Intelligent document high-speed positioning self-service printer system

Abstract

The application belongs to the technical field of printing, and specifically relates to an intelligent document high-speed positioning self-service printer system, which realizes high-precision document analysis by integrating advanced image processing technology and multi-module collaborative work, can efficiently and accurately identify various document contents from simple pure text to complex graphic-text mixed arrangement; based on deep understanding of the document content, the system constructs an accurate page logic framework to ensure that the position and format of each element in the printing output meet the requirements of the original document; in addition, the close cooperation between the positioning instruction processor and the dynamic calibration component enables the system to adjust the printing parameters in real time during the printing process, maintain high positioning accuracy, and ensure high-quality printing output even in the face of paper offset or other mechanical errors; in summary, the system significantly improves the accuracy of document recognition and positioning and the efficiency and quality of the overall printing process.

Description

Technical Field

[0001] This invention belongs to the field of printing technology, specifically relating to a high-speed intelligent document positioning self-service printer system. Background Technology

[0002] Existing document printing systems typically include basic document input, image capture, content recognition, and print output functions. These systems can handle various document types, from simple text files to complex graphic documents, but often have limitations in the following aspects: Insufficient document recognition and location accuracy: Existing systems may rely on relatively basic optical character recognition (OCR) technology to parse document content. However, for documents with complex layouts or containing a large number of non-text elements (such as charts and images), the recognition rate and location accuracy of existing systems are often unsatisfactory.

[0003] Multi-step processing is inefficient: In traditional printing systems, the process of receiving documents, capturing images, analyzing physical features, and finally printing is usually carried out in stages. There is a lack of effective coordination mechanisms between each stage, resulting in slow overall processing speed. This is especially true when processing large batches of documents, where the efficiency problem becomes more prominent.

[0004] Regarding the problems of the existing technologies mentioned above, a clear technical issue is the accuracy of document recognition and positioning. Specifically, when a document contains a complex layout structure or mixes multiple types of elements (text, charts, images, etc.), existing systems struggle to accurately parse the document content and correctly locate each element. This can lead to inaccurate printing output, affecting document quality and usability. Summary of the Invention

[0005] The purpose of this invention is to provide an intelligent document high-speed positioning self-service printer system, which not only solves the problem of insufficient document recognition and positioning accuracy in the existing technology, but also significantly improves the efficiency and quality of the entire printing process.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: an intelligent document high-speed positioning self-service printer system, comprising: a document entry device for receiving documents to be printed; an image capture unit connected to the document entry device for acquiring document image information; a physical feature analyzer connected to the image capture unit for analyzing the physical attributes of the document, including but not limited to boundaries and layout; a content parsing interface connected to the physical feature analyzer for interpreting document content and distinguishing between text and non-text elements; a page structure generator connected to the content parsing interface for constructing a page logic framework based on the parsing results; a positioning instruction processor connected to the page structure generator for developing a printing position guidance scheme; a dynamic calibration component coupled to the positioning instruction processor for adjusting printing parameters in real time to ensure positioning accuracy; an output control center connected to the dynamic calibration component for directing printing operations and ensuring that documents are output in sequence; and a user interaction panel connected to the output control center for providing a user interface for operation selection and status monitoring.

[0007] Preferably, the document entry device includes: The receiving unit captures the document to be processed and starts an initialization sequence, which includes detecting the width W and length L of the document; The dimension measuring tool calculates the document diagonal D_doc based on the formula D_doc=sqrt(W^2+L^2); The orientation corrector compares the values ​​of W and L. When W is greater than L, it performs a 90-degree clockwise rotation; otherwise, it maintains the original orientation. The transmission verifier checks whether the document is within the preset track by using the boundary detection function B_bound=|x|+|y|-(W+L) / 2, where x and y represent the offset of the document center relative to the ideal position. If B_bound is less than zero, the document is confirmed to be in the correct position.

[0008] Preferably, the image capturing unit includes: The photosensitive array receives the orientation-corrected document and generates a preliminary grayscale image G_gray(x,y) by scanning; The brightness normalization processor processes the initial grayscale image G_gray(x,y) and applies the formula G_norm(x,y)=(G_gray(x,y)-Min(G_gray)) / (Max(G_gray)-Min(G_gray))*255; The edge enhancer uses the Laplacian operator ΔG_norm(x,y)=G_norm(x+1,y)+G_norm(x-1,y)+G_norm(x,y+1)+G_norm(x,y-1)-4*G_norm(x,y) to enhance the boundary features of the document content. The image optimizer uses interpolation to calculate new pixel values: P_new(x',y')=(P_old(floor(x'),floor(y'))+P_old(ceil(x'),ceil(y'))) / 2, ensuring image clarity while maintaining the original document aspect ratio; In the formula, G_norm is the standardized gray value, ΔG_norm is the value after Laplacian processing, P_old is the original pixel value, P_new is the new pixel value, x,y are the original coordinates, and x',y' are the high-resolution coordinates.

[0009] Preferably, the physical feature analyzer includes: The boundary detection module receives a high-resolution image P_new(x',y') from the image capture unit and calculates the gradient intensity I_grad(x',y')=sqrt(Δx^2+Δy^2) for each pixel using the edge detection operator; The boundary tracker identifies and connects adjacent strong edge points based on the gradient intensity I_grad(x',y') to form a closed boundary path B_path; The layout parser uses the resulting boundary path B_path to divide the document into regions and calculates the area of ​​each region: A_area=∑_(i=1)^n(x'i*y'(i+1)-x'_(i+1)*y'_i) / 2; The structural description generator constructs a geometric descriptor D_geom=(L_block,W_block,Cx_block,Cy_block) for each identified content block; In the formula, Δx and Δy are the grayscale change rates, x'_i and y'_i are the boundary point coordinates, L_block is the block length, W_block is the block width, and Cx_block and Cy_block are the block center coordinates.

[0010] Preferably, the content parsing interface includes: The character detection module receives the geometric descriptor D_geom and boundary path B_path provided by the physical feature analyzer. Through local contrast enhancement, it calculates the enhancement value E_enhance(x',y')=P_new(x',y')*(1+α*|I_grad(x',y')|). The text region recognition unit uses connected component analysis to find possible text blocks T_text based on the enhanced image E_enhance(x',y'); for each candidate text block, the area threshold method is used for screening, with the formula Area(T_text)>A_min; The symbol splitter finely splits the text block T_text that meets the conditions to separate independent characters or symbols S_symbol; the projection histogram H_proj(x)=∑_(y'=min_y)^max_yE_enhance(x',y') is used to determine the cutting position between characters; The non-text element classifier evaluates the remaining parts that have not been recognized as text by calculating the texture complexity index: C_complexity=Var(E_enhance(x',y')) / Mean(E_enhance(x',y')) distinguishes image and chart non-text elements and marks their positions; In the formula: P_new is the pixel value of the high-resolution image, I_grad is the gradient intensity, α is the enhancement coefficient, Area is the area, A_min is the minimum text block area threshold, and C_complexity is the texture complexity.

