Battery cell printing image processing method, device, equipment, medium and ink-jet printer

Abstract

The invention discloses a cell printing image processing method, device and equipment, a medium and an ink-jet printer, and the method comprises the steps: obtaining edge compensation information, the edge compensation information comprises one or more target edges and compensation demands corresponding to the target edges, and the target edges are used for indicating to-be-compensated edges in an original image; and compensating the target edge by using a bar kernel according to the compensation requirement to obtain a target image. The target edge is compensated by adopting the bar-shaped core, so that any edge in the original image can be independently compensated, the precision can reach the pixel level, and the precision and flexibility of processing the cell printing image can be improved.

Description

Technical Field

[0001] This application relates to the field of battery cell inkjet printing, and in particular to a battery cell printing image processing method, apparatus, equipment, medium and inkjet printer. Background Technology

[0002] Inkjet printing is a crucial step in battery cell production. It involves printing inkjet images onto each surface of the battery cell individually, precisely printing a pre-defined pattern onto the surface of the prismatic cell. However, due to the varying sizes of different types of battery cells, achieving precise alignment between the printed image and the cell's edges is challenging, resulting in discrepancies between the printed image edges and the actual edges of the cell. The current industry-standard solution is to pre-adjust the image edges using software compensation algorithms. However, the compensation algorithms in these technologies have some drawbacks. For example, they can only increase or decrease all edges of the image at the same time, which can lead to the phenomenon that the compensated image edges still cannot match the actual battery cell edges after inkjet printing. Or, one edge can match the actual battery cell edge after compensation adjustment, but another edge cannot match the actual battery cell edge.

[0003] In summary, the image processing for battery cell printing in related technologies suffers from low accuracy and poor flexibility. Summary of the Invention

[0004] This application aims to provide a method, apparatus, device, medium, and inkjet printer for image processing of battery cell printing, which can improve the accuracy and flexibility of image processing for battery cell printing.

[0005] In a first aspect, embodiments of this application provide a method for processing printed images of battery cells, comprising the following steps: Obtain edge compensation information, which includes one or more target edges and compensation requirements corresponding to the target edges, wherein the target edges are used to indicate the edges to be compensated in the original image; Based on the compensation requirements and by using a bar kernel to compensate for the target edges, a target image is obtained; The bar kernel comprises N elements arranged in a column or row, where N is an odd number greater than or equal to 3. The bar kernel includes (N+1) / 2 valid elements and (N-1) / 2 invalid elements, with the valid elements located at the center point of the bar kernel and to one side of the center point, and the invalid elements located on the other side of the center point.

[0006] According to some embodiments of this application, before obtaining the edge compensation information, the method further includes: Obtain a printed image, wherein the printed image is the actual image printed on the surface of the battery cell based on the original image; Image difference information is obtained from the printed image, and the image difference information is used to indicate the difference between the edge of the printed image and the edge of the battery cell. Edge compensation information is generated based on image difference information.

[0007] According to some embodiments of this application, the compensation requirement includes edge enhancement requirement and edge reduction requirement, and the step of compensating the target edge according to the compensation requirement and using a bar kernel to obtain a target image includes: When the edge compensation requirement is an edge augmentation requirement, a bar kernel is used for dilation processing to compensate for the target edge, resulting in the target image; When the edge compensation requirement is the same as the edge reduction requirement, a strip kernel is used for erosion processing to compensate the target edge, thus obtaining the target image.

[0008] According to some embodiments of this application, the compensation requirement further includes a compensation width, wherein the compensation width information is used to indicate the width of the target edge that needs to be compensated. Based on the compensation requirement and using a bar kernel to compensate the target edge, a target image is obtained, including: The length of the strip core is adjusted according to the compensation width to obtain the target strip core; The target edge is compensated based on the compensation width information and using the target bar kernel.

[0009] According to some embodiments of this application, the compensation requirement is an edge reduction requirement. After compensating the target edge according to the compensation requirement and using a bar kernel to obtain the target image, the method further includes: Subtracting the target image from the original image yields the edge image; Generate an edge printing command based on the edge image.

