Digital UV cold ironing all-in-one machine camera positioning system based on image recognition

Abstract

A digital UV cold ironing all-in-one machine camera positioning system based on image recognition comprises an image collecting and processing module, a positioning feature extraction module and a positioning analysis module. The image acquisition and processing module is used for completing acquisition and processing of image data, the positioning feature extraction module is used for carrying out feature extraction on the processed image data, and the positioning analysis module is used for carrying out hot stamping pattern analysis according to extracted positioning features. The control parameters of the digital UV cold stamping all-in-one machine are adjusted according to the analysis result, so that accurate hot stamping is achieved; according to the invention, the method of dynamically adjusting the size of the Gaussian kernel and enhancing the area contrast is adopted to pre-process the image data, so that the image noise is effectively removed, and the contrast of the image is enhanced; by constructing an image pyramid and a Laplacian pyramid, positioning features in an image are extracted, and a homography matrix is utilized to map a hot stamping image template into image data, so that high-precision positioning analysis is realized.

Description

Technical Field

[0001] The invention relates to the technical field of image data processing, and in particular to a camera positioning system for a digital UV cold stamping machine based on image recognition. Background Art

[0002] In the modern printing and packaging industry, hot stamping technology is widely used to improve the aesthetics and anti-counterfeiting of products. Traditional hot stamping processes rely on manual operations, which have problems such as inaccurate positioning and low efficiency. With the development of science and technology, digital UV cold stamping technology has gradually emerged. It combines the flexibility of digital printing with the fast drying characteristics of UV curing technology and has become an efficient solution.

[0003] However, the existing digital UV cold stamping equipment still faces the problem of insufficient positioning accuracy when performing pattern stamping. Due to the physical characteristics of materials and equipment, the stamping process is prone to deviation, resulting in an increase in the defective rate of products. Therefore, a system that can automatically and accurately position the stamping pattern is urgently needed to improve product quality and production efficiency.

[0004] Therefore, in order to achieve accurate positioning and automatic correction of the hot stamping pattern and improve the intelligence level of the production line, the present application proposes a camera positioning system for a digital UV cold stamping machine based on image recognition. Summary of the invention

[0005] In view of the above-mentioned problems, the present invention is proposed.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions: a camera positioning system for a digital UV cold-ironing integrated machine based on image recognition, comprising an image acquisition and processing module, a positioning feature extraction module and a positioning analysis module;

[0007] The image acquisition and processing module includes an image acquisition unit and an image processing unit, specifically:

[0008] Data acquisition under different light intensities is achieved by dynamically adjusting camera parameters, and a trigger mechanism is set to achieve real-time acquisition of image data. Image data preprocessing is then achieved by dynamically adjusting the Gaussian kernel size and regional contrast enhancement.

[0009] The positioning feature extraction module determines the position and direction of feature points by constructing an image pyramid and a Laplacian pyramid to extract positioning features;

[0010] The positioning analysis module maps the hot stamping image template to the image data through the homography matrix, performs positioning analysis according to the mapping coordinates and the positioning feature coordinates, and finally completes the control adjustment of the machine parameters according to the positioning analysis results.

[0011] As a preferred solution of the camera positioning system of the digital UV cold stamping machine based on image recognition described in the present invention, the data acquisition under different light intensities by dynamically adjusting the camera parameters is specifically implemented as follows:

[0012]

[0013] Where t1 and t2 represent the camera exposure time range, L(x,y,t) represents the light intensity in the (x,y) direction at time t, R(x,y) represents the camera parameters in the (x,y) direction, which are set by the implementer according to the actual application scenario, I represents the collected image data, and satisfies I={I t ,I t-1}, I t Represents the image data of the object before hot stamping, I t-1 Represents the image data of the object after hot stamping.

[0014] As a preferred solution of the camera positioning system of a digital UV cold stamping machine based on image recognition described in the present invention, the setting of the trigger mechanism to realize the real-time collection of image data is specifically implemented as follows:

[0015] A photoelectric sensor is installed in the all-in-one machine to detect the arrival of the object to be stamped. When the object is detected to enter the camera's field of view, the photoelectric sensor sends a signal to the system;

[0016] When the system receives the signal sent by the photoelectric sensor, it converts the received signal into a trigger signal for image data acquisition and sends it to the camera;

[0017] After receiving the trigger signal, the camera immediately captures the image data of the current object and sets the shooting frequency and camera parameters according to the light intensity of the current environment.

