CN115661054B - Seal detection method and device, electronic equipment and storage medium - Google Patents
Seal detection method and device, electronic equipment and storage medium Download PDFInfo
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Abstract
The invention discloses a seal detection method and device, electronic equipment and a storage medium, and belongs to the technical field of industrial control. Wherein the method comprises the following steps: collecting pseudo-color images and temperature images of the aluminum foil seals; extracting shape characteristics of the aluminum foil seal according to the pseudo-color image, and calculating temperature characteristics of the aluminum foil seal according to the temperature image; and detecting the packaging defect of the aluminum foil seal according to the shape characteristic and/or the temperature characteristic. The invention solves the technical problem of low efficiency of detecting the defects of the aluminum foil seal in the related technology, improves the efficiency, avoids the risk of missed detection, and can effectively classify the defects.
Description
Technical Field
The present invention relates to the field of industrial control technologies, and in particular, to a method and apparatus for detecting a seal, an electronic device, and a storage medium.
Background
In the related art, aluminum foil sealing packaging of plastic or glass containers such as medicines, foods, cosmetics, lubricating oil and the like, particularly, aluminum foil sealing of plastic or glass containers such as non-metal containers is a very necessary procedure for detecting sealing quality. After the bottled container is sealed by the aluminum foil, the quality of the sealing needs to be detected, and the tightness and the integrity of the sealing of the aluminum foil are detected. The product with poor tightness or missing aluminum foil is prevented from being transferred to the next working procedure, so that reworking, scrapping or market entering is avoided, and loss is caused.
In the related art, in order to prevent products with poor sealing performance and missing aluminum foil from flowing into later working procedures, so that reworking, scrapping or flowing into the market, one method is manual detection, but the defect is that whether the sealing performance and the integrity of the aluminum foil seal are normal or not can be observed through naked eyes only by unscrewing the bottle cap, the degree of automation is low, the labor cost is not very low, and the efficiency is low.
In view of the above problems in the related art, an effective solution has not been found.
Disclosure of Invention
The invention provides a seal detection method and device, electronic equipment and storage medium.
According to an aspect of the embodiment of the present application, there is provided a method for detecting a seal, including: collecting pseudo-color images and temperature images of the aluminum foil seals; extracting shape characteristics of the aluminum foil seal according to the pseudo-color image, and calculating temperature characteristics of the aluminum foil seal according to the temperature image; and detecting the packaging defect of the aluminum foil seal according to the shape characteristic and/or the temperature characteristic.
Optionally, extracting the shape feature of the aluminum foil seal according to the pseudo color image includes: extracting a first gray scale image of the pseudo color image in an R channel, wherein the pseudo color image comprises R, G, B channels; dividing the aluminum foil area of the aluminum foil seal from the pseudo-color image based on the first gray scale image; extracting a first shape feature of the aluminum foil region.
Optionally, after dividing the aluminum foil region of the aluminum foil seal from the pseudo color image based on the first gray scale image, the method further comprises: extracting a second gray level image of the pseudo color image in the B channel; positioning the aluminum foil area in a second gray level image, and intercepting a white area in the aluminum foil area; and extracting a second shape characteristic of the white region.
Optionally, calculating the packaging temperature of the aluminum foil seal according to the temperature image includes: acquiring global temperature data of the temperature image, and storing the global temperature data into a first temperature array, wherein the first temperature array comprises a plurality of temperature data; sequencing a plurality of temperature data in the first temperature array, and filtering abnormal temperatures to obtain a second temperature array; and extracting the maximum M pieces of temperature data in the second temperature array, calculating the highest temperature of the aluminum foil seal based on the M pieces of temperature data, extracting the minimum N pieces of temperature data in the second temperature array, calculating the lowest temperature of the aluminum foil seal based on the N pieces of temperature data, and calculating the temperature average value and the temperature variance of the aluminum foil region of the aluminum foil seal, wherein M is an integer greater than 0, and N is an integer greater than 0.
Optionally, the temperature characteristic includes a temperature average value and a temperature variance of the aluminum foil region of the aluminum foil seal, and detecting the packaging defect of the aluminum foil seal according to the temperature characteristic includes: comparing the temperature average value by adopting a minimum threshold value and a maximum threshold value; if the average temperature is smaller than the minimum threshold value, judging that the sealing power of the aluminum foil sealing machine is too low; if the average temperature is greater than the maximum threshold value, judging that the sealing power of the aluminum foil sealing machine is too high; judging whether the temperature variance is larger than a preset threshold value or not; and if the temperature variance is larger than a preset threshold value, judging that the temperature distribution of the aluminum foil sealing area is uneven.
Optionally, the shape feature includes a first shape feature of an aluminum foil region, and detecting the package defect of the aluminum foil seal according to the shape feature includes: determining a pixel point set where the aluminum foil area is located based on the first shape feature; hole filling is carried out on the pixel point set of the aluminum foil area, so that a hole area is obtained; calculating the first area of the hole area, and judging whether the first area is larger than a first defect area threshold value or not; and if the area of the area is larger than a first defect area threshold value, determining that the aluminum foil of the aluminum foil seal is reverse.
Optionally, the shape feature includes a first shape feature of an aluminum foil region, and detecting the package defect of the aluminum foil seal according to the shape feature includes: determining a pixel point set where the aluminum foil area is located based on the first shape feature; sampling boundary pixel points in the pixel point set, and fitting the boundary pixel points to form an elliptical area; obtaining a difference area between the aluminum foil area and the elliptical area; calculating the second area of the difference area, and judging whether the second area is larger than a second defect area threshold value or not; and if the area of the second area is larger than a second defect area threshold value, determining that the aluminum foil of the aluminum foil seal is missing.
Optionally, the shape feature includes a second shape feature of a white area in the aluminum foil area, and detecting the package defect of the aluminum foil seal according to the shape feature includes: calculating the matching degree of the white area and a preset regular shape based on the second shape characteristic; and if the matching degree of the white area and the preset regular shape is smaller than a matching threshold value, determining that the aluminum foil seal has the defect of loose cover or distorted cover.
