Paper fiber raw material and proportion analysis method based on dyeing method and image recognition technology

Abstract

The invention provides a paper fiber raw material and proportion analysis method based on a dyeing method and an image recognition technology, and the analysis method comprises the following steps: dyeing a paper fiber raw material suspension by using a dye to obtain a dyed sample; acquiring an image of the dyed sample by using an imaging device to obtain a dyed fiber image; preprocessing the dyed fiber image, and converting a color space into an HSV color space; extracting and separating fibers in the dyed fiber image by using a color threshold method, and counting the number of pixels of each fiber; and calculating the mass ratio of each fiber according to the pixel number of each fiber. According to the analysis method, color space conversion and threshold segmentation are carried out on the obtained dyeing image, and different types of fibers are effectively separated and extracted, so that the types and proportions of paper fiber raw materials are accurately identified.

Description

Technical Field

[0001] The invention belongs to the field of image recognition analysis and relates to a paper fiber raw material and ratio analysis method based on a dyeing method and image recognition technology. Background Art

[0002] Paper fibers contain a wide variety of fiber types, typically including softwood, hardwood, and bast fibers. Different fiber types possess distinct characteristics. For example, hardwood fibers are typically thin and short, while softwood fibers exhibit elongated, tubular cells with slightly pointed ends. Different fiber types can be distinguished solely based on their morphological characteristics. Common analytical techniques include fiber morphology analyzers (FQA) and optical microscopy. However, these methods have limitations when dealing with complex and large samples, making accurate analysis difficult. While traditional staining methods have made some progress, such as using alkaline dyes to dye different fiber types in different colors for easier identification, the complex composition of paper fibers, often involving multiple fiber sources, makes it difficult to accurately identify all fiber types with a single dye. Therefore, there is a pressing need for combining other methods to improve identification accuracy. In this context, the Graff "C" staining method, due to its excellent performance in staining wood pulp fibers, has become an effective option, effectively distinguishing between softwood and hardwood pulps. However, the subsequent process of using Image J software to measure relevant parameters of the stained images is cumbersome, time-consuming and labor-intensive, and is also greatly affected by subjective factors. Summary of the Invention

[0003] In order to solve the technical problems existing in the prior art, the present invention provides a paper fiber raw material and ratio analysis method based on dyeing method and image recognition technology. The analysis method performs color space conversion and threshold segmentation on the acquired dyeing image, effectively separates and extracts different types of fibers, thereby realizing accurate identification of the types and ratios of paper fiber raw materials.

[0004] In order to achieve the above technical effects, the present invention adopts the following technical solutions:

[0005] The present invention provides a paper fiber raw material and ratio analysis method based on a dyeing method and image recognition technology, the analysis method comprising:

[0006] Performing a first dyeing on the paper fiber raw material suspension using a first dye to obtain a first dyed sample;

[0007] performing a second dyeing on the paper fiber raw material suspension using a second dye to obtain a second dyed sample;

[0008] Using an imaging device to independently acquire images of the first dyed sample and the second dyed sample, respectively, to obtain a first dyed fiber image and a second dyed fiber image;

[0009] Preprocessing the first dyed fiber image and / or the second dyed fiber image, and converting the color space into an HSV color space;

[0010] extracting and separating fibers from the first dyed fiber image and / or the second dyed fiber image using a color threshold method, and counting the number of pixels of each fiber;

[0011] The mass proportion of each fiber is calculated according to the number of pixels of each fiber.

[0012] As a preferred technical solution of the present invention, the first dye includes Herzberg dye, and the second dye includes Graff "C" dye.

[0013] As a preferred technical solution of the present invention, the imaging device includes an optical microscope.

[0014] As a preferred technical solution of the present invention, the preprocessing includes adjusting the saturation gain factor and the brightness gain factor of the first dyed fiber image and / or the second dyed fiber image.

[0015] As a preferred technical solution of the present invention, the saturation gain factor of the first dyed fiber image is adjusted to 1.0-2.0, and the brightness gain factor is adjusted to 1.0-1.5.

[0016] As a preferred technical solution of the present invention, the saturation gain factor of the second dyed fiber image is adjusted to 1.0-3.0, and the brightness gain factor is adjusted to 1.0-1.5.

[0017] As a preferred technical solution of the present invention, after converting the color space into the HSV color space, the maximum and minimum values of the hue, saturation and brightness of the image are adjusted.

[0018] As a preferred technical solution of the present invention, a color threshold method is used to extract all fibers and dyed fibers in the first dyed fiber image and / or the second dyed fiber image.

[0019] As a preferred technical solution of the present invention, image processing software is used to adjust the image obtained after extraction and separation using the color threshold method.

