A method for detecting and quantitatively characterizing the spatial morphology of tobacco shreds in cigarettes

Abstract

A method for detecting and quantitatively characterizing the spatial morphology of tobacco shreds in a cigarette is characterized by: defining a physical parameter S, namely the tobacco shred morphology index, and calculating the tobacco shred morphology index in the cigarette by measuring a three-dimensional reconstruction model. The advantages of this invention are: (1) the three-dimensional distribution state of tobacco shreds in a cigarette is detected by CT scanning three-dimensional reconstruction, and the results are real and reliable; (2) the tobacco shred morphology index defined by this method can better characterize the spatial distribution state of tobacco shreds in a cigarette; (3) this method can not only be used for quantitative analysis of the degree of spatial distribution state of tobacco shreds, but also provide guidance for the optimization and improvement of parameter conditions of different tobacco processing processes.

Description

Technical Field

[0001] This invention relates to the field of cigarette product testing technology, and in particular to a method for detecting and quantitatively characterizing the spatial morphology of tobacco shreds in a cigarette. Background Technology

[0002] The morphology of tobacco shreds in a cigarette is closely related to its quality indicators, such as density distribution, end-to-end shedding, and draw resistance, as well as the temperature distribution and smoke component release during combustion, and the sensory quality of the smoke. Especially with the rapid increase in the production and sales of slim cigarettes in recent years, the impact of tobacco morphology on cigarette quality has become more prominent due to the characteristics of slim cigarettes. The requirements and control over tobacco morphology during processing are more refined and stringent compared to conventional cigarettes. Currently, the main method for detecting tobacco morphology is image-based detection. This method requires the tobacco shreds to be displayed in the imaging area, where the morphology differs significantly from the actual morphology inside the cigarette. Furthermore, the features obtained by image-based methods are those of tobacco morphology in a two-dimensional image, which also differs from the actual three-dimensional morphology. Therefore, a new detection method is needed that can accurately and reliably reflect the morphological characteristics of tobacco shreds inside the cigarette. Summary of the Invention

[0003] The purpose of this invention is to address the shortcomings of existing technologies and provide a method for detecting and quantitatively characterizing the spatial morphology of tobacco shreds in cigarettes. This method defines a physical parameter S (tobacco morphology index) and calculates the tobacco morphology index in cigarettes by measuring a three-dimensional reconstruction model.

[0004] This invention achieves digitization of the three-dimensional structure of a cigarette through industrial CT scanning. It uses filtered back-projection technology to obtain a two-dimensional image of the tobacco distribution inside the cigarette. This two-dimensional image undergoes noise preprocessing to remove background noise. Then, a three-dimensional reconstruction model of the cigarette is obtained through three-dimensional reconstruction and interpolation techniques. This model reflects the morphology of the tobacco inside the cigarette, and finally, the tobacco morphology index is quantitatively characterized. The specific steps are as follows: 1. Place the cigarette to be tested on the stage of the industrial CT equipment, using clamps to maintain its vertical position and ensure the tobacco portion...

[0005] The area is within the CT scan range;

[0006] 2. Start the CT scanning device to scan the cigarette. The digital flat panel detector will transmit and save the received signals to the computer.

[0007] 3. The data processing system in the computer uses the Filtered Back Projection Algorithm (FDK algorithm) to process the acquired data and obtain a two-dimensional image of the distribution of tobacco shreds inside the cigarette.

[0008] The computer's image processing system performs image matching, image smoothing, and image enhancement on the sequence of two-dimensional CT images to facilitate edge extraction and image segmentation; it interpolates images between adjacent two-dimensional CT images to improve the accuracy of the three-dimensional reconstruction model; finally, the image processing system reconstructs the three-dimensional structural model and extracts the outline of the tobacco skeleton inside the cigarette.

[0009] Starting from one end of the tobacco shred and moving to the other end in units of voxels, the middle voxels of the long and short sides of the contour image are connected to each other in sequence, and the intersection of the two connecting lines is determined as the middle voxel. These middle voxels are combined to form a tobacco shred shape feature line: the width is 1 voxel and the length is n (≥5) voxels.

[0010] Starting from the first voxel at any end of the obtained tobacco shape feature line, draw a straight line ST1 connecting the first voxel to the third voxel, with the angle between ST1 and the central axis of the tobacco stick being θ1; draw a straight line ST2 connecting the third voxel to the fifth voxel, with the angle between ST2 and the central axis of the tobacco stick being θ2; and so on, drawing a straight line ST by connecting the (n-2)th voxel to the nth voxel. (n-1) / 2 Straight line ST (n-1) / 2 The angle between the cigarette and the central axis is θ (n-1) / 2 (If n is even, then draw a straight line connecting the last two voxel points (i.e., the (n-1)th and the nth voxel points).