According to another aspect of the embodiment of the present application, there is also provided a device for detecting a seal, including: the acquisition module is used for acquiring pseudo-color images and temperature images of the aluminum foil seals; the processing module is used for extracting the shape characteristics of the aluminum foil seal according to the pseudo-color image and calculating the temperature characteristics of the aluminum foil seal according to the temperature image; and the detection module is used for detecting the packaging defect of the aluminum foil seal according to the shape characteristic and/or the temperature characteristic.
Optionally, the processing module includes: a first extracting unit, configured to extract a first gray scale image of the pseudo color image in an R channel, where the pseudo color image includes R, G, B channels; a dividing unit for dividing the aluminum foil region of the aluminum foil seal from the pseudo color image based on the first gray image; and the second extraction unit is used for extracting the first shape characteristic of the aluminum foil area.
Optionally, the processing module further includes: a third extracting unit, configured to extract a second gray level image of the pseudo color image in a B channel after the dividing unit divides the aluminum foil region of the aluminum foil seal from the pseudo color image based on the first gray level image; the positioning unit is used for positioning the aluminum foil area in the second gray level image and intercepting a white area in the aluminum foil area; and a fourth extraction unit for extracting the second shape feature of the white region.
Optionally, the processing module includes: the temperature image acquisition unit is used for acquiring global temperature data of the temperature image and storing the global temperature data into a first temperature array, wherein the first temperature array comprises a plurality of temperature data; the processing unit is used for sequencing the plurality of temperature data in the first temperature array, filtering abnormal temperatures and obtaining a second temperature array; the calculating unit is used for extracting the maximum M pieces of temperature data in the second temperature array, calculating the highest temperature of the aluminum foil seal based on the M pieces of temperature data, extracting the minimum N pieces of temperature data in the second temperature array, calculating the lowest temperature of the aluminum foil seal based on the N pieces of temperature data, and calculating the temperature average value and the temperature variance of the aluminum foil area of the aluminum foil seal, wherein M is an integer greater than 0, and N is an integer greater than 0.
Optionally, the temperature characteristic includes a temperature average value and a temperature variance of the aluminum foil region of the aluminum foil seal, and the detection module includes: a comparison unit for comparing the temperature average value using a minimum threshold value and a maximum threshold value; the first judging unit is used for judging that the sealing power of the aluminum foil sealing machine is too low if the average temperature is smaller than the minimum threshold value; if the average temperature is greater than the maximum threshold value, judging that the sealing power of the aluminum foil sealing machine is too high; the judging unit is used for judging whether the temperature variance is larger than a preset threshold value or not; and the second judging unit is used for judging that the temperature distribution of the aluminum foil sealing area is uneven if the temperature variance is larger than a preset threshold value.
Optionally, the shape feature includes a first shape feature of an aluminum foil region, and the detection module includes: a determining unit, configured to determine a set of pixel points where the aluminum foil area is located based on the first shape feature; the first detection unit is used for filling holes in the pixel point set of the aluminum foil area to obtain a hole area; calculating the first area of the hole area, and judging whether the first area is larger than a first defect area threshold value or not; and if the area of the area is larger than a first defect area threshold value, determining that the aluminum foil of the aluminum foil seal is reverse.
Optionally, the shape feature includes a first shape feature of an aluminum foil region, and the detection module includes: a determining unit, configured to determine a set of pixel points where the aluminum foil area is located based on the first shape feature; the second detection unit is used for sampling boundary pixel points in the pixel point set, and fitting the boundary pixel points to form an elliptical area; obtaining a difference area between the aluminum foil area and the elliptical area; calculating the second area of the difference area, and judging whether the second area is larger than a second defect area threshold value or not; and if the area of the second area is larger than a second defect area threshold value, determining that the aluminum foil of the aluminum foil seal is missing.
Optionally, the shape feature includes a second shape feature of a white area in the aluminum foil area, and the detection module includes: a calculating unit, configured to calculate a matching degree between the white area and a preset regular shape based on the second shape feature; and the determining unit is used for determining that the aluminum foil seal has the defect of loose cover or distorted cover if the matching degree of the white area and the preset regular shape is smaller than a matching threshold value.
According to another aspect of the embodiments of the present application, there is also provided a storage medium including a stored program that performs the above steps when running.
According to another aspect of the embodiment of the present application, there is also provided an electronic device including a processor, a communication interface, a memory, and a communication bus, where the processor, the communication interface, and the memory complete communication with each other through the communication bus; wherein: a memory for storing a computer program; and a processor for executing the steps of the method by running a program stored on the memory.
Embodiments of the present application also provide a computer program product comprising instructions which, when run on a computer, cause the computer to perform the steps of the above method.
According to the invention, the pseudo-color image and the temperature image of the aluminum foil seal are collected, the shape characteristic of the aluminum foil seal is extracted according to the pseudo-color image, the temperature characteristic of the aluminum foil seal is calculated according to the temperature image, the packaging defect of the aluminum foil seal is detected according to the shape characteristic and/or the temperature characteristic, the shape characteristic of the pseudo-color image and the temperature characteristic of the temperature image are collected, the defect detection can be carried out on the aluminum foil seal according to the shape characteristic and the temperature characteristic, whether the aluminum foil seal is qualified or not is judged, the efficient detection method is realized, the technical problem of low efficiency of detecting the defect of the aluminum foil seal in the related art is solved, the efficiency is improved, the risk of omission detection is avoided, and the defect can be effectively classified.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this specification, illustrate embodiments of the application and together with the description serve to explain the application and do not constitute a limitation on the application. In the drawings:
FIG. 1 is a block diagram of a hardware architecture of an industrial control console according to an embodiment of the present invention;
FIG. 2 is a flow chart of a method of detecting a seal according to an embodiment of the present invention;
FIG. 3 is a pseudo color image and a temperature image of an aluminum foil seal in accordance with an embodiment of the present invention;
FIG. 4 is a pseudo color image and temperature image of the case where the power of the aluminum foil seal is too low and too high in the embodiment of the present invention;
FIG. 5 is a pseudo color image and a temperature image when the aluminum foil is reversed in accordance with an embodiment of the present invention;
FIG. 6 is a pseudo color image and a temperature image when the aluminum foil is absent in accordance with an embodiment of the present invention;
FIG. 7 is a pseudo color image and a temperature image of an aluminum foil seal when the cover is released in accordance with an embodiment of the present invention;
FIG. 8 is a pseudo color image and a temperature image of an aluminum foil seal with a skewed cover in accordance with an embodiment of the invention;
fig. 9 is a flowchart of a thermal imaging-based aluminum foil seal quality detection method in the present embodiment;
fig. 10 is a block diagram of a seal detecting device according to an embodiment of the present invention.