[0010] Secondly, embodiments of this application provide a battery cell printing image processing apparatus, comprising: The compensation information acquisition module is used to acquire edge compensation information, which includes one or more target edges and compensation requirements corresponding to the target edges. The target edges are used to indicate the edges to be compensated in the original image. An edge compensation processing module is used to compensate the target edge according to the compensation requirements and using a bar kernel to obtain a target image; wherein, the bar kernel includes N elements arranged in a column or row, where N is an odd number greater than or equal to 3, and the bar kernel includes (N+1) / 2 valid elements and (N-1) / 2 invalid elements.

[0011] Thirdly, embodiments of this application provide an electronic device, the device comprising: a processor and a memory storing computer program instructions; When the processor executes the computer program instructions, it implements the cell printing image processing method as described in the first aspect.

[0012] Fourthly, embodiments of this application provide a computer-readable storage medium storing computer program instructions, which, when executed by a processor, implement the cell printing image processing method as described in the first aspect.

[0013] Fifthly, embodiments of this application provide an inkjet printer, including the electronic device described in the third aspect embodiment.

[0014] The battery cell printing image processing method, apparatus, device, medium, and inkjet printer of the present application embodiments have at least the following beneficial effects: In this embodiment, edge compensation information is first obtained, which includes one or more target edges and compensation requirements corresponding to the target edges. Then, the target edges are compensated according to the compensation requirements and using a bar kernel to obtain the target image. Since the target edges are compensated using a bar kernel, any edge in the original image can be compensated independently with pixel-level accuracy, which can improve the accuracy and flexibility of cell printing image processing.

[0015] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0016] The present application will be further described below with reference to the accompanying drawings and embodiments, wherein: Figure 1 A schematic flowchart illustrating an embodiment of the battery cell printing image processing method provided in this application; Figure 2a This is a schematic diagram of the first transverse strip core in an embodiment of this application; Figure 2b This is a schematic diagram of the second transverse strip core in an embodiment of this application; Figure 2c This is a schematic diagram of the first vertical strip core in an embodiment of this application; Figure 2d This is a schematic diagram of the second vertical strip core in an embodiment of this application; Figure 3 This is a schematic diagram of the first type of original image; Figure 4 This is a schematic diagram showing the intersection of the bar kernel and the original image in this application; Figure 5 This is a schematic diagram of the original image after erosion processing. Figure 6This is a schematic diagram of the original image after dilation processing; Figure 7a This is a schematic diagram of the second type of original image; Figure 7b To Figure 7a A schematic diagram of the target image undergoing etch processing; Figure 7c A schematic diagram showing custom edge processing; Figure 8 A schematic diagram of the battery cell printing image processing device provided in this application; Figure 9 A schematic diagram of the structure of the electronic device provided in this application. Detailed Implementation

[0017] The features and exemplary embodiments of various aspects of this application will be described in detail below. To make the objectives, technical solutions, and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain this application and not to limit it. For those skilled in the art, this application can be implemented without some of these specific details. The following description of the embodiments is merely to provide a better understanding of this application by illustrating examples.

[0018] In this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, without necessarily requiring or implying any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising..." does not exclude the presence of additional identical elements in the process, method, article, or apparatus that includes said element.

[0019] To address the problems of the prior art, embodiments of this application provide a method, apparatus, device, medium, and inkjet printer for processing images of battery cells. The image processing method for processing battery cells provided in this application embodiment will be described first below.

[0020] Figure 1 A schematic flowchart of a battery cell printing image processing method provided in an embodiment of this application is shown. This method is applied to electronic devices and includes the following steps: S101. Obtain edge compensation information. The edge compensation information includes one or more target edges and compensation requirements corresponding to the target edges. The target edges are used to indicate the edges to be compensated in the original image. S102. Based on the compensation requirements, the target edge is compensated using a bar kernel to obtain the target image; The bar kernel consists of N elements arranged in a column or row, where N is an odd number greater than or equal to 3. The bar kernel includes (N+1) / 2 valid elements and (N-1) / 2 invalid elements, with the valid elements located at the center point of the bar kernel and to one side of the center point, and the invalid elements located on the other side of the center point.