[0020] As a preferred technical solution of the present invention, the formulas for calculating the mass proportion of each fiber are shown in Formulas 1, 2 and 3:

[0021]

[0022] Among them, Xn : mass percentage; f n : fiber quality factor; C n : Fiber thickness, unit is mg / m; N n : total length of the fiber, in mm; Average quality factor of mixed fibers; N 总 : The total length of all types of fibers, in mm; M n : pixel area of fiber; W n : Width of the fiber, in μm.

[0023] Compared with the prior art, the present invention has at least the following beneficial effects:

[0024] (1) The present invention provides a paper fiber raw material and ratio analysis method based on dyeing method and image recognition technology. Compared with the method of measuring fiber length using Image J software, this analysis method significantly improves the analysis efficiency and saves time and labor costs.

[0025] (2) The present invention provides a method for analyzing paper fiber raw materials and their proportions based on dyeing and image recognition technology. Compared with the observation method, this analysis method is based on color constancy and adopts a unified measurement standard, which greatly enhances the scientificity and reliability of the results.

[0026] (3) The present invention provides a paper fiber raw material and ratio analysis method based on dyeing method and image recognition technology. The analysis method reduces the impact on the results from the observation perspective and reduces the interference of human factors by using the color threshold method.

[0027] (4) The present invention provides a paper fiber raw material and ratio analysis method based on dyeing method and image recognition technology. Compared with the morphological observation method under a microscope and the fiber morphology analyzer method, the analysis process of this analysis method is simpler, the cost is lower, and the results are more comprehensive.

[0028] (5) The present invention provides a paper fiber raw material and ratio analysis method based on dyeing method and image recognition technology. The analysis method has simple steps, low detection cost, and the analysis results have a high accuracy rate. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 This is a picture of the mixed pulp of coniferous pulp and broadleaf pulp in Example 1 collected under an optical microscope.

[0030] Figure 2a This is a picture of all fibers after separation and extraction in Example 1.

[0031] Figure 2b This is a picture of the broadleaf pulp fiber separated and extracted in Example 1.

[0032] Figure 3 This is a picture of the mixed pulp of coniferous pulp and broadleaf pulp in Example 2 collected under an optical microscope.

[0033] Figure 4a This is a picture of all fibers after separation and extraction in Example 2.

[0034] Figure 4b This is a picture of the broadleaf pulp fibers separated and extracted in Example 2.

[0035] Figure 5 This is a picture of the mixed pulp of coniferous pulp and hemp pulp in Example 3 collected under an optical microscope.

[0036] Figure 6a This is a picture of all fibers after separation and extraction in Example 3.

[0037] Figure 6b This is a picture of the coniferous pulp fiber separated and extracted in Example 3.

[0038] Figure 7 This is a picture of the mixed pulp of coniferous pulp and hemp pulp in Example 4 collected under an optical microscope.

[0039] Figure 8a This is a picture of all fibers after separation and extraction in Example 4.

[0040] Figure 8b This is a picture of the coniferous pulp fiber separated and extracted in Example 4.

[0041] Figure 9a This is a picture of the mixed pulp of coniferous pulp, hardwood pulp and hemp pulp in Example 5 collected under an optical microscope (stained with Herzberg stain).

[0042] Figure 9b This is a picture of the mixed pulp of coniferous pulp, hardwood pulp and hemp pulp in Example 5 collected under an optical microscope (stained with Graff "C" dye).

[0043] Figure 10a This is a picture of all fibers after separation and extraction, stained with Herzberg stain in Example 5.

[0044] Figure 10b This is a picture of the wood pulp fibers obtained by separation and extraction from the picture dyed with Herzberg dye in Example 5.

[0045] Figure 11a This is a picture of all fibers after separation and extraction using Graff "C" stain in Example 5.

[0046] Figure 11b This is a picture of the hardwood pulp fibers obtained by separation and extraction using Graff "C" dye in Example 5.

[0047] Figure 12a This is a picture of the mixed pulp of coniferous pulp, hardwood pulp and hemp pulp in Example 6 collected under an optical microscope (stained with Herzberg stain).

[0048] Figure 12b This is a picture of the mixed pulp of coniferous pulp, hardwood pulp and hemp pulp in Example 6 collected under an optical microscope (stained with Graff "C" dye).

[0049] Figure 13a This is a picture of all fibers after separation and extraction, stained with Herzberg stain in Example 6.

[0050] Figure 13b This is a picture of the wood pulp fibers obtained by separation and extraction using the Herzberg dye in Example 6.

[0051] Figure 14a This is a picture of all fibers after separation and extraction using Graff "C" stain in Example 6.

[0052] Figure 14b This is a picture of the hardwood pulp fibers obtained by separation and extraction using Graff "C" dye in Example 6.

[0053] The present invention is further described in detail below. However, the following examples are merely simplified examples of the present invention and do not represent or limit the scope of protection of the present invention. The scope of protection of the present invention shall be subject to the claims. DETAILED DESCRIPTION

[0054] The technical solution of this application is further explained below through specific implementation methods.

