Scanning method and system based on pre-scanning and dynamic optimization, medium and equipment

Abstract

The invention discloses a scanning method and system based on pre-scanning and dynamic optimization, a medium and equipment, and the method comprises the specific steps: a pre-scanning step: carrying out the preliminary scanning of a file through light sources with different wavelengths through a multispectral scanning technology, and obtaining image information containing visible light and invisible light wave bands; a pre-scanning analysis step: based on a deep learning image analysis algorithm, analyzing a preliminary scanning image in real time, and identifying a file type, a non-uniform illumination region and a potential scanning problem; a light supplement adjustment step: dynamically adjusting the brightness, angle and spectral range of a light supplement lamp according to the pre-scanning analysis result; a high-precision scanning step: performing high-precision formal scanning to obtain a scanning image; and a post-processing step: based on AI denoising, sharpening, color correction and semantic analysis, generating an optimized scanning file. According to the method, dynamic adaptation to different document features can be realized through setting of the pre-scanning analysis step and the light supplementing adjustment step, and the scanning quality and efficiency are remarkably improved.

Description

Technical Field

[0001] The present invention relates to the field of automatic scanning, and particularly to a scanning method, system, medium and device based on pre-scanning and dynamic optimization. Background Art

[0002] In the prior art, automatic scanning devices and methods are usually used for the digital processing of documents, images or other objects. However, traditional scanning methods often lack flexibility and efficiency, especially when dealing with documents of different sizes, qualities and types. In addition, traditional scanning devices often cannot make dynamic adjustments according to the actual characteristics of the document during the scanning process, resulting in uneven quality of the scanning results. Therefore, there is an urgent need in the market for a scanning method that can overcome these defects and improve the scanning efficiency and quality. Summary of the Invention

[0003] The technical problem solved by the present invention is to provide a scanning method based on pre-scanning and dynamic optimization that improves scanning clarity.

[0004] The technical solution adopted by the present invention to solve its technical problems is: a scanning method based on pre-scanning and dynamic optimization, and the specific steps are as follows:

[0005] Pre-scanning step: Using multi-spectral scanning technology, initially scan the document with light sources of different wavelengths to obtain image information containing visible and non-visible light bands;

[0006] Pre-scanning analysis step: Based on a deep learning image analysis algorithm, analyze the initially scanned image in real time to identify the document type, uneven illumination areas and potential scanning problems;

[0007] Light compensation adjustment step: According to the pre-scanning analysis results, dynamically adjust the brightness, angle and spectral range of the fill light;

[0008] High-precision scanning step: Perform high-precision formal scanning to obtain a scanned image;

[0009] Post-processing step: Based on AI-based denoising, sharpening, color correction and semantic analysis, generate an optimized scanned file.

[0010] Furthermore: The multi-spectral scanning technology uses light sources in the infrared, ultraviolet and visible light bands to identify hidden information, watermarks and faded content in the document, and generates a scanned image through a multi-spectral image fusion algorithm.

[0011] Furthermore: The light compensation adjustment step is specifically:

[0012] Real-time monitor the illumination intensity, reflectivity and shadow distribution on the surface of the document through a light sensor;

[0013] Determine the target brightness, angle, and spectral range of the fill light according to the pre-scan analysis results;

[0014] Adopt an LED light source with high response speed, and combine with pre-scan feedback to dynamically adjust the power, angle, and light transmittance of the filter of the fill light.

[0015] Furthermore: It also includes a scanning authentication step, specifically:

[0016] After the scanning is completed, automatically generate the digital fingerprint of the file and upload the fingerprint to the blockchain network

[0017] Users can query the scanning time, modification records, and authentication information of the file through the blockchain.

[0018] Furthermore: The specific steps of the AI-based denoising, sharpening, color correction, and semantic analysis include:

[0019] Denoising step: Adopt a deep learning-based denoising model to identify and remove random noise in the image while retaining detail information;

[0020] Sharpening step: Through edge detection and enhancement algorithms, improve the clarity of text and images, and do not perform targeted processing on blurred areas;

[0021] Color correction step: Use color balance and white point correction algorithms to automatically adjust the color deviation of the image;

[0022] Semantic analysis step: Perform OCR recognition on the scanned text, and combine natural language processing technology to automatically supplement unclear parts.