[0021] In this embodiment, edge compensation information is first obtained, which includes one or more target edges and compensation requirements corresponding to the target edges. Then, the target edges are compensated according to the compensation requirements and using a bar kernel to obtain the target image. Since the target edges are compensated using a bar kernel, any edge in the original image can be compensated independently with pixel-level accuracy, which can improve the accuracy and flexibility of cell printing image processing.

[0022] The edge compensation information in step S101 above can be generated manually by observing the actual printed battery cell and determining which edge needs compensation. Then, the edge with defects requiring compensation, along with its compensation requirement, is manually entered. The compensation requirement refers to the adjustments needed for that edge. For example, if an edge needs to completely cover the right side of the battery cell, and after printing, observation reveals a slight difference between the printed image and the actual battery cell edge, then the right side of the original image needs to be widened—this is the edge compensation information. Besides manual input, it can also be automatically generated by an image recognition algorithm that compares the original image with the image of the actual finished product.

[0023] It should be noted that the target edge mentioned above can be any one or more edges of the original image. For example, only the top edge needs to be compensated, or the top, bottom, and right edges need to be compensated simultaneously.

[0024] The compensation of the target edge in step S102 above refers to morphological processing of the target edge. The aforementioned strip kernel refers to the special kernel structure used in this application for compensation processing in morphological algorithms. It should be noted that most software compensation algorithms in related technologies use kernel structures from morphological algorithms to compensate for image edges. Traditional morphological kernel structures include rectangles, circles, and crosses. The kernel size is set to N×N with equal width and height, and all elements in the kernel are 1, i.e., effective elements. By moving the center of the kernel structure elements in the image from left to right and top to bottom, the kernel structure processes the image; that is, elements with a value of 1 in the kernel structure participate in morphological processing. Since rectangular, circular, and cross kernel structures all have 1 elements in the four directions (up, down, left, and right) around the center, when the kernel structure moves in the image, the image can intersect with the 1 elements in the kernel structure in all four directions. Pixels intersecting with 1 elements will undergo morphological operations. Therefore, as long as there are 1 elements around the center point, morphological operations will definitely be performed. Regardless of whether a rectangular, circular, or cross-shaped kernel structure is used in the related technologies, it will intersect with the four directions in the original image. Therefore, there are problems such as low compensation accuracy and inability to customize the compensation edge.

[0025] The bar kernel used in this application comprises N elements arranged in a column or row, where N is an odd number greater than or equal to 3. The bar kernel includes (N+1) / 2 valid elements and (N-1) / 2 invalid elements. Valid elements refer to the 1 element in the graph, and invalid elements refer to the 0 element in the graph.

[0026] Specifically, the bar cores in this application can adopt a 1×N or N×1 structure, and can be arranged sequentially in a column or a row. Therefore, there are a total of four types: first horizontal bar core, second horizontal bar core, first vertical bar core, and second vertical bar core, as detailed below: refer to Figure 2a As shown, the first horizontal bar kernel uses a kernel of size 1×N, with elements of 1 in the row direction [0, (N+1) / 2] and elements of 0 in the row direction [(N+1) / 2, N]. refer to Figure 2b As shown, the second horizontal bar kernel uses a kernel of size 1×N, with elements in the row direction [0, N / 2] being 0 and elements in the row direction [N / 2, N] being 1; refer to Figure 2c As shown, the first vertical bar kernel uses a kernel of size N×1, with elements in the column direction [0, N / 2] being 1 and elements in the column direction [N / 2, N] being 0; refer to Figure 2d As shown, the second vertical bar kernel uses a kernel of size N×1, with elements in the column direction [0, N / 2] being 0 and elements in the column direction [N / 2, N] being 1.