[0018] As a preferred solution of the camera positioning system of a digital UV cold stamping machine based on image recognition described in the present invention, the dynamic adjustment of the Gaussian kernel size is specifically implemented as follows:

[0019] Divide the collected image data into multiple small blocks and calculate the local variance of each small block;

[0020] According to the calculated local variance, the size of the Gaussian kernel is dynamically adjusted, then,

[0021] σ(x,y)=var(I i (x,y))·α+β

[0022] Among them, I i(x, y) represents the image data of the ith small block, α and β represent adjustment coefficients, and satisfy the formula α+β=1, which is set by the implementer according to the actual application scenario, and σ(x, y) represents the Gaussian kernel size;

[0023] According to the adjusted Gaussian kernel size, the image data is denoised using a Gaussian filter;

[0024] The regional contrast enhancement is specifically as follows:

[0025] For the segmented small block image data I i (x, y), perform brightness histogram analysis to identify different brightness areas;

[0026] According to different brightness areas, the contrast of image data is adaptively enhanced, then:

[0027] I i,reg (x,y)=I i (x,y)·α(x,y)+β(x,y)

[0028] Among them, I i (x, y) represents the image data of the ith small block, α and β represent adjustment coefficients, and satisfy the formula α+β=1, which is set by the implementer according to the actual application scenario. i,reg (x,y) means increasing the contrast of the (x,y) region of the i-th small block of the image.

[0029] As a preferred solution of the camera positioning system of a digital UV cold stamping machine based on image recognition described in the present invention, the image pyramid and the Laplacian pyramid are specifically constructed as follows:

[0030] By building an image pyramid and reducing the image data resolution layer by layer, we have:

[0031] I′ j (x,y)=G(x,y,σ i )*I′(x,y)

[0032]

[0033] Among them, I′(x,y) represents the image data at the position (x,y) after data preprocessing, G(x,y,σ i ) represents the Gaussian image data of the i-th layer in the image pyramid, I′ j (x, y) represents the image data of the jth layer in the image pyramid, j represents the image pyramid layer index, i and n represent the small block index and the upper limit of the number of blocks respectively;

[0034] Using the Latulas pyramid to improve the detail information of image data, we have:

[0035] L j (x,y)=I′ j (x,y)-UP(I′ j+1 (x,y)

[0036] Among them, I′ j (x,y),I′ j+1 (x, y) represent the image data of the i-th layer and the i+1-th layer in the image pyramid, UP() represents the up-sampling function, which is used to improve the data details in the image pyramid, L j (x,y) represents the Laplacian image data of the jth layer.

[0037] As a preferred solution of the camera positioning system of a digital UV cold stamping machine based on image recognition described in the present invention, the extraction of the positioning features is specifically as follows:

[0038] Select L in the Laplace pyramid j The maximum value in the area around (x, y) is used as the initial feature point information, and then the selected feature point information is refined according to Taylor expansion, and finally the direction of the feature point is determined according to the gradient rotation, as follows:

[0039]

[0040] θ(x,y)=tan -1 (G x,y )

[0041] Among them, D(x,y) represents the determined feature point information, The second-order derivative matrix, represents the first-order derivative matrix, G x,y The Gaussian gradient representing the feature point information, θ(x, y) representing the direction of the feature point information, and the extraction of the positioning feature information D(x, y, θ) are completed based on the determined feature point information and direction.

[0042] As a preferred solution of the camera positioning system of a digital UV cold stamping machine based on image recognition described in the present invention, the mapping of the stamping image template to the image data through the homography matrix is ​​specifically as follows:

[0043] Using the determined feature point information to construct a 3-row 3-column homography matrix H, we have:

[0044]

[0045] Use the homography matrix to transform the image coordinates of the hot stamping image template to the collected image data, then we have,

[0046]

[0047] Where w represents the normalization factor, Indicates the image coordinates of the hot stamping image template mapped to the image data.