[0023] Furthermore: It also includes a voice control step, specifically:

[0024] Start the scanning device through voice commands. The device parses the user's commands through a voice recognition engine and executes corresponding operations;

[0025] The device provides real-time feedback on the operation status and uses voice prompts to inform the user of the current operation progress.

[0026] The present invention also discloses a scanning system based on pre-scanning and dynamic optimization, including a pre-scanning module, a pre-scanning analysis module, a fill light adjustment module, a high-precision scanning module, and a post-processing module;

[0027] The pre-scanning module is used to use multi-spectral scanning technology to preliminarily scan the file through light sources of different wavelengths to obtain image information including visible and non-visible light bands;

[0028] The pre-scanning analysis module is used to analyze the preliminarily scanned image in real time based on a deep learning image analysis algorithm to identify the file type, uneven illumination areas, and potential scanning problems;

[0029] The supplementary light adjustment module is used to dynamically adjust the brightness, angle and spectral range of the supplementary light according to the pre-scanning analysis result;

[0030] The high-precision scanning module is used to perform high-precision formal scanning to obtain a scanned image;

[0031] The post-processing module is used to generate an optimized scanned file based on AI-based denoising, sharpening, color correction and semantic analysis.

[0032] Furthermore: The multispectral scanning technology uses light sources in the infrared, ultraviolet and visible light bands to identify hidden information, watermarks and faded content in the document, and generates a scanned image through a multispectral image fusion algorithm.

[0033] The present invention also discloses a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the above-mentioned scanning method based on pre-scanning and dynamic optimization are implemented.

[0034] The present invention also discloses a computer device, including a processor, a communication interface, a memory and a communication bus. Among them, the processor, the communication interface, and the memory complete communication with each other through the communication bus; among them:

[0035] The memory is used to store a computer program;

[0036] The processor is used to execute the steps of the above-mentioned scanning method based on pre-scanning and dynamic optimization by running the program stored on the memory.

[0037] The beneficial effects of the present invention are:

[0038] 1. In the present invention, through the settings of the pre-scanning analysis step and the supplementary light adjustment step, dynamic adaptation to different document features can be achieved, significantly improving the scanning quality and efficiency.

[0039] 2. By combining the multispectral scanning technology and the deep learning image analysis algorithm, the present invention can identify and process hidden information, watermarks and faded content in the document, improving the comprehensiveness and accuracy of scanning.

[0040] 3. The scanning authentication step of the present invention uses blockchain technology to provide reliable digital fingerprints and authentication information for the scanned file, enhancing the security and credibility of the file.

[0041] 4. By adding the voice control step, the user can easily control the scanning device through voice commands, improving the usability of the device and the user experience. Description of the Drawings

[0042] Figure 1 This is a flowchart showing the pre-scanning and dynamic optimization scanning method according to an embodiment of the present application.

[0043] Figure 2 This is a schematic framework diagram of the pre-scanning and dynamic optimization scanning system according to an embodiment of the present application. Detailed implementation manners

[0044] To make the above objects, features, and advantages of the present invention more obvious and understandable, the following will describe in detail the specific implementation manners of the present invention with reference to the accompanying drawings.

[0045] As Figure 1 shown, the embodiments of the present application disclose a scanning method based on pre-scanning and dynamic optimization. The specific steps are as follows:

[0046] Pre-scanning step: Using multi-spectral scanning technology, preliminarily scan the document with light sources of different wavelengths to obtain image information including visible and non-visible light bands.

[0047] Pre-scanning analysis step: Based on a deep learning image analysis algorithm, analyze the preliminarily scanned image in real time to identify the document type, uneven illumination areas, and potential scanning problems.

[0048] Light compensation adjustment step: Dynamically adjust the brightness, angle, and spectral range of the fill light according to the pre-scanning analysis results.

[0049] High-precision scanning step: Perform high-precision formal scanning to obtain a scanned image.

[0050] Post-processing step: Generate an optimized scanned document based on AI-based denoising, sharpening, color correction, and semantic analysis.