[0011] Preferably, the page structure generator includes: The text block association module receives the text block T_text and its position information provided by the content parsing interface; the text block association module determines the relative position relationship between text blocks by calculating the distance D_dist=sqrt((Cx_i-Cx_j)^2+(Cy_i-Cy_j)^2) between adjacent text blocks; The logical hierarchy construction unit establishes the hierarchical relationship of text blocks according to the distance D_dist between text blocks; for each text block, the formula Level_i=sum(D_dist<Dist_thresh) is used to determine its hierarchical level; The paragraph recognizer uses the hierarchical relationship to recognize and combine text blocks belonging to the same paragraph; it judges whether text blocks should be merged into one paragraph by calculating the overlap degree O_overlap=max(0,min_yi-max_yj) in the vertical direction of the text blocks; The frame builder integrates the position information of all text and non-text elements to generate a complete page logical framework F_layout; using the formula: F_layout={S_symbol,T_text,NonTextElements}∪SegmentRelations to ensure that the page structure is clear and orderly; In the formula: Cx_i, Cy_i are the center coordinates of the text block, Dist_thresh is the distance threshold, Level_i is the text block hierarchy level, O_overlap is the degree of overlap in the vertical direction, min_yi, max_yj are the upper and lower boundary coordinates of the text block, S_symbol is the symbol, NonTextElements are non-text elements, and SegmentRelations is the set of relationships between paragraphs.

[0012] Preferably, the positioning instruction processor includes: The position initialization module receives the page logic framework F_layout provided by the page structure generator; the position initialization module calculates the initial printing coordinates (P_start_x, P_start_y) of each text block T_text and non-text element NonTextElements based on the element position information in the framework, using the formulas P_start_x=Cx-Offset_x and P_start_y=Cy-Offset_y; The boundary adjustment unit checks whether the initial print coordinates (P_start_x, P_start_y) exceed the print area boundary; if they do, it adjusts them using the formula P_adjusted=(P_start_x+Δx_adj, P_start_y+Δy_adj) to ensure that all elements are within the valid print area, thus ensuring that the final print coordinates (P_final_x, P_final_y) satisfy the condition MinPrint≤P_adjusted≤MaxPrint. The relative position optimizer uses the adjusted print coordinates (P_final_x, P_final_y) to optimize the relative position between adjacent elements; it ensures that elements maintain an appropriate interval by calculating the ideal spacing between adjacent elements D_ideal=(P_final_xi-P_final_xj) / Scale_factor. The instruction generator generates a precise print instruction I_print for each element based on the optimized print coordinates and spacing information; using the formula: I_print={P_final_x,P_final_y,D_ideal} defines the set of print parameters for each element, ensuring accurate execution during the printing process; In the formula: Cx, Cy are the center coordinates of the element, Offset_x, Offset_y are the offsets, P_adjusted are the adjusted coordinates, Δx_adj, Δy_adj are the offset increments, MinPrint, MaxPrint are the boundaries of the print area, D_ideal is the ideal spacing, Scale_factor is the scaling factor, and I_print is the print command.

[0013] Preferably, the dynamic calibration component includes: The error detection module receives the print command I_print from the positioning command processor; the error detection module monitors the print head position in real time and calculates the deviation ΔP_err=(P_actual_x-P_final_x,P_actual_y) between the actual printed coordinates (P_actual_x,P_actual_y) and the expected coordinates (P_final_x,P_final_y); The compensation calculation unit calculates the compensation values ​​in the X-axis and Y-axis directions based on the positioning error ΔP_err using the formulas Comp_x=ΔP_err_x*K_comp and Comp_y=ΔP_err_y*K_comp. The parameter adjuster uses the calculated compensation value (Comp_x, Comp_y) to correct the original print instruction I_print and generate a new print parameter I_new; the print position of each element is updated by the formula I_new={P_final_x+Comp_x,P_final_y+Comp_y,D_ideal}. The feedback verification unit monitors the adjusted printing effect; by comparing the difference between the old and new printing coordinates ΔP_new=(P_new_x-P_final_x,P_new_y-P_final_y), the formula ErrorRate=sqrt(ΔP_new_x^2+ΔP_new_y^2) / Distance is used to verify the adjustment effect; if ErrorRate is lower than the preset threshold Err_thresh, the adjustment is confirmed to be successful. In the formula: Comp_x, Comp_y are compensation values, K_comp is the compensation coefficient, I_new is the new printing parameter, ErrorRate is the error rate, Distance is the ideal spacing, and Err_thresh is the preset error threshold.

[0014] Preferably, the output control center includes: The task scheduling module receives the final printing parameters I_new from the dynamic calibration component; the task scheduling module arranges the printing task order according to the document priority and page logical framework F_layout, and assigns a unique task identifier TaskID to each task; The instruction execution unit retrieves the corresponding I_new from the print parameter library based on the task identifier TaskID and starts the print head to perform the actual printing operation; the execution status of each task is tracked by the formula PrintStat=Execute(I_new); During the printing process of the sequence verifier, the page output order is monitored in real time; the formula SeqCheck=(TaskID_i-TaskID_(i-1))==1 is used to check the continuity between two adjacent task identifiers; The completion confirmation module records completed tasks and their output status; updates the task completion log using the formula CompletionLog={TaskID,PrintStat,OutputTime}, and checks whether all expected tasks have been successfully completed. It also verifies whether the entire document has been output in order using the formula TaskComplete=sum(PrintStat=='Completed')==TotalTasks. In the formula: PrintStat is the printing status, SeqCheck is the sequence check result, OutputTime is the output time, CompletionLog is the task completion log, and TotalTasks is the total number of tasks.

[0015] Preferably, the user interaction panel includes: The operation selection interface receives print requests from users; the operation selection interface provides a series of preset options for users to choose from, including document type DocType, number of copies (Copies), and duplex printing setting (Duplex); the user's selection is encoded as configuration parameter ConfigParam, and the user settings are recorded using the formula ConfigParam={DocType,Copies,Duplex}. The status monitoring module connects to the output control center to obtain the execution status of the current print job in real time (PrintStat); via the formula: TaskProgress = (PagesCompleted / PagesTotal) * 100 calculates the printing progress percentage; The error reporting unit monitors the information fed back by the status monitoring module; if an abnormal situation is detected, it will generate an error code ErrCode and display the specific error information to the user through the formula ErrMsg="Error:"+ErrCode; The operation confirmation module integrates all user interaction data, including configuration parameters ConfigParam, print progress TaskProgress, and error messages ErrMsg, to form a complete operation log OpLog; using the formula: OpLog={ConfigParam,TaskProgress,ErrMsg,TimeStamp} updates the log to ensure that every user interaction is recorded in detail for review. In the formula: PrintStat is the printing status, PagesCompleted is the number of pages completed, PagesTotal is the total number of pages, and TimeStamp is the timestamp.

[0016] Technical effects and advantages of the present invention: The intelligent document high-speed positioning self-service printer system proposed in this invention has the following advantages compared with the prior art: This invention achieves high-precision document parsing by integrating advanced image processing technology and multi-module collaborative operation. It can efficiently and accurately identify various document contents, ranging from simple plain text to complex mixed text and graphics. Based on a deep understanding of the document content, the system constructs a precise page logic framework, ensuring that the position and format of each element in the printed output conforms to the original requirements. Furthermore, the close collaboration between the positioning instruction processor and the dynamic calibration component allows the system to adjust printing parameters in real time during the printing process, maintaining extremely high positioning accuracy and ensuring high-quality print output even in the face of paper misalignment or other mechanical errors. In summary, this system significantly improves the accuracy of document recognition and positioning, as well as the efficiency and quality of the overall printing process. Attached Figure Description

[0017] Figure 1 This is a block diagram of the intelligent document high-speed positioning self-service printer system of the present invention. Detailed Implementation

[0018] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The specific embodiments described herein are merely used to explain the present invention and are not intended to limit the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] This invention provides, for example Figure 1 The intelligent document high-speed positioning self-service printer system shown includes: Document entry device for receiving documents to be printed; further comprising: The receiving unit captures the document to be processed and initiates an initialization sequence, which includes detecting the document's width W and length L. This step ensures that the system can accurately receive and initially measure the document's dimensions, providing the necessary physical parameters for subsequent processing. By accurately obtaining the document's width and length, processing errors caused by size differences can be effectively avoided, improving the system's adaptability and accuracy.