Detailed Description
In order that those skilled in the art will better understand the present application, a technical solution in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present application, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present application without making any inventive effort, shall fall within the scope of the present application. It should be noted that, without conflict, the embodiments of the present application and features of the embodiments may be combined with each other.
It should be noted that the terms "first," "second," and the like in the description and the claims of the present application and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the application described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
Example 1
The method embodiment provided in the first embodiment of the application can be executed in an industrial control console, a mobile phone, a controller, a server, a computer, a tablet or a similar operation scheduling device. Taking an example of operation on an industrial console, fig. 1 is a hardware structure block diagram of the industrial console according to an embodiment of the present application. As shown in fig. 1, the industrial console may include one or more (only one is shown in fig. 1) processors 102 (the processor 102 may include, but is not limited to, a microprocessor MCU or a processing device such as a programmable logic device FPGA) and a memory 104 for storing data, and optionally, a transmission device 106 for communication functions and an input-output device 108. It will be appreciated by those skilled in the art that the configuration shown in fig. 1 is merely illustrative, and is not intended to limit the configuration of the industrial control console. For example, the industrial console may also include more or fewer components than shown in FIG. 1, or have a different configuration than shown in FIG. 1.
The memory 104 may be used to store an industrial personal computer program, for example, a software program of application software and a module, such as an industrial personal computer program corresponding to a video dynamic and static rate identification method in an embodiment of the present invention, and the processor 102 executes the industrial personal computer program stored in the memory 104 to perform various functional applications and data processing, that is, implement the method described above. Memory 104 may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, memory 104 may further include memory remotely located with respect to processor 102, which may be connected to the industrial console via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The transmission device 106 is used to receive or transmit data via a network. Specific examples of the network include wireless networks provided by communication providers of industrial consoles. In one example, the transmission device 106 includes a network adapter (Network Interface Controller, simply referred to as a NIC) that can connect to other network devices through a base station to communicate with the internet. In one example, the transmission device 106 may be a Radio Frequency (RF) module, which is configured to communicate with the internet wirelessly.
In this embodiment, a method for detecting a seal is provided, and fig. 2 is a flowchart of a method for detecting a seal according to an embodiment of the present invention, as shown in fig. 2, where the flowchart includes the following steps:
Step S202, collecting pseudo-color images and temperature images of aluminum foil seals;
The embodiment can adopt an infrared thermal imaging camera for acquisition, and acquire images of targets (aluminum foil seals) passing through the infrared thermal imaging camera, so that a pseudo-color image and a temperature image can be obtained. Besides aluminum foil, the solution of this embodiment may also be applied to other metal, metal plating or other sealing processes, such as tin foil, lead foil, paper foil, etc.
Fig. 3 is a pseudo color image and a temperature image of the aluminum foil seal in the embodiment of the present invention when it is normal.
Step S204, extracting shape characteristics of the aluminum foil seal according to the pseudo-color image, and calculating temperature characteristics of the aluminum foil seal according to the temperature image;
and S206, detecting the packaging defect of the aluminum foil seal by adopting the shape characteristic and/or the temperature characteristic.
Optionally, the packaging defects of the aluminum foil seal include defects of a packaging process, such as abnormal sealing power, too high or too low of an aluminum foil sealing machine, and also include sealing defects of the aluminum foil seal, such as aluminum foil reversal, aluminum foil missing, aluminum foil loose cover or cover distortion defects.
Through the steps, the pseudo-color image and the temperature image of the aluminum foil seal are collected, the shape characteristic of the aluminum foil seal is extracted according to the pseudo-color image, the temperature characteristic of the aluminum foil seal is calculated according to the temperature image, the packaging defect of the aluminum foil seal is detected according to the shape characteristic and/or the temperature characteristic, the pseudo-color image and the temperature image of the aluminum foil seal are collected, the shape characteristic and the temperature characteristic of the pseudo-color image are obtained, the defect detection can be carried out on the aluminum foil seal according to the shape characteristic and the temperature characteristic, whether the aluminum foil seal is qualified or not is judged, an efficient detection method is realized, the technical problem of low efficiency of detecting the defect of the aluminum foil seal in the related art is solved, the efficiency is improved, the risk of omission is avoided, and the defect can be effectively classified.
In one implementation of this embodiment, extracting shape features of the aluminum foil seal from the pseudo-color image includes:
S11, extracting a first gray level image of a pseudo-color image in an R channel, wherein the pseudo-color image comprises R, G, B channels;
S12, dividing an aluminum foil area of the aluminum foil seal from the pseudo-color image based on the first gray level image;
In another aspect of the present embodiment, after dividing the aluminum foil region of the aluminum foil seal from the pseudo color image based on the first gray scale image, further comprising: extracting a second gray level image of the pseudo-color image in the B channel; positioning an aluminum foil area in the second gray level image, and intercepting a white area in the aluminum foil area; and extracting a second shape characteristic of the white region.
S13, extracting first shape features of the aluminum foil area.
In this embodiment, the step of analyzing and obtaining the aluminum foil region in the thermal imaging image by analyzing the gray scale image of the R channel in the thermal imaging pseudo-color image includes:
the pseudo color image in this embodiment is an RGB image or an RGB image, and the three-channel pseudo color image is decomposed into three single-channel gray scale images with the same definition, which are then R, G, B-channel gray scale images.