[0048] As a preferred solution of the camera positioning system of a digital UV cold stamping machine based on image recognition described in the present invention, the positioning analysis based on the mapping coordinates and the positioning feature coordinates is specifically as follows:

[0049] The extracted positioning feature information D(x, y, θ) is mapped to the image coordinates in the image data Make a comparison and implement positioning analysis based on the comparison results, as follows:

[0050] The positioning analysis includes primary analysis and secondary analysis. The primary analysis is a preliminary analysis of the position coordinates. The secondary analysis is based on the satisfaction of the primary analysis and verifies the direction. The specific analysis is as follows:

[0051] The primary analysis is performed by mapping the image coordinates to the image data Compared with the position feature value without direction in the extracted positioning feature information D(x,y,θ), we have:

[0052] If the comparison result satisfies the formula When , it means that there is a deviation in the pattern currently stamped on the target object. It is necessary to adjust the control parameters of the current cold stamping machine, collect image data of the target object placed in the digital UV cold stamping machine, and preset the stamping pattern coordinates D″(x″,y″,θ″) in the collected image data until the preset stamping pattern coordinates meet the formula So far, and then conduct secondary analysis;

[0053] If the comparison result satisfies the formula When , it means that the pattern currently stamped on the target object has no deviation in coordinate position, and the secondary analysis is continued to ensure the accuracy of the stamping pattern;

[0054] The secondary analysis is to conduct a secondary verification analysis on the coordinate position of the pattern currently stamped on the target object. If there is no deviation, then,

[0055] Calculate the direction rotation of the hot stamping pattern, then we have:

[0056] Compare the result of the rotation calculation with the directional feature value in the positioning feature information to complete the secondary analysis, and then we have:

[0057] When the comparison result satisfies the formula θ′≡θ, it means that the pattern currently stamped on the target object is consistent with the position and direction of the preset template pattern, which meets the stamping requirements, maintains the current machine parameters, and continues to operate normally;

[0058] When the comparison result satisfies the formula θ′≠θ, it means that the direction of the pattern currently stamped on the target object is inconsistent with the preset template pattern. It is necessary to adjust the reverse control parameters in the digital UV cold stamping machine until the formula θ′≡θ is satisfied, so as to achieve precise stamping of the cold stamping machine.

[0059] The beneficial effects of the present invention are as follows: the present invention can collect high-quality image data in real time under different light intensities by dynamically adjusting camera parameters and setting trigger mechanisms, effectively avoiding image blur or distortion problems caused by light changes; the image data is preprocessed by dynamically adjusting the Gaussian kernel size and regional contrast enhancement method, effectively removing image noise, enhancing the image contrast, and providing a clearer and more accurate image basis for subsequent positioning feature extraction; the positioning features in the image are extracted by constructing an image pyramid and a Laplace pyramid, and the hot stamping image template is mapped to the image data using a homography matrix, thereby achieving high-precision positioning analysis. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work. Among them:

[0061] Figure 1 The present invention is a schematic diagram of the overall composition of a camera positioning system of a digital UV cold stamping machine based on image recognition. DETAILED DESCRIPTION

[0062] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0063] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0064] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0065] The present invention is described in detail with reference to schematic diagrams. When describing the embodiments of the present invention, for the sake of convenience, the cross-sectional diagrams showing the device structure will not be partially enlarged according to the general scale, and the schematic diagrams are only examples, which should not limit the scope of protection of the present invention. In addition, in actual production, the three-dimensional dimensions of length, width and depth should be included.

[0066] Meanwhile, in the description of the present invention, it should be noted that the terms "first, second or third" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0067] In the present invention, unless otherwise clearly specified and limited, the terms "install, connect, connect" should be understood in a broad sense, for example: it can be a fixed connection, a detachable connection or an integral connection; it can also be a mechanical connection, an electrical connection or a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0068] Example 1

[0069] Reference Figure 1 , which is the first embodiment of the present invention, provides a digital UV cold stamping machine camera positioning system based on image recognition, including an image acquisition and processing module, a positioning feature extraction module, and a positioning analysis module;

[0070] Specifically, the image acquisition and processing module is used to complete the acquisition and processing of image data, the positioning feature extraction module is used to extract features from the processed image data, and the positioning analysis module is used to analyze the hot stamping pattern according to the extracted positioning features, and adjust the control parameters of the digital UV cold stamping machine according to the analysis results to achieve precise hot stamping.