[0020] The size measuring tool calculates the document diagonal D_doc using the formula D_doc=sqrt(W^2+L^2); this formula is based on the Pythagorean theorem to calculate the length of the document diagonal. D_doc represents the actual length of the document diagonal, while W and L are the width and length of the document, respectively. By calculating the diagonal length, the system can obtain a uniform scale to assess the consistency of documents of different sizes, which is crucial for subsequent page layout analysis.

[0021] Assuming the document's width W = 210mm (A4 paper width) and length L = 297mm (A4 paper length); according to the formula: D_doc=sqrt(210^2+297^2)=sqrt(44100+88209)=sqrt(132309)≈363.74mm; Therefore, the document's diagonal length is approximately 363.74 mm.

[0022] The orientation corrector compares the values ​​W and L. When W is greater than L, it performs a 90-degree clockwise rotation; otherwise, it maintains the original orientation. This step ensures that all documents have a uniform orientation upon entering the system, facilitating consistent processing by subsequent modules. For documents placed horizontally or vertically, the system can automatically adjust their orientation, thereby simplifying the complexity of subsequent content parsing and improving processing efficiency.

[0023] If the document width W=297mm and the length L=210mm (i.e., an A4 paper placed horizontally), the system will automatically rotate it 90 degrees clockwise so that the document enters the subsequent processing flow in portrait mode.

[0024] The transmission verifier checks whether the document is within the preset track using the boundary detection function B_bound = |x| + |y| - (W + L) / 2, where x and y represent the offset of the document center relative to the ideal position. If B_bound is less than zero, the document is confirmed to be in the correct position. This formula is used to determine whether the document has deviated from the preset transmission path. B_bound is an indicator of document position deviation, calculated by combining the document center coordinates (x, y) and document dimensions (W, L). Ideally, the document should be located in the center of the track, at which point the value of B_bound is close to zero. If B_bound is less than zero, it means the document is within the preset track and in the correct position; otherwise, adjustments are needed.

[0025] Example: Assume the document center offset is x = -5mm and y = 3mm, the document width W = 210mm, and the length L = 297mm; according to the formula: B_bound=|x|+|y|-(W+L) / 2=|-5|+|3|-(210+297) / 2 =5 + 3 - 253.5 =8-253.5 =-245.5; Since B_bound < 0, this indicates that the document is indeed within the preset track and is in the correct position.

[0026] The steps described above work together to ensure that documents are received and initially processed accurately and efficiently, laying a solid foundation for subsequent, more complex processes such as image capture and content parsing. The technical effects of each step not only improve the overall performance of the system but also enhance user convenience and reliability.

[0027] An image capture unit, connected to the document entry device, is used to acquire document image information; further comprising: The photosensitive array receives the orientation-corrected document and generates a preliminary grayscale image G_gray(x,y) through scanning. This step ensures that the system can accurately acquire the document's image information and convert it into a preliminary grayscale image. The high-resolution scanning of the photosensitive array allows subsequent processing to be based on high-quality image data, improving the overall system's resolution accuracy.

[0028] A brightness normalization processor processes the initial grayscale image G_gray(x,y) using the formula G_norm(x,y)=(G_gray(x,y)-Min(G_gray)) / (Max(G_gray)-Min(G_gray))*255. This formula normalizes each pixel value in the initial grayscale image to the range [0,255], ensuring a uniform brightness range across all images. G_norm(x,y) represents the normalized grayscale value, while Min(G_gray) and Max(G_gray) are the minimum and maximum grayscale values ​​in the original grayscale image, respectively. This normalization process enhances image contrast, making subsequent analysis easier.

[0029] Suppose that the grayscale value ranges from 50 to 180 within a certain region, and for a specific pixel (x, y) its grayscale value is 120; according to the formula: G_norm(x,y)=(120-50) / (180-50)*255=70 / 130*255 ≈140.77; Therefore, the standardized grayscale value is approximately 140.77.

[0030] The edge enhancer utilizes the Laplacian operator ΔG_norm(x,y) = G_norm(x+1,y) + G_norm(x-1,y) + G_norm(x,y+1) + G_norm(x,y-1) - 4*G_norm(x,y) to strengthen the boundary features of the document content. The Laplacian operator is a commonly used edge detection method that highlights edges in an image by calculating the difference between adjacent pixels. ΔG_norm(x,y) represents the change in grayscale value after Laplacian processing. This step strengthens the boundary features of the document content, making text and other important elements more prominent in the image, facilitating subsequent recognition and parsing.

[0031] Example: Suppose the standardized gray values ​​of a pixel (x, y) and its surrounding neighboring pixels are as follows: G_norm(x+1,y)=160; G_norm(x-1,y)=140; G_norm(x,y+1)=150; G_norm(x,y-1)=130; G_norm(x,y)=145; According to the formula: ΔG_norm(x,y)=160+140+150+130-4*145 =580-580 =0; If the pixel is located in a flat region, ΔG_norm(x,y) is close to zero; if it is located at an edge, ΔG_norm(x,y) will deviate significantly from zero, thus effectively highlighting edge features.

[0032] The image optimizer uses interpolation to calculate new pixel values: P_new(x',y')=(P_old(floor(x'),floor(y'))+P_old(ceil(x'),ceil(y'))) / 2, ensuring image clarity while maintaining the original document aspect ratio; In the formula, G_norm is the standardized gray value, ΔG_norm is the value after Laplacian processing, P_old is the original pixel value, P_new is the new pixel value, x,y are the original coordinates, and x',y' are the high-resolution coordinates.

[0033] Interpolation methods are used to improve image resolution while maintaining the document's aspect ratio. P_old represents the original pixel value, P_new represents the newly calculated pixel value, and floor(x') and ceil(x') represent the floor and ceiling operations, respectively. This step smoothly increases image detail and improves image sharpness without changing the original aspect ratio using linear interpolation.

[0034] Suppose a pixel in the original image has coordinates (x', y') = (2.3, 4.7), and its two closest integer coordinates are (2, 4) and (3, 5), with pixel values ​​as follows: P_old(2,4)=150; P_old(3,5)=160; According to the formula: P_new(2.3,4.7)=(P_old(2,4)+P_old(3,5)) / 2=(150+160) / 2 =155; Therefore, the new pixel value is 155, which allows the image to maintain high clarity and original proportions even when enlarged.

[0035] The above steps work together to ensure that the image capture unit can efficiently and accurately acquire and process document image information. The technical effects of each step not only improve image quality but also provide a solid foundation for subsequent content parsing, enhancing the overall performance and reliability of the system.

[0036] A physical feature analyzer, following the image capture unit, parses the physical properties of the document, including but not limited to boundaries and layout; further including: The boundary detection module receives a high-resolution image P_new(x',y') from the image capture unit and calculates the gradient intensity I_grad(x',y')=sqrt(Δx^2+Δy^2) for each pixel using the edge detection operator. This step ensures that the system can accurately identify boundaries and contours in the document. By calculating the gradient intensity of each pixel, different regions of the document can be effectively distinguished, providing basic data for subsequent layout analysis.

[0037] Application principle and meaning: This formula is used to calculate the rate of grayscale change of each pixel in the horizontal direction (Δx) and the vertical direction (Δy), and the gradient strength I_grad(x',y') is obtained by using the Pythagorean theorem. The gradient strength reflects the degree of brightness change in the image; a larger gradient strength means more obvious edges.