[0027] refer to Figure 3 This is a schematic diagram of the original image in this application, which includes four sides: top, bottom, left, and right. (Refer to...) Figure 4 As shown, when the first horizontal bar kernel moves across the image, only on the right side does an element with a value of 1 intersect with a foreground pixel in the original image. The foreground pixel is an element with a pixel value of 1 in the image. Therefore, the second horizontal bar kernel only intersects with the original image on the left side. Similarly, the first vertical bar kernel only intersects with the bottom of the original image, and the second vertical bar kernel only intersects with the top of the original image.

[0028] Traditional rectangular, circular, and cross-shaped kernel structures can only intersect with four directions in the original image simultaneously, so all four directions undergo the same morphological processing at the same time. However, the bar kernel of this application can intersect with pixels in only one direction of the original image. That is, the edges of the original image in the four directions can be customized and compensated through the bar kernel of this application, i.e., customized morphological processing.

[0029] It should be noted that edge compensation involves increasing or decreasing the width of the edges in the original image. In graphic printing, this translates to increasing or decreasing the number of edge pixels. Since the bar kernel in this application comprises N elements arranged sequentially, its length is adjustable, with a minimum length of 3 (N=3). In this case, it contains two valid elements (1) and one invalid element (0). One side of the center point (1) is 1, and the other side is 0. This is the minimum form of the bar kernel. This kernel allows for the increase or decrease of single pixels with pixel-level precision, significantly improving compensation accuracy and edge printing accuracy.

[0030] In some implementations, before obtaining edge compensation information, the following may be included: Obtain the printed image, which is the actual image printed on the surface of the battery cell based on the original image; Image difference information is obtained from the printed image, which is used to indicate the difference between the edge of the printed image and the edge of the battery cell. Edge compensation information is generated based on image difference information.

[0031] In this embodiment, a printed image is first acquired, then image difference information is obtained based on the printed image, and finally edge compensation information is generated based on the image difference information. This allows for the automatic generation of edge compensation information without the need for manual visual judgment, further improving the automation level of image processing and increasing processing efficiency.

[0032] It should be noted that the above-mentioned printed image refers to first printing ink on the surface of the battery cell based on the original image, and then obtaining the image of the battery cell through an industrial camera or other image sensor. Obtaining image difference information based on the printed image means identifying which edges of the printed image differ from the actual edges of the battery cell through image analysis and other means. Edges with differences need to be compensated. It can also be determined from the printed image whether the width needs to be increased or decreased, as well as the specific compensation width, etc.

[0033] In some implementations, the compensation requirements include edge enhancement requirements and edge reduction requirements. Based on these requirements and using a bar kernel to compensate for the target edges, a target image is obtained, which may include: When edge compensation increases the demand for edge compensation, a strip kernel is used for dilation to compensate for the target edge, thus obtaining the target image. When the edge compensation requirement is the same as the edge reduction requirement, a strip kernel is used for erosion processing to compensate for the target edge and obtain the target image.

[0034] In this embodiment, when the edge compensation requirement is to increase the edge size, a strip kernel is used for dilation to compensate the target edge, resulting in the target image. Conversely, when the edge compensation requirement is to decrease the edge size, a strip kernel is used for erosion to compensate the target edge, also resulting in the target image. The appropriate processing method can be selected based on different compensation requirements, further improving the automation level of image processing and increasing processing efficiency.

[0035] It should be noted that edge compensation involves increasing or decreasing the width of edges. When compensating for the original image, this can be translated into increasing or decreasing the number of edge pixels. In this embodiment, erosion and dilation processes are used to compensate for the original image, thereby increasing or decreasing the width of image edge pixels, which ultimately affects the actual printed image. In morphological algorithms, erosion reduces edge pixels, while dilation increases edge width.