After the aluminum foil is heated and sealed, the temperature of the aluminum foil area is higher than the ambient temperature, the gray value of the aluminum foil area is larger and white, and the gray value of the background area is smaller and black in an R channel image, so that a gray threshold value can be set, the aluminum foil area is extracted, and the extracted original area is RegionFoilIni;
RegionFoilIni = { (x, y) | mingray < g (x, y) < maxgray }, g (x, y) is the gray value of the pixel (x, y), mingray and maxgray are the upper and lower gray thresholds.
Using the Seed-sizing algorithm to segment RegionFoilIni into a plurality of connected regions ConnectedRegions;
Wherein A is a set of one or more connected components, regionFoilIni in this example, the size of array X 0 is the same as the array containing A, B is a structural element, when X k＝Xk-1, the iteration ends and X k contains all connected components of the input region, symbols For the dilation operator in morphological image processing, the symbol ∈is the intersection operator;
Smoothing the outline of the aluminum foil region and eliminating finer protrusions using morphological opening operations ConnectedRegions;
Wherein the symbols are Symbol/>, for erosion operators in morphological image processingIs a dilation operator in morphological image processing. Open operation/>, of structural element B to ANamely, B corrodes A, and then the corrosion result is expanded by using B;
Finally, calculating the area of each connected region in ConnectedRegions, namely the number of the pixel points, and storing the area into an array; selecting a communication region with the largest area as a finally extracted aluminum foil region FoilRegion;
FoliRegion＝MaxAreaOf(ConnectedRegions)。
further, a white region in the middle of the aluminum foil region of the B-channel gray image in the thermal imaging pseudo-color image is extracted, and shape characteristics of the white region are analyzed.
In this embodiment, calculating the packaging temperature of the aluminum foil seal from the temperature image includes: acquiring global temperature data of a temperature image, and storing the global temperature data into a first temperature array, wherein the first temperature array comprises a plurality of temperature data; sequencing a plurality of temperature data in the first temperature array, and filtering abnormal temperatures to obtain a second temperature array; extracting the largest M pieces of temperature data in the second temperature array, calculating the highest temperature of the aluminum foil seal based on the M pieces of temperature data, extracting the smallest N pieces of temperature data in the second temperature array, calculating the lowest temperature of the aluminum foil seal based on the N pieces of temperature data, and calculating the temperature average value and the temperature variance of the aluminum foil area of the aluminum foil seal, wherein M is an integer greater than 0, and N is an integer greater than 0.
In one example, global data of the whole temperature image is obtained, the temperature data is stored in an array, the array is sorted in ascending order, abnormal points are filtered out due to possible existence of dead points of the thermal imaging camera, the abnormal points comprise high temperature points with temperature lower than the ambient temperature and unlikely to occur, and the algorithm is as follows:
Tselect＝{T|0＜T＜100}
Tsort＝Sort(Tselect)
Treverse＝Reverse(Tsort)
Wherein, T select is temperature data after filtering out abnormal temperature data, and T sort and T reverse are sequencing the filtered temperature data in ascending order and descending order.
In one example, M, N takes 10, the filtered temperature data takes the smallest top ten point calculated average as the thermal imaging region minimum temperature T min, and the largest ten point calculated average as the thermal imaging region maximum temperature T max; the formula is as follows:
Tmin＝Mean(Sum(Tsort[0：9]))
Tmax＝Mean(Sum(Treverse[0：9]))
After the lowest temperature and the highest temperature are calculated, the method can further judge that if the lowest temperature is higher than a set threshold value, the environment temperature is too high or the thermal imaging camera does not perform temperature correction, cooling treatment or temperature correction is needed, and if the highest temperature is higher than the set threshold value, the aluminum foil area temperature is too high after aluminum foil sealing, which may be caused by too high power of the aluminum foil sealing machine or the thermal imaging camera does not perform temperature correction, and the sealing power of the aluminum foil sealing machine needs to be adjusted or the temperature correction needs to be performed.
In one implementation scenario of the present embodiment, the temperature characteristics include a temperature average value and a temperature variance of an aluminum foil region of the aluminum foil seal, and detecting the package defect of the aluminum foil seal according to the temperature characteristics includes: comparing the temperature average value by adopting a minimum threshold value and a maximum threshold value; if the average temperature is smaller than the minimum threshold value, judging that the sealing power of the aluminum foil sealing machine is too low; if the average temperature is greater than the maximum threshold value, judging that the sealing power of the aluminum foil sealing machine is too high; judging whether the temperature variance is larger than a preset threshold value or not; if the temperature variance is larger than a preset threshold value, judging that the temperature distribution of the aluminum foil sealing area is uneven.
In this implementation scenario, the temperature average T mean, the standard deviation σ of the aluminum foil region are calculated by counting the gray information of the aluminum foil region in the temperature map and converting the gray information into temperature data, and the temperature minimum and maximum thresholds, and the variance threshold are set. Finally, carrying out defect judgment, and judging that the sealing power of the aluminum foil sealing machine is too low if the average temperature of the aluminum foil area is smaller than a set minimum temperature threshold value; if the average temperature of the aluminum foil area is larger than the set maximum temperature threshold, judging that the sealing power of the aluminum foil sealing machine is too high; and if the standard deviation of the temperature of the aluminum foil area is larger than the set threshold value, judging that the temperature distribution of the aluminum foil sealing area is uneven. Fig. 4 is a pseudo color image and a temperature image of the case where the power of the aluminum foil seal is too low and too high in the embodiment of the present invention.
In one implementation scenario of the present embodiment, the shape features include a first shape feature of the aluminum foil region, and detecting the package defect of the aluminum foil seal based on the shape feature includes: determining a pixel point set where the aluminum foil area is located based on the first shape characteristic; filling holes in a pixel point set of the aluminum foil area to obtain a hole area; calculating the first area of the hole area, and judging whether the first area is larger than a first defect area threshold value or not; and if the area of the area is larger than the first defect area threshold value, determining that the aluminum foil sealed by the aluminum foil is reverse.