[0038] Suppose that the grayscale change rate of a certain pixel (x', y') and its surrounding adjacent pixels is: Δx = 50; Δy=30; According to the formula: I_grad(x',y')=sqrt(50^2+30^2)=sqrt(2500+900)=sqrt(3400)≈58.31; Therefore, the gradient intensity of this pixel is approximately 58.31.

[0039] The boundary tracker identifies and connects adjacent strong edge points based on the gradient strength I_grad(x',y'), forming a closed boundary path B_path. This step connects the identified strong edge points to form a complete closed boundary path. This helps to accurately define different parts of the document, such as text boxes and charts, thus providing clear separation for subsequent content parsing.

[0040] Boundary trackers identify and connect pixels with high gradient intensities in an image to form continuous boundary paths. These paths define not only the outer contour of a document but may also include enclosed internal regions (such as tables and graphics).

[0041] Suppose a series of edge points with high gradient intensity are identified in the image. The boundary tracker will connect these points sequentially according to their spatial relationship, and finally form one or more closed boundary paths B_path.

[0042] The layout parser uses the resulting boundary path B_path to divide the document into regions and calculates the area of ​​each region: A_area = ∑_(i=1)^n(x'i*y'(i+1)-x'_(i+1)*y'_i) / 2; This formula, based on the polygon area calculation formula, is used to determine the area A_area of ​​the region enclosed by the boundary path B_path. x'_i and y'_i are the coordinates of the i-th point on the boundary path, respectively, and n is the total number of points on the path. By calculating the area, the document's layout can be further understood, such as text areas, chart areas, etc.

[0043] Suppose a closed boundary path contains the following coordinate points: (x'_1,y'_1)=(10,20); (x'_2,y'_2)=(30,40); (x'_3,y'_3)=(50,60); (x'_4,y'_4)=(70,80); According to the formula: A_area=(10*40+30*60+50*80+70*20-(20*30+40*50+60*70+80*10)) / 2=(400+1800+4000+1400-(600+2000+4200+800)) / 2 =(7600-7600) / 2 =0; This example demonstrates how to calculate the area of ​​a polygon using a formula. In practical applications, complex boundary paths will produce non-zero area values, helping to parse different regions of a document.

[0044] The structural description generator constructs a geometric descriptor D_geom=(L_block,W_block,Cx_block,Cy_block) for each identified content block; In the formula, Δx and Δy are the grayscale change rates, x'_i and y'_i are the boundary point coordinates, L_block is the block length, W_block is the block width, and Cx_block and Cy_block are the block center coordinates.

[0045] Detailed geometric descriptors are generated for each identified content block, including the block length L_block, width W_block, and center coordinates (Cx_block, Cy_block). These descriptors provide key information about the shape and location of the content block, facilitating subsequent processing and output control.

[0046] The geometric descriptor D_geom describes the main physical attributes of each content block. L_block and W_block represent the length and width of the block, respectively, and Cx_block and Cy_block represent the coordinates of the block's center. These parameters enable the system to accurately locate and manipulate individual elements within the document.

[0047] Suppose a rectangular content block is identified, with its top-left corner coordinates at (10, 20) and its bottom-right corner coordinates at (50, 60); according to the formula: L_block=50-10=40W_block=60-20=40; Cx_block=(10+50) / 2=30; Cy_block = (20 + 60) / 2 = 40; Therefore, the geometric descriptor of this block is D_geom=(40,40,30,40).

[0048] The above steps work together to ensure that the physical feature analyzer can efficiently and accurately parse the physical attributes of a document, including but not limited to boundaries and layout. The technical effects of each step not only improve the system's parsing accuracy but also provide a solid foundation for subsequent content parsing and page structure generation, enhancing the overall performance and reliability of the system.

[0049] The content parsing interface, following the physical feature analyzer, interprets document content and distinguishes between text and non-text elements; it further includes: The character detection module receives the geometric descriptor D_geom and boundary path B_path from the physical feature analyzer. Through local contrast enhancement, it calculates the enhancement value E_enhance(x',y')=P_new(x',y')*(1+α*|I_grad(x',y')|) for each pixel. This step enhances the contrast of characters and symbols in the image, making text regions more prominent and facilitating subsequent recognition and segmentation. By enhancing contrast, the system can more accurately distinguish text from the background, improving recognition accuracy.

[0050] This formula is used to enhance the brightness of each pixel in an image. E_enhance(x',y') represents the enhanced grayscale value, P_new(x',y') is the pixel value of the original high-resolution image, I_grad(x',y') is the gradient strength, and α is a preset enhancement coefficient. The enhancement value is based on the product of the original pixel value and the gradient strength to highlight edges and details.

[0051] Suppose a pixel (x', y') has an original pixel value of 150, a gradient strength of 58.31 (from the previous example), and an enhancement factor α = 0.2: E_enhance(x',y')=150*(1+0.2*|58.31|)=150*(1+11.662)=150*12.662≈1899.3.

[0052] Therefore, the enhanced grayscale value is approximately 1899.3, which will significantly improve the contrast of the character area.

[0053] The text region recognition unit uses connected component analysis to find possible text blocks T_text based on the enhanced image E_enhance(x',y'). For each candidate text block, an area thresholding method is used for filtering, with the formula Area(T_text)>A_min. This step identifies possible text regions through connected component analysis and filters out text blocks that meet the criteria using the area thresholding method. This method can effectively exclude non-text regions, ensuring that subsequent processing only targets the actual text content.

[0054] Connected component analysis is a commonly used image segmentation method that groups adjacent pixels with similar attributes into the same region. Area(T_text) represents the area of ​​the text block, and A_min is a preset minimum text block area threshold. Only text blocks with an area greater than A_min are considered valid text regions.

[0055] Suppose a candidate text block has an area of ​​500 square pixels, and the minimum text block area threshold A_min is set to 400 square pixels: Area(T_text) = 500; A_min = 400; Since Area(T_text) > A_min, the text block is recognized as a valid text region.

[0056] The symbol segmenter performs fine segmentation on the text block T_text that meets the conditions, separating individual characters or symbols S_symbol. A projection histogram H_proj(x) = ∑_(y'=min_y)^max_yE_enhance(x',y') is used to determine the cutting positions between characters. C_complexity = Var(E_enhance(x',y')) / Mean(E_enhance(x',y')) distinguishes non-text elements such as images and charts and marks their positions. This step further segments the text block into individual characters or symbols, providing a precise foundation for subsequent content parsing. The projection histogram method determines the boundaries between characters by calculating the grayscale value distribution in the vertical direction, thus achieving accurate segmentation.

[0057] Projected histograms are a commonly used text segmentation method that generates a histogram by accumulating the grayscale values ​​of each column. H_proj(x) represents the projected histogram calculated in the x-direction, E_enhance(x',y') is the enhanced grayscale value, and min_y and max_y are the upper and lower boundary coordinates of the text block, respectively. By analyzing the peaks and valleys in the histogram, the cutting positions between characters can be determined.

[0058] Suppose a text block has a height range of min_y=10 to max_y=50, and the grayscale values ​​in a certain column x' are distributed as follows: E_enhance(x',10)=1899.3E_enhance(x',11)=1890.0...E_enhance(x',50)=1880.0; According to the formula: H_proj(x')=1899.3+1890.0+...+1880.0; By calculating the total grayscale value of each column, a histogram is formed, which in turn determines the cutting positions between characters.

[0059] The non-text element classifier evaluates the remaining portions not recognized as text by calculating a texture complexity metric: In the formula: P_new is the pixel value of the high-resolution image, I_grad is the gradient strength, α is the enhancement coefficient, Area is the area, A_min is the minimum text block area threshold, and C_complexity is the texture complexity.