[0011] Each straight line ST i The spatial angle between the direction vector and the direction vector (0, 0, 1) of the cigarette's central axis is calculated using the following formula:

[0012]

[0013] In the formula, k i For the straight line ST i The standard direction vector, k2 is the direction vector of the central axis (0, 0, 1), θ i It is the spatial angle.

[0014] Straight lines ST with the same spatial angle i The direction vectors are standardized for comparison, and the standard is whether the standard direction vectors are the same, and the line ST is compared. i Classify and count the number n of each category. j Then the correction coefficient for the spatial distribution of tobacco shreds is defined as follows: In the formula, n max For n j The maximum value in.

[0015] Each straight line ST in the statistical graph i Forming cosθ with the central axis of the cigarettei The tobacco morphology index S is calculated using the following formula. j ;

[0016]

[0017] In the formula, S j Cosθ is the tobacco morphology index, with a unit of 1. i ST is the straight line in the tobacco shape feature line. i The cosine of the spatial angle between the cigarette and the central axis, in units of 1; n≥5 and if n is even, then let

[0018] n = n + 1.

[0019] The cigarettes being measured can be slim cigarettes, medium-length cigarettes, short cigarettes, and regular cigarettes.

[0020] The cigarette imaging technology employs X-ray transmission imaging and three-dimensional reconstruction techniques.

[0021] The advantages of this invention are: (1) the three-dimensional distribution of tobacco in cigarettes is detected by CT scanning three-dimensional reconstruction method, and the results are real and reliable; (2) the tobacco morphology index defined by this method can better characterize the spatial distribution of tobacco in cigarettes; (3) this method can not only be used for quantitative analysis of the degree of spatial distribution of tobacco, but also provide guidance for the optimization and improvement of the parameter conditions of different tobacco processing processes. Attached Figure Description

[0022] Figure 1 A flowchart of the method for detecting and quantitatively characterizing the spatial distribution of tobacco shreds in a cigarette provided by the present invention;

[0023] Figure 2 This is a schematic diagram showing the spatial distribution of tobacco shreds within a cigarette segment.

[0024] Figure 3 This diagram illustrates the spatial distribution of a single tobacco shred, and is used as an appendix to the abstract.

[0025] Figure 4 A diagram of a cone-beam scanning structure with a planar detector;

[0026] In the figure, 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.

[0027] 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 converted to (x,y,z) and express the same spatial position information in different coordinate systems. Detailed Implementation

[0028] The specific embodiments of the present invention will be further described in detail below with reference to the accompanying drawings.

[0029] 1. Place the cigarette to be tested on the stage of the industrial CT equipment, keep it vertical with clamps and ensure that the tobacco part is within the CT scanning 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.

[0030] 2. Start the CT scanning device 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.

[0031] 3. 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 the distribution of tobacco shreds inside the cigarette. The FDK algorithm mainly includes several steps: pre-weighting of the projection data, one-dimensional filtering, and back projection.

[0032] (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.

[0033] (2) Then, perform one-dimensional filtering in the horizontal direction on the projection data of different projection angles;

[0034] (3) Perform a weighted back projection of the filtered data using a cone-beam array. The weight function in the back projection depends on the distance from the reconstructed point to the focal point. See the attached diagram for a cone-beam scanning structure with a planar detector. Figure 4 .

[0035] The FDK reconstruction algorithm for flat panel detectors can be expressed by the following formula:

[0036]

[0037]

[0038] Where R represents the radius of rotation. b(x,y,z,β)) represents the filtered projection data, g(a) is the filtering function, and U(x,y,β)) represents the distance of the reconstructed pixel from the X-ray source in the xy plane.

[0039] Here, a and b represent the coordinates on the virtual detector.

[0040]

[0041] 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...

[0042] for

[0043]

[0044] The weighted function can be decomposed into the following expression:

[0045]

[0046] Z is the Z-axis coordinate of the point to be reconstructed. Similarly, we can obtain the length of U based on geometric relationships.

[0047] U(x,y,β)=R+xcosβ+ysinβ

[0048] 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.

[0049] 4. 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 significant difference only in the Z direction. Therefore, a process is performed in the Z direction...

[0050] Linear interpolation. The calculation formula is:

[0051]

[0052] 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.

[0053] Multifractal spectrum technology is used to extract the internal and contour features of each cigarette CT image. The images are then analyzed using their intuitiveness. 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, and the contour of the tobacco skeleton inside the cigarette is extracted.