[0055] A specific embodiment of the present invention provides a paper fiber raw material and ratio analysis method based on dyeing method and image recognition technology, the analysis method comprising:

[0056] Performing a first dyeing on the paper fiber raw material suspension using a first dye to obtain a first dyed sample;

[0057] performing a second dyeing on the paper fiber raw material suspension using a second dye to obtain a second dyed sample;

[0058] Using an imaging device to independently acquire images of the first dyed sample and the second dyed sample, respectively, to obtain a first dyed fiber image and a second dyed fiber image;

[0059] Preprocessing the first dyed fiber image and / or the second dyed fiber image, and converting the color space into an HSV color space;

[0060] extracting and separating fibers from the first dyed fiber image and / or the second dyed fiber image using a color threshold method, and counting the number of pixels of each fiber;

[0061] The mass proportion of each fiber is calculated according to the number of pixels of each fiber.

[0062] In one embodiment of the present invention, the first dye comprises Herzberg stain and the second dye comprises Graff "C" stain.

[0063] In one embodiment of the present invention, the formula of Herzberg stain includes ZnCl2 solution, iodine solution and solid iodine element. For example, it can be 15mL ZnCl2 solution, 5mL iodine solution and small piece iodine 0.05~0.1g, preferably 0.05g.

[0064] In one embodiment of the present invention, the ZnCl2 solution is prepared as 18-22 g of anhydrous ZnCl2, and the solvent is 10 mL of water, preferably 20 g of anhydrous ZnCl2.

[0065] In one embodiment of the present invention, the iodine solution is 2.1 g KI and 0.1 g I2, and the solvent is 4 to 6 mL water, preferably 5 mL water.

[0066] In one embodiment of the present invention, the Graff "C" stain comprises an AlCl solution, a CaCl solution, a ZnCl solution, an iodine solution, and solid iodine. For example, the composition may comprise 20 mL of AlCl solution, 10 mL of CaCl solution, 10 mL of ZnCl solution, 12.5 mL of iodine solution, and 0.03-0.08 g of a small iodine flake.

[0067] In one embodiment of the present invention, the AlCl3 solution comprises 38-44 g AlCl3, and the solvent is 100 mL water, preferably 40 g AlCl3.

[0068] In one embodiment of the present invention, the CaCl2 solution comprises 98-104 g of CaCl2, and the solvent is 150 mL of water, preferably 100 g of CaCl2.

[0069] In one embodiment of the present invention, the ZnCl2 solution comprises 98-104 g ZnCl2, and the solvent is 50 mL water, preferably 100 g ZnCl2.

[0070] In one embodiment of the present invention, the iodine solution is 0.9 g KI and 0.65 g I2, and the solvent is 40 to 50 mL water, preferably 50 mL water.

[0071] In one embodiment of the present invention, the first staining method comprises diluting the Herzberg stain to 70% to 95% of the original concentration and staining for 10 to 40 seconds. Preferably, the Herzberg stain is diluted to 90% of the original concentration and staining for 20 seconds.

[0072] In one embodiment of the present invention, the second staining method comprises diluting Graff "C" stain to 75% to 95% of the original concentration and staining for 20 to 50 seconds. Preferably, diluting Graff "C" stain to 90% of the original concentration and staining for 30 seconds.

[0073] In one embodiment of the present invention, the imaging device comprises an optical microscope. Any optical microscope that can obtain an image that can clearly identify dyed fibers is applicable to the present analysis method, and is not further limited herein.

[0074] In one embodiment of the present invention, the preprocessing includes adjusting the saturation gain factor and the brightness gain factor of the first dyed fiber image and / or the second dyed fiber image.

[0075] In one embodiment of the present invention, the first dyed fiber image is adjusted, that is, the saturation gain factor of the image obtained by optical microscopy after the first dyeing using Herzberg dye is adjusted to 1.0-2.0, and the brightness gain factor is adjusted to 1.0-1.5. Among them, the saturation gain factor can be 1.0, 1.1, 1.2, 1.3, 1.4, 1.5, 1.6, 1.7, 1.8, 1.9 or 2.0, etc., and the brightness gain factor can be 1.0, 1.1, 1.2, 1.3, 1.4 or 1.5, etc., but are not limited to the listed values. Other values not listed in this numerical range are also applicable. Preferably, the saturation gain factor is adjusted to 1.5 and the brightness gain factor is adjusted to 1.1.

[0076] In one embodiment of the present invention, the saturation gain factor of the second dyed fiber image, that is, the saturation gain factor of the image obtained by optical microscopy after the first dyeing using Graff "C" dye is adjusted to 1.0-3.0, and the brightness gain factor is adjusted to 1.0-1.5. Among them, the saturation gain factor can be 1.0, 1.2, 1.5, 1.8, 2.0, 2.2, 2.5, 2.8 or 3.0, etc., and the brightness gain factor can be 1.0, 1.1, 1.2, 1.3, 1.4 or 1.5, etc., but are not limited to the listed values. Other values not listed within this numerical range are also applicable. Preferably, the saturation gain factor is adjusted to 2.0 and the brightness gain factor is adjusted to 1.1.

