A method for detecting different density materials in a cigarette based on three-dimensional reconstruction of an industrial CT

Abstract

A kind of detection method of different density materials in cigarette based on three-dimensional reconstruction of industrial CT, characterized by: through industrial CT scanning, realize the digitization of three-dimensional structure of cigarette, obtain the two-dimensional image of tobacco distribution inside cigarette through filtered back projection technology, then obtain the three-dimensional reconstruction model of cigarette through three-dimensional reconstruction technology, since X-ray will attenuate when penetrating through object, the attenuation degree of ray of four different materials, tobacco, cut stem, expanded tobacco and expanded cut stem is different, which is reflected in the different gray values in three-dimensional reconstruction model, so the tobacco, cut stem, expanded tobacco and expanded cut stem in cigarette sample can be identified based on gray value.The advantages of the present application are that the tobacco, cut stem, expanded tobacco and expanded cut stem in cigarette can be automatically and accurately detected, with high detection efficiency and low error rate, and the method of the present application belongs to non-destructive testing technology, which can effectively reduce the loss of cigarette and has important significance for the development of the industry.

Description

Technical Field

[0001] This invention relates to the field of cigarette product testing technology, and in particular to a method for detecting materials of different densities within cigarettes based on industrial CT three-dimensional reconstruction. Background Technology

[0002] Most commercially available finished tobacco products are a blend of shredded tobacco and expanded tobacco, containing a portion of stems and expanded stems. The addition of expanded tobacco and expanded stems effectively reduces the content of harmful components in the smoke while ensuring the finished tobacco's processing resistance. The different flavor profiles of cigarettes from different brands are the result of many factors. Among these, the varying blending ratios of shredded tobacco, stems, expanded tobacco, and expanded stems have a significant impact on the taste and flavor of the cigarette smoke.

[0003] Due to differences in composition and processing methods, the four materials—shredded tobacco, shredded stems, expanded tobacco, and expanded stems—have significantly different densities. The principle of CT imaging is that X-rays penetrate the object being measured, are attenuated, and are then received by a flat-panel detector and converted into data signals. Different objects have different attenuation coefficients for X-rays, resulting in different data signals after penetration. This allows for the differentiation of different materials in the reconstructed 2D CT images and 3D models. Because of their different densities, the attenuation coefficients of the four materials—shredded tobacco, shredded stems, expanded tobacco, and expanded stems—are also different, resulting in different grayscale values ​​in the reconstructed 2D CT images and 3D models. Therefore, different materials can be distinguished in the reconstructed 2D CT images and 3D models by adjusting the grayscale values.

[0004] Currently, the detection method for tobacco shreds, stems, expanded tobacco shreds, and expanded stems inside cigarettes is generally a manual sampling method. This involves manually cutting open the cigarette with a blade to separate the tobacco shreds, stems, expanded tobacco shreds, and expanded stems, and then visually inspecting them. This method is inefficient, unable to promptly and comprehensively detect the number of stems inside the cigarette. Furthermore, it is heavily influenced by the operator's subjective factors, as the criteria for distinguishing tobacco shreds, stems, expanded tobacco shreds, and expanded stems are greatly affected by the operator, making it difficult to ensure accuracy. Additionally, the cigarettes, having been cut open, are unusable after testing, resulting in a waste of raw tobacco materials. Therefore, researching an automated and accurate method for detecting tobacco shreds, stems, expanded tobacco shreds, and expanded stems in cigarettes to improve detection efficiency and reduce the error rate is of great significance to the industry's development. Summary of the Invention

[0005] The purpose of this invention is to address the problems of existing technologies by providing a method for detecting materials of different densities inside cigarettes based on industrial CT three-dimensional reconstruction. This method can solve the problems of low efficiency and high error rate in existing material detection. At the same time, since CT three-dimensional reconstruction technology is a non-destructive testing technology, it can effectively reduce cigarette loss and thus achieve higher economic benefits.

