A method, system and related device for processing rasterized primitive edge data

Abstract

This application provides a method, system, and related equipment for processing rasterized primitive edge data to improve laser imaging accuracy. The method includes: acquiring the coordinate position data of each primitive in an original image and identifying overlapping regions of positive and negative polarity primitives; the positive polarity primitives are regions composed of exposure points, the negative polarity primitives are regions composed of non-exposure points, and the overlapping region of positive and negative polarity primitives is a non-exposure point; expanding the edge coordinates of the negative polarity primitives in the overlapping region to non-integer edge regions, while simultaneously performing differential rounding processing on the edge regions of the positive polarity primitives in the original image to generate a dot matrix image composed of exposure points and non-exposure points.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, and in particular to a method, system and related equipment for processing edge data of rasterized primitives. Background Technology

[0002] Direct laser imaging refers to generating the desired image by scanning preset pixel exposure points on the surface of a photosensitive emulsion coating with a moving laser, after the emulsion coating has developed. In applications of direct laser imaging technology, before controlling the laser exposure of the photosensitive coating, the image file to be imaged needs to be converted from a vector image file to a raster image file.

[0003] The vector image file in the original image may be composed of positive and negative polarity primitives. In the existing rasterization algorithm, the edges of primitives with different attributes are rasterized in the same way according to the primitive size. Although this improves the rasterization speed, it cannot guarantee the consistency of the image after the positive and negative polarity primitives are overlapped and rasterized. This leads to gaps between adjacent primitives or the expansion of primitive edges. The image after exposure and development based on the rasterized image has a low restoration accuracy relative to the original image. Summary of the Invention

[0004] This application provides a method, system, and related equipment for processing rasterized primitive edge data to improve laser imaging accuracy.

[0005] The first aspect of this application provides a method for processing edge data of rasterized primitives, which may include:

[0006] The coordinate position data of each primitive in the original image are obtained, and the combined regions where positive and negative polarity primitives overlap are identified; the positive polarity primitives are regions composed of exposure points, the negative polarity primitives are regions composed of non-exposure points, and the overlapping regions of positive and negative polarity primitives after rasterization are non-exposure points.

[0007] The edge regions of negative polarity primitives in the combined region are expanded to have non-integer edge coordinates, while the edge regions of positive polarity primitives in the original image are distinguished and rounded to generate a dot matrix image composed of exposure points and non-exposure points.

[0008] Optionally, as a possible implementation, in this embodiment of the application, expanding the region where the edge coordinates of the negative polarity primitives in the combined region are non-integer may include:

[0009] The coordinates of the left edge region of the negative polarity primitive are rounded to the nearest integer to obtain the coordinates R(x1) of the left edge pixel. According to the formula... Calculate the coordinates of the right edge, where R is the rounding operator, and x1 and x2 are the coordinates of the left and right edge regions of the negative polarity primitive, respectively.

[0010] Optionally, as a possible implementation, in this embodiment of the application, expanding the region where the edge coordinates of the negative polarity primitives in the combined region are non-integer may include:

[0011] The coordinates of the left edge region of the negative polarity primitive are rounded down, and the coordinates of the right edge region are rounded up.

[0012] Optionally, as a possible implementation, in this embodiment of the application, the differential rounding processing of the edge regions of positive polarity primitives in the original image may include:

[0013] The non-integer region coordinates of the positive polarity primitives in the original image are rounded to the nearest integer.

[0014] Optionally, as a possible implementation, in this embodiment of the application, the differential rounding processing of the edge regions of positive polarity primitives in the original image may include:

[0015] The non-integer region coordinates of the positive polarity primitives in the original image are rounded down.

[0016] A second aspect of this application provides a rasterized primitive edge data processing system, which may include:

[0017] The recognition module acquires the coordinate position data of each element in the original image and identifies the combined regions where positive and negative polarity elements overlap; the positive polarity elements are regions composed of exposure points, the negative polarity elements are regions composed of non-exposure points, and the overlapping regions of positive and negative polarity elements are non-exposure points.

[0018] The first processing module expands the edge region of the negative polarity primitives in the combined region to have non-integer edge coordinates;

[0019] The second processing module performs differential rounding on the edge regions of positive polarity primitives in the original image to generate a dot matrix image composed of exposed and unexposed points.