[0077] In one embodiment of the present invention, the saturation gain factor and brightness gain factor of the first dyed fiber image and / or the second dyed fiber image can be adjusted using mathematical software or image analysis software, such as Matlab software. The specific method for adjusting the saturation gain factor and brightness gain factor of an image using Matlab software is a known method for using Matlab software, and the steps are not further defined herein.

[0078] In a specific embodiment of the present invention, after the color space is converted into the HSV color space, the maximum and minimum values of the hue, saturation, and brightness of the image are adjusted.

[0079] In one embodiment of the present invention, mathematical software or image analysis software can be used to perform HSV color space conversion and adjust the maximum and minimum values of hue, saturation, and lightness. For example, Matlab software can be used. The specific method of using Matlab software to perform HSV color space conversion of an image and adjust the maximum and minimum values of hue, saturation, and lightness is a known method for using Matlab software, and the steps are not further defined herein.

[0080] In a specific embodiment of the present invention, a color threshold method is used to extract all fibers and dyed fibers in the first dyed fiber image and / or the second dyed fiber image.

[0081] In a specific embodiment of the present invention, the color threshold method refers to limiting the hue, saturation and brightness of the target color by thresholds, generating a binary mask through logical operations, and the pixels that meet the threshold range are white, and the rest are black. The mask and the original image are bit-wise operated to obtain the segmented image.

[0082] In one embodiment of the present invention, the color threshold method can be performed using mathematical software or image analysis software, such as Matlab software.

[0083] In one embodiment of the present invention, image processing software, such as Photoshop, is used to fine-tune the image obtained after extraction and separation using the color thresholding method. The fine-tuning can specifically address issues with pixel attribution in areas of fiber breakage or adhesion after binarization. To improve the accuracy of the method, fibers that were not clearly extracted are corrected using manual tools in Photoshop.

[0084] In one embodiment of the present invention, the formulas for calculating the mass proportion of each fiber are shown in Formulas 1, 2, and 3:

[0085]

[0086] Among them, X n : mass percentage; f n : fiber quality factor; C n : Fiber thickness, unit is mg / m; N n : total length of the fiber, in mm; Average quality factor of mixed fibers; N 总 : The total length of all types of fibers, in mm; M n : pixel area of fiber; W n : Width of the fiber, in μm.

[0087] In one embodiment of the present invention, the average quality factor of the mixed fiber is The calculation method is that the average quality factor of the mixed fiber = the coarseness of the mixed fiber / 0.18. The coarseness index can be measured according to the FQA instrument.

[0088] To better illustrate the present invention and facilitate understanding of the technical solutions of the present invention, typical but non-limiting embodiments of the present invention are as follows:

[0089] Example 1

[0090] This embodiment provides a paper fiber raw material and ratio analysis method based on dyeing method and image recognition technology, which includes:

[0091] Weigh 0.1 g of bone-dry pulp (coniferous to hardwood pulp, mass ratio 2:3) to prepare a 0.01% fiber suspension. Two drops were placed on the center of a glass slide and dried in an oven at 65°C. The suspension was first stained with Herzberg dye diluted to 85% of its original concentration for 20 seconds. A microscopic specimen was prepared and images were collected under an optical microscope.

[0092] Two drops of the suspension were then placed on the center of a glass slide and dried in an oven at 65°C. The slide was then stained with Graff "C" dye diluted to 80% of its original concentration for 20 seconds. A microscopic specimen was prepared and imaged using an optical microscope. The Herzberg-stained fibers all appeared blue, indicating the absence of hemp pulp. Therefore, only the Graff "C"-stained fibers were analyzed.

[0093] Select 10 images stained with Graff "C" ( Figure 1 ), the collected fiber images were preprocessed in MATLAB software. For the images dyed with Graff "C" dye, the saturation gain factor was adjusted to 2.0 and the brightness gain factor was adjusted to 1.5. The color space was converted to HSV color space, and the min and max values of H, S, and V were adjusted. Figure 2a and Figure 2bThe color threshold method is used to extract all types of fibers and blue-gray fibers (blue-gray fibers are hardwood pulp fibers).

[0094] The separated images were fine-tuned in Photoshop to improve extraction accuracy. The pixel counts for each fiber type were then counted. Analyzing the pixel counts for all fiber types and hardwood pulp fibers revealed a mass ratio of 53.85% for hardwood pulp and 46.15% for softwood pulp (100% minus the mass ratio for hardwood pulp). Calculating the relative error for each fiber type yielded an average error of 12.82% and an accuracy of 87.18% (corresponding to data set 3 in Table 1).