[0006] The objective of this invention is achieved through the following technical solution:

[0007] A method for detecting materials of different densities within cigarettes based on 3D reconstruction using industrial CT scans is proposed. This method digitizes the 3D structure of the cigarette using industrial CT scanning, obtains a 2D image of the tobacco distribution inside the cigarette using filtered back projection technology, and then generates a 3D reconstructed model of the cigarette using 3D reconstruction technology. Since X-rays attenuate as they pass through objects, and the four different materials—tobacco, stems, expanded tobacco, and expanded stems—attenuate X-rays to different degrees, resulting in different grayscale values ​​in the 3D reconstruction model, the method can identify tobacco, stems, expanded tobacco, and expanded stems in the cigarette sample based on these grayscale values. The specific steps are as follows:

[0008] (1) Using tobacco shreds, stem shreds, expanded tobacco shreds and expanded stem shreds as raw materials, respectively, they are rolled into standard samples that are consistent with the standard of the cigarette to be tested;

[0009] (2) Place the cigarette to be tested on the stage of the industrial CT equipment, use a clamp to keep it vertical and ensure that the tobacco part is within the CT scanning range;

[0010] (3) Start the industrial CT equipment to scan the cigarette, and the digital flat panel detector will transmit and save the received signal to the computer;

[0011] (4) The data processing system in the computer uses the filtered back projection technique (FDK algorithm) to process the acquired data and obtain a two-dimensional image of the cross-sectional slice inside the cigarette.

[0012] (5) The image processing system in the computer performs image matching, image smoothing, and image enhancement on the tomographic two-dimensional CT image sequence in order to extract edges; interpolates images between adjacent two-dimensional CT images to improve the accuracy of the three-dimensional reconstruction model; and finally reconstructs the three-dimensional model using the image processing system.

[0013] (6) Perform CT scanning three-dimensional reconstruction operation on the four standard samples prepared with tobacco shreds, stem shreds, expanded tobacco shreds and expanded stem shreds as raw materials, in the same way as steps (2)-(5) of the cigarette to be tested, to obtain the three-dimensional reconstruction model of the four standard samples.

[0014] (7) In the image processing system, multi-point gray value acquisition is performed on the three-dimensional reconstruction models of the four standard samples to obtain the gray value range of the four materials: tobacco shreds, stem shreds, expanded tobacco shreds and expanded stem shreds.

[0015] (8) In the image processing system, a gray-value-based ROI (region of interest) is created in the three-dimensional reconstruction model of the cigarette to be tested according to the obtained gray value range. Then, operations such as splitting ROI, merging ROI and correction are performed to further optimize the different material volumes obtained, and different colors can be used to render different material volumes.

[0016] (9) Calculate the volume data of different materials to obtain the volume ratio of four materials: tobacco shreds, stem shreds, expanded tobacco shreds and expanded stem shreds. Compare the ratio with the theoretical formula to obtain the conclusion of whether the actual cigarette meets the formula standard.

[0017] (10) Divide the three-dimensional reconstruction model into segments and calculate the volume ratio of four materials, namely tobacco, stem, expanded tobacco and expanded stem, in different segments. Determine whether the material ratio in different tobacco segments meets the formula standard. It can predict whether the smoke produced when the cigarette is burned meets the expected standard.

[0018] The advantages of this invention are: it can automatically and accurately detect tobacco shreds, stems, expanded tobacco shreds and expanded stems in cigarettes, with high detection efficiency and low error rate. At the same time, the method of this invention belongs to non-destructive testing technology, which can effectively reduce cigarette loss and is of great significance to the development of the industry. Attached Figure Description

[0019] Figure 1 This is a flowchart of a method for detecting materials of different densities inside cigarettes based on industrial CT 3D reconstruction.