[0054] 5. Starting from one end of the tobacco shred and moving towards the other end in units of voxels, connect the middle voxels of the long and short sides of the contour image in sequence and determine the intersection of the two connecting lines as the middle voxel points. These middle voxels are combined to form a tobacco shred shape feature line: the width is 1 voxel point and the length is n (≥5) voxels points.

[0055] 6. Starting from any end of the obtained tobacco shape feature line, at the first voxel point, draw a straight line ST1 connecting the first voxel point to the third voxel point, with the angle between ST1 and the central axis of the tobacco stick being θ1; then, starting from the third voxel point, draw a straight line ST2 connecting the fifth voxel point, with the angle between ST2 and the central axis of the tobacco stick being θ2; and so on, drawing a straight line ST by connecting the nth voxel point to the nth voxel point starting from the (n-2)th voxel point. (n-1) / 2 Straight line ST (n-1) / 2 The angle between the cigarette and the central axis is θ (n-1) / 2 (If n is even, then draw a straight line connecting the last two voxel points (i.e., the (n-1)th and nth voxel points). Industrial CT equipment can obtain the overall point cloud data of a cigarette by scanning it, which includes three-dimensional coordinates X, Y, Z, etc., and utilizes the points...

[0056] Cloud data can obtain the specific coordinates of voxels and thus obtain the ST of each straight line. i The expression for and its direction vector.

[0057] 7. Adjust each straight line ST i Spatially sandwiched between the direction vector and the direction vector (0, 0, 1) of the cigarette's central axis.

[0058] Angle calculation, the formula is as follows:

[0059]

[0060] In the formula, k i For the straight line ST i The standard direction vector is k2, the direction vector of the central axis is (0, 0, 1), and θ is the spatial angle. Additionally, 0 <cosθ i <1, cosθ i The closer the value is to 0, the more the straight line ST... i The more perpendicular to the central axis;

[0061] cosθ i The closer the value is to 1, the more straight line ST becomes. i The more parallel to the central axis.

[0062] 8. Compare the standard direction vectors of tobacco feature lines with the same spatial angle. Based on whether the standard direction vectors are the same, classify the tobacco feature lines and count their number n. j Then the correction coefficient for the spatial distribution of tobacco shreds is defined as follows: In the formula, n max For n j The maximum value in the equation. As can be seen from the three-dimensional geometry of a cone, any generatrix on the cone makes the same spatial angle with the central axis. However, it can be observed that generatrixes with the same spatial angle have different spatial distributions. Therefore, after classifying different tobacco shreds using spatial angles, the shreds with the same spatial angle need to be further subdivided to obtain a precise value for the spatial distribution of the tobacco shreds.

[0063] 9. The straight lines ST in the statistical graph i Forming cosθ with the central axis of the cigarette i The tobacco morphology index S is calculated using the following formula. j ;

[0064]

[0065] In the formula, S j Cosθ is the tobacco morphology index, with a unit of 1. i ST is the straight line in the tobacco shape feature line. i The cosine of the spatial angle between the cigarette and the central axis, in units of 1; n≥5 and if n is even, let n=n+1.

[0066] From the above formula, we can obtain that 0 j <1,S j The closer to 0, the more complex the shape of the tobacco shreds, and the more bends they have; S j The closer the value is to 1, the simpler the tobacco morphology and the fewer the bends. Normal tobacco should be in a balanced state, possessing both a suitable amount of bend to achieve the desired processing performance and a relatively simple overall structure to facilitate smoke flow. Furthermore, different types of cigarettes have different tobacco morphology indices (S) due to their different processing methods and desired smoke characteristics. j They are not the same and need to be analyzed specifically according to the type of cigarette.​