[0071] Furthermore, the image acquisition and processing module includes an image acquisition unit and an image processing unit. The image acquisition unit is used to acquire image data in real time, and the image processing unit is used to process the acquired image data to improve the quality of the image data.

[0072] Specifically, the image acquisition unit adjusts the parameters of the camera carried by the digital UV cold stamping machine to adapt to the acquisition of image data under different lighting conditions, and sets a trigger mechanism to capture image data. The acquisition of image data under different lighting conditions is to dynamically adjust the camera parameters according to the light intensity, then,

[0073]

[0074] Where t1 and t2 represent the camera exposure time range, L(x,y,t) represents the light intensity in the (x,y) direction at time t, R(x,y) represents the camera parameters in the (x,y) direction, which are set by the implementer according to the actual application scenario, I represents the collected image data, and satisfies I={I t ,I t-1}, I t Represents the image data of the object before hot stamping, I t-1 Represents the image data of the object after hot stamping;

[0075] Setting the trigger mechanism to capture image data is to achieve real-time acquisition of image data by setting the trigger mechanism. The specific implementation is as follows:

[0076] A photoelectric sensor is installed in the all-in-one machine to detect the arrival of the object to be stamped. When the object is detected to enter the camera's field of view, the photoelectric sensor sends a signal to the system;

[0077] When the system receives the signal sent by the photoelectric sensor, it converts the received signal into a trigger signal for image data acquisition and sends it to the camera;

[0078] After receiving the trigger signal, the camera immediately captures the image data of the current object. At the same time, the shooting frequency and camera parameters can be set according to the light intensity of the current environment.

[0079] The image processing unit processes the collected image data using data preprocessing technology to improve the image data quality. The data preprocessing technology includes adaptive denoising and regional contrast enhancement.

[0080] Adaptive denoising is based on Gaussian filter denoising. The Gaussian kernel size is dynamically adjusted to achieve adaptive denoising. The details are as follows:

[0081] Divide the collected image data into multiple small blocks and calculate the local variance of each small block;

[0082] According to the calculated local variance, the size of the Gaussian kernel is dynamically adjusted, then,

[0083] σ(x,y)=var(I i (x,y))·α+β

[0084] Among them, I i (x, y) represents the image data of the ith small block, α and β represent adjustment coefficients, and satisfy the formula α+β=1, which is set by the implementer according to the actual application scenario, and σ(x, y) represents the Gaussian kernel size;

[0085] According to the adjusted Gaussian kernel size, the image data is denoised using a Gaussian filter. The Gaussian filter is a conventional application technology for image denoising and will not be described in detail here.

[0086] Regional contrast enhancement is to adaptively enhance the contrast of image data based on the brightness histogram of image data, as follows:

[0087] For the segmented small block image data I i (x, y), perform brightness histogram analysis to identify different brightness areas;

[0088] According to different brightness areas, the contrast of image data is adaptively enhanced, then:

[0089] I i,reg (x,y)=I i (x,y)·α(x,y)+β(x,y)

[0090] Among them, I i (x, y) represents the image data of the ith small block, α and β represent adjustment coefficients, and satisfy the formula α+β=1, which is set by the implementer according to the actual application scenario. i,reg (x,y) means increasing the contrast of the (x,y) region of the i-th small block of the image.

[0091] It should be noted that after the image data I is collected, the image data is processed by a data preprocessing technique, and the processed data I′ is sent to a positioning feature extraction module for subsequent feature extraction and positioning analysis.

[0092] Furthermore, the positioning feature extraction module is obtained from the image data of the object after the pattern is stamped. t ' -1 Extract positioning feature information;

[0093] Specifically, the extraction of positioning feature information is to reduce the image data resolution layer by layer by constructing an image pyramid, and at the same time use the Laplacian pyramid to increase the detail information of the image data, and then complete the positioning feature extraction based on the detected feature point information by detecting feature point information. The specific implementation is as follows:

[0094] Using Gaussian filtering to reduce the resolution of image data layer by layer, we have:

[0095] I′ j (x,y)=G(x,y,σ i )*I′(x,y)

[0096]

