Image-based fiber-broken softened veneer manufacturing method and fiber-broken softened veneer

Abstract

Embodiments of the present invention provide an image-based method for manufacturing a fiber-softened veneer and a fiber-softened veneer, relating to the technical field of image processing technology. The method includes: obtaining a first image of a first veneer; performing a first processing on the first image to obtain a de-cluttered texture image of the first veneer; and determining a veneer processing strategy based on the de-cluttered texture image. This invention addresses the issue of low image processing accuracy in the wood processing field, thereby improving image processing accuracy.

Description

Technical Field

[0001] The embodiments of the present invention relate to the field of image processing, and in particular, to a method for manufacturing an image-based fiber-breaking and softening veneer and a fiber-breaking and softening veneer. Background Art

[0002] With the continuous development of computer vision and image processing technology, image recognition and analysis are becoming more and more widely used in wood processing. Image processing technology can realize the automatic detection and analysis of wood veneer, improve the accuracy and efficiency of detection, and reduce manual intervention.

[0003] However, existing methods still have some shortcomings. For example, the accuracy and stability of existing image processing methods when dealing with complex wood textures and tiny defects still need to be improved, especially in the field of eucalyptus processing.

[0004] There is currently no better solution to the above problems. Summary of the Invention

[0005] The embodiments of the present invention provide an image-based method for manufacturing a fiber-broken and softened veneer and a fiber-broken and softened veneer, so as to at least solve the problem of low precision in image processing of wood veneers in the related art.

[0006] According to one embodiment of the present invention, a method for manufacturing a fiber-breaking and softened veneer based on an image is provided, comprising:

[0007] Acquire a first image of a first single board, wherein the first single board is obtained after preprocessing an initial single board, and the first image includes a front image and a back image of the first single board;

[0008] Performing a first processing on the first image to obtain a deconstructed texture image of the first single board, wherein the first processing includes at least grayscale processing, image sharpening processing, contrast compensation processing, and morphological processing, wherein the morphological processing includes erosion and dilation processing;

[0009] Based on the deconstructed texture image, a veneer processing strategy is determined, wherein the veneer processing strategy includes a hydrothermal strategy and a pressure strategy.

[0010] In an exemplary embodiment, determining a veneer processing strategy based on the deconstructed texture image includes:

[0011] Determining first single board parameters of the first single board based on the de-resolved texture image;

[0012] The single board processing strategy is determined according to the first single board parameters.

[0013] In an exemplary embodiment, after determining the single board processing strategy according to the first single board parameter, the method further includes:

[0014] Acquire a second image of a second single board, wherein the second single board is obtained by processing based on the single board processing strategy;

[0015] Performing a second processing on the second image to obtain second single board parameters, wherein the second processing at least includes grayscale processing, threshold segmentation processing, and morphological processing;

[0016] The processing quality of the second single board is determined according to the second single board parameters.

[0017] In an exemplary embodiment, after determining the processing quality of the second single board according to the second single board parameters, the method further includes:

[0018] When the processing quality of the second veneer meets the requirements, the second veneer is sequentially subjected to a third treatment to obtain a target veneer, wherein the third treatment at least includes peeling, drying, dipping, and assembly.

[0019] In an exemplary embodiment, before acquiring the first image of the first board, the method further includes:

[0020] Acquire an initial image of the first board;

[0021] The initial image is enhanced to obtain the first image.

[0022] According to another embodiment of the present invention, there is provided an image-based fiber-breaking and softening veneer manufacturing device, comprising:

[0023] a first image acquisition module, configured to acquire a first image of a first single board, wherein the first single board is obtained after preprocessing an initial single board, and the first image includes a front image and a back image of the first single board;

[0024] a first processing module, configured to perform a first processing on the first image to obtain a de-resolved texture image of the first single board, wherein the first processing includes at least grayscale processing, image sharpening processing, contrast compensation processing, and morphological processing, wherein the morphological processing includes erosion and dilation processing;

[0025] A strategy determination module is used to determine a single board processing strategy based on the deconstructed texture image, wherein the single board processing strategy includes a hydrothermal strategy and a pressure strategy.

[0026] In an exemplary embodiment, determining a veneer processing strategy based on the deconstructed texture image includes:

[0027] Determining first single board parameters of the first single board based on the de-resolved texture image;

[0028] The single board processing strategy is determined according to the first single board parameters.