[0060] By classifying non-text elements, the system distinguishes complex structures such as images and charts, avoiding the mistaken treatment of these elements as text. Through calculating texture complexity metrics, the system can effectively identify and label non-text elements, ensuring the accuracy of subsequent processing.

[0061] Application principle and meaning: The texture complexity metric C_complexity measures the complexity of a region by calculating the variance Var(E_enhance(x',y')) and the mean Mean(E_enhance(x',y')) of the grayscale values ​​within the region. Complex textures typically have a high variance and a low mean ratio, which helps distinguish non-text elements such as images and charts.

[0062] Suppose the enhanced grayscale value distribution within a region is as follows: E_enhance(x',y')=[1899.3,1890.0,...,1880.0]; According to the formula: Mean(E_enhance(x',y'))=(1899.3+1890.0+...+1880.0) / nVar(E_enhance(x',y'))=Σ((E_enhance(x', y')-Mean(E_enhance(x',y')))²) / nC_complexity=Var(E_enhance(x',y')) / Mean(E_enhance(x',y')); By calculating the C_complexity value, the system can determine whether the region is a non-text element and mark it accordingly.

[0063] The above steps work together to ensure that the content parsing interface can efficiently and accurately interpret document content and distinguish between text and non-text elements. The technical effects of each step not only improve the system's parsing accuracy but also provide a solid foundation for subsequent page structure generation and printing, enhancing the overall performance and reliability of the system.

[0064] The page structure generator, located after the content parsing interface, constructs the page logic framework based on the parsing results; it further includes: The text block association module receives the text block T_text and its position information from the content parsing interface. It then determines the relative positional relationship between text blocks by calculating the distance D_dist = sqrt((Cx_i - Cx_j)^2 + (Cy_i - Cy_j)^2). This step ensures the system can accurately identify and quantify the spatial relationships between text blocks, providing foundational data for subsequent construction of logical hierarchies and paragraph combinations. By calculating the distance between the center points of text blocks, it is possible to effectively determine which text blocks are closely related.

[0065] This formula, based on the Euclidean distance formula, is used to calculate the distance D_dist between the center coordinates (Cx_i, Cy_i) and (Cx_j, Cy_j) of two text blocks. This step helps to identify adjacent or close text blocks, thus inferring that they may belong to the same logical unit.

[0066] Assume the center coordinates of the two text blocks are as follows: (Cx_i,Cy_i)=(30,50); (Cx_j,Cy_j)=(60,80); According to the formula: D_dist=sqrt((30-60)^2+(50-80)^2)=sqrt((-30)^2+(-30)^2)=sqrt(900+900)=sqrt(1800)≈42.43; Therefore, the distance between these two text blocks is approximately 42.43.

[0067] The logical hierarchy construction unit establishes the hierarchical relationship of text blocks according to the distance D_dist between text blocks; for each text block, the formula Level_i = sum(D_dist < Dist_thresh) is used to determine its hierarchical level; this step analyzes the distance between text blocks to establish the hierarchical relationship of text blocks, making the document structure more organized. The construction of the hierarchical relationship helps to understand the logical organization of the document, such as headings, body texts, etc.

[0068] This formula is used to calculate whether the distance between each text block and other text blocks is less than the preset distance threshold Dist_thresh. Level_i represents the hierarchical level of text block i, and sum(D_dist < Dist_thresh) calculates the number of adjacent text blocks that meet the condition to determine the hierarchical depth of the text block.

[0069] Example: Assume that the distances between a certain text block i and three surrounding text blocks are respectively: D_dist_1 = 20; D_dist_2 = 30; D_dist_3 = 50; The set distance threshold Dist_thresh = 40; According to the formula: Level_i = sum(D_dist < Dist_thresh) = sum([20, 30, 50] < 40) = sum([True, True, False]) = 2; Therefore, the hierarchical level of this text block is 2.

[0070] The paragraph recognizer uses the hierarchical relationship to identify and combine text blocks belonging to the same paragraph; by calculating the vertical overlap degree O_overlap = max(0, min_yi - max_yj) of text blocks to determine whether the text blocks should be merged into one paragraph; this step analyzes the vertical overlap degree of text blocks to identify and combine text blocks belonging to the same paragraph. This helps to maintain the logical coherence of the document content and simplifies subsequent processing.

[0071] This formula is used to calculate the vertical overlap degree O_overlap of text blocks. min_yi and max_yj respectively represent the y coordinates of the upper and lower boundaries of two text blocks. If min_yi - max_yj is positive, it means that the two text blocks overlap vertically, otherwise there is no overlap.

[0072] Assume the upper and lower boundary coordinates of the two text blocks are as follows: Text block i: (min_yi=10,max_yi=30); Text block j:(min_yj=20,max_yj=40); According to the formula: O_overlap=max(0,min_yi-max_yj)=max(0,10-40)=max(0,-30)=0; Since O_overlap=0, the two text blocks do not overlap vertically and therefore should not be merged into one piece.

[0073] The framework builder integrates the positional information of all text and non-text elements to generate a complete page logic framework F_layout; using the formula: F_layout={S_symbol,T_text,NonTextElements}∪SegmentRelations ensures a clear and orderly page structure; In the formula: Cx_i, Cy_i are the center coordinates of the text block, Dist_thresh is the distance threshold, Level_i is the text block hierarchy level, O_overlap is the degree of overlap in the vertical direction, min_yi, max_yj are the upper and lower boundary coordinates of the text block, S_symbol is the symbol, NonTextElements are non-text elements, and SegmentRelations is the set of relationships between paragraphs.

[0074] This step integrates the positional information of all text and non-text elements to build a complete page logical framework, ensuring a clear and orderly document structure. This framework not only includes the specific location of each element but also the logical relationships between them, facilitating subsequent printing.

[0075] This formula is used to generate the page's logical framework F_layout, where S_symbol is a symbol, T_text is a text block, NonTextElements are non-text elements (such as images and charts), and SegmentRelations is a set of relationships between paragraphs. By integrating this information, the system can comprehensively describe the page's content layout and logical structure.

[0076] Example: Suppose a page contains the following elements: Symbol S_symbol=[symbol1,symbol2]; Text block T_text = [text_block1, text_block2]; NonTextElements = [image1, chart1]; The set of relationships between paragraphs is SegmentRelations = [(text_block1, text_block2)]. According to the formula: F_layout={symbol1,symbol2,text_block1,text_block2,image1,chart1}∪[(text_block1,text_block2)]; The final generated page logic framework covers all elements and their logical relationships, ensuring a clear and orderly document structure.

[0077] The above steps work together to ensure that the page structure generator can efficiently and accurately construct the page logic framework based on the parsing results. The technical effects of each step not only improve the system's parsing accuracy but also provide a solid foundation for subsequent printing output, enhancing the overall performance and reliability of the system.

[0078] The positioning instruction processor, connected to the page structure generator, formulates a print position guidance scheme; further including: The position initialization module receives the page logical framework F_layout provided by the page structure generator. Based on the element position information within the framework, the position initialization module calculates the initial print coordinates (P_start_x, P_start_y) for each text block T_text and non-text elements NonTextElements using the formulas P_start_x = Cx - Offset_x and P_start_y = Cy - Offset_y. This step ensures that the system can determine the initial print coordinates for each element based on its position information within the page logical framework. By applying offsets, the starting position of elements on the page can be adjusted to meet specific layout requirements.

[0079] This formula is used to calculate the initial print coordinates (P_start_x, P_start_y) for each element. Cx and Cy are the center coordinates of the element, respectively, and Offset_x and Offset_y are preset offsets. This step ensures that elements are printed from the correct starting position.