[0051] Specifically, the specific steps of the AI-based denoising, sharpening, color correction, and semantic analysis include:

[0052] Denoising step: Adopt a deep learning-based denoising model to identify and remove random noise in the image while retaining detailed information.

[0053] Sharpening step: Through edge detection and enhancement algorithms, improve the clarity of text and images, rather than performing targeted processing on blurred areas.

[0054] Color correction step: Use color balance and white point correction algorithms to automatically adjust the color deviation of the image.

[0055] Semantic analysis step: Perform OCR recognition on the scanned text, and combine natural language processing technology to automatically supplement unclear parts.

[0056] Specifically, a high-precision optical sensor is used to continuously monitor the light intensity, reflectivity, and shadow distribution on the document surface. Subsequently, based on the pre-scan analysis results, the system uses advanced algorithms to determine the optimal brightness, angle, and spectral range of the fill light to achieve optimal illumination for different document features. Then, the system uses a high-resolution scanning head to formally scan the document. In this step, the scanning head precisely captures every detail on the document surface to ensure the clarity and accuracy of the scanned image. Meanwhile, the system also fine-tunes the scanning parameters according to the previous pre-scan analysis results to adapt to the special requirements of different documents. In the post-processing step, the system further optimizes the scanned image using AI-based denoising, sharpening, color correction, and semantic analysis algorithms.

[0057] In the present invention, the settings of the pre-scan analysis step and the fill light adjustment step enable dynamic adaptation to different document features, significantly improving the scanning quality and efficiency.

[0058] In this embodiment, the multispectral scanning technology uses light sources in the infrared, ultraviolet, and visible light bands to identify hidden information, watermarks, and faded content in the document, and generates a scanned image through a multispectral image fusion algorithm.

[0059] Specifically, during the scanning process, the infrared light source can penetrate the paper to identify watermarks or anti-counterfeiting marks hidden under the text; the ultraviolet light source can excite fluorescent substances in the document to make them visible; and the light source in the visible light band is responsible for capturing the regular image information of the document. The image information obtained by these light sources in different bands is then fused through a multispectral image fusion algorithm to generate a scanned image that contains both regular image information, hidden information, and high-fidelity color information.

[0060] In this embodiment, the fill light adjustment step specifically includes:

[0061] Continuously monitor the light intensity, reflectivity, and shadow distribution on the document surface through an optical sensor;

[0062] Determine the target brightness, angle, and spectral range of the fill light according to the pre-scan analysis results;

[0063] Adopt an LED light source with a high response speed, and dynamically adjust the power, angle, and filter transmittance of the fill light in combination with the pre-scan feedback.

[0064] Specifically, the system first comprehensively monitors the lighting conditions on the document surface through high-precision optical sensors. These sensors can capture the lighting intensity, reflectivity, and shadow distribution on the document surface in real time. Subsequently, based on the results of the deep learning image analysis algorithm in the pre-scanning step, the system determines the target brightness, angle, and spectral range that the fill light needs to achieve. After determining the fill light parameters, the system uses an LED light source with a high response speed and combines the real-time feedback in the pre-scanning step to dynamically adjust the power, angle, and light transmittance of the filter of the fill light, thereby achieving optimal lighting for different document features and further improving the quality and efficiency of scanning.

[0065] In this embodiment, it further includes a scanning authentication step, specifically:

[0066] After the scanning is completed, a digital fingerprint of the document is automatically generated and uploaded to the blockchain network.

[0067] Users can query the scanning time, modification records, and authentication information of the document through the blockchain.

[0068] Specifically, after the scanning task is completed, the system will automatically extract feature information from the scanned image and generate a unique digital fingerprint using an advanced encryption algorithm. Subsequently, the system will upload this fingerprint information to a secure and reliable blockchain network for distributed storage and verification. Users can simply query the detailed information of their scanned documents in the blockchain network, including the specific scanning time, whether the document has been modified, and the authentication information of the document. This step not only provides a convenient query method for users but also greatly enhances the security and credibility of the scanned documents.