[0029] In an exemplary embodiment, the apparatus further comprises:

[0030] A second image acquisition module is configured to acquire a second image of a second single board after determining the single board processing strategy according to the first single board parameters, wherein the second single board is obtained after processing based on the single board processing strategy;

[0031] a second processing module, configured to perform a second processing on the second image to obtain second single board parameters, wherein the second processing at least includes grayscale processing, threshold segmentation processing, and morphological processing;

[0032] The quality determination module is used to determine the processing quality of the second single board according to the parameters of the second single board.

[0033] According to another embodiment of the present invention, there is provided a fiber-broken softened veneer, comprising:

[0034] A wood veneer layer, comprising at least three layers, wherein the grain directions of the wood veneers are perpendicular to each other, wherein the wood veneer layer is manufactured according to any of the aforementioned methods for manufacturing a fiber-destroying and softened veneer based on an image;

[0035] The polypropylene film layer is sandwiched between any two of the wood veneer layers.

[0036] According to yet another embodiment of the present invention, a computer-readable storage medium is provided, in which a computer program is stored. The computer program is configured to execute the steps of any one of the above method embodiments when run.

[0037] According to another embodiment of the present invention, an electronic device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor is configured to run the computer program to perform the steps in any one of the above method embodiments.

[0038] The present invention obtains an image of a wood veneer and performs a series of image processing operations on it to obtain a deconstructed texture image. Based on the deconstructed texture image, the veneer processing strategy, including a hydrothermal strategy and a pressure strategy, is determined. This method not only improves the accuracy and efficiency of detection, but also dynamically adjusts the processing strategy based on the actual state of the wood veneer, ensuring the stability and consistency of processing quality. Therefore, it can solve the problem of low image processing accuracy in the wood processing field and achieve the effect of improving image processing accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 is a flow chart of a method for manufacturing a fiber-broken and softened veneer based on an image according to an embodiment of the present invention;

[0040] Figure 2 This is a structural block diagram of an image-based fiber-breaking and softening veneer manufacturing device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0041] The technical solutions in the embodiments of the present application will be described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments.

[0042] Hereinafter, the terms "first," "second," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of the technical features being referred to. Thus, a feature identified with "first," "second," etc., may explicitly or implicitly include one or more of the features. In the description of this application, unless otherwise specified, "plurality" means two or more.

[0043] In addition, in this application, directional terms such as "up", "down", "left", and "right" may be defined including but not limited to the orientation relative to the schematic placement of the components in the drawings. It should be understood that these directional terms may be relative concepts. They are used for relative descriptions and clarifications, and they may change accordingly according to changes in the orientation of the components in the drawings.

[0044] In this application, unless otherwise specified or limited, the term "connection" should be understood broadly. For example, "connection" can mean fixed connection, detachable connection, or integration; it can mean direct connection or indirect connection through an intermediate medium. In addition, the term "coupling" can refer to the manner in which electrical connection is achieved for signal transmission.

[0045] As used herein, "about," "substantially," or "approximately" includes the stated value and an average value that is within an acceptable range of deviation from the particular value as determined by one of ordinary skill in the art taking into account the measurements in question and the errors associated with the measurement of the particular quantity (i.e., the limitations of the measurement system).

[0046] In this embodiment, a method for manufacturing a fiber-broken and softened veneer based on an image is provided. Figure 1 FIG. 1 is a flow chart of a method for manufacturing a fiber-broken and softened veneer based on an image according to an embodiment of the present invention. Figure 1 As shown, the process includes the following steps:

[0047] Step S11, obtaining a first image of a first single board, wherein the first single board is obtained after preprocessing an initial single board, and the first image includes a front image and a back image of the first single board;

[0048] In this embodiment, during the wood processing process, if subtle defects in the wood are identified by the naked eye, on the one hand, it greatly increases the labor cost, and on the other hand, it also poses a great challenge to the staff performing the identification, especially when continuous wood processing is required. Therefore, defect identification through images becomes a necessary means.