[0080] Suppose the center coordinates of a certain text block are: (Cx,Cy)=(150,200); The offset is: (Offset_x,Offset_y)=(10,20); According to the formula: P_start_x=150-10=140P_start_y=200-20=180; Therefore, the initial print coordinates of this text block are (140, 180).

[0081] The boundary adjustment unit checks whether the initial print coordinates (P_start_x, P_start_y) exceed the print area boundary. If they do, it adjusts them using the formula P_adjusted = (P_start_x + Δx_adj, P_start_y + Δy_adj) to ensure all elements are within the valid print area. This guarantees that the final print coordinates (P_final_x, P_final_y) satisfy the condition MinPrint ≤ P_adjusted ≤ MaxPrint. This step ensures that the print coordinates of all elements are within the valid print area, preventing printing errors or material waste due to exceeding the boundary. Through appropriate adjustments, the system can guarantee that all elements are printed correctly.

[0082] This formula is used to adjust print coordinates that exceed the boundaries. Δx_adj and Δy_adj are the adjustment increments, and MinPrint and MaxPrint are the minimum and maximum boundaries of the print area, respectively. By adjusting the increments, it ensures that the adjusted coordinates P_adjusted are within the valid print area.

[0083] Suppose the initial print coordinates of a text block are: (P_start_x,P_start_y)=(30,280); The print area boundaries are: MinPrint=(50,50), MaxPrint=(250,250); The adjustment increment is: (Δx_adj,Δy_adj)=(20,-30); According to the formula: P_adjusted=(30+20,280-30)=(50,250); Therefore, the adjusted print coordinates are (50, 250), which are exactly within the print area.

[0084] The relative position optimizer uses the adjusted print coordinates (P_final_x, P_final_y) to optimize the relative position between adjacent elements; it ensures that elements maintain an appropriate spacing by calculating the ideal spacing between adjacent elements D_ideal=(P_final_xi-P_final_xj) / Scale_factor. This step optimizes the relative position between adjacent elements, ensuring that they have an appropriate spacing and avoiding overlap or overly close arrangement, thereby improving the readability and aesthetics of the document.

[0085] This formula is used to calculate the ideal spacing D_ideal between adjacent elements. P_final_xi and P_final_xj are the final printed coordinates of two adjacent elements in the x-direction, respectively, and Scale_factor is a preset scaling factor. By adjusting the scaling factor, the spacing between elements can be controlled.

[0086] Assume the final printed coordinates of two adjacent text blocks are as follows: (P_final_xi,P_final_yi)=(100,200); (P_final_xj,P_final_yj)=(150,200); The scaling factor is: Scale_factor=2; According to the formula: D_ideal=(150-100) / 2=50 / 2=25; Therefore, the ideal spacing between these two text blocks is 25.

[0087] The instruction generator generates a precise print instruction I_print for each element based on the optimized print coordinates and spacing information; using the formula: `I_print={P_final_x,P_final_y,D_ideal}` defines the set of print parameters for each element, ensuring accurate execution during printing. This step generates detailed print instructions, ensuring each element is printed accurately at the specified position and spacing. These instructions provide clear operating guidelines for the printer, guaranteeing high-quality print output.

[0088] This formula is used to construct the print parameter set I_print for each element. P_final_x and P_final_y are the final print coordinates, and D_ideal is the ideal spacing. By integrating this information, the system can generate precise print instructions for each element.

[0089] Suppose the final print coordinates of a text block are: (P_final_x,P_final_y)=(140,180); The ideal spacing is: D_ideal=25; According to the formula: I_print={140,180,25}; Therefore, the printing instruction for this text block is {140,180,25}, ensuring that it is printed accurately at the specified position and spacing.

[0090] The above steps work together to ensure that the positioning instruction processor can efficiently and accurately formulate print position guidance schemes. The technical effect of each step not only improves the system's resolution accuracy but also provides a solid foundation for subsequent printing operations, enhancing the overall performance and reliability of the system.

[0091] In the formula: Cx, Cy are the center coordinates of the element, Offset_x, Offset_y are the offsets, P_adjusted are the adjusted coordinates, Δx_adj, Δy_adj are the offset increments, MinPrint, MaxPrint are the boundaries of the print area, D_ideal is the ideal spacing, Scale_factor is the scaling factor, and I_print is the print command.

[0092] A dynamic calibration component, coupled with a positioning instruction processor, adjusts printing parameters in real time to ensure positioning accuracy; further including: The error detection module receives the print command I_print from the positioning command processor. By monitoring the print head position in real time, the error detection module calculates the deviation ΔP_err = (P_actual_x - P_final_x, P_actual_y - P_final_y) between the actual printed coordinates (P_actual_x, P_actual_y) and the expected coordinates (P_final_x, P_final_y). This step ensures that the system can monitor positional deviations during the printing process in real time, promptly detecting and recording any deviations from expectations. This provides an accurate data basis for subsequent compensation adjustments.

[0093] This formula is used to calculate the deviation ΔP_err between the actual position (P_actual_x, P_actual_y) and the expected position (P_final_x, P_final_y) of the print head. The deviation value reflects the positional error that may occur during the printing process and is the basic data for compensation and adjustment.

[0094] Suppose the expected print coordinates of a certain element are: (P_final_x,P_final_y)=(140,180); The actual printed coordinates are: (P_actual_x, P_actual_y) = (138, 179); According to the formula: ΔP_err=(138-140,179-180)=(-2,-1); Therefore, the positional deviation of the printhead is (-2, -1).

[0095] The compensation calculation unit calculates compensation values ​​in the X and Y axes based on the positioning error ΔP_err using the formulas Comp_x = ΔP_err_x * K_comp and Comp_y = ΔP_err_y * K_comp. This step corrects the printhead's positional deviation by calculating appropriate compensation values, ensuring the accuracy of the final printing position. The compensation value calculation is based on the deviation value and a preset compensation coefficient to achieve precise adjustment.

[0096] This formula is used to calculate the compensation values ​​Comp_x and Comp_y in the X and Y axes. ΔP_err_x and ΔP_err_y are the components of the deviation value in the x and y directions, respectively, and K_comp is a preset compensation coefficient. The compensation values ​​are used to adjust the printhead position to reduce deviation.

[0097] Assume the deviation value is: ΔP_err=(-2,-1); The compensation coefficient is: K_comp = 0.8; According to the formula: Comp_x=-2*0.8=-1.6Comp_y=-1*0.8=-0.8; Therefore, the compensation values ​​in the X-axis and Y-axis directions are -1.6 and -0.8, respectively.

[0098] The parameter adjuster uses the calculated compensation values ​​(Comp_x, Comp_y) to correct the original print command I_print, generating new print parameters I_new. The print position of each element is updated using the formula I_new = {P_final_x + Comp_x, P_final_y + Comp_y, D_ideal}. This step, by correcting the original print command and generating new print parameters, ensures that each element is accurately printed in its adjusted position. This dynamic adjustment guarantees high precision in the printing process.

[0099] This formula is used to generate the new print parameters I_new. P_final_x and P_final_y are the original expected print coordinates, Comp_x and Comp_y are the calculated compensation values, and D_ideal is the ideal spacing. By updating the print coordinates, the system can correct positional deviations and ensure print accuracy.

[0100] Assume the original print command is: I_print={140,180,25}; The compensation value is: (Comp_x,Comp_y)=(-1.6,-0.8); According to the formula: I_new = {140 + (-1.6), 180 + (-0.8), 25} = {138.4, 179.2, 25}; Therefore, the new printing parameters are {138.4, 179.2, 25}.