In another implementation, the shape features include a first shape feature of the aluminum foil region, and detecting a package defect of the aluminum foil seal based on the shape feature includes: determining a pixel point set where the aluminum foil area is located based on the first shape characteristic; sampling boundary pixel points in the pixel point set, and fitting the boundary pixel points to form an elliptical area; obtaining a difference region between the aluminum foil region and the elliptical region; calculating the second area of the difference set area, and judging whether the second area is larger than a second defect area threshold value or not; and if the area of the second area is larger than the second defect area threshold value, determining that the aluminum foil of the aluminum foil seal is missing.
In the analysis of reverse defects of aluminum foil: when the aluminum foil is in reverse defect, the temperature of the middle part of the aluminum foil area is lower than that of the edge part in the thermal imaging pseudo-color chart, the high-temperature area forms a ring shape, and if the shape characteristic is present, the aluminum foil is judged to be in reverse. The algorithm comprises the following specific steps:
hole filling is carried out on the extracted aluminum foil area FoilRegion, and the formula is as follows:
Wherein A c is the complement of region FoilRegion, B is a suitable structural element, and the X 0 array is the same size as the array comprising A, and is given the symbol For the dilation operator in morphological image processing, the sign ∈is an intersection operator, and when X k＝Xk-1, the iteration is ended, so that the pixel point set X k is the hole area HoleRegion;
and calculating the area of the hole region HoleRegion, namely the number of pixel points contained in the region, and judging that the aluminum foil is reverse if the area is larger than a set defect area threshold value.
Fig. 5 is a pseudo color image and a temperature image when the aluminum foil is reversed according to an embodiment of the present invention.
In the analysis of the defect of aluminum foil deficiency: since the aluminum foil seal is complete, the extracted aluminum foil area FoilRegion is approximately circular, and if the aluminum foil is notched, the extracted aluminum foil area FoilRegion will also be notched accordingly. If the FoilRegion aluminum foil area has a notch, the aluminum foil is judged to be absent, and the algorithm specifically comprises the following steps:
Sampling FoilRegion points on the boundary and fitting the points to an elliptical region RegionEllipse according to the least squares method;
using the fitted elliptical region RegionEllipse and aluminum foil region FoilRegion as a difference to obtain a difference region RegionDiff;
RegionDiff＝{(x，y)|RegionEllipse-FoilRegion}
Using morphological open processing RegionDiff, the elongated interference region is eliminated, resulting in region RegionDiffOpening;
Wherein, the radius of the structural element B can be set to be large and small so as to adapt to eliminating interference areas with different fineness;
And calculating the area of the region RegionDiffOpening, namely the number of pixel points contained in the region, and judging that the aluminum foil is absent if the area is larger than a set defect area threshold value.
Fig. 6 is a pseudo color image and a temperature image when the aluminum foil is absent in the embodiment of the present invention.
In one implementation scenario of the present embodiment, the shape features include a second shape feature of the self-colored region in the aluminum foil region, and detecting the encapsulation defect of the aluminum foil seal according to the shape features includes: calculating the matching degree of the white area and a preset regular shape based on the second shape characteristic; if the matching degree of the white area and the preset regular shape is smaller than the matching threshold value, determining that the aluminum foil seal has the defects of loose cover or distorted cover.
The B channel gray level image in the thermal imaging pseudo color image with the aluminum foil sealed is regular, and a white area similar to a circular ring shape is arranged in the middle of the aluminum foil area. If the bottle cap is skewed or loose when the aluminum foil is sealed, the B channel gray level image in the thermal imaging pseudo-color image is different from the normal image, and the shape of the white area in the middle of the aluminum foil area is irregular.
Fig. 7 is a pseudo color image and a temperature image when the aluminum foil seal is opened in the embodiment of the invention, and fig. 8 is a pseudo color image and a temperature image when the aluminum foil seal is distorted in the embodiment of the invention.
In an implementation scene, whether the aluminum foil seal is good or not can be judged according to the shape characteristics of the middle white area of the aluminum foil area in the B-channel gray level image.
Fig. 9 is a flowchart of a thermal imaging-based aluminum foil seal quality detection method in the embodiment, which shows a detection algorithm for detecting a series of defects such as tightness and integrity of an aluminum foil seal, and solves the problems of complicated detection steps, low efficiency, low automation degree and the like in the aluminum foil seal quality detection process. Comprising the following steps:
Step 1, collecting an aluminum foil sealing thermal imaging pseudo-color image and a temperature image;
step 2, analyzing the acquired temperature image information, and calculating the highest temperature and the lowest temperature of a thermal imaging area;
step 3, analyzing the highest temperature and the lowest temperature of the thermal imaging area obtained by calculation, comparing the highest temperature and the lowest temperature with a set temperature threshold, and judging whether the temperature range is within the set threshold range;
step 4, analyzing an R channel gray level image in the thermal imaging pseudo-color image, and Bolb analyzing and obtaining an aluminum foil area in the thermal imaging image;
Step 5, analyzing the shape characteristics of the aluminum foil area, and judging whether the shape characteristics have irregular conditions or not;
Step 6, analyzing gray value information of the aluminum foil area of the temperature image, counting temperature information of the aluminum foil area, calculating statistical data such as average temperature and variance of the aluminum foil area, and judging whether the statistical data is in a normal range;
step 7, analyzing a B-channel gray level image in the thermal imaging pseudo-color image, and judging whether a regular white area similar to a circular ring shape exists in an aluminum foil area of the B-channel gray level image;
Firstly, an infrared thermal imaging camera is used for collecting a thermal imaging image of an aluminum foil seal, wherein the thermal imaging image comprises a pseudo-color image and a temperature information image, then the highest temperature and the lowest temperature of a thermal imaging area are calculated according to the temperature information image, and whether the temperature of the aluminum foil seal is in a normal range is judged by comparing the temperature with a set temperature threshold; performing Bolb analysis on the R channel gray level image in the pseudo color image, dividing an aluminum foil area, analyzing the shape characteristics of the aluminum foil area, and judging whether the aluminum foil area has irregular shape characteristics or not; next, counting temperature information of the aluminum foil area, calculating average temperature and standard deviation of the aluminum foil area, and judging whether the statistical data are in a normal range; and finally, analyzing whether a regular white area similar to a circular ring shape exists in the aluminum foil area of the B-channel gray level image in the pseudo color image. Compared with a pattern matching algorithm, the algorithm not only analyzes the shape characteristics of the aluminum foil area in the thermal imaging pseudo-color image, but also analyzes the related temperature statistical data in the temperature image, and judges whether the aluminum foil seal is qualified or not according to the characteristics and the temperature data. The algorithm has the advantages of simpler and clearer calculation process, stronger resolving power, higher accuracy, stronger adaptability, capability of classifying different defect types and the like.