[0095] The original Herzberg stain formula is a mixture of 15 mL of ZnCl2 solution (19 g ZnCl2 dissolved in 10 mL water) and an iodine solution (2.1 g KI and 0.1 g I2 dissolved in 5 mL water), followed by the addition of 0.1 g iodine. The Graff "C" stain formula is a mixture of 20 mL of AlCl3 solution (40 g AlCl3 dissolved in 100 mL water), 10 mL of CaCl2 solution (99 g CaCl2 dissolved in 150 mL water), 10 mL of ZnCl2 solution (100 g pure ZnCl2 dissolved in 50 mL water), and 12.5 mL of iodine solution (0.9 g KI and 0.65 g I2 dissolved in 45 mL water), followed by the addition of 0.05 g iodine.

[0096] Example 2

[0097] This embodiment provides a paper fiber raw material and ratio analysis method based on dyeing method and image recognition technology, which includes:

[0098] Weigh 0.1 g of bone-dry pulp (coniferous to hardwood pulp, mass ratio 3:2) to prepare a 0.01% fiber suspension. Two drops were placed on the center of a glass slide and dried in an oven at 65°C. The suspension was first stained with Herzberg dye diluted to 85% of its original concentration for 30 seconds. A microscopic specimen was prepared and images were collected under an optical microscope.

[0099] Two drops of the suspension were then placed on the center of a glass slide and dried in an oven at 65°C. The slide was then stained with Graff "C" dye diluted to 90% of its original concentration for 20 seconds. A microscopic specimen was prepared and imaged using an optical microscope. Observation of the image revealed that the Herzberg-stained fibers all exhibited a blue hue, indicating the absence of hemp pulp fibers. Therefore, only the Graff "C"-stained fiber images were required for analysis.

[0100] Select 10 images stained with Graff "C" ( Figure 3), the collected fiber images were preprocessed in MATLAB software. For the images dyed with Graff "C" dye, the saturation gain factor was adjusted to 3.0 and the brightness gain factor was adjusted to 1.1. The color space was converted to HSV color space, and the min and max values of H, S, and V were adjusted. Figure 4a and Figure 4b The color threshold method is used to extract all types of fibers and blue-gray fibers (blue-gray fibers are hardwood pulp fibers).

[0101] The separated images were fine-tuned in Photoshop to improve extraction accuracy. The pixel counts for each fiber type were then counted. Analyzing the pixel counts for all fiber types and hardwood pulp fibers revealed a mass ratio of 35.23% for hardwood pulp and 64.77% for softwood pulp (100% minus the mass ratio for hardwood pulp). Calculating the relative error for each fiber type yielded an average error of 9.94% and an accuracy of 90.06% (corresponding to data set 5 in Table 1).

[0102] The original Herzberg stain formula is a mixture of 15 mL of ZnCl₂ solution (20 g ZnCl₂ dissolved in 10 mL water) and an iodine solution (2.1 g KI and 0.1 g I₂ dissolved in 4 mL water), followed by the addition of 0.1 g iodine. The Graff "C" stain formula is a mixture of 20 mL of AlCl₃ solution (42 g AlCl₃ dissolved in 100 mL water), 10 mL of CaCl₂ solution (100 g CaCl₂ dissolved in 150 mL water), 10 mL of ZnCl₂ solution (100 g pure ZnCl₂ dissolved in 50 mL water), and 12.5 mL of iodine solution (0.9 g KI and 0.65 g I₂ dissolved in 45 mL water), followed by the addition of 0.06 g iodine.

[0103] Example 3

[0104] This embodiment provides a paper fiber raw material and ratio analysis method based on dyeing method and image recognition technology, which includes:

[0105] Weigh 0.1 g of bone-dry pulp (coniferous pulp: hemp pulp ratio of 2:3 by mass) to prepare a 0.01% fiber suspension. Two drops were placed on the center of a glass slide and dried in an oven at 65°C. The suspension was first stained with Herzberg dye diluted to 90% of its original concentration for 20 seconds. A microscopic specimen was prepared and images were collected under an optical microscope.

[0106] Two drops of the suspension were then placed on the center of a glass slide and dried in an oven at 65°C. The slides were then stained with Graff "C" dye diluted to 90% of their original concentration for 30 seconds. Microscopic specimens were then prepared and images were acquired using an optical microscope. Observation of the images revealed that the Herzberg-stained fibers exhibited blue and wine-red hues, indicating the presence of wood and hemp fibers. However, the Graff "C"-stained fibers exhibited wine-red hues, indicating the absence of hardwood fibers. This indicates that the mixed pulp contains only softwood and hemp fibers. Therefore, only the Herzberg-stained fiber images were analyzed.

[0107] Select 10 Herzberg-stained images ( Figure 5 ), the collected fiber images were preprocessed in MATLAB software. For the images stained with Herzberg dye, the saturation gain factor was adjusted to 1.5 and the brightness gain factor was adjusted to 1.1. The color space was converted to HSV color space, and the min and max values of H, S, and V were adjusted. Figure 6a and Figure 6b The color threshold method is used to extract all types of fibers and blue fibers (blue fibers are coniferous pulp fibers).