[0101] The feedback verification unit monitors the printing effect after adjustment; by comparing the difference ΔP_new = (P_new_x - P_final_x, P_new_y - P_final_y) between the new and old printing coordinates, the adjustment effect is verified using the formula ErrorRate = sqrt(ΔP_new_x^2 + ΔP_new_y^2) / Distance; if ErrorRate is lower than the preset threshold Err_thresh, the adjustment is confirmed to be successful; this step evaluates the effectiveness of the compensation adjustment by monitoring the printing effect after adjustment. By calculating the error rate, the system can determine whether the expected printing accuracy has been achieved and further adjust if necessary.

[0102] This formula is used to calculate the difference ΔP_new between the adjusted printing coordinates (P_new_x, P_new_y) and the expected coordinates (P_final_x, P_final_y), and to calculate the error rate ErrorRate. Distance is the ideal spacing, and Err_thresh is the preset error threshold. The lower the error rate, the better the adjustment effect.

[0103] Assume the adjusted printing coordinates are: (P_new_x, P_new_y) = (138.4, 179.2); The expected coordinates are: (P_final_x, P_final_y) = (140, 180); The ideal spacing is: Distance = 25; The preset error threshold is: Err_thresh = 0.05; According to the formula: ΔP_new = (138.4 - 140, 179.2 - 180) = (-1.6, -0.8) ErrorRate = sqrt((-1.6)^2 + (-0.8)^2) / 25 = sqrt(2.56 + 0.64) / 25 = sqrt(3.2) / 25 ≈ 0.357 / 25 ≈ 0.0143; Since ErrorRate = 0.0143 < Err_thresh = 0.05, the adjustment is confirmed to be successful.

[0104] The above steps work together to ensure that the dynamic calibration component can adjust printing parameters in real time to guarantee positioning accuracy. The technical effects of each step not only improve the system's printing accuracy but also provide a solid foundation for high-quality print output, enhancing the overall performance and reliability of the system.

[0105] In the formula: Comp_x, Comp_y are compensation values, K_comp is the compensation coefficient, I_new is the new printing parameter, ErrorRate is the error rate, Distance is the ideal spacing, and Err_thresh is the preset error threshold.

[0106] The output control center, connected to the dynamic calibration component, directs printing operations and ensures documents are output in sequence; it further includes: The task scheduling module receives the final printing parameters I_new from the dynamic calibration component; the task scheduling module arranges the printing task order according to the document priority and page logical framework F_layout, and assigns a unique task identifier TaskID to each task; This step ensures that the system can rationally arrange print jobs according to document priority and logical structure, improving printing efficiency and sequential accuracy. Assigning a unique identifier to each job facilitates subsequent tracking and management.

[0107] The task scheduling module determines the order of printing tasks based on document priority and the page layout F_layout. Each task is assigned a unique TaskID for identification and tracking during execution.

[0108] Suppose we have a document with three pages, and the page logic framework is as follows: Page 1: High priority, contains title and important information. Page 2: Medium priority, contains main text content. Page 3: Low priority, includes appendix Based on document priority, the print task scheduling module arranges the print tasks in the following order: TaskID_1 = Page 1; TaskID_2 = Page 2; TaskID_3 = Page 3.

[0109] The instruction execution unit retrieves the corresponding I_new from the print parameter library based on the task identifier TaskID and starts the print head to perform the actual printing operation. The execution status of each task is tracked using the formula PrintStat=Execute(I_new). This step ensures that each print task can be executed accurately according to the predetermined parameters and monitors the task status in real time. This helps to promptly identify and handle any potential problems, ensuring the smooth progress of the printing process.

[0110] This formula is used to initiate a printing operation and track its execution status. I_new is the final printing parameter, and the Execute(I_new) function is responsible for starting the print head and returning the current task's printing status, PrintStat, such as "Executing", "Completed", or "Failed".

[0111] Suppose the printing parameters for a certain task are: I_new={138.4,179.2,25}; The instruction execution unit starts the print head and returns the status: PrintStat=Execute({138.4,179.2,25})="Executing"; When printing is complete: PrintStat="Completed".

[0112] During the printing process, the sequence verifier monitors the page output order in real time. It uses the formula SeqCheck=(TaskID_i-TaskID_(i-1))==1 to check the continuity between two adjacent task identifiers. This step ensures that print tasks are output in the correct order, avoiding sequence confusion caused by task scheduling errors or anomalies. By monitoring the continuity of task identifiers in real time, problems can be detected and corrected promptly.

[0113] This formula checks whether the difference between two adjacent task IDs, TaskID_i and TaskID_(i-1), is 1. If the difference is 1, it indicates that the task order is correct; otherwise, there may be an order error.

[0114] Assume the current task identifier is: TaskID_i=2; The previous task identifier is: TaskID_(i-1)=1; According to the formula: SeqCheck = (2-1) == 1 = True; Therefore, the task order is correct.

[0115] The completion confirmation module records completed tasks and their output status; it updates the task completion log using the formula CompletionLog={TaskID,PrintStat,OutputTime}, and checks whether all expected tasks have been successfully completed. It then verifies whether the entire document has been output in sequence using the formula TaskComplete=sum(PrintStat=='Completed')==TotalTasks. This step ensures that the system accurately records the completion status of each task and verifies it after all tasks are completed to confirm that the entire document has been output in sequence. This helps ensure the integrity and accuracy of print jobs.

[0116] This formula is used to update the task completion log (CompletionLog), recording the TaskID, PrintStat, and OutputTime for each task. `sum(PrintStat=='Completed')` calculates the number of completed tasks, and `TotalTasks` is the total number of tasks. By comparing these two values, it can be verified whether all tasks have been successfully completed.

[0117] Assume the task completion log is as follows: TaskID_1 = Page 1, PrintStat="Completed",OutputTime="2024-12-30T16:00:00"; TaskID_2 = Page 2, PrintStat="Completed",OutputTime="2024-12-30T16:01:00"; TaskID_3 = Page 3, PrintStat="Completed",OutputTime="2024-12-30T16:02:00"; According to the formula: CompletionLog={{1,"Completed","2024-12-30T16:00:00"},{2,"Completed","2024-12-30T16:01:00"},{3,"Completed","2024-12-30T16:02:00"}}; TaskComplete=sum(PrintStat=='Completed')==3=3==3=True; Therefore, confirm that the entire document has been output in sequence.

[0118] The above steps work together to ensure that the output control center can efficiently and accurately direct the printing operation and ensure that documents are output in sequence.

[0119] In the formula: PrintStat is the printing status, SeqCheck is the sequence check result, OutputTime is the output time, CompletionLog is the task completion log, and TotalTasks is the total number of tasks.

[0120] The user interface panel, connected to the output control center, provides a user interface for operation selection and status monitoring; it further includes: The system receives print requests from users via an operation selection interface. This interface offers a range of preset options for users to choose from, including document type (DocType), number of copies (Copies), and duplex printing setting. User selections are encoded as configuration parameters (ConfigParam), recorded using the formula ConfigParam={DocType,Copies,Duplex}. This step ensures users can easily select the desired print settings through an intuitive interface and encodes these selections as system-recognizable configuration parameters. This improves user experience and system flexibility.

[0121] This formula is used to create a ConfigParam containing configuration parameters selected by the user. DocType indicates the document type (such as PDF, Word, etc.), Copies indicates the number of copies to print, and Duplex indicates whether duplex printing is enabled. These parameters provide necessary information for subsequent print jobs.