[0020] Optionally, as one possible implementation, in this embodiment of the application, the first processing module may include:

[0021] The first processing unit rounds the coordinates of the left edge region of the negative polarity primitive to obtain the coordinates R(x1) of the left edge pixel. Then, it calculates the coordinates of the right edge according to the formula. Calculate the coordinates S of the right edge, where R is the rounding operator, and x1 and x2 are the coordinates of the left and right edge regions of the negative polarity primitive, respectively.

[0022] Optionally, as one possible implementation, in this embodiment of the application, the first processing module may include:

[0023] The second processing unit rounds down the coordinates of the left edge region of the negative polarity primitive and rounds up the coordinates of the right edge region.

[0024] Optionally, as one possible implementation, in this embodiment of the application, the second processing module may include:

[0025] The third processing unit performs rounding on the non-integer region coordinates of the positive polarity primitives in the original image.

[0026] Optionally, as one possible implementation, in this embodiment of the application, the second processing module may include:

[0027] The fourth processing unit performs a floor function to round down the non-integer region coordinates of the positive polarity primitives in the original image.

[0028] A third aspect of this application provides a computer device including a processor, which executes a computer program stored in a memory to implement the steps of the first aspect and any possible implementation thereof.

[0029] A fourth aspect of this application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the first aspect and any possible implementation thereof.

[0030] As can be seen from the above technical solutions, the embodiments of this application have the following advantages:

[0031] In this embodiment, based on the coordinate position data of each graphic element, different polarity regions with non-integer edge coordinates are differentiated and rounded to avoid gaps between adjacent graphic elements of the same polarity. Simultaneously, for the edge regions of negative polarity graphic elements in the expanded combined region where the edge coordinates are non-integer, the edges of positive polarity graphic elements are erased to shrink the edges of positive polarity graphic elements, ultimately offsetting or reducing errors caused by large laser spot exposure and improving the accuracy of laser imaging. Attached Figure Description

[0032] Figure 1 This is a schematic diagram of an embodiment of a rasterized primitive edge data processing method in this application.

[0033] Figure 2 This is a schematic diagram comparing a specific embodiment of a rasterized primitive edge data processing method with related technologies.

[0034] Figure 3 This is a schematic diagram of one embodiment of a computer device according to the present application. Detailed Implementation

[0035] To enable those skilled in the art to better understand the present invention, the technical solutions of the embodiments of this application 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. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0036] The terms "first," "second," "third," "fourth," etc., used in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0037] In the description of this application, unless otherwise stated, "a plurality of" means two or more. Unless otherwise expressly specified and limited, the terms "installed," "connected," and "linked" shall be interpreted broadly, for example, as a fixed connection, a detachable connection, or an integral connection; as a mechanical connection or an electrical connection; as a direct connection or an indirect connection through an intermediate medium; or as a connection within two components.

[0038] For ease of understanding, the specific processes in the embodiments of this application are described below. Please refer to [link / reference]. Figure 1 One embodiment of a rasterized primitive edge data processing method in this application may include:

[0039] S101: Obtain the position data of each primitive in the original image and identify the combined regions where positive and negative polarity primitives overlap;

[0040] In the field of direct laser imaging technology, the original image to be imaged may be composed of positive and negative polarity primitives. Positive polarity primitives are regions composed of exposed points, while negative polarity primitives are regions composed of unexposed points. In the rasterized bitmap image, the overlapping areas of negative and positive polarity primitives can be erased; that is, the overlapping areas of positive and negative polarity primitives are the unexposed points.

[0041] For example, such as Figure 2 As shown, there is a 2.2*2 positive polarity rectangle in the vector file (area A in the upper left corner of the figure), but in the vector image, it is actually composed of a 3*2 positive polarity rectangle and two 1.4*2 negative polarity rectangles (decomposition shown in the upper right corner of the figure). The two negative polarity rectangles cover the positive polarity rectangle by 0.4 on each side.

[0042] In related technologies, primitives with different attributes undergo the same rasterization process along their edges based on the graphic size, such as rounding to the nearest integer. This results in gaps or expansion between adjacent primitives. For example, if a vector file contains two adjacent rectangles with a length of 4.3 and a height of 2, existing solutions rasterize these two identical primitives only once. The length 4.3 is rounded to 4, resulting in a 4x2 rectangle in the rasterized bitmap image. Then, copying and shifting the image to its corresponding position creates a one-pixel gap between the two images in the bitmap.