[0036] It should be understood that the erosion processing of the original image in this application refers to combining all valid elements 1 in the bar kernel with elements 1 of the original image, and eliminating corresponding areas by combining invalid elements 0 with elements 1 of the original image, thereby reducing pixels. (Reference) Figure 5 As shown, applying erosion to the left and right edges of the original image reduces the width of the left and right edges.

[0037] Similarly, the dilation process applied to the original image in this application refers to combining at least one effective element 1 from the bar kernel with element 1 of the original image, and increasing the number of pixels through the extension of at least one effective element 1. (See reference) Figure 6As shown, applying dilation to the top and right edges of the original image increases their width.

[0038] It should be noted that in this embodiment, since a bar kernel is used for edge compensation, each edge of the image can be independently eroded or dilated. That is, a combination of erosion and compensation processing is performed on the image; one edge of the original image is dilated while another edge is eroded, to meet the needs of specific application scenarios. For example, the upper edge of the original image can be dilated while the lower edge is eroded; or the upper and lower edges of the original image can be dilated while the left and right edges are eroded. It should be understood that the above are only two examples of combined processing of the original image in this embodiment. Any combination of erosion and compensation processing for any edge can be performed using a bar kernel according to actual needs.

[0039] In some implementations, the compensation requirement also includes a compensation width, whereby the compensation width information indicates the width of the target edge that needs to be compensated. Based on the compensation requirement and using a bar kernel to compensate the target edge, a target image is obtained, which may include: The length of the bar kernel is adjusted according to the compensation width to obtain the target bar kernel; The target edge is compensated based on the compensation width information and using the target bar kernel.

[0040] In this embodiment, the length of the bar kernel is first adjusted according to the compensation width to obtain the target bar kernel; then, the target edge is compensated based on the compensation width information and the target bar kernel. Precise adjustment of the original image edge can be achieved by adjusting the length of the bar kernel, greatly improving compensation accuracy.

[0041] It should be understood that the compensation width can be derived from the difference between the printed image of the original image on the cell surface and the actual edge of the cell. This difference can be determined manually by visual inspection or calculated using image analysis algorithms. Once the compensation width is determined, the length of the bar core is adjusted accordingly. The length of the bar core is determined by changing the value of N.

[0042] In some implementations, the compensation requirement is an edge reduction requirement. After compensating the target edges according to the compensation requirement and using a bar kernel to obtain the target image, the process may further include: Subtracting the target image from the original image yields the edge image; Generate edge printing commands based on the edge image.

[0043] In this embodiment, the original image is first subtracted from the target image to obtain the edge image, and then an edge printing command is generated based on the edge image. This allows for customized printing of battery cell edges, improving flexibility.

[0044] It should be noted that in some inkjet printing processes for battery cells, a method of printing a 3-5mm edge first and then printing the entire surface is used. However, current printing image processing software does not have the function of customizing edge printing. Therefore, in this application, the edges to be printed in the original image are first eroded to obtain a target image. Then, the original image and the eroded target image are subtracted, and the actual printing area is the "eroded" area. The width of the printing area is then the pixel width of the "eroded" area, and this printing area is the edge printing area.

[0045] refer to Figures 7a to 7c As shown, if you need to customize the top and left edges of the original image for printing, the specific process is as follows: First, the original image is eroded, which reduces the width of the top and left edges, while leaving the right and bottom edges unprocessed. Then, the original image is subtracted from the eroded target image to obtain the printed images of the top and left edges, thus achieving custom edge printing.

[0046] Based on the cell printing image processing method provided in the above embodiments, this application also provides specific implementation methods of the cell printing image processing device.

[0047] like Figure 8 As shown, the cell printing image processing apparatus 200 provided in this application embodiment may include: The compensation information acquisition module 201 is used to acquire edge compensation information, which includes one or more target edges and compensation requirements corresponding to the target edges. The target edges are used to indicate the edges to be compensated in the original image. The edge compensation processing module 202 is used to compensate the target edge according to the compensation requirements and using a bar kernel to obtain the target image; wherein, the bar kernel includes N elements arranged in a column or row, where N is an odd number greater than or equal to 3, and the bar kernel includes (N+1) / 2 valid elements and (N-1) / 2 invalid elements.