[0097] Among them, I′(x,y) represents the image data at the position (x,y) after data preprocessing, G(x,y,σ i ) represents the Gaussian image data of the i-th layer in the image pyramid, I′ j (x, y) represents the image data of the jth layer in the image pyramid, j represents the image pyramid layer index, i and n represent the small block index and the upper limit of the number of blocks respectively;

[0098] Using the Latulas pyramid to improve the detail information of image data, we have:

[0099] L j (x,y)=I′ j (x,y)-UP(I′ j+1 (x,y)

[0100] Among them, I′ j (x,y),I′ j+1 (x, y) represent the image data of the i-th layer and the i+1-th layer in the image pyramid, UP() represents the up-sampling function, which is used to improve the data details in the image pyramid, L j (x,y) represents the Laplacian image data of the jth layer;

[0101] The location feature extraction is completed according to the detected feature point information by selecting L in the Laplace pyramid j The maximum value in the area around (x, y) is used as the initial feature point information, and then the selected feature point information is refined according to Taylor expansion, and finally the direction of the feature point is determined according to the gradient rotation, as follows:

[0102]

[0103] θ(x,y)=tan -1 (G x,y )

[0104] Among them, D(x,y) represents the determined feature point information, The second-order derivative matrix, represents the first-order derivative matrix, G x,y The Gaussian gradient representing the feature point information, θ(x, y) representing the direction of the feature point information, and the extraction of the positioning feature information D(x, y, θ) are completed based on the determined feature point information and direction.

[0105] Furthermore, the positioning analysis module maps the hot stamping pattern template in the digital UV cold stamping machine to the hot stamping image data based on the positioning feature information extracted from the hot stamping image data, and completes the positioning analysis by comparing the extracted positioning feature information with the mapped position coordinates.

[0106] Specifically, the hot stamping pattern template of the digital UV cold stamping machine is mapped to the image data of the completed hot stamping by mapping the image coordinates of the hot stamping image template to the collected image data through the homography matrix, and then determining the position of the hot stamping image in the image data, as follows:

[0107] Using the determined feature point information to construct a 3-row 3-column homography matrix H, we have:

[0108]

[0109] Use the homography matrix to transform the image coordinates of the hot stamping image template to the collected image data, then we have,

[0110]

[0111] Where w represents the normalization factor, Indicates the image coordinates of the hot stamping image template mapped to the image data;

[0112] Positioning analysis is to extract the positioning feature information D(x, y, θ) and map it to the image coordinates in the image data. Make a comparison and implement positioning analysis based on the comparison results, as follows:

[0113] Positioning analysis includes primary analysis and secondary analysis. The primary analysis is a preliminary analysis of the location coordinates. The secondary analysis is based on the satisfaction of the primary analysis and verifies the direction. The specific analysis is as follows:

[0114] An analysis is performed by mapping the image coordinates into the image data Compared with the position feature value without direction in the extracted positioning feature information D(x,y,θ), we have:

[0115] If the comparison result satisfies the formula When , it means that there is a deviation in the pattern currently stamped on the target object. It is necessary to adjust the control parameters of the current cold stamping machine, collect image data of the target object placed in the digital UV cold stamping machine, and preset the stamping pattern coordinates D″(x″,y″,θ″) in the collected image data until the preset stamping pattern coordinates meet the formula So far, and then conduct secondary analysis;

[0116] If the comparison result satisfies the formula When , it means that the pattern currently stamped on the target object has no deviation in coordinate position, and the secondary analysis is continued to ensure the accuracy of the stamping pattern;

[0117] Secondary analysis is to verify that there is no deviation in the coordinate position of the pattern currently stamped on the target object.

[0118] Calculate the direction rotation of the hot stamping pattern, then we have:

[0119] Compare the result of the rotation calculation with the directional feature value in the positioning feature information to complete the secondary analysis, and then we have:

[0120] When the comparison result satisfies the formula θ′≡θ, it means that the pattern currently stamped on the target object is consistent with the position and direction of the preset template pattern, which meets the stamping requirements, maintains the current machine parameters, and continues to operate normally;

[0121] When the comparison result satisfies the formula θ′≠θ, it means that the direction of the pattern currently stamped on the target object is inconsistent with the preset template pattern. It is necessary to adjust the reverse control parameters in the digital UV cold stamping machine until the formula θ′≡θ is satisfied, so as to achieve precise stamping of the cold stamping machine.