According to the embodiment, the shape characteristics and the temperature information of the pseudo-color image and the temperature information image shot by the infrared thermal imaging camera are analyzed, the values of the characteristics and the temperature are calculated through an algorithm, whether the aluminum foil seal is qualified or not is judged according to comparison between the calculated values and a plurality of set thresholds, so that an efficient detection method is realized, the efficiency is improved, the risk of omission is avoided, and defects can be effectively classified.
From the description of the above embodiments, it will be clear to a person skilled in the art that the method according to the above embodiments may be implemented by means of software plus the necessary general hardware platform, but of course also by means of hardware, but in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art in the form of a software product stored in a storage medium (e.g. ROM/RAM, magnetic disk, optical disk) comprising instructions for causing a terminal device (which may be a mobile phone, a computer, a server, or a network device, etc.) to perform the method according to the embodiments of the present invention.
Example 2
The embodiment also provides a device for detecting a seal, which is used for realizing the embodiment and the preferred embodiment, and is not described in detail. As used below, the term "module" may be a combination of software and/or hardware that implements a predetermined function. While the means described in the following embodiments are preferably implemented in software, implementation in hardware, or a combination of software and hardware, is also possible and contemplated.
Fig. 10 is a block diagram of a seal detecting device according to an embodiment of the present invention, as shown in fig. 10, the device includes: an acquisition module 100, a processing module 102, a detection module 104, wherein,
The acquisition module 100 is used for acquiring pseudo-color images and temperature images of the aluminum foil seals;
a processing module 102, configured to extract a shape feature of the aluminum foil seal according to the pseudo color image, and calculate a temperature feature of the aluminum foil seal according to the temperature image;
And the detection module 104 is used for detecting the packaging defect of the aluminum foil seal according to the shape characteristic and/or the temperature characteristic.
Optionally, the processing module includes: a first extracting unit, configured to extract a first gray scale image of the pseudo color image in an R channel, where the pseudo color image includes R, G, B channels; a dividing unit for dividing the aluminum foil region of the aluminum foil seal from the pseudo color image based on the first gray image; and the second extraction unit is used for extracting the first shape characteristic of the aluminum foil area.
Optionally, the processing module further includes: a third extracting unit, configured to extract a second gray level image of the pseudo color image in a B channel after the dividing unit divides the aluminum foil region of the aluminum foil seal from the pseudo color image based on the first gray level image; the positioning unit is used for positioning the aluminum foil area in the second gray level image and intercepting a white area in the aluminum foil area; and a fourth extraction unit for extracting the second shape feature of the white region.
Optionally, the processing module includes: the temperature image acquisition unit is used for acquiring global temperature data of the temperature image and storing the global temperature data into a first temperature array, wherein the first temperature array comprises a plurality of temperature data; the processing unit is used for sequencing the plurality of temperature data in the first temperature array, filtering abnormal temperatures and obtaining a second temperature array; the calculating unit is used for extracting the maximum M pieces of temperature data in the second temperature array, calculating the highest temperature of the aluminum foil seal based on the M pieces of temperature data, extracting the minimum N pieces of temperature data in the second temperature array, calculating the lowest temperature of the aluminum foil seal based on the N pieces of temperature data, and calculating the temperature average value and the temperature variance of the aluminum foil area of the aluminum foil seal, wherein M is an integer greater than 0, and N is an integer greater than 0.
Optionally, the temperature characteristic includes a temperature average value and a temperature variance of the aluminum foil region of the aluminum foil seal, and the detection module includes: a comparison unit for comparing the temperature average value using a minimum threshold value and a maximum threshold value; the first judging unit is used for judging that the sealing power of the aluminum foil sealing machine is too low if the average temperature is smaller than the minimum threshold value; if the average temperature is greater than the maximum threshold value, judging that the sealing power of the aluminum foil sealing machine is too high; the judging unit is used for judging whether the temperature variance is larger than a preset threshold value or not; and the second judging unit is used for judging that the temperature distribution of the aluminum foil sealing area is uneven if the temperature variance is larger than a preset threshold value.
Optionally, the shape feature includes a first shape feature of an aluminum foil region, and the detection module includes: a determining unit, configured to determine a set of pixel points where the aluminum foil area is located based on the first shape feature; the first detection unit is used for filling holes in the pixel point set of the aluminum foil area to obtain a hole area; calculating the first area of the hole area, and judging whether the first area is larger than a first defect area threshold value or not; and if the area of the area is larger than a first defect area threshold value, determining that the aluminum foil of the aluminum foil seal is reverse.
Optionally, the shape feature includes a first shape feature of an aluminum foil region, and the detection module includes: a determining unit, configured to determine a set of pixel points where the aluminum foil area is located based on the first shape feature; the second detection unit is used for sampling boundary pixel points in the pixel point set, and fitting the boundary pixel points to form an elliptical area; obtaining a difference area between the aluminum foil area and the elliptical area; calculating the second area of the difference area, and judging whether the second area is larger than a second defect area threshold value or not; and if the area of the second area is larger than a second defect area threshold value, determining that the aluminum foil of the aluminum foil seal is missing.