[0048] The cell printing image processing apparatus 200 of this application embodiment is used to execute the cell printing image processing method in the above embodiment. Its specific processing procedure is the same as that of the cell printing image processing method in the above embodiment, and will not be described in detail here.

[0049] Figure 9 A schematic diagram of the hardware structure of the electronic device provided in an embodiment of this application is shown.

[0050] The electronic device may include a processor 301 and a memory 302 storing computer program instructions.

[0051] Specifically, the processor 301 may include a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits that can be configured to implement the embodiments of this application.

[0052] Memory 302 may include mass storage for data or instructions. For example, and not limitingly, memory 302 may include a hard disk drive (HDD), floppy disk drive, flash memory, optical disk, magneto-optical disk, magnetic tape, or Universal Serial Bus (USB) drive, or a combination of two or more of these. Where appropriate, memory 302 may include removable or non-removable (or fixed) media. Where appropriate, memory 302 may be internal or external to the integrated gateway disaster recovery device. In a particular embodiment, memory 302 is non-volatile solid-state memory.

[0053] In some embodiments, memory 302 may include read-only memory (ROM), random access memory (RAM), disk storage media device, optical storage media device, flash memory device, electrical, optical, or other physical / tangible memory storage device. Thus, generally, memory includes one or more tangible (non-transitory) computer-readable storage media (e.g., memory devices) encoded with software including computer-executable instructions, and when the software is executed (e.g., by one or more processors), it is operable to perform the operations described with reference to the method according to one aspect of this disclosure.

[0054] The processor 301 reads and executes computer program instructions stored in the memory 302 to implement any of the cell printing image processing methods in the above embodiments.

[0055] In one example, the electronic device may also include a communication interface 303 and a bus 310. For example, Figure 3 As shown, the processor 301, memory 302, and communication interface 303 are connected through bus 310 and complete communication with each other.

[0056] The communication interface 303 is mainly used to realize communication between various modules, devices, units and / or equipment in the embodiments of this application.

[0057] Bus 310 includes hardware, software, or both, that couples components of an online data traffic metering device together. For example, and not limitingly, the bus may include an Accelerated Graphics Port (AGP) or other graphics bus, an Enhanced Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), HyperTransport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an Infinite Bandwidth Interconnect, a Low Pin Count (LPC) bus, a memory bus, a Microchannel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association Local (VLB) bus, or other suitable buses, or combinations of two or more of these. Where appropriate, bus 310 may include one or more buses. Although specific buses are described and illustrated in embodiments of this application, any suitable bus or interconnect is contemplated herein.

[0058] Furthermore, in conjunction with the cell printing image processing method in the above embodiments, this application embodiment can provide a computer storage medium for implementation. The computer storage medium stores computer program instructions; when these computer program instructions are executed by a processor, they implement any of the cell printing image processing methods in the above embodiments.

[0059] It should be clarified that this application is not limited to the specific configurations and processes described above and shown in the figures. For the sake of brevity, detailed descriptions of known methods are omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of this application is not limited to the specific steps described and shown. Those skilled in the art can make various changes, modifications, and additions, or change the order of steps, after understanding the spirit of this application.

[0060] The functional blocks shown in the above-described structural diagram can be implemented as hardware, software, firmware, or a combination thereof. When implemented in hardware, they can be, for example, electronic circuits, application-specific integrated circuits (ASICs), appropriate firmware, plug-ins, function cards, etc. When implemented in software, the elements of this application are programs or code segments used to perform the required tasks. Programs or code segments can be stored on a machine-readable medium or transmitted over a transmission medium or communication link via data signals carried on a carrier wave. "Machine-readable medium" can include any medium capable of storing or transmitting information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, fiber optic media, radio frequency (RF) links, etc. Code segments can be downloaded via computer networks such as the Internet, intranets, etc.