[0020] Figure 2 A diagram of a cone-beam scanning structure with a flat panel detector;

[0021] Figure 2 In this context, γ is the angle between the ray and the central ray, β is the angle formed by the central ray and the y-axis, called the projection angle, and κ is the cone angle in the Z-axis direction of the cone beam.

[0022] In the figure, the ab coordinate system is the coordinate system on the virtual detector. In this patent, a, b and a(x, y, β) and b(x, y, z, β) are the same, all representing the coordinate information on the virtual detector. Among them, x, y, z, and β represent the expression factors of the ab coordinate system in the xyz coordinate system, that is, (a, b) can be transformed into (x, y, z) and express the same spatial position information in different coordinate systems.

[0023] Figure 3 This is a schematic diagram for identifying cigarette materials of different densities (grayscale values).

[0024] The image shows a section of a cigarette from a 3D reconstruction model of a cigarette. The outer transparent ring is the cigarette paper, and the four parts inside, red, yellow, blue, and green, are cigarette materials of different densities (grayscale values). Detailed implementation method:

[0025] The specific embodiments of the present invention will be further described in detail below (see [link]). Figure 1 ).

[0026] 1. Using tobacco shreds, stem shreds, expanded tobacco shreds, and expanded stem shreds as raw materials, standard samples are rolled into samples consistent with the standard of the cigarette to be tested. The tobacco shreds, stem shreds, expanded tobacco shreds, and expanded stem shreds in the standard samples are produced in the same process as those in the cigarette to be tested, which can ensure that the gray value measured by the standard samples can represent the gray value of the four materials in the sample to be tested.

[0027] 2. Place the cigarette to be tested on the stage of the CT equipment, keep it vertical with clamps and ensure that the tobacco part is within the CT scan range; the cigarette sample to be tested needs to be placed in the equilibration chamber for temperature and humidity equilibration before the experiment. The specific values ​​are: temperature 22℃, relative humidity 65%, equilibration time of more than 24 hours.

[0028] 3. Start the industrial CT equipment to scan the cigarette. The digital flat panel detector transmits and saves the received signals to the computer. Before scanning the cigarette, the industrial CT equipment needs to be pre-set with the following parameters: image size of 2048x2048, X-ray source tube voltage of 100kV, X-ray source tube current of 70uA, scanning thickness of 0.004mm, scanning interval of 0.004mm, CT scanning method of cone-beam scanning, and CT scanning mode of Normal scanning.

[0029] 4. The data processing system in the computer uses the Filtered Back Projection (FDK) algorithm to process the acquired data, obtaining a two-dimensional image of a cross-sectional slice inside the cigarette. The FDK algorithm mainly includes several steps: pre-weighting of the projection data, one-dimensional filtering, and back projection.

[0030] (1) First, the projection data is weighted using a function similar to cosine, and the distance and angle difference between the voxel and the source point are appropriately corrected.

[0031] (2) Then, perform one-dimensional filtering in the horizontal direction on the projection data of different projection angles;

[0032] (3) Perform a cone-beam weighted back projection on the filtered data. The weight function in the back projection depends on the distance from the reconstructed point to the focal point.

[0033] The FDK reconstruction algorithm for flat panel detectors can be expressed by the following formula:

[0034]

[0035]

[0036] Where R represents the radius of rotation. Let g(a) represent the filtered projection data, where g(a) is the filtering function. U(x, y, β) represents the distance of the reconstructed pixel in the xy plane to the X-ray source.

[0037] Here, a and b represent the coordinates on the virtual detector.

[0038]

[0039] a(x, y, β) represents the horizontal position of the corresponding ray on the virtual detector, and the corresponding vertical position can be represented as...

[0040]

[0041] The weighted function can be decomposed into the following expression:

[0042]

[0043] Z is the Z-axis coordinate of the point to be reconstructed. Similarly, we can obtain the length of U based on geometric relationships.