[0069] In this embodiment, it further includes a voice control step, specifically:

[0070] Start the scanning device through voice commands. The device parses the user commands through a voice recognition engine and performs corresponding operations;

[0071] The device provides real-time feedback on the operation status and prompts the user of the current operation progress through voice.

[0072] Specifically, users can control the operation of the scanning device through simple voice commands such as "start scanning" and "stop scanning". The device is built with an advanced voice recognition engine that can accurately parse the user's voice commands and quickly perform corresponding operations. At the same time, the device also provides real-time feedback on the operation status and prompts the user of the current operation progress through voice, such as "pre-scanning", "fill light adjustment in progress", "scanning completed", etc. The addition of this voice control function enables users to easily complete the scanning task without manual operation of the device, greatly improving the usability of the device and the user experience.

[0073] The present invention also discloses a scanning system based on pre-scanning and dynamic optimization, including a pre-scanning module, a pre-scanning analysis module, a supplementary light adjustment module, a high-precision scanning module, and a post-processing module;

[0074] The pre-scanning module is used to use multi-spectral scanning technology to preliminarily scan a document through light sources of different wavelengths, and obtain image information including visible light and non-visible light bands;

[0075] The pre-scanning analysis module is used to analyze the preliminarily scanned image in real time based on a deep learning image analysis algorithm, and identify the document type, uneven illumination areas, and potential scanning problems;

[0076] The supplementary light adjustment module is used to dynamically adjust the brightness, angle, and spectral range of the supplementary light according to the pre-scanning analysis results;

[0077] The high-precision scanning module is used to perform high-precision formal scanning to obtain a scanned image;

[0078] The post-processing module is used to perform denoising, sharpening, color correction, and semantic analysis based on AI to generate an optimized scanned document.

[0079] Specifically, the multi-spectral scanning technology uses light sources in the infrared, ultraviolet, and visible light bands to identify hidden information, watermarks, and faded content in the document, and generates a scanned image through a multi-spectral image fusion algorithm.

[0080] Through the settings of the pre-scanning analysis step and the supplementary light adjustment step, this system can achieve dynamic adaptation to different document characteristics, significantly improve the scanning quality and efficiency. At the same time, through the combination of multi-spectral scanning technology and deep learning image analysis algorithm, it can identify and process hidden information, watermarks, and faded content in the document, improving the comprehensiveness and accuracy of scanning.

[0081] The present invention also discloses a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it realizes the steps of the above-mentioned scanning method based on pre-scanning and dynamic optimization.

[0082] In addition, the computer-readable storage medium of this embodiment can adopt any combination of one or more readable storage media, where the readable storage medium includes an electrical, optical, electromagnetic, infrared, or semiconductor system, device, or component, or any combination of the above.

[0083] The present invention also discloses a computer device, including a processor, a communication interface, a memory, and a communication bus. Among them, the processor, the communication interface, and the memory complete mutual communication through the communication bus; where:

[0084] The memory is used to store computer programs;

[0085] The processor is configured to execute the steps of the above-mentioned scanning method based on pre-scanning and dynamic optimization by running the programs stored on the memory.

[0086] As an implementation manner of the present invention, the communication bus mentioned in the above terminal may be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. This communication bus can be divided into an address bus, a data bus, a control bus, etc.

[0087] As an implementation manner of the present invention, the communication interface is used for communication between the above terminal and other devices.

[0088] As an implementation manner of the present invention, the memory may include a Random Access Memory (RAM), or may also include a non-volatile memory, such as at least one disk memory. Optionally, the memory may also be at least one storage device located far from the aforementioned processor.

[0089] As an implementation manner of the present invention, the above-mentioned processor may be a general-purpose processor, including a Central Processing Unit (CPU), a Network Processor (NP), etc.; it may also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.