[0108] The separated images were fine-tuned in Photoshop to improve extraction accuracy. The pixel counts for each fiber type were then counted. Analyzing the pixel counts for all fiber types and hemp pulp, the mass ratio of hemp pulp was 62.22%, and the mass ratio of softwood pulp, minus the mass ratio of hardwood pulp, was 37.78%. Calculating the relative error for each fiber type yielded an average error of 4.63%, for an accuracy of 95.37% (corresponding to data set 9 in Table 1).

[0109] The original Herzberg stain formula is a mixture of 15 mL of ZnCl2 solution (20 g ZnCl2 dissolved in 10 mL water) and an iodine solution (2.1 g KI and 0.1 g I2 dissolved in 5 mL water), followed by the addition of 0.1 g iodine. The Graff "C" stain formula is a mixture of 20 mL of AlCl3 solution (40 g AlCl3 dissolved in 100 mL water), 10 mL of CaCl2 solution (100 g CaCl2 dissolved in 150 mL water), 10 mL of ZnCl2 solution (100 g pure ZnCl2 dissolved in 50 mL water), and 12.5 mL of iodine solution (0.9 g KI and 0.65 g I2 dissolved in 50 mL water), followed by the addition of 0.05 g iodine.

[0110] Example 4

[0111] This embodiment provides a paper fiber raw material and ratio analysis method based on dyeing method and image recognition technology, which includes:

[0112] Weigh 0.1 g of bone-dry pulp (coniferous pulp: hemp pulp mass ratio of 72.7:27.3) to prepare a 0.01% fiber suspension. Two drops were placed on the center of a glass slide and dried in an oven at 65°C. The suspension was first stained with Herzberg dye diluted to 90% of its original concentration for 20 seconds. A microscopic specimen was prepared and images were collected under an optical microscope.

[0113] Two drops of the suspension were then placed on the center of a glass slide and dried in an oven at 65°C. The slides were then stained with Graff "C" dye diluted to 90% of their original concentration for 40 seconds. Microscopic specimens were then prepared and images were collected using an optical microscope. Observation of the images revealed that the Herzberg-stained fibers exhibited blue and wine-red hues, indicating the presence of wood and hemp fibers. However, the Graff "C"-stained fibers exhibited wine-red hues, indicating the absence of hardwood fibers. This indicates that the mixed pulp contains only softwood and hemp fibers. Therefore, only the Herzberg-stained fiber images were analyzed.

[0114] Select 10 Herzberg-stained images ( Figure 7 ), the collected fiber images were preprocessed in MATLAB software. For the images stained with Herzberg dye, the saturation gain factor was adjusted to 1.5 and the brightness gain factor was adjusted to 1.1. The color space was converted to HSV color space, and the min and max values of H, S, and V were adjusted. Figure 8a and Figure 8b The color threshold method is used to extract all types of fibers and blue fibers (blue fibers are coniferous pulp fibers).

[0115] The separated images were fine-tuned in Photoshop (to improve extraction accuracy), and the number of pixels for each fiber type was then counted. By analyzing the pixel counts for all fiber types and hemp pulp, the mass ratio of hemp pulp was found to be 29.55%, and the mass ratio of softwood pulp, minus the mass ratio of hardwood pulp, was 70.45%. Calculating the relative error for each of these two fiber types yielded an average error of 5.67%, with an accuracy of 94.33%. (Corresponding to data set 12 in Table 1)

[0116] The original Herzberg stain formula is a mixture of 15 mL of ZnCl2 solution (20 g ZnCl2 dissolved in 10 mL water) and an iodine solution (2.1 g KI and 0.1 g I2 dissolved in 5 mL water), followed by the addition of 0.1 g iodine. The Graff "C" stain formula is a mixture of 20 mL of AlCl3 solution (38 g AlCl3 dissolved in 100 mL water), 10 mL of CaCl2 solution (100 g CaCl2 dissolved in 150 mL water), 10 mL of ZnCl2 solution (100 g pure ZnCl2 dissolved in 50 mL water), and 12.5 mL of iodine solution (0.9 g KI and 0.65 g I2 dissolved in 48 mL water), followed by the addition of 0.06 g iodine.

[0117] Example 5

[0118] This embodiment provides a paper fiber raw material and ratio analysis method based on dyeing method and image recognition technology, which includes:

[0119] Weigh 0.1 g of bone-dry pulp (coniferous, hardwood, and hemp pulp in a mass ratio of 5:3:2) to prepare a 0.01% fiber suspension. Two drops were placed on the center of a glass slide and dried in an oven at 65°C. The suspension was first stained with Herzberg dye diluted to 90% of its original concentration for 30 seconds. A microscopic specimen was prepared and images were collected under an optical microscope.