[0044] U(x,y,β)=R+xcosβ+ysinβ

[0045] The weighting factor U is similar to the weighting factor in the two-dimensional filtering back projection algorithm. Geometrically, it is related to the projection of the line connecting the ray source point and the reconstructed image onto the intermediate ray.

[0046] 5. The image processing system in the computer performs image matching, smoothing, and enhancement operations on the 2D CT image sequence to facilitate edge extraction and image segmentation; it also interpolates between adjacent 2D CT images to improve the accuracy of the 3D reconstruction model; finally, the image processing system reconstructs the 3D structural model. In CT scan images, the spacing in the X and Y directions is equal during sampling, with a larger difference only in the Z direction. Therefore, a linear interpolation is performed in the Z direction. The calculation formula is:

[0047]

[0048] In the formula, P1 and P2 are the CT values ​​of corresponding points in adjacent CT images, a1 and a2 are the Z-axis distances of the two corresponding points from the interpolation point, and P is the CT value of the interpolation point.

[0049] Multifractal spectrum technology is used to extract the internal and contour features of each cigarette CT image. The images are then analyzed using their visual appeal. The range of spectral values ​​in the multifractal spectrum theory is set, and the edges of the cigarette CT images are detected and extracted. The contour of the three-dimensional image is drawn using the edge information extracted from each cigarette CT image. The original cigarette CT image and the contour image extracted by using linear interpolation are then integrated to form a three-dimensional reconstruction model.

[0050] 6. Perform CT scanning three-dimensional reconstruction operation on the four standard samples prepared with tobacco shreds, stem shreds, expanded tobacco shreds and expanded stem shreds as raw materials, in the same way as steps (2)-(5) of the cigarette to be tested, to obtain the three-dimensional reconstruction model of the four standard samples; during the scanning process, all parameters of the equipment remain consistent.

[0051] 7. In the image processing system, the grayscale values ​​of the four standard samples are collected point by point in the three-dimensional reconstruction model to obtain the grayscale value range of the four materials: tobacco shreds, stem shreds, expanded tobacco shreds, and expanded stem shreds. Using the image processing system, the grayscale values ​​of multiple points are collected in different regions of these standard samples until all the collected grayscale values ​​are between the maximum and minimum values ​​of the collected grayscale values. Then the grayscale value range of the material in this three-dimensional reconstruction model can be determined.

[0052] 8. In the image processing system, a grayscale-based Region of Interest (ROI) is created in the 3D reconstruction model of the cigarette to be tested based on the acquired grayscale value range. Then, operations such as splitting, merging, and correcting the ROI are performed to further optimize the different material volumes obtained. Different material volumes can be rendered using different colors. Using the drawing function, an ROI encompassing the entire cigarette is drawn in the three-view diagram of the image processing system, and a grayscale value range is set based on the acquired data to obtain a rough ROI. The ROI splitting function is used to delete discontinuous small components in the ROI by specifying a minimum volume; only components with volumes greater than the specified minimum volume are saved in the new ROI. Then, the split ROIs are identified one by one, ROIs containing fragments are removed, and the remaining ROIs are merged to obtain the target material volume. Then, considering local grayscale gradients, the correction function is used to move the selected ROI boundaries, thereby producing more accurate ROI boundaries. Finally, the rendering function is used to render the selected ROIs with colors, thereby better distinguishing different materials (see...). Figure 3 ).

[0053] 9. Calculate the volume data of different materials to obtain the volume ratio of four materials: tobacco shreds, stem shreds, expanded tobacco shreds, and expanded stem shreds. Compare this ratio with the theoretical formula to determine whether the actual cigarette meets the formula standard. Use an image processing system to statistically analyze the volume of tobacco shreds, stem shreds, expanded tobacco shreds, and expanded stem shreds, and denote it as V. 烟 V 梗 V 膨烟 V 膨梗 Then, the volume percentage of different materials is calculated separately, as shown in the formula below; finally, the percentages are compared with those in the theoretical formula to evaluate whether the actual cigarettes meet the expectations.