[0049] Among them, the first image can be obtained by capturing the image of the pre-treated wood veneer through an industrial camera, and then the first image is processed so that the first image can be recognized, thereby determining the subsequent processing method; the pre-processing of the initial veneer can be to dry-clean the initial veneer after peeling into slices, store it for moisture balance, and other treatments, among which the dry cleaning treatment is to remove debris, sand and gravel in the template to ensure that the sand content after dry cleaning is less than or equal to 0.04%; and obtaining the front image and the back image can realize the comprehensive judgment of the veneer status from both sides of the veneer, effectively improving the accuracy of the veneer processing strategy.

[0050] It should be noted that the wood veneer can be eucalyptus veneer or other veneer.

[0051] Step S12: performing a first processing on the first image to obtain a de-resolved texture image of the first single board, wherein the first processing at least includes grayscale processing, image sharpening processing, contrast compensation processing, and morphological processing, wherein the morphological processing includes erosion and dilation processing;

[0052] In this embodiment, the first processing is performed on the first image in order to facilitate subsequent determination of the actual state of the first board according to the deconstructed texture image.

[0053] The first processing includes image grayscale processing, image sharpening processing, contrast compensation processing, threshold segmentation processing and corrosion and expansion processing, which are performed in sequence. Specifically:

[0054] First, the first image is converted into a grayscale image by taking the average value of the three RGB channels as the grayscale value. Then, the convolution kernel is used for sharpening to enhance the edge features of the image. At the same time, the contrast of the grayscale image is enhanced by histogram equalization or linear transformation. Then, a threshold is selected to set the pixels with grayscale values ​​above the threshold to 1 and the pixels below the threshold to 0 to convert the processed grayscale image into a binary image. Finally, morphological operations are used to erode and dilate the binary image to remove noise and small holes, thereby further enhancing the edge features of the image.

[0055] Step S13: determining a single board processing strategy based on the decomposed texture image, wherein the single board processing strategy includes a hydrothermal strategy and a pressure strategy.

[0056] In this embodiment, after obtaining the de-resolved texture image, the image is analyzed to determine the various parameters of the single board, and the subsequent processing strategy is determined based on the relevant parameters; it is easy to understand that the determination of the processing strategy is based on a trained neural network model or other algorithm model, that is, the de-resolved texture image is input into the relevant algorithm model, and then the relevant algorithm model outputs the corresponding strategy value, and then the corresponding processing strategy is matched from the strategy library according to the strategy value.

[0057] Among them, the hydrothermal strategy includes the number of times, duration, temperature, etc. of heating the veneer, and the pressure strategy includes the pressure size and duration of pressurization of the veneer; for example, the hydrothermal strategy may include pre-cooking and formal cooking, wherein the pre-cooking temperature is 170 to 180°C, the time is 5 to 6 minutes, and the pressure is 7.0 to 8.5 MPa, the purpose of which is to soften the wood chips and make them easier for subsequent hot grinding treatment; formal cooking is basically the same as pre-cooking, the purpose of which is to further soften the wood chips and loosen their fiber structure for subsequent Hot grinding treatment; pressure strategies include hot grinding, pre-pressing and hot pressing. Hot grinding is to adjust the pressure of the hot grinding machine according to the specific equipment and the softening degree of the wood chips to ensure that the fibers can be fully separated; pre-pressing is to adjust the pressure of the pre-pressing machine according to the thickness of the slab and the looseness of the fibers to ensure the initial formation of the slab; hot pressing is to hot press for 7 to 12 minutes at a temperature of 105°C to 115°C and a pressure of 20 MPa to 22 MPa. Its purpose is to make the glue fully react through high temperature and high pressure to improve the bonding performance and dimensional stability of the board.

[0058] The step of determining a single board processing strategy based on the deconstructed texture image includes:

[0059] Step S131, determining first single board parameters of the first single board based on the de-resolved texture image;

[0060] Step S132: determining the single board processing strategy according to the first single board parameters.

[0061] In this embodiment, the first single board parameters include pixel occupancy, crack resolving power, crack coherence, crack number, crack average width, and the like.

[0062] Among them, pixel occupancy is the ratio of texture pixels to total pixels in the calculated image, and this parameter reflects the density of the fiber structure; crack resolvability is the ratio of the area of ​​the calculated crack region to the total image area, and this parameter reflects the distribution of cracks; crack coherence is the coherence of the calculated cracks, and this parameter reflects the continuity of the cracks; the number of cracks is the number of cracks in the calculated image, and this parameter reflects the density of the cracks; the average crack width is the average width of the calculated cracks, and this parameter reflects the width distribution of the cracks; since the water, heat and pressure that can be tolerated in different crack conditions are different, it is necessary to determine the relevant parameters and then select the corresponding processing strategy to ensure the quality of veneer processing.