[0120] Two drops of the suspension were then placed on the center of a glass slide and dried in an oven at 65°C. The slide was then stained with Graff "C" dye diluted to 90% of its original concentration for 30 seconds. A microscopic specimen was prepared and imaged using an optical microscope. The images revealed that Herzberg-stained fibers exhibited blue and wine-red hues, indicating the presence of both wood and hemp fibers in the mixed pulp. Graff "C"-stained fibers exhibited bluish-gray and wine-red hues, indicating the presence of hardwood fibers.

[0121] 10 images stained with Herzberg stain and Graff "C" stain were selected respectively ( Figure 9a and Figure 9b ), the collected fiber images were preprocessed in MATLAB software. For the images stained with Herzberg dye, the saturation gain factor was adjusted to 1.5, and the brightness gain factor was adjusted to 1.1. For the images stained with Graff "C" dye, the saturation gain factor was adjusted to 2.0, and the brightness gain factor was adjusted to 1.1. The color space was converted to HSV color space, and the min and max values of H, S, and V were adjusted. Figure 10a and Figure 10b The color threshold method is used to extract all types of fibers and blue fibers (blue fibers are wood pulp fibers) after Herzberg staining. Figure 11a and Figure 11b The color threshold method is used to extract all types of fibers and blue-gray fibers after Graff "C" dyeing (blue-gray fibers are broadleaf pulp fibers).

[0122] The separated images were fine-tuned in Photoshop to improve extraction accuracy. The pixel counts for each fiber type were then counted. Analyzing the pixel counts for all fiber types and hardwood pulp fibers revealed a mass ratio of 22.32% for hemp pulp, 28.35% for hardwood pulp, and 49.33% for softwood pulp (100% minus the hardwood ratio). Calculating the relative error for each of these three fiber types yielded an average error of 6.15%, for an accuracy of 93.85% (corresponding to data set 13 in Table 1).

[0123] The original Herzberg stain formula is a mixture of 15 mL of ZnCl2 solution (18 g ZnCl2 dissolved in 10 mL water) and an iodine solution (2.1 g KI and 0.1 g I2 dissolved in 4 mL water), followed by the addition of 0.1 g iodine. The Graff "C" stain formula is a mixture of 20 mL of AlCl3 solution (38 g AlCl3 dissolved in 100 mL water), 10 mL of CaCl2 solution (98 g CaCl2 dissolved in 150 mL water), 10 mL of ZnCl2 solution (100 g pure ZnCl2 dissolved in 50 mL water), and 12.5 mL of iodine solution (0.9 g KI and 0.65 g I2 dissolved in 48 mL water), followed by the addition of 0.05 g iodine.

[0124] Example 6

[0125] This embodiment provides a paper fiber raw material and ratio analysis method based on dyeing method and image recognition technology, which includes:

[0126] Weigh 0.1 g of bone-dry pulp (coniferous, hardwood, and hemp pulp in a mass ratio of 5:2:3) to prepare a 0.01% fiber suspension. Two drops were placed on the center of a glass slide and dried in an oven at 65°C. The suspension was first stained with Herzberg dye diluted to 90% of its original concentration for 20 seconds. A microscopic specimen was prepared and images were collected under an optical microscope.

[0127] Two drops of the suspension were then placed on the center of a glass slide and dried in an oven at 65°C. The slide was then stained with Graff "C" dye diluted to 90% of its original concentration for 30 seconds. A microscopic specimen was prepared and imaged using an optical microscope. The images revealed that Herzberg-stained fibers exhibited blue and wine-red hues, indicating the presence of both wood and hemp fibers in the mixed pulp. Graff "C"-stained fibers exhibited bluish-gray and wine-red hues, indicating the presence of hardwood fibers.

[0128] 10 images stained with Herzberg stain and Graff "C" stain were selected respectively ( Figure 12a and Figure 12b ), the collected fiber images were preprocessed in MATLAB software. For the images stained with Herzberg dye, the saturation gain factor was adjusted to 1.5, and the brightness gain factor was adjusted to 1.1. For the images stained with Graff "C" dye, the saturation gain factor was adjusted to 2.0, and the brightness gain factor was adjusted to 1.1. The color space was converted to HSV color space, and the min and max values of H, S, and V were adjusted. Figure 13a and Figure 13b The color threshold method is used to extract all types of fibers and blue fibers (blue fibers are wood pulp fibers) after Herzberg staining. Figure 14a and Figure 14b The color threshold method is used to extract all types of fibers and blue-gray fibers after Graff "C" dyeing (blue-gray fibers are broadleaf pulp fibers).