[0122] Furthermore, if the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art or the 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 a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the various embodiments of the system of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0123] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0124] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering, or processing in another suitable manner as necessary, and then stored in a computer memory.

[0125] Additionally, in order to provide a concise description of exemplary embodiments, all features of an actual embodiment (ie, those features that are not relevant to the best mode presently contemplated for carrying out the invention or those that are not relevant to implementing the invention) may not be described.

[0126] It should be understood that in the development of any actual implementation, as in any engineering or design project, numerous implementation-specific decisions may be made. Such a development effort may be complex and time-consuming, but for those of ordinary skill having the benefit of this disclosure, the development effort will be a routine task of design, fabrication, and production without undue experimentation.

[0127] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A camera positioning system for digital UV cold stamping machine based on image recognition. Features: Including, image acquisition and processing module, positioning feature extraction module and positioning analysis module; The image acquisition and processing module includes an image acquisition unit and an image processing unit, specifically: Data acquisition under different light intensities is achieved by dynamically adjusting camera parameters, and a trigger mechanism is set to achieve real-time acquisition of image data. Image data preprocessing is then achieved by dynamically adjusting the Gaussian kernel size and regional contrast enhancement. The positioning feature extraction module determines the position and direction of feature points by constructing an image pyramid and a Laplacian pyramid to extract positioning features; The positioning analysis module maps the hot stamping image template to the image data through the homography matrix, performs positioning analysis according to the mapping coordinates and the positioning feature coordinates, and finally completes the control adjustment of the machine parameters according to the positioning analysis results.

2. A camera positioning system for a digital UV cold stamping machine based on image recognition as claimed in claim 1, Features: The data acquisition under different light intensities by dynamically adjusting the camera parameters is specifically implemented as follows: Where t1 and t2 represent the camera exposure time range, L(x,y,t) represents the light intensity in the (x,y) direction at time t, R(x,y) represents the camera parameters in the (x,y) direction, which are set by the implementer according to the actual application scenario, I represents the collected image data, and satisfies I={I t ,I t-1 }, I t Represents the image data of the object before hot stamping, I t-1 Represents the image data of the object after hot stamping.

3. A camera positioning system for a digital UV cold stamping machine based on image recognition as claimed in claim 2, Features: The specific implementation of setting the trigger mechanism to realize the real-time acquisition of image data is as follows: A photoelectric sensor is installed in the all-in-one machine to detect the arrival of the object to be stamped. When the object is detected to enter the camera's field of view, the photoelectric sensor sends a signal to the system; When the system receives the signal sent by the photoelectric sensor, it converts the received signal into a trigger signal for image data acquisition and sends it to the camera; After receiving the trigger signal, the camera immediately captures the image data of the current object and sets the shooting frequency and camera parameters according to the light intensity of the current environment.

4. A camera positioning system for a digital UV cold stamping machine based on image recognition as claimed in claim 3, Features: The dynamic adjustment of the Gaussian kernel size is specifically implemented as follows: Divide the collected image data into multiple small blocks and calculate the local variance of each small block; According to the calculated local variance, the size of the Gaussian kernel is dynamically adjusted, then, σ(x,y)=var(I i (x,y))·α+β Among them, I i (x, y) represents the image data of the ith small block, α and β represent adjustment coefficients, and satisfy the formula α+β=1, which is set by the implementer according to the actual application scenario, and σ(x, y) represents the Gaussian kernel size; According to the adjusted Gaussian kernel size, the image data is denoised using a Gaussian filter; The regional contrast enhancement is specifically as follows: For the segmented small block image data I i (x, y), perform brightness histogram analysis to identify different brightness areas; According to different brightness areas, the contrast of image data is adaptively enhanced, then: I i,reg (x,y)=I i (x,y)·α(x,y)+β(x,y) Among them, I i (x, y) represents the image data of the ith small block, α and β represent adjustment coefficients, and satisfy the formula α+β=1, which is set by the implementer according to the actual application scenario. i,reg (x,y) means increasing the contrast of the (x,y) region of the i-th small block of the image.