[0054]

[0055]

[0056]

[0057]

[0058] The 3D reconstruction model is evenly divided into 10 segments. Similar to operation 7, the volume and volume ratio of the four materials, namely tobacco, stem, expanded tobacco and expanded stem, in different segments are statistically analyzed to determine whether the material ratio in different tobacco segments meets the formula standard. In turn, it can be predicted whether the smoke produced when the cigarette is burned meets the expected standard.

Claims

1. A method for detecting materials of different densities inside cigarettes based on three-dimensional reconstruction using industrial CT, characterized in that: The 3D structure of cigarettes is digitized using industrial CT scanning. A 2D image of the tobacco distribution inside the cigarette is obtained through filtered back projection technology, and a 3D reconstruction model of the cigarette is then generated. Since X-rays attenuate as they pass through objects, and the four different materials—tobacco, stems, expanded tobacco, and expanded stems—attenuate X-rays to different degrees, resulting in different grayscale values ​​in the 3D reconstruction model, the tobacco, stems, expanded tobacco, and expanded stems in the cigarette sample can be identified based on their grayscale values. The specific steps are as follows: (1) Using tobacco shreds, stem shreds, expanded tobacco shreds and expanded stem shreds as raw materials, respectively, they are rolled into standard samples that are consistent with the standard of the cigarette to be tested; (2) Place the cigarette to be tested on the stage of the industrial CT equipment, use a clamp to keep it vertical and ensure that the tobacco part is within the CT scanning range; (3) Start the industrial CT equipment to scan the cigarette, and the digital flat panel detector will transmit and save the received signal to the computer; (4) The data processing system in the computer uses filtering back projection technology to process the acquired data and obtain a two-dimensional image of the internal cross-section slice of the cigarette. (5) The image processing system in the computer performs image matching, image smoothing and image enhancement operations on the tomographic two-dimensional CT image sequence in order to perform edge extraction and image segmentation; interpolates images between adjacent two-dimensional CT images to improve the accuracy of the three-dimensional reconstruction model; finally, the three-dimensional model is reconstructed using the image processing system. (6) Perform CT scanning three-dimensional reconstruction operation on the four standard samples prepared with tobacco shreds, stem shreds, expanded tobacco shreds and expanded stem shreds as raw materials, in the same way as steps (2)-(5) of the cigarette to be tested, to obtain the three-dimensional reconstruction model of the four standard samples. (7) In the image processing system, multi-point gray value acquisition is performed on the three-dimensional reconstruction models of the four standard samples to obtain the gray value range of the four materials: tobacco shreds, stem shreds, expanded tobacco shreds and expanded stem shreds. (8) In the image processing system, a gray-value-based ROI is created in the three-dimensional reconstruction model of the cigarette to be tested according to the obtained gray value range. Then, the ROI splitting, ROI merging and correction operations are performed to further optimize the different material volumes obtained, and different colors are used to render the different material volumes. (9) Calculate the volume data of different materials to obtain the volume ratio of four materials: tobacco shreds, stem shreds, expanded tobacco shreds and expanded stem shreds. Compare the ratio with the theoretical formula to obtain the conclusion of whether the actual cigarette meets the formula standard. (10) Divide the three-dimensional reconstruction model into segments, calculate the volume ratio of four materials in different segments: tobacco shreds, stem shreds, expanded tobacco shreds and expanded stem shreds, determine whether the material ratio in different tobacco segments meets the formula standard, and predict whether the smoke produced when the cigarette is burned meets the expected standard.

2. The method for detecting materials of different densities inside a cigarette based on industrial CT three-dimensional reconstruction according to claim 1, characterized in that: In step (1), the tobacco shreds, stem shreds, expanded tobacco shreds and expanded stem shreds in the standard sample are produced in the same way as the tobacco shreds, stem shreds, expanded tobacco shreds and expanded stem shreds in the cigarette to be tested.