[0063] In particular, in addition to judging the processing strategy of the first single board through image processing and analysis, the processing strategy of the first single board can also be judged by combining ultrasonic detection with images; specifically, ultrasonic waves are emitted to the single board, and then the echo of the ultrasonic waves is received through the microphone matrix. Generally, the single board reflects part of the sound waves while absorbing them. At this time, the situation of the single board is judged by the distribution of the reflected sound waves (energy distribution, frequency distribution, etc.), and then associated with the parameters of the first single board for matching. When the two are successfully matched, the processing strategy is determined based on the parameters of the first single board and the sound wave distribution. Among them, the energy distribution calculation is to calculate the energy distribution of the reflected sound wave and analyze the energy attenuation at different frequencies. The sound absorption performance and reflection characteristics of the single board can be preliminarily judged through the energy distribution diagram; frequency analysis is to use Fourier transform to convert the sound wave signal in the time domain into a signal in the frequency domain. The frequency distribution diagram is used to determine the absorption and reflection characteristics of the single board for sound waves of different frequencies. Time domain analysis uses short-time Fourier transform (STFT) for time-frequency analysis to determine the changes of sound waves at different times and frequencies. The correlation matching of the sound wave distribution with the first single board parameters is to use or machine learning algorithms to fuse the sound wave reflection data (energy distribution, frequency distribution, etc.) with the first single board parameters of the single board (such as pixel occupancy, crack resolvability, crack coherence, number of cracks, average crack width, etc.), and establish a correlation model between the sound wave reflection data and the first single board parameters. Then, through the correlation model, it is determined whether the sound wave reflection data matches the first single board parameters. If the match is successful, it means that the acoustic performance of the single board is consistent with the physical structure characteristics, and the next step can be continued. If the match fails, the processing strategy needs to be readjusted, and so on.

[0064] Through the above steps, by acquiring an image of the wood veneer and performing a series of image processing operations on it to obtain a deconstructed texture image, and based on the deconstructed texture image, determining the processing strategy of the veneer, including the hydrothermal strategy and the pressure strategy, the problem of low image processing accuracy in the wood processing field is solved, the image processing accuracy is improved, and the processing strategy can be dynamically adjusted according to the actual state of the wood veneer to ensure the stability and consistency of the processing quality.

[0065] In an optional embodiment, after determining the single board processing strategy according to the first single board parameter, the method further includes:

[0066] Step S14, acquiring a second image of a second single board, wherein the second single board is obtained by processing based on the single board processing strategy;

[0067] Step S15, performing a second processing on the second image to obtain second single board parameters, wherein the second processing at least includes grayscale processing, threshold segmentation processing, and morphological processing;

[0068] Step S16: determining the processing quality of the second single board according to the second single board parameters.

[0069] In this embodiment, after the processing is completed, it is necessary to perform a quality inspection on the processed single board to determine whether the relevant processing process and the quality of the single board meet the requirements.

[0070] Among them, the threshold segmentation process includes using a global threshold to separate the fiber structure and background in the image. Here, the Otsu algorithm can be used to automatically calculate the optimal threshold. The parameters of the second veneer are the same as those of the first veneer. In addition, the moisture content and moisture content distribution of the second veneer need to be detected by ultrasound. The second veneer parameters include moisture content. Since the propagation speed of ultrasound in wood is affected by the moisture content of wood, the moisture content of wood can be inferred by measuring the propagation speed of ultrasound. It can be calculated according to the following formula:

[0071] Assuming that v is the propagation velocity of ultrasound in wood, v0 is the propagation velocity of ultrasound in absolutely dry wood, and w is the moisture content of wood, the following relationship can be established:

[0072] v = v0 × (a × w + b) (Formula 1)

[0073] Where a and b are constants obtained by fitting experimental data; thus, we can obtain:

[0074]

[0075] Of course, the moisture content can also be calculated directly according to the following formula 3 according to the provisions of 4.3.3 of GB / T17657-2013, which is not limited here:

[0076]

[0077] Where wc(ij) is the moisture content at position (i, j), G ij is the initial mass of the board at position (i, j), G d(ij) is the absolute dry mass of the veneer at position (i, j) after drying, and i is the numerical fiber direction.