[0043] Considering that the laser spot size used in direct laser imaging is often larger than the size of a single pixel (the ratio of spot size to pixel size is not less than 2), the large spot size tends to further expand the exposure area at the edges, ultimately resulting in a lower reproduction accuracy of the image after exposure and development compared to the original image. For example, Figure 2 As shown in area B in the lower left corner: x2 is rounded to 1, and x3 is rounded to 4. Therefore, the two negative rectangles no longer cover the positive rectangle, and a 3*2 rectangle is generated in the bitmap, which causes the primitives in the bitmap image to expand. The large spot causes the image after exposure and development to be further enlarged relative to the original image.

[0044] To improve the accuracy of laser imaging, in this embodiment, a coordinate system is pre-established, and the non-integer coordinates of the edge regions are rounded based on the coordinate position data of each primitive in the original image to avoid gaps between adjacent primitives.

[0045] S102: Expand the edge region where the edge coordinates of the negative polarity primitives in the combined region are non-integer.

[0046] To further improve the accuracy of laser imaging, in this embodiment, the area of ​​the edge region of the negative polarity primitive in the combined region is expanded. The edges of the positive polarity primitive are erased from the edges of the negative polarity primitive to reduce the edge of the positive polarity primitive (the reduced area is less than 1 pixel), ultimately offsetting or reducing the error caused by the large spot exposure of the laser, thus improving the accuracy of laser imaging. For example, expanding the area of ​​the edge region of the negative polarity primitive in the combined region may include: rounding the coordinates of the left edge region of the negative polarity primitive to obtain the coordinates of the left edge pixel R(x1), and then using the formula to determine the coordinates of the right edge region... Calculate the coordinates S of the right edge, where R is the rounding operator, and x1 and x2 are the coordinates of the left and right edge regions of the negative polarity primitive, respectively. That is, (x2-x1) is rounded up (the entire primitive's size is only expanded if (x2-x1) is a non-integer, i.e., the primitive's overall size is a non-integer), meaning the expansion of the negative polarity primitive's overall size does not exceed one coordinate value, avoiding over-expansion. For example, with... Figure 2 The specific application example shown has the first negative primitive having a left edge coordinate of 0 and a right edge coordinate of 2, and the second negative primitive having a left edge coordinate of 4 and a right edge coordinate of 6. The first negative primitive covers the positive rectangle, generating a 2x2 rectangle in the bitmap. Figure 2 (As shown in area C in the lower right corner), the final image rectangle size will be closer to the original design size.

[0047] It is understood that the method of expanding one side of the edge region of the negative polarity primitive in the above-mentioned expanded combination region is merely an example. In practical applications, other methods can be used to expand the non-integer region of the edge of the negative polarity primitive according to the imaging accuracy and the spot size of the light source. For example, the non-integer region on the right can be rounded to the nearest integer, and the non-integer region on the left can be rounded down. Alternatively, the non-integer region on the left can be rounded down and the non-integer region on the right can be rounded up (which may expand more than one coordinate dimension). This is not limited here.

[0048] S103: Perform differential rounding on the position coordinates of the edge regions of positive polarity primitives in the original image.

[0049] To avoid expansion of overlapping areas while maintaining efficiency in rasterization of the original image, all edge regions of all positive polarity primitives in the original image need to undergo the same differential rounding process, ensuring that positive polarity primitives do not experience simultaneous area expansion on both sides. For example, in this embodiment, all edge regions of positive polarity primitives undergo the same differential rounding process. For instance, the position coordinates of all non-integer edge regions of all positive polarity primitives in the original image can be rounded to the nearest integer, ensuring that the difference between the rasterized primitives and the original image does not exceed one pixel.

[0050] Optionally, as a possible implementation, in this embodiment, the differential rounding processing performed on all edge regions of the positive polarity primitive in the same manner can also be used to round down the position coordinates of all non-integer edge regions of the positive polarity primitive. After completing the data processing of all primitives, a dot matrix image can be generated. This dot matrix image can be used to determine the position of the pixels to be exposed in each pixel row, and laser scanning exposure imaging can be performed based on the position of the exposed pixels.