3. The method for detecting materials of different densities inside a cigarette based on industrial CT three-dimensional reconstruction according to claim 1, characterized in that: In step (2), the cigarette sample to be tested needs to be placed in a equilibration chamber for temperature and humidity equilibration before the experiment. The specific values ​​are: temperature 22℃, relative humidity 65%, and equilibration time of more than 24 hours.

4. The method for detecting materials of different densities inside a cigarette based on industrial CT three-dimensional reconstruction according to claim 1, characterized in that: The FDK algorithm in step (4) mainly includes several steps: pre-weighting of the projected data, one-dimensional filtering, and back projection. (1) First, the projection data is weighted using a function similar to cosine, and the distance and angle difference between the voxel and the source point are appropriately corrected. (2) Then, perform one-dimensional filtering in the horizontal direction on the projection data of different projection angles; (3) Perform a weighted back projection of the filtered data using a cone beam. The weight function in the back projection depends on the distance from the reconstructed point to the focal point. The FDK reconstruction algorithm for flat panel detectors can be expressed by the following formula: ； The weighting factor U is similar to the weighting factor in the two-dimensional filtering back projection algorithm. Geometrically, it is related to the projection of the line connecting the ray source point and the reconstructed image onto the intermediate ray.

5. The method for detecting materials of different densities inside a cigarette based on industrial CT three-dimensional reconstruction according to claim 1, characterized in that: The specific process of step (5) is as follows: In the CT scan image, the spacing in the X and Y directions is equal during sampling, while the spacing in the Z direction has a larger difference. Therefore, a linear interpolation is performed in the Z direction; the calculation formula is: ; In the formula, P1 and P2 are the CT values ​​of corresponding points in adjacent CT images, a1 and a2 are the Z-axis distances between the two corresponding points and the interpolation point, and P is the CT value of the interpolation point. Multifractal spectrum technology is used to extract the internal and contour features of each cigarette CT image. The images are then analyzed using their visual appeal. The range of spectral values ​​in the multifractal spectrum theory is set, and the edges of the cigarette CT images are detected and extracted. The contour of the three-dimensional image is drawn using the edge information extracted from each cigarette CT image. The original cigarette CT image and the contour image extracted by using linear interpolation are then integrated to form a three-dimensional reconstruction model.

6. The method for detecting materials of different densities inside a cigarette based on industrial CT three-dimensional reconstruction according to claim 1, characterized in that: In step (7), the gray values ​​of multiple points are collected in different areas of these standard samples using the image processing system until the collected gray values ​​are all between the maximum and minimum values ​​of the collected gray values. Then the gray value range of the material in this three-dimensional reconstruction model can be determined.

7. The method for detecting materials of different densities inside a cigarette based on industrial CT three-dimensional reconstruction according to claim 1, characterized in that: The specific process of step (8) includes: using the drawing function to draw an ROI containing the entire cigarette in the three views of the image processing system, and setting the gray value range according to the obtained data to obtain a rough ROI; using the split ROI function to delete small components that are not connected in the ROI, the method is to specify a minimum volume, and only components with a volume greater than the specified minimum volume will be saved in the new ROI; then identify the split ROI one by one, remove ROIs containing fragments, merge the remaining ROIs to obtain the target material volume; then consider the local gray value gradient, use the correction function to move the selected ROI boundary to generate a more accurate ROI boundary; finally, use the rendering function to render the selected ROI with color, so as to better distinguish different materials.

8. The method for detecting materials of different densities inside a cigarette based on industrial CT three-dimensional reconstruction according to claim 1, characterized in that: In step (9), the volume of tobacco shreds, stem shreds, expanded tobacco shreds and expanded stem shreds is counted by the image processing system, and then the volume ratio of different materials is calculated. Finally, the ratio is compared with the ratio in the theoretical formula to evaluate whether the actual cigarette meets the expectations.

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