black box body which is opaque in photographing and is used for isolating the interference of an external light source; and the control box 2 is provided with an opening 3 for placing peanuts on the object stage 8.
The industrial camera 5 is a prismatic industrial R-G-B area array scanning camera, and can acquire peanut images with better color fidelity and spatial resolution.
The ultraviolet lamp sources 6 and 7 comprise lamp panels 9, and ultraviolet lamp tubes 10 are inlaid on the lamp panels through grooves formed in the lamp panels and are matched with the industrial camera 5 for use.
The stage 8 is a glass sheet with both sides frosted.
The control cable 4 comprises a GigE gigabit network port digital connecting wire for controlling the connection of the industrial camera 5 and the computer 1, and a control cable for controlling the connection of the ultraviolet light sources 6 and 7 and the computer 1, and is matched with the industrial camera 5 and the computer 1.
The computer 1 is used for receiving the image data of the peanuts collected by the industrial camera 5, and the computer 1 processes and analyzes the image data to determine whether the peanuts are infected with aflatoxin.
Referring to fig. 4, the invention also provides a peanut aflatoxin detection method based on prismatic RGB color extraction, which adopts the peanut aflatoxin detection device based on prismatic RGB color extraction, and comprises the following steps:
S10, after a peanut aflatoxin detection device based on prismatic RGB color extraction is built, an ultraviolet light source is turned on, and an industrial camera collects color RGB images of peanuts;
s20, the industrial camera sends the acquired color RGB image of the peanut to a computer for filtering treatment, and then the background segmentation is carried out on the treated image to obtain an image with the background removed;
And S30, extracting R, G, B colors of the images with the background removed in the S20, judging the similar colors of the aflatoxins on each peanut, and judging that the peanut is infected by the aflatoxins if the colors exceed a set threshold value.
The aflatoxins G1 and G2 can emit green fluorescence under the irradiation of an ultraviolet light source, the aflatoxins B1 and B2 can emit blue fluorescence under the irradiation of the ultraviolet light source, in S10, if the peanut is infected with aflatoxin, the color RGB image of the peanut collected by the industrial camera under the irradiation of the ultraviolet light source also shows fluorescence reaction. In S20, the filter processing adopts wiener filter, and the local mean value of each pixel point is as follows:
the variance of each pixel is:
The wiener filter estimation formula is:
Wherein S represents a local neighborhood of MxN of each pixel point in the image; δ 2 represents the noise variance, which can be replaced by the average of all local estimated variances.
The background segmentation of the peanut color RGB image after the filtering processing in S20 comprises the following steps:
S21, edge extraction, namely processing the peanut color RGB image subjected to the filtering processing by adopting a Canny edge detection operator and extracting edges to obtain a peanut edge extraction image;
s22, morphological filtering is carried out on the peanut edge extracted image, and image noise is removed by adopting morphological filtering, so that a peanut image after morphological filtering treatment is obtained;
S23, image filling and marking, namely marking the occupied area of the peanut in the image by adopting a scanning line seed filling method on the peanut area in the peanut image after morphological filtering treatment to obtain a marked peanut image;
S24, image synthesis, namely taking the marked peanut image as a mask, performing AND operation on the mask and R, G, B of the source image respectively to obtain a bit and operated R, G, B image, and combining the bit and operated R, G, B image to obtain a background segmented image.
The method for processing and extracting the edges by adopting the Canny edge detection operator comprises the following steps:
s211, smoothing the image by using a Gaussian filter;
s212, calculating a gradient amplitude image and a gradient angle image;
S213, applying non-maximum suppression to the gradient magnitude image;
s214, edges are detected and connected using dual thresholding and connectivity.
Morphological filtering in S22 includes dilation, erosion, open and closed operations.
When R, G, B color extraction is performed on the image in S30, the following discrimination rules are adopted for the R, G, B three colors: and judging that a certain pixel point is a certain color according to the fact that the difference value between a certain color component and the other two color components in R, G, B is larger than a set value, and controlling the color of the judging condition by setting a judging threshold value.
And S30, judging that the threshold value is a value of the color area of the image after R, G, B color extraction, and judging that the peanut is infected with aflatoxin if the value exceeds the set range of the value.
In a specific embodiment, when R, G, B color extraction is performed on the image in S30, the following discriminant rule is adopted for the R, G, B three colors: when the difference between one color component and the other two color components in R, G, B is larger than the set value, namely, judging that a certain pixel point is a certain color, and controlling the color of the judging condition by setting a judging threshold value, the specific operation steps are as follows: setting R, G, B three color extraction thresholds, namely an extraction threshold value of extraction_r=0, an extraction threshold value of extraction_g=0 and an extraction threshold value of extraction_b=0, wherein the color extraction threshold value is preset to be zero, the larger the color extraction threshold value is, the smaller the extraction range is, then extracting R, G, B three colors respectively, wherein the red extraction condition is that the difference value of an R component and a G, B component is larger than the set value, the green extraction condition is that the difference value of a G component and a R, B component is larger than the set value, and the green extraction condition is that the difference value of a G component and a R, B component is larger than the set value.