[0090] The specific embodiments described above further elaborate on the purpose, technical solutions, and beneficial effects of the present invention. It should be understood that the above are only specific embodiments of the present invention and are not used to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A scanning method based on pre-scanning and dynamic optimization, characterized in that, The specific steps are as follows: Pre-scanning step: Using multi-spectral scanning technology, initially scan the document with light sources of different wavelengths to obtain image information including visible and non-visible light bands; Pre-scanning analysis step: Based on deep learning image analysis algorithms, analyze the initially scanned images in real time to identify document types, unevenly illuminated areas, and potential scanning problems; Light compensation adjustment step: Dynamically adjust the brightness, angle, and spectral range of the fill light according to the pre-scanning analysis results; High-precision scanning step: Conduct high-precision formal scanning to obtain scanned images; Post-processing step: Generate optimized scanned documents based on AI-based denoising, sharpening, color correction, and semantic analysis; 2. The scanning method based on pre-scanning and dynamic optimization according to claim 1, wherein The multi-spectral scanning technology uses light sources in the infrared, ultraviolet, and visible light bands to identify hidden information, watermarks, and faded content in the document, and generates scanned images through multi-spectral image fusion algorithms; 3. The scanning method based on pre-scanning and dynamic optimization according to claim 1, characterized in that The light compensation adjustment step specifically includes: Real-time monitoring of the light intensity, reflectivity, and shadow distribution on the document surface through light sensors; Determine the target brightness, angle, and spectral range of the fill light according to the pre-scanning analysis results; Adopt LED light sources with high response speed, and dynamically adjust the power, angle, and light transmittance of the filter of the fill light in combination with pre-scanning feedback; 4. The scanning method based on pre-scanning and dynamic optimization according to claim 1, characterized in that It also includes a scanning authentication step, specifically: After scanning is completed, automatically generate a digital fingerprint of the document and upload the fingerprint to the blockchain network; Users can query the scanning time, modification records, and authentication information of the document through the blockchain; 5. The scanning method based on pre-scanning and dynamic optimization according to claim 1, characterized in that The specific steps of the AI-based denoising, sharpening, color correction, and semantic analysis include: Denoising step: Adopt a deep learning-based denoising model to identify and remove random noise in the image while retaining detail information; Sharpening step: Improve the clarity of text and images through edge detection and enhancement algorithms, rather than specifically processing blurred areas; Color correction step: Use color balance and white point correction algorithms to automatically adjust the color deviation of the image; Semantic analysis step: Perform OCR recognition on the scanned text, and combine natural language processing technology to automatically supplement unclear parts; 6. The scanning method based on pre-scanning and dynamic optimization according to claim 1, wherein: It also includes a voice control step, specifically: Start the scanning device through voice commands. The device analyzes the user's commands through a voice recognition engine and executes corresponding operations; The device provides real-time feedback on the operation status and prompts the user of the current operation progress through voice; 7. A scanning system based on pre-scanning and dynamic optimization, characterized in that It includes a pre-scanning module, a pre-scanning analysis module, a light compensation adjustment module, a high-precision scanning module, and a post-processing module; The pre-scanning module is used to initially scan the document with light sources of different wavelengths using multi-spectral scanning technology to obtain image information including visible and non-visible light bands; The pre-scanning analysis module is used to analyze the initially scanned images in real time based on deep learning image analysis algorithms to identify document types, unevenly illuminated areas, and potential scanning problems; The light compensation adjustment module is used to dynamically adjust the brightness, angle, and spectral range of the fill light according to the pre-scanning analysis results; The high-precision scanning module is used to conduct high-precision formal scanning to obtain scanned images; The post-processing module is used to generate optimized scanned documents based on AI-based denoising, sharpening, color correction, and semantic analysis.

8. The scanning system based on pre-scanning and dynamic optimization according to claim 7, wherein The multi-spectral scanning technology uses light sources in the infrared, ultraviolet, and visible light bands to identify hidden information, watermarks, and faded content in documents, and generates a scanned image through a multi-spectral image fusion algorithm.

9. A computer-readable storage medium, characterized in that, A computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the steps of the scanning method based on pre-scanning and dynamic optimization according to any one of claims 1 to 6 are implemented.

10. A computer device, characterized in that, It includes a processor, a communication interface, a memory, and a communication bus. Among them, the processor, the communication interface, and the memory complete communication with each other through the communication bus; where: The memory is used to store a computer program; The processor is used to execute the steps of the scanning method based on pre-scanning and dynamic optimization according to any one of claims 1 to 6 by running the program stored on the memory.

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