[0078] In an optional embodiment, after determining the processing quality of the second single board according to the second single board parameters, the method further includes:

[0079] When the processing quality of the second veneer meets the requirements, the second veneer is sequentially subjected to a third treatment to obtain a target veneer, wherein the third treatment at least includes peeling, drying, dipping, and assembly.

[0080] In this embodiment, the peeling process includes fixing the second veneer on the clamp of the peeling machine to ensure that the veneer is flat and firmly fixed, and then adjusting the parameters of the peeling machine, such as the peeling speed, feed rate, etc., wherein the relevant parameters need to be adjusted according to the thickness and material of the veneer, and then starting the peeling machine to perform the peeling operation to peel the veneer into the required thickness and size; the drying process includes placing the peeled veneer on a drying rack to ensure that there is enough gap between the veneers for air circulation; then placing the drying rack into the drying equipment and setting appropriate temperature and humidity parameters. Typically, the drying temperature is 60°C-80°C, and the humidity is 10%-20%. The drying time varies depending on the thickness and material of the veneer, typically taking 2-4 hours. The adhesive dipping process involves placing the dried veneer in a dipping tank, ensuring it is completely immersed in the adhesive. The dipping time varies depending on the thickness and type of adhesive, typically taking 3-5 minutes. After dipping, the veneer is removed and any excess adhesive is drained, ensuring an even coating of adhesive across the surface. The assembly process involves stacking the dipped veneer according to design requirements, ensuring alignment and flatness of each layer. During the stacking process, tape or clamps may be used to secure the veneer to prevent shifting. The stacked veneer is then placed in the assembly equipment, where pressure and time parameters are adjusted for hot pressing. Typically, the pressure is 1.5-2.0 MPa, and the pressing time is 10-15 minutes.

[0081] In an optional embodiment, before acquiring the first image of the first board, the method further includes:

[0082] Step S101, obtaining an initial image of the first board;

[0083] Step S102: performing enhancement processing on the initial image to obtain the first image.

[0084] In this embodiment, in order to improve the generalization ability and robustness of the model, data augmentation operations such as gamma transform, Laplace transform, random cropping, random horizontal flipping, Gaussian blur, Gaussian noise and salt and pepper noise processing can be performed on the image; and for images with fewer defect categories, the Copy-Paste strategy can be adopted to copy and paste the missing defect category images into random positions of the main image, and update the label information at the same time. The specific selection and adjustment are made according to the actual situation.

[0085] Through the description of the above embodiments, those skilled in the art can clearly understand that the method according to the above embodiment can be implemented by means of software plus the necessary general hardware platform, and of course it can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes a number of instructions for enabling a terminal device (which can be a mobile phone, computer, server, or network device, etc.) to execute the methods described in each embodiment of the present invention.

[0086] This embodiment also provides an image-based device for manufacturing fiber-destroying and softened veneer boards. This device is used to implement the aforementioned embodiments and preferred implementations, and details already described will not be repeated. As used below, the term "module" may refer to a combination of software and / or hardware that implements a predetermined function. While the devices described in the following embodiments are preferably implemented in software, implementation using hardware, or a combination of software and hardware, is also possible and contemplated.

[0087] Figure 2 FIG. 1 is a structural block diagram of an image-based fiber-breaking and softening veneer manufacturing device according to an embodiment of the present invention. Figure 2 As shown, the device includes:

[0088] a first image acquisition module, configured to acquire a first image of a first single board, wherein the first single board is obtained after preprocessing an initial single board, and the first image includes a front image and a back image of the first single board;

[0089] a first processing module, configured to perform a first processing on the first image to obtain a de-resolved texture image of the first single board, wherein the first processing includes at least grayscale processing, image sharpening processing, contrast compensation processing, and morphological processing, wherein the morphological processing includes erosion and dilation processing;

[0090] A strategy determination module is used to determine a single board processing strategy based on the deconstructed texture image, wherein the single board processing strategy includes a hydrothermal strategy and a pressure strategy.