[0051] As can be seen from the above disclosure, in this embodiment, the coordinate position data of each primitive are used to differentiate and round down primitive regions with non-integer edge coordinates, thus avoiding gaps between adjacent primitives of the same polarity. Simultaneously, for the edge regions of negative polarity primitives in the expanded combined region where the edge coordinates are non-integer, the edges of positive polarity primitives are erased to shrink the non-integer edge regions of positive polarity primitives, ultimately offsetting or reducing errors caused by large laser spot exposure and improving the accuracy of laser imaging.

[0052] It is understood that, in the various embodiments of this application, the order of the steps does not imply the order of execution. The execution order of each step should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0053] This application embodiment also provides a rasterized primitive edge data processing system, which may include: an identification module, which acquires the coordinate position data of each primitive in the original image and identifies a combined region where positive and negative polarity primitives overlap; the positive polarity primitive is a region composed of exposure points, the negative polarity primitive is a region composed of non-exposure points, and the overlapping region of positive and negative polarity primitives is a non-exposure point; a first processing module, which expands the edge region of the negative polarity primitive in the combined region to have non-integer edge coordinates; and a second processing module, which performs differential rounding processing on the edge region of the positive polarity primitive in the original image to generate a dot matrix image composed of exposure points and non-exposure points.

[0054] Optionally, as one possible implementation, in this embodiment of the application, the first processing module may include:

[0055] The first processing unit rounds the coordinates of the left edge region of the negative polarity primitive to obtain the coordinates R(x1) of the left edge pixel. Then, it calculates the coordinates of the right edge according to the formula. Calculate the coordinates S of the right edge, where R is the rounding operator, and x1 and x2 are the coordinates of the left and right edge regions of the negative polarity primitive, respectively.

[0056] Optionally, as one possible implementation, in this embodiment of the application, the first processing module may include:

[0057] The second processing unit rounds down the coordinates of the left edge region of the negative polarity primitive and rounds up the coordinates of the right edge region.

[0058] Optionally, as one possible implementation, in this embodiment of the application, the second processing module may include:

[0059] The third processing unit performs rounding on the non-integer region coordinates of the positive polarity primitives in the original image.

[0060] Optionally, as one possible implementation, in this embodiment of the application, the second processing module may include:

[0061] The fourth processing unit performs a floor function to round down the non-integer region coordinates of the positive polarity primitives in the original image.

[0062] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0063] The rasterized primitive edge data processing system in this application embodiment has been described above from the perspective of modular functional entities. Please refer to [link to relevant documentation]. Figure 3 The computer device in the embodiments of this application will now be described from the perspective of hardware processing:

[0064] The computer device 1 may include a memory 11, a processor 12, and an input / output bus 13. The processor 12 executes the computer program to implement the above-described... Figure 1 The steps in the method embodiments shown, for example Figure 1 Steps 101 to 103 are shown. Alternatively, the processor executes a computer program to implement the functions of each module or unit in the above-described device embodiments.

[0065] The memory 11 includes at least one type of readable storage medium, including flash memory, hard disk, multimedia card, card-type memory (e.g., SD or DX memory), magnetic memory, magnetic disk, optical disk, etc. In some embodiments, the memory 11 can be an internal storage unit of the computer device 1, such as the hard disk of the computer device 1. In other embodiments, the memory 11 can be an external storage device of the computer device 1, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc., equipped on the computer device 1. Furthermore, the memory 11 can include both internal storage units and external storage devices of the computer device 1. The memory 11 can be used not only to store application software and various types of data installed on the computer device 1, such as computer program code, but also to temporarily store data that has been output or will be output.

[0066] In some embodiments, processor 12 may be a central processing unit (CPU), controller, microcontroller, microprocessor or other data processing chip, used to run program code stored in memory 11 or process data, such as executing computer programs.

[0067] The input / output bus 13 can be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. This bus can be divided into address bus, data bus, control bus, etc.

[0068] Furthermore, the computer device may also include a wired or wireless network interface 14, which may optionally include a wired interface and / or a wireless interface (such as a Wi-Fi interface, a Bluetooth interface, etc.), typically used to establish communication connections between the computer device 1 and other electronic devices.