Optionally, the shape feature includes a second shape feature of a white area in the aluminum foil area, and the detection module includes: a calculating unit, configured to calculate a matching degree between the white area and a preset regular shape based on the second shape feature; and the determining unit is used for determining that the aluminum foil seal has the defect of loose cover or distorted cover if the matching degree of the white area and the preset regular shape is smaller than a matching threshold value.
It should be noted that each of the above modules may be implemented by software or hardware, and for the latter, it may be implemented by, but not limited to: the modules are all located in the same processor; or the above modules may be located in different processors in any combination.
Example 3
An embodiment of the invention also provides a storage medium having a computer program stored therein, wherein the computer program is arranged to perform the steps of any of the method embodiments described above when run.
Alternatively, in the present embodiment, the above-described storage medium may be configured to store a computer program for performing the steps of:
s1, collecting a pseudo-color image and a temperature image of an aluminum foil seal;
S2, extracting shape characteristics of the aluminum foil seal according to the pseudo-color image, and calculating temperature characteristics of the aluminum foil seal according to the temperature image;
s3, detecting the packaging defect of the aluminum foil seal according to the shape characteristic and/or the temperature characteristic.
Alternatively, in the present embodiment, the storage medium may include, but is not limited to: a usb disk, a Read-Only Memory (ROM), a random access Memory (Random Access Memory RAM), a removable hard disk, a magnetic disk, or an optical disk, or other various media capable of storing a computer program.
An embodiment of the invention also provides an electronic device comprising a memory having stored therein a computer program and a processor arranged to run the computer program to perform the steps of any of the method embodiments described above.
Optionally, the electronic device may further include a transmission device and an input/output device, where the transmission device is connected to the processor, and the input/output device is connected to the processor.
Alternatively, in the present embodiment, the above-described processor may be configured to execute the following steps by a computer program:
s1, collecting a pseudo-color image and a temperature image of an aluminum foil seal;
S2, extracting shape characteristics of the aluminum foil seal according to the pseudo-color image, and calculating temperature characteristics of the aluminum foil seal according to the temperature image;
s3, detecting the packaging defect of the aluminum foil seal according to the shape characteristic and/or the temperature characteristic.
Alternatively, specific examples in this embodiment may refer to examples described in the foregoing embodiments and optional implementations, and this embodiment is not described herein.
The foregoing embodiment numbers of the present application are merely for the purpose of description, and do not represent the advantages or disadvantages of the embodiments.
In the foregoing embodiments of the present application, the descriptions of the embodiments are emphasized, and for a portion of this disclosure that is not described in detail in this embodiment, reference is made to the related descriptions of other embodiments.
In the several embodiments provided in the present application, it should be understood that the disclosed technology may be implemented in other manners. The above-described embodiments of the apparatus are merely exemplary, and the division of the units, such as the division of the units, is merely a logical function division, and may be implemented in another manner, for example, multiple units or components may be combined or may be integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be through some interfaces, units or modules, or may be in electrical or other forms.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in the embodiments of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application may be embodied essentially or in part or all of the technical solution or in part in the form of a software product stored in a storage medium, including instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a usb disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a removable hard disk, a magnetic disk, or an optical disk, or other various media capable of storing program codes.
The foregoing is merely a preferred embodiment of the present application and it should be noted that modifications and adaptations to those skilled in the art may be made without departing from the principles of the present application, which are intended to be comprehended within the scope of the present application.
Claims (8)
1. A method of detecting a seal, the method comprising:
Collecting pseudo-color images and temperature images of the aluminum foil seals;
extracting shape characteristics of the aluminum foil seal according to the pseudo-color image, and calculating temperature characteristics of the aluminum foil seal according to the temperature image;
detecting packaging defects of the aluminum foil seal according to the shape characteristics and/or the temperature characteristics;
Wherein extracting the shape feature of the aluminum foil seal according to the pseudo color image comprises: extracting a first gray scale image of the pseudo color image in an R channel, wherein the pseudo color image comprises R, G, B channels; dividing the aluminum foil area of the aluminum foil seal from the pseudo-color image based on the first gray scale image; extracting a first shape feature of the aluminum foil area and extracting a second gray level image of the pseudo color image in a B channel; positioning the aluminum foil area in a second gray level image, and intercepting a white area in the aluminum foil area; extracting a second shape feature of the white region;
Wherein calculating the temperature characteristics of the aluminum foil seal according to the temperature image comprises: acquiring global temperature data of the temperature image, and storing the global temperature data into a first temperature array, wherein the first temperature array comprises a plurality of temperature data; sequencing a plurality of temperature data in the first temperature array, and filtering abnormal temperatures to obtain a second temperature array; and extracting the maximum M pieces of temperature data in the second temperature array, calculating the highest temperature of the aluminum foil seal based on the M pieces of temperature data, extracting the minimum N pieces of temperature data in the second temperature array, calculating the lowest temperature of the aluminum foil seal based on the N pieces of temperature data, and calculating the temperature average value and the temperature variance of the aluminum foil region of the aluminum foil seal, wherein M is an integer greater than 0, and N is an integer greater than 0.
2. The method of claim 1, wherein the temperature characteristics include a temperature average and a temperature variance of an aluminum foil region of the aluminum foil seal, and detecting an encapsulation defect of the aluminum foil seal based on the temperature characteristics includes:
comparing the temperature average value by adopting a minimum threshold value and a maximum threshold value;
If the average temperature is smaller than the minimum threshold value, judging that the sealing power of the aluminum foil sealing machine is too low; if the average temperature is greater than the maximum threshold value, judging that the sealing power of the aluminum foil sealing machine is too high;
judging whether the temperature variance is larger than a preset threshold value or not;
And if the temperature variance is larger than a preset threshold value, judging that the temperature distribution of the aluminum foil sealing area is uneven.