[0091] In an optional embodiment, determining a single board processing strategy based on the deconstructed texture image includes:

[0092] Determining first single board parameters of the first single board based on the de-resolved texture image;

[0093] The single board processing strategy is determined according to the first single board parameters.

[0094] In an optional embodiment, the device further comprises:

[0095] A second image acquisition module is configured to acquire a second image of a second single board after determining the single board processing strategy according to the first single board parameters, wherein the second single board is obtained after processing based on the single board processing strategy;

[0096] a second processing module, configured to perform a second processing on the second image to obtain second single board parameters, wherein the second processing at least includes grayscale processing, threshold segmentation processing, and morphological processing;

[0097] The quality determination module is used to determine the processing quality of the second single board according to the parameters of the second single board.

[0098] It should be noted that the above modules can be implemented through software or hardware. For the latter, it can be implemented in the following ways, but not limited to: the above modules are all located in the same processor; or the above modules are located in different processors in any combination.

[0099] An embodiment of the present invention further provides a fiber-broken softened veneer, comprising:

[0100] A wood veneer layer, comprising at least three layers, wherein the grain directions of the wood veneers are perpendicular to each other, wherein the wood veneer layer is manufactured according to the aforementioned image-based fiber-breaking and softening veneer manufacturing method;

[0101] The polypropylene film layer is sandwiched between any two of the wood veneer layers.

[0102] An embodiment of the present invention further provides a computer-readable storage medium, in which a computer program is stored. The computer program is configured to execute the steps of any one of the above method embodiments when running.

[0103] In an exemplary embodiment, the computer-readable storage medium may include, but is not limited to, various media that can store computer programs, such as a USB flash drive, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk, or an optical disk.

[0104] An embodiment of the present invention further provides an electronic device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor is configured to run the computer program to execute the steps in any one of the above method embodiments.

[0105] In an exemplary embodiment, the electronic device may further include a transmission device and an input / output device, wherein the transmission device is connected to the processor, and the input / output device is connected to the processor.

[0106] Through the description of the above implementation methods, technical personnel in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional modules is used as an example. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above.

[0107] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of modules or units is only a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0108] Units described as separate components may or may not be physically separate, and components shown as units may be one physical unit or multiple physical units, that is, they may be located in one place or distributed in multiple places. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0109] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0110] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a readable storage medium. Based on this understanding, the technical solution of the embodiment of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for enabling a device (which can be a single-chip microcomputer, chip, etc.) or a processor (processor) to execute all or part of the steps of the various embodiments of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0111] The above content is only a specific embodiment of this application, but the scope of protection of this application is not limited to this. Any changes or replacements within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

Claims

1. A method for manufacturing a fiber-broken and softened veneer based on an image, characterized in that: include: Acquire a first image of a first single board, wherein the first single board is obtained after preprocessing an initial single board, and the first image includes a front image and a back image of the first single board; Performing a first processing on the first image to obtain a deconstructed texture image of the first single board, wherein the first processing includes at least grayscale processing, image sharpening processing, contrast compensation processing, and morphological processing, wherein the morphological processing includes erosion and dilation processing; Determining a veneer processing strategy based on the resolved texture image, wherein the veneer processing strategy includes a hydrothermal strategy and a pressure strategy; Wherein, determining the single board processing strategy based on the deconstructed texture image includes: determining first single board parameters of the first single board based on the deconstructed texture image; determining the single board processing strategy according to the first single board parameters; After determining the single board processing strategy according to the first single board parameter, the method further includes: Acquire a second image of a second single board, wherein the second single board is obtained by processing based on the single board processing strategy; Performing a second processing on the second image to obtain second veneer parameters, wherein the second processing includes at least grayscale processing, threshold segmentation processing, and morphological processing; the second veneer parameters include moisture content, which is calculated using the following formula: Where v is the propagation velocity of ultrasound in wood, v0 is the propagation velocity of ultrasound in absolutely dry wood, w is the moisture content of wood, and a and b are constants obtained by fitting experimental data. determining a processing quality of the second single board according to the second single board parameters; After determining the processing quality of the second single board according to the second single board parameters, the method further includes: When the processing quality of the second veneer meets the requirements, the second veneer is sequentially subjected to a third process to obtain a target veneer, wherein the third process at least includes peeling, drying, dipping, and assembly; wherein the peeling process includes fixing the second veneer on a fixture of a peeling machine, then adjusting the parameters of the peeling machine, and then starting the peeling machine to perform a peeling operation to peel the veneer into a desired thickness and size; the drying process includes placing the peeled veneer on a drying rack; then placing the drying rack in a drying device and setting the drying temperature to 60 ℃-80℃, humidity is 10%-20%, and the drying time is 2-4 hours; the dipping treatment includes placing the dried veneer into the dipping tank and ensuring that the veneer is completely immersed in the adhesive, and adjusting the dipping time according to the thickness of the veneer and the type of adhesive; after dipping, the veneer is taken out and the excess adhesive is drained; the assembly treatment includes stacking the dipped veneer; then the laminated veneer is placed in the assembly equipment, the pressure and time parameters are adjusted, and hot pressing treatment is performed, wherein the pressure of the hot pressing treatment is 1.5-2.0MPa and the time is 10-15 minutes.