5. A camera positioning system for a digital UV cold stamping machine based on image recognition as claimed in claim 4, Features: The construction of the image pyramid and the Laplacian pyramid is specifically as follows: By building an image pyramid and reducing the image data resolution layer by layer, we have: I j ′(x,y)=G(x,y,σ i )*I′(x,y) Among them, I′(x,y) represents the image data at the position (x,y) after data preprocessing, G(x,y,σ i ) represents the Gaussian image data of the i-th layer in the image pyramid, I j ′(x,y) represents the image data of the jth layer in the image pyramid, j represents the image pyramid layer index, i and n represent the small block index and the upper limit of the number of blocks respectively; Using the Latulas pyramid to improve the detail information of image data, we have: L j (x,y)=I j ′(x,y)-UP(I j ′ +1 (x,y)) Among them, I′ j (x,y),I′ j+1 (x, y) represent the image data of the i-th layer and the i+1-th layer in the image pyramid, UP() represents the up-sampling function, which is used to improve the data details in the image pyramid, L j (x,y) represents the Laplacian image data of the jth layer.

6. A camera positioning system for a digital UV cold stamping machine based on image recognition as claimed in claim 5, Features: The extraction of the positioning features is specifically as follows: Select L in the Laplace pyramid j The maximum value in the area around (x, y) is used as the initial feature point information, and then the selected feature point information is refined according to Taylor expansion, and finally the direction of the feature point is determined according to the gradient rotation, as follows: θ(x,y)=tan -1 (G x,y ) Among them, D(x,y) represents the determined feature point information, The second-order derivative matrix, represents the first-order derivative matrix, G x,y The Gaussian gradient representing the feature point information, θ(x, y) representing the direction of the feature point information, and the extraction of the positioning feature information D(x, y, θ) are completed based on the determined feature point information and direction.

7. A camera positioning system for a digital UV cold stamping machine based on image recognition as claimed in claim 6, Features: The mapping of the hot stamping image template to the image data through the homography matrix is ​​specifically as follows: Using the determined feature point information to construct a 3-row 3-column homography matrix H, we have: Use the homography matrix to transform the image coordinates of the hot stamping image template to the collected image data, then we have, Where w represents the normalization factor, Indicates the image coordinates of the hot stamping image template mapped to the image data.

8. A camera positioning system for a digital UV cold stamping machine based on image recognition as claimed in claim 7, It is characterized in that The positioning analysis based on the mapping coordinates and the positioning feature coordinates is specifically as follows: The extracted positioning feature information D(x, y, θ) is mapped to the image coordinates in the image data Make a comparison and implement positioning analysis based on the comparison results, as follows: The positioning analysis includes primary analysis and secondary analysis. The primary analysis is a preliminary analysis of the position coordinates. The secondary analysis is based on the satisfaction of the primary analysis and verifies the direction. The specific analysis is as follows: The primary analysis is performed by mapping the image coordinates to the image data Compared with the position feature value without direction in the extracted positioning feature information D(x,y,θ), we have: If the comparison result satisfies the formula When , it means that there is a deviation in the pattern currently stamped on the target object. It is necessary to adjust the control parameters of the current cold stamping machine, collect image data of the target object placed in the digital UV cold stamping machine, and preset the stamping pattern coordinates D″(x″,y″,θ″) in the collected image data until the preset stamping pattern coordinates meet the formula So far, and then conduct secondary analysis; If the comparison result satisfies the formula When , it means that the pattern currently stamped on the target object has no deviation in coordinate position, and the secondary analysis is continued to ensure the accuracy of the stamping pattern; The secondary analysis is to conduct a secondary verification analysis on the coordinate position of the pattern currently stamped on the target object. If there is no deviation, then, Calculate the direction rotation of the hot stamping pattern, then we have: Compare the result of the rotation calculation with the directional feature value in the positioning feature information to complete the secondary analysis, and then we have: When the comparison result satisfies the formula θ′≡θ, it means that the pattern currently stamped on the target object is consistent with the position and direction of the preset template pattern, which meets the stamping requirements, maintains the current machine parameters, and continues to operate normally; When the comparison result satisfies the formula θ′≠θ, it means that the direction of the pattern currently stamped on the target object is inconsistent with the preset template pattern. It is necessary to adjust the reverse control parameters in the digital UV cold stamping machine until the formula θ′≡θ is satisfied, so as to achieve precise stamping of the cold stamping machine.

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