3. The method of claim 1, wherein the shape feature comprises a first shape feature of an aluminum foil region, and detecting an encapsulation defect of the aluminum foil seal based on the shape feature comprises:
determining a pixel point set where the aluminum foil area is located based on the first shape feature;
Hole filling is carried out on the pixel point set of the aluminum foil area, so that a hole area is obtained; calculating the first area of the hole area, and judging whether the first area is larger than a first defect area threshold value or not; and if the area of the area is larger than a first defect area threshold value, determining that the aluminum foil of the aluminum foil seal is reverse.
4. The method of claim 1, wherein the shape feature comprises a first shape feature of an aluminum foil region, and detecting an encapsulation defect of the aluminum foil seal based on the shape feature comprises:
determining a pixel point set where the aluminum foil area is located based on the first shape feature;
Sampling boundary pixel points in the pixel point set, and fitting the boundary pixel points to form an elliptical area; obtaining a difference area between the aluminum foil area and the elliptical area; calculating the second area of the difference area, and judging whether the second area is larger than a second defect area threshold value or not; and if the area of the second area is larger than a second defect area threshold value, determining that the aluminum foil of the aluminum foil seal is missing.
5. The method of claim 1, wherein the shape feature comprises a second shape feature of a white area in an aluminum foil area, and detecting an encapsulation defect of the aluminum foil seal based on the shape feature comprises:
Calculating the matching degree of the white area and a preset regular shape based on the second shape characteristic;
and if the matching degree of the white area and the preset regular shape is smaller than a matching threshold value, determining that the aluminum foil seal has the defect of loose cover or distorted cover.
6. A sealed inspection device, comprising:
the acquisition module is used for acquiring pseudo-color images and temperature images of the aluminum foil seals;
The processing module is used for extracting the shape characteristics of the aluminum foil seal according to the pseudo-color image and calculating the temperature characteristics of the aluminum foil seal according to the temperature image;
The detection module is used for detecting the packaging defect of the aluminum foil seal according to the shape characteristic and/or the temperature characteristic;
Wherein the processing module comprises: a first extracting unit, configured to extract a first gray scale image of the pseudo color image in an R channel, where the pseudo color image includes R, G, B channels; a dividing unit for dividing the aluminum foil region of the aluminum foil seal from the pseudo color image based on the first gray image; a second extraction unit for extracting a first shape feature of the aluminum foil region; a third extracting unit, configured to extract a second gray level image of the pseudo color image in a B channel after the dividing unit divides the aluminum foil region of the aluminum foil seal from the pseudo color image based on the first gray level image; the positioning unit is used for positioning the aluminum foil area in the second gray level image and intercepting a white area in the aluminum foil area; a fourth extraction unit configured to extract a second shape feature of the white region;
Wherein the processing module comprises: the temperature image acquisition unit is used for acquiring global temperature data of the temperature image and storing the global temperature data into a first temperature array, wherein the first temperature array comprises a plurality of temperature data; the processing unit is used for sequencing the plurality of temperature data in the first temperature array, filtering abnormal temperatures and obtaining a second temperature array; the calculating unit is used for extracting the maximum M pieces of temperature data in the second temperature array, calculating the highest temperature of the aluminum foil seal based on the M pieces of temperature data, extracting the minimum N pieces of temperature data in the second temperature array, calculating the lowest temperature of the aluminum foil seal based on the N pieces of temperature data, and calculating the temperature average value and the temperature variance of the aluminum foil area of the aluminum foil seal, wherein M is an integer greater than 0, and N is an integer greater than 0.
7. The electronic equipment is characterized by comprising a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory are communicated with each other through the communication bus; wherein:
a memory for storing a computer program;
a processor for executing the method steps of any one of claims 1 to 5 by running a program stored on a memory.
8. A storage medium comprising a stored program, wherein the program when run performs the method steps of any of the preceding claims 1 to 5.
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105921421A (en) * | 2016-06-13 | 2016-09-07 | 广州弥特智能科技有限公司 | Aluminum foil sealing detection device and method |
| CN112712496A (en) * | 2020-12-16 | 2021-04-27 | 广州大学 | Aluminum blister package pill defect detection method, system and storage medium |
| CN114067212A (en) * | 2021-11-25 | 2022-02-18 | 浙江天铂云科光电股份有限公司 | Intelligent detection method and device based on temperature vision and electronic equipment |
| CN114119466A (en) * | 2021-10-09 | 2022-03-01 | 武汉禾富信科技有限公司 | Method, device and equipment for detecting surface defects of aluminum foil and computer storage medium |
| CN114235758A (en) * | 2021-12-10 | 2022-03-25 | 苏州凌云视界智能设备有限责任公司 | Defect detection method, device, equipment and storage medium |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7322160B2 (en) * | 2004-05-17 | 2008-01-29 | Herzog Kenneth J | Monitoring system for induction sealer |
-
2022
- 2022-10-14 CN CN202211262534.2A patent/CN115661054B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105921421A (en) * | 2016-06-13 | 2016-09-07 | 广州弥特智能科技有限公司 | Aluminum foil sealing detection device and method |
| CN112712496A (en) * | 2020-12-16 | 2021-04-27 | 广州大学 | Aluminum blister package pill defect detection method, system and storage medium |
| CN114119466A (en) * | 2021-10-09 | 2022-03-01 | 武汉禾富信科技有限公司 | Method, device and equipment for detecting surface defects of aluminum foil and computer storage medium |
| CN114067212A (en) * | 2021-11-25 | 2022-02-18 | 浙江天铂云科光电股份有限公司 | Intelligent detection method and device based on temperature vision and electronic equipment |
| CN114235758A (en) * | 2021-12-10 | 2022-03-25 | 苏州凌云视界智能设备有限责任公司 | Defect detection method, device, equipment and storage medium |
Non-Patent Citations (2)
| Title |
|---|
| Defect detection of seals in multilayer aseptic packages using deep learning;Kemal ADEM et al;《Turkish Journal Of Electrical & Computer Sciences》;第2019卷(第27期);4220-4230 * |
| 包装热封缺陷的红外无损检测;黄冬梅;《中国优秀硕士学位论文全文数据库（电子期刊）》;第2006卷(第09期);全文 * |
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