[0069] Optionally, the computer device 1 may further include a user interface, which may include a display, an input unit such as a keyboard, and optionally, a standard wired interface or a wireless interface. Optionally, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, or an OLED (Organic Light-Emitting Diode) touchscreen, etc. The display may also be appropriately referred to as a screen or display unit, used to display information processed in the computer device 1 and to display a visual user interface.

[0070] Figure 3 Only computer device 1 with components 11-14 and computer programs is shown; those skilled in the art will understand that... Figure 3 The structure shown does not constitute a limitation on the computer device 1, and may include fewer or more components than shown, or combine certain components, or have different component arrangements.

[0071] The present invention also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, can perform the above-described functions. Figure 1 The steps in the method embodiments shown, for example Figure 1 Steps 101 to 103 are shown. Alternatively, the processor executes a computer program to implement the functions of each module or unit in the above-described device embodiments.

[0072] In the embodiments provided in this application, it should be understood that the disclosed systems, modules, and units can be implemented in other ways. For example, the system embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection through some interfaces, devices, or units, and may be electrical, mechanical, or other forms.

[0073] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0074] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0075] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0076] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for processing edge data of rasterized primitives, characterized in that, include: Obtain the coordinate position data of each primitive in the original image and identify the combined regions where positive and negative polarity primitives overlap; The positive polarity primitive is a region composed of exposure points, and the negative polarity primitive is a region composed of non-exposure points. The overlapping area of ​​the positive and negative polarity primitives after rasterization is a non-exposure point. The edge regions of negative polarity primitives in the combined region are expanded to have non-integer edge coordinates, while the edge regions of positive polarity primitives in the original image are distinguished and rounded to generate a dot matrix image composed of exposure points and non-exposure points.

2. The method according to claim 1, characterized in that, Expanding the region where the edge coordinates of the negative polarity primitives in the combined region are non-integer includes: The coordinates of the left edge region of the negative polarity primitive are rounded to the nearest integer to obtain the coordinates R(x1) of the left edge pixel. According to the formula... Calculate the coordinates of the right edge, where R is the rounding operator, and x1 and x2 are the coordinates of the left and right edge regions of the negative polarity primitive, respectively.

3. The method according to claim 1, characterized in that, Expanding the region where the edge coordinates of the negative polarity primitives in the combined region are non-integer includes: The coordinates of the left edge region of the negative polarity primitive are rounded down, and the coordinates of the right edge region are rounded up.

4. The method according to any one of claims 1 to 3, characterized in that, The differential rounding process for the edge regions of positive polarity primitives in the original image includes: The non-integer region coordinates of the positive polarity primitives in the original image are rounded to the nearest integer.

5. The method according to any one of claims 1 to 3, characterized in that, The differential rounding process for the edge regions of positive polarity primitives in the original image includes: The non-integer region coordinates of the positive polarity primitives in the original image are rounded down.

6. A rasterized primitive edge data processing system, characterized in that, include: The recognition module acquires the coordinate position data of each primitive in the original image and identifies the combined regions where positive and negative polarity primitives overlap. The positive polarity primitive is a region composed of exposure points, and the negative polarity primitive is a region composed of non-exposure points. The overlapping area of ​​the positive and negative polarity primitives after rasterization is a non-exposure point. The first processing module expands the edge region of the negative polarity primitives in the combined region to have non-integer edge coordinates; The second processing module performs differential rounding on the edge regions of positive polarity primitives in the original image to generate a dot matrix image composed of exposed and unexposed points.

7. The system according to claim 6, characterized in that, The first processing module includes: The first processing unit rounds the coordinates of the left edge region of the negative polarity primitive to obtain the coordinates R(x1) of the left edge pixel. Then, it calculates the coordinates of the right edge according to the formula. Calculate the coordinates S of the right edge, where R is the rounding operator, and x1 and x2 are the coordinates of the left and right edge regions of the negative polarity primitive, respectively.

8. The system according to claim 6, characterized in that, The first processing module includes: The second processing unit rounds down the coordinates of the left edge region of the negative polarity primitive and rounds up the coordinates of the right edge region.

9. A computer device, characterized in that, The computer device includes a processor that executes a computer program stored in a memory to implement the method as described in any one of claims 1 to 5.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, it implements the method as described in any one of claims 1 to 5.

Images