Claims

1. A method for detecting and quantitatively characterizing the spatial morphology of tobacco shreds in a cigarette, characterized in that... This method defines a physical parameter S, namely the tobacco morphology index, and calculates the tobacco morphology index in the cigarette by measuring a three-dimensional reconstruction model. The specific steps are as follows: 1) Place the cigarette to be tested on the stage of the industrial CT equipment, keep it vertical with clamps and ensure that the tobacco part is within the CT scanning range; 2) Start the CT scanning device to scan the cigarette. The digital flat panel detector will transmit and save the received signals to the computer. 3) The data processing system in the computer uses a filtering back projection algorithm to process the acquired data and obtain a two-dimensional image of the distribution of tobacco inside the cigarette. 4) The computer's image processing system performs image matching, image smoothing, and image enhancement operations on the two-dimensional CT image sequence to facilitate edge extraction and image segmentation; it interpolates images between adjacent two-dimensional CT images to improve the accuracy of the three-dimensional reconstruction model; finally, the image processing system reconstructs the three-dimensional structural model and extracts the outline of the tobacco skeleton inside the cigarette. 5) Starting from one end of the tobacco shred and moving towards the other end in units of voxels, connect the middle voxels of the long and short sides of the contour image in sequence and determine the intersection of the two connecting lines as the middle voxel points. These middle voxels are combined to form a tobacco shred shape feature line: the width is 1 voxel point and the length is n≥5 voxels. 6) Starting from the first voxel at any end of the obtained tobacco shape feature line, draw a straight line ST1 connecting the first voxel to the third voxel, with the angle between ST1 and the central axis of the tobacco stick being θ1; draw a straight line ST2 connecting the third voxel to the fifth voxel, with the angle between ST2 and the central axis of the tobacco stick being θ2; and so on, drawing a straight line ST by connecting the (n-2)th voxel to the nth voxel. （n-1） / 2 Straight line ST （n-1） / 2 The angle between the cigarette and the central axis is θ （n-1） / 2 If n is even, then draw a straight line connecting the last two voxel points, i.e., the (n-1)th and the nth voxel points. 7) Set each straight line ST i The spatial angle between the direction vector and the direction vector (0, 0, 1) of the cigarette's central axis is calculated using the following formula: ； In the formula, k i For the straight line ST i The standard direction vector, k2 is the direction vector of the central axis (0, 0, 1), θ i It is the included angle in space; 8) Straight lines ST with the same spatial angle i The direction vectors are standardized for comparison, and the standard is whether the standard direction vectors are the same, and the line ST is compared. i Classify and count the number n of each category. j Then the correction coefficient for the spatial distribution of tobacco shreds is defined as follows: ； In the formula, n max For n j The maximum value in; 9) Statistical analysis of each straight line ST in the graph i Forming cosθ with the central axis of the cigarette i The tobacco morphology index S is calculated using the following formula. j： ； In the formula, S j Cosθ is the tobacco morphology index, with a unit of 1. i ST is the straight line in the tobacco shape feature line. i The cosine of the spatial angle between the cigarette and the central axis, in units of 1; n≥5 and if n is even, let n=n+1.

2. The method for detecting and quantitatively characterizing the spatial morphology of tobacco shreds in a cigarette according to claim 1, characterized in that: In step 1), the cigarette sample to be tested needs to be placed in an 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.

3. The method for detecting and quantitatively characterizing the spatial morphology of tobacco shreds in a cigarette according to claim 1 or 2, characterized in that: The cigarettes to be tested are slim cigarettes, medium-length cigarettes, or regular cigarettes.

4. The method for detecting and quantitatively characterizing the spatial morphology of tobacco shreds in a cigarette according to claim 1, characterized in that: The CT equipment is set with the following parameters: image size of 2048x2048 for dedicated cigarette structure scanning, X-ray source tube voltage of 100 kV, X-ray source tube current of 70 uA, scanning thickness of 0.004 mm, scanning interval of 0.004 mm, CT scanning mode of cone-beam scanning, and CT scanning mode of Normal scanning.

5. The method for detecting and quantitatively characterizing the spatial morphology of tobacco shreds in a cigarette according to claim 1, characterized in that: Step 3) of the filtering back projection algorithm mainly includes several steps: pre-weighting of the projection 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 voxels and the source point are appropriately corrected; (2) Then, one-dimensional filtering is performed on the projection data at different projection angles in the horizontal direction; (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. The FDK reconstruction algorithm for flat panel detectors can be expressed by the following formula: Where R represents the radius of rotation. This represents the filtered projection data, where g(a) is the filtering function. () represents the distance of the reconstructed pixel in the xy plane to the X-ray source; This represents the horizontal position of the corresponding ray on the virtual detector, and the corresponding vertical position can be represented as... The weighted function can be decomposed into the following expression: Z is the Z-axis coordinate of the point to be reconstructed. Similarly, we can obtain the length of U based on geometric relationships. 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.

6. The method for detecting and quantitatively characterizing the spatial morphology of tobacco shreds in a cigarette according to claim 1, characterized in that: Step 4) involves the following process: In the CT scan image, the spacing in the X and Y directions is equal during sampling, while the spacing in the Z direction differs significantly. Therefore, a linear interpolation is performed in the Z direction, calculated using the following formula: 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 intuitiveness. 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, and the contour of the tobacco skeleton inside the cigarette is extracted.

Images