[0129] The separated images were fine-tuned in Photoshop to improve extraction accuracy. The pixel counts for each fiber type were then counted. Analyzing the pixel counts for all fiber types and hardwood pulp fibers revealed a mass ratio of 32.73% for hemp pulp, 17.59% for hardwood pulp, and 49.68% for softwood pulp (100% minus the hardwood ratio). Calculating the relative error for each of these three fiber types yielded an average error of 7.26% and an accuracy of 92.74% (corresponding to data set 14 in Table 1).

[0130] The original Herzberg stain formula is a mixture of 15 mL of ZnCl2 solution (20 g ZnCl2 dissolved in 10 mL water) and an iodine solution (2.1 g KI and 0.1 g I2 dissolved in 5 mL water), followed by the addition of 0.1 g iodine. The Graff "C" stain formula is a mixture of 20 mL of AlCl3 solution (40 g AlCl3 dissolved in 100 mL water), 10 mL of CaCl2 solution (100 g CaCl2 dissolved in 150 mL water), 10 mL of ZnCl2 solution (100 g pure ZnCl2 dissolved in 50 mL water), and 12.5 mL of iodine solution (0.9 g KI and 0.65 g I2 dissolved in 50 mL water), followed by the addition of 0.05 g iodine.

[0131] Table 1

[0132]

[0133] Table 1 was obtained by mixing different types of fiber raw materials and conducting experiments in groups to illustrate the accuracy of the method. The mass ratio of the dyeing analysis sample was calculated using formula 1-3.

[0134] The applicant declares that the present invention is intended to illustrate the detailed structural features of the present invention through the above-described embodiments, but the present invention is not limited to the above-described detailed structural features. This does not mean that the present invention must rely on the above-described detailed structural features in order to be implemented. Those skilled in the art should understand that any improvements to the present invention, equivalent replacements for selected components, additions of auxiliary components, and selection of specific embodiments, etc., fall within the scope of protection and disclosure of the present invention.

[0135] The preferred embodiments of the present invention are described in detail above. However, the present invention is not limited to the specific details in the above embodiments. Within the technical concept of the present invention, various simple modifications can be made to the technical solution of the present invention, and these simple modifications all fall within the scope of protection of the present invention.

[0136] It should also be noted that the various specific technical features described in the above specific embodiments can be combined in any appropriate manner without contradiction. In order to avoid unnecessary repetition, the present invention will not further describe various possible combinations.

[0137] In addition, the various embodiments of the present invention may be arbitrarily combined, and as long as they do not violate the concept of the present invention, they should also be regarded as the contents disclosed by the present invention.

Claims

1. A paper fiber raw material and ratio analysis method based on dyeing method and image recognition technology, characterized in that: The analysis method comprises: Performing a first dyeing on the paper fiber raw material suspension using a first dye to obtain a first dyed sample; performing a second dyeing on the paper fiber raw material suspension using a second dye to obtain a second dyed sample; Using an imaging device to independently acquire images of the first dyed sample and the second dyed sample, respectively, to obtain a first dyed fiber image and a second dyed fiber image; Preprocessing the first dyed fiber image and / or the second dyed fiber image, and converting the color space into an HSV color space; extracting and separating fibers from the first dyed fiber image and / or the second dyed fiber image using a color threshold method, and counting the number of pixels of each fiber; The mass proportion of each fiber is calculated according to the number of pixels of each fiber.

2. The analysis method according to claim 1, characterized in that The first dye comprises Herzberg's stain and the second dye comprises Graff "C" stain.

3. The analysis method according to claim 1, characterized in that The imaging device includes an optical microscope.

4. The analysis method according to claim 1, characterized in that The preprocessing includes adjusting a saturation gain factor and a brightness gain factor of the first dyed fiber image and / or the second dyed fiber image.

5. The analysis method according to claim 4, characterized in that The saturation gain factor of the first dyed fiber image is adjusted to 1.0-2.0, and the brightness gain factor is adjusted to 1.0-1.

5.

6. The analysis method according to claim 4, characterized in that The saturation gain factor of the second dyed fiber image is adjusted to 1.0-3.0, and the brightness gain factor is adjusted to 1.0-1.

5.

7. The analysis method according to claim 1, characterized in that After converting the color space to the HSV color space, the maximum and minimum values of the hue, saturation, and brightness of the image are adjusted.

8. The analysis method according to claim 1, characterized in that A color threshold method is used to extract all fibers and dyed fibers in the first dyed fiber image and / or the second dyed fiber image.

9. The analysis method according to claim 1, characterized in that Image processing software is used to adjust the image obtained after extraction and separation using the color threshold method.

10. The analysis method according to claim 1, characterized in that The formulas for calculating the mass proportion of each fiber are shown in Formulas 1, 2, and 3: Among them, X n : mass percentage; f n : fiber quality factor; C n : Fiber thickness, unit is mg / m; N n : total length of the fiber, in mm; Average quality factor of mixed fibers; N 总 : The total length of all types of fibers, in mm; M n : pixel area of fiber; W n : Width of the fiber, in μm.

Images