2. The method according to claim 1, characterized in that Before acquiring the first image of the first board, the method further includes: Acquire an initial image of the first board; The initial image is enhanced to obtain the first image.

3. An image-based fiber-breaking and softening veneer manufacturing device, characterized in that: include: a first image acquisition module, configured to acquire a first image of a first single board, wherein the first single board is obtained after preprocessing an initial single board, and the first image includes a front image and a back image of the first single board; a first processing module, configured to perform a first processing on the first image to obtain a de-resolved texture image of the first single board, wherein the first processing includes at least grayscale processing, image sharpening processing, contrast compensation processing, and morphological processing, wherein the morphological processing includes erosion and dilation processing; A strategy determination module, configured to determine a veneer processing strategy based on the deconstructed texture image, wherein the veneer processing strategy includes a hydrothermal strategy and a pressure strategy; The step of determining a single board processing strategy based on the deconstructed texture image includes: Determining first single board parameters of the first single board based on the de-resolved texture image; Determining the single board processing strategy according to the first single board parameter; Wherein, the device further includes: A second image acquisition module is configured to acquire a second image of a second single board after determining the single board processing strategy according to the first single board parameters, wherein the second single board is obtained after processing based on the single board processing strategy; The second processing module is configured to perform a second processing on the second image to obtain second veneer parameters, wherein the second processing includes at least grayscale processing, threshold segmentation processing, and morphological processing; the second veneer parameters include moisture content, which is calculated using the following formula: Where v is the propagation velocity of ultrasound in wood, v0 is the propagation velocity of ultrasound in absolutely dry wood, w is the moisture content of wood, and a and b are constants obtained by fitting experimental data. a quality determination module, configured to determine the processing quality of the second single board according to the second single board parameters; After determining the processing quality of the second single board according to the second single board parameters, the method further includes: When the processing quality of the second veneer meets the requirements, the second veneer is sequentially subjected to a third process to obtain a target veneer, wherein the third process at least includes peeling, drying, dipping, and assembly; wherein the peeling process includes fixing the second veneer on a fixture of a peeling machine, then adjusting the parameters of the peeling machine, and then starting the peeling machine to perform a peeling operation to peel the veneer into a desired thickness and size; the drying process includes placing the peeled veneer on a drying rack; then placing the drying rack in a drying device and setting the drying temperature to 60 ℃-80℃, humidity is 10%-20%, and the drying time is 2-4 hours; the dipping treatment includes placing the dried veneer into the dipping tank and ensuring that the veneer is completely immersed in the adhesive, and adjusting the dipping time according to the thickness of the veneer and the type of adhesive; after dipping, the veneer is taken out and the excess adhesive is drained; the assembly treatment includes stacking the dipped veneer; then the laminated veneer is placed in the assembly equipment, the pressure and time parameters are adjusted, and hot pressing treatment is performed, wherein the pressure of the hot pressing treatment is 1.5-2.0MPa and the time is 10-15 minutes.

4. A fiber-broken softened veneer, characterized in that: include: A wood veneer layer, comprising at least three layers, wherein the grain directions of the wood veneers are perpendicular to each other, wherein the wood veneer layer is manufactured according to the image-based fiber-destroying and softening veneer manufacturing method according to any one of claims 1-2; The polypropylene film layer is sandwiched between any two of the wood veneer layers.

5. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, wherein the computer program is configured to execute the method according to any one of claims 1 to 2 when executed.

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