There are many ways in which the invention may be practiced, no matter how detailed the above appears in the specification, what is described in what way is illustrative of the invention. All equivalent changes or modifications made according to the spirit of the present invention should be included in the scope of the present invention.
The foregoing detailed description of embodiments of the invention is not intended to be exhaustive or to limit the invention to the precise form disclosed. While specific embodiments of, and examples for, the invention are described above for illustrative purposes, various equivalent modifications are possible within the scope of the invention, as those skilled in the relevant art will recognize.
While the above description describes particular embodiments of the invention and describes the best mode contemplated, no matter how detailed the above appears in text, the invention can be practiced in many ways. The details of the above-described circuit structure and manner of controlling it may vary considerably in its implementation details, while still being encompassed by the invention disclosed herein.
As noted above, it should be noted that particular terminology used in describing certain features or aspects of the invention should not be taken to imply that the terminology is being redefined herein to be restricted to certain specific characteristics, features, or aspects of the invention with which that terminology is associated. In general, the terms used in the following claims should not be construed to limit the invention to the specific embodiments disclosed in the specification, unless the above detailed description section explicitly defines such terms. Therefore, the actual scope of the invention encompasses not only the disclosed embodiments, but also all equivalent ways of practicing or implementing the invention under the claims.
The foregoing description of the preferred embodiments of the invention is not intended to be limiting, but rather is intended to cover all modifications, equivalents, and alternatives falling within the spirit and principles of the invention.
Claims (1)
1. The peanut aflatoxin detection method based on the prismatic RGB color extraction is characterized by comprising a control box and a computer, wherein the control box and the computer are connected through a control cable, an industrial camera and an ultraviolet lamp light source are arranged in the control box, the industrial camera is connected with the computer, an objective table is further arranged in the control box, the objective table is arranged under the industrial camera, and the two sides of the industrial camera are respectively provided with the ultraviolet lamp light source;
the control box is a black box body which is opaque in photographing, an opening is formed in the side face of the control box, and peanuts are placed on the objective table through the opening;
The industrial camera is a prismatic industrial R-G-B area array scanning camera;
The control cable comprises a GigE gigabit network port digital connecting wire for controlling the industrial camera to be connected with the computer and a control cable for controlling the ultraviolet lamp light source to be connected with the computer;
the computer receives the image data of the peanuts collected by the industrial camera, processes and analyzes the image data and determines whether the peanuts are infected with aflatoxin;
The ultraviolet lamp light source comprises a lamp panel, and an ultraviolet lamp tube is inlaid on the lamp panel through a groove arranged on the lamp panel;
The object stage is a glass sheet with both frosted surfaces
The detection method comprises the following steps:
S10, after a peanut aflatoxin detection device based on prismatic RGB color extraction is built, an ultraviolet light source is turned on, and an industrial camera collects color RGB images of peanuts;
s20, the industrial camera sends the acquired color RGB image of the peanut to a computer for filtering treatment, and then the background segmentation is carried out on the treated image to obtain an image with the background removed;
S30, extracting R, G, B colors of the images with the background removed in S20, judging the similar colors of the aflatoxins on each peanut, and judging that the peanut is infected by the aflatoxins if the colors exceed a set threshold value;
in the step S20, wiener filtering is adopted for filtering, and the local mean value of each pixel point is:
the variance of each pixel is:
The wiener filter estimation formula is:
Wherein S represents a local neighborhood of MxN of each pixel point in the image; δ ( represents the noise variance, which can be replaced by the average of all local estimated variances;
The step of performing background segmentation on the peanut color RGB image after the filtering processing in the step S20 comprises the following steps:
S21, edge extraction, namely processing the peanut color RGB image subjected to the filtering processing by adopting a Canny edge detection operator and extracting edges to obtain a peanut edge extraction image;
s22, morphological filtering is carried out on the peanut edge extracted image, and image noise is removed by adopting morphological filtering, so that a peanut image after morphological filtering treatment is obtained;
S23, image filling and marking, namely marking the occupied area of the peanut in the image by adopting a scanning line seed filling method on the peanut area in the peanut image after morphological filtering treatment to obtain a marked peanut image;
S24, image synthesis, namely taking the marked peanut image as a mask, respectively performing AND operation on the mask and R, G, B of a source image to obtain a bit and operated R, G, B image, and combining the bit and operated R, G, B image to obtain a background segmented image;
the processing and extracting the edge by adopting the Canny edge detection operator comprises the following steps:
s211, smoothing the image by using a Gaussian filter;
s212, calculating a gradient amplitude image and a gradient angle image;
S213, applying non-maximum suppression to the gradient magnitude image;
S214, detecting and connecting edges using dual threshold processing and connectivity;
The morphological filtering in the S22 comprises expansion, corrosion, open operation and closed operation;
When R, G, B color extraction is performed on the image in S30, the following discrimination rules are adopted for the R, G, B three colors: judging that a certain pixel point is a certain color according to the fact that the difference value between a certain color component and other two color components in R, G, B is larger than a set value, and controlling the color of a judging condition by setting a judging threshold value;
and the threshold in the step S30 is a value for judging the color area of the image after R, G, B color extraction, and if the value exceeds the set range of the value, the peanut is judged to be infected with aflatoxin.
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