[0122] Suppose the user selected the following option: Document type DocType="PDF"; Number of copies to print: 2; Set Duplex="True" for double-sided printing; According to the formula: ConfigParam={"PDF",2,"True"}; Therefore, the configuration parameter is {"PDF",2,"True"}.

[0123] The status monitoring module connects to the output control center to obtain the execution status of the current print job in real time (PrintStat); via the formula: TaskProgress = (PagesCompleted / PagesTotal) * 100 calculates the printing progress percentage; this step ensures users can understand the progress of the print job in real time, improving transparency and user satisfaction. By calculating the printing progress percentage, users can clearly know the degree to which the task is completed.

[0124] This formula is used to calculate the percentage of progress for a print job (TaskProgress). PagesCompleted is the number of pages completed, and PagesTotal is the total number of pages. The percentage of print progress is obtained by dividing the number of completed pages by the total number of pages and then multiplying by 100.

[0125] Suppose the total number of pages in a certain print job is: PagesTotal=10; The number of completed pages is: PagesCompleted=7; According to the formula: TaskProgress = (7 / 10) * 100 = 70; Therefore, the printing progress is 70%.

[0126] The error reporting unit monitors the information fed back by the status monitoring module. If an anomaly is detected, it generates an error code ErrCode and displays the specific error information to the user using the formula ErrMsg="Error:"+ErrCode. This step ensures that users receive detailed error information immediately when an anomaly occurs, helping them to quickly diagnose and resolve the problem. This improves system reliability and user experience.

[0127] This formula is used to generate the error message ErrMsg. ErrCode is a system-generated error code, which is appended to the "Error:" string to form the complete error message.

[0128] Suppose the status monitoring module detects an error and generates the following error code: ErrCode="E001"; According to the formula: ErrMsg="Error:E001"; Therefore, the error message is "Error:E001".

[0129] The operation confirmation module integrates all user interaction data, including configuration parameters ConfigParam, print progress TaskProgress, and error messages ErrMsg, to form a complete operation log OpLog; using the formula: The OpLog={ConfigParam,TaskProgress,ErrMsg,TimeStamp} update log records ensure that every user interaction is recorded in detail for review. This step ensures that all user interaction data is completely recorded, facilitating subsequent review and analysis. This not only improves system transparency but also provides a basis for troubleshooting and performance optimization.

[0130] This formula is used to create the operation log OpLog. ConfigParam is the configuration parameter selected by the user, TaskProgress is the percentage of progress to be printed, ErrMsg is the error message, and TimeStamp is the timestamp. By combining this information, the system can generate detailed log records.

[0131] Suppose the data from a user interaction is as follows: Configure parameter ConfigParam={"PDF",2,"True"}; Print progress TaskProgress=70; Error message ErrMsg="Error:E001"; Timestamp TimeStamp="2024-12-30T16:45:00"; According to the formula: OpLog={{"PDF",2,"True"},70,"Error:E001","2024-12-30T16:45:00"}; Therefore, the operation log is as follows: {{"PDF",2,"True"},70,"Error:E001","2024-12-30T16:45:00"}; The four steps described above work together to ensure that the user interface panel can efficiently and accurately provide a user interface for operation selection and status monitoring. The technical effects of each step not only enhance the user experience and system flexibility but also provide a solid foundation for high-quality print output, thereby improving the overall performance and reliability of the system.

[0132] In the formula: PrintStat is the printing status, PagesCompleted is the number of pages completed, PagesTotal is the total number of pages, and TimeStamp is the timestamp.

[0133] In summary, by integrating advanced image processing technologies and multi-module collaborative operation, high-precision document parsing is achieved, enabling efficient and accurate identification of various document content, ranging from simple plain text to complex mixed text and graphics. Based on a deep understanding of the document content, the system constructs a precise page logic framework, ensuring that the position and format of each element in the printed output conform to the original requirements. Furthermore, the close collaboration between the positioning instruction processor and the dynamic calibration component allows the system to adjust printing parameters in real time during the printing process, maintaining extremely high positioning accuracy and ensuring high-quality print output even in the face of paper misalignment or other mechanical errors. In conclusion, this system significantly improves the accuracy of document recognition and positioning, as well as the efficiency and quality of the overall printing process.

[0134] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A high-speed intelligent document positioning self-service printer system, characterized in that: Include: A document entry device used to receive documents to be printed; An image capture unit, connected to the document entry device, is used to acquire document image information; The physical feature analyzer, following the image capture unit, parses the physical attributes of the document based on the document image information, including boundaries and layout. The content parsing interface, which follows the physical feature analyzer, parses the document content based on the physical attributes and distinguishes between text blocks and non-text elements. The page structure generator, located after the content parsing interface, constructs the page logic framework based on text blocks and non-text elements. The location instruction processor connects to the page structure generator and outputs print instructions based on the page logic framework. The dynamic calibration component, coupled with the positioning instruction processor, adjusts the printing parameters in real time according to the printing instructions, thereby generating new printing parameters to ensure positioning accuracy; The output control center connects to the dynamic calibration component, directs the printing operation based on the new printing parameters output by the dynamic calibration component, and ensures that documents are output in sequence; The user interaction panel is connected to the output control center and provides a user interface for operation selection and status monitoring. The content parsing interface is used to filter out text blocks in the document that are larger than the minimum text block area threshold using the area threshold method, and is used to evaluate the remaining parts of the document that are not identified as text blocks. It identifies non-text elements by calculating texture complexity and marks their positions. The non-text elements include images and charts. The page structure generator is used to identify and combine text blocks belonging to the same paragraph, generate paragraph relationships, and integrate paragraph relationships with the positions of non-text elements to generate a page logic framework. The positioning instruction processor is used to calculate the expected coordinates of the printed elements and the ideal spacing between adjacent printed elements according to the page logic framework, and then generate a printing instruction. The dynamic calibration component includes: The error checking module is used to receive printing instructions output from the positioning instruction processor, and calculate the positioning error between the actual printing coordinates and the expected coordinates by monitoring the print head position in real time. The compensation calculation unit is used to calculate the compensation values ​​in the X-axis and Y-axis directions respectively based on the positioning error; A parameter adjuster is used to adjust the expected coordinates according to the calculated compensation value to obtain the updated printing coordinates of the printing element, thereby generating new printing parameters. The feedback verification unit is used to obtain the difference value by subtracting the updated printing coordinates from the expected coordinates, and to calculate the error rate based on the difference value and the ideal distance. When the error rate is less than a preset threshold, the new printing parameters are adjusted and output to the output control center.

2. The intelligent document high-speed positioning self-service printer system according to claim 1, characterized in that: The user interaction panel includes: The user interface receives print requests from users; the user interface includes document type DocType, number of copies (Copies), and duplex setting; the user's print request is encoded as a configuration parameter ConfigParam, and the user settings are recorded using the formula ConfigParam={DocType,Copies,Duplex}. The status monitoring module connects to the output control center to obtain the execution status of the current print job in real time (PrintStat); via the formula: TaskProgress = (PagesCompleted / PagesTotal) * 100 calculates the printing progress percentage; The error reporting unit monitors the information fed back by the status monitoring module; if an abnormal situation is detected, it displays the specific error information ErrMsg to the user. The operation confirmation module integrates all user interaction data, including configuration parameters ConfigParam, print progress TaskProgress, and error messages ErrMsg, to form a complete operation log OpLog; using the formula: OpLog={ConfigParam,TaskProgress,ErrMsg,TimeStamp} updates the log record to ensure that every user interaction is recorded in detail for review. In the formula: PagesCompleted represents the number of completed pages, PagesTotal represents the total number of pages, and TimeStamp represents the timestamp.

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