[0061] It should also be noted that the exemplary embodiments mentioned in this application describe methods or systems based on a series of steps or apparatus. However, this application is not limited to the order of the above steps; that is, the steps can be performed in the order mentioned in the embodiments, or in a different order, or several steps can be performed simultaneously.

[0062] The aspects of this disclosure have been described above with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this disclosure. It should be understood that each block in the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine such that these instructions, executable via the processor of the computer or other programmable data processing apparatus, enable the implementation of the functions / actions specified in one or more blocks of the flowchart illustrations and / or block diagrams. Such a processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor, or a field-programmable logic circuit. It is also understood that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can also be implemented by special-purpose hardware performing the specified functions or actions, or can be implemented by a combination of special-purpose hardware and computer instructions.

[0063] This application also relates to an inkjet printer, including the electronic device described in the above embodiments. The electronic device can be a controller for the inkjet printer or a separate print image processing module to process the image to be printed.

[0064] The above description is merely a specific implementation of this application. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, modules, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here. It should be understood that the protection scope of this application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in this application, and these modifications or substitutions should all be covered within the protection scope of this application.

Claims

1. A method for processing printed images of battery cells, characterized in that, Includes the following steps: Obtain edge compensation information, which includes one or more target edges and compensation requirements corresponding to the target edges, wherein the target edges are used to indicate the edges to be compensated in the original image; Based on the compensation requirements and by using a bar kernel to compensate for the target edges, a target image is obtained; The bar kernel comprises N elements arranged in a column or row, where N is an odd number greater than or equal to 3. The bar kernel includes (N+1) / 2 valid elements and (N-1) / 2 invalid elements, with the valid elements located at the center point of the bar kernel and to one side of the center point, and the invalid elements located on the other side of the center point.

2. The cell printing image processing method according to claim 1, characterized in that, Before obtaining the edge compensation information, the process also includes: Obtain a printed image, wherein the printed image is the actual image printed on the surface of the battery cell based on the original image; Image difference information is obtained from the printed image, and the image difference information is used to indicate the difference between the edge of the printed image and the edge of the battery cell. Edge compensation information is generated based on image difference information.

3. The cell printing image processing method according to claim 1, characterized in that, The compensation requirements include edge enhancement requirements and edge reduction requirements. The step of compensating the target edges according to the compensation requirements and using a bar kernel to obtain the target image includes: When the edge compensation requirement is an edge augmentation requirement, a bar kernel is used for dilation processing to compensate for the target edge, resulting in the target image; When the edge compensation requirement is the same as the edge reduction requirement, a strip kernel is used for erosion processing to compensate the target edge, thus obtaining the target image.

4. The cell printing image processing method according to claim 1, characterized in that, The compensation requirement also includes a compensation width, wherein the compensation width information is used to indicate the width of the target edge that needs to be compensated. Based on the compensation requirement and using a bar kernel to compensate the target edge, a target image is obtained, including: The length of the strip core is adjusted according to the compensation width to obtain the target strip core; The target edge is compensated based on the compensation width information and using the target bar kernel.

5. The cell printing image processing method according to claim 1, characterized in that, The compensation requirement is an edge reduction requirement. After compensating the target edge according to the compensation requirement and using a bar kernel to obtain the target image, the process further includes: Subtracting the target image from the original image yields the edge image; Generate an edge printing command based on the edge image.

6. A cell printing image processing device, characterized in that, include: The compensation information acquisition module is used to acquire edge compensation information, which includes one or more target edges and compensation requirements corresponding to the target edges. The target edges are used to indicate the edges to be compensated in the original image. An edge compensation processing module is used to compensate the target edge according to the compensation requirements and using a bar kernel to obtain a target image; wherein, the bar kernel includes N elements arranged in a column or row, where N is an odd number greater than or equal to 3, and the bar kernel includes (N+1) / 2 valid elements and (N-1) / 2 invalid elements.

7. An electronic device, characterized in that, The device includes: a processor and a memory storing computer program instructions; When the processor executes the computer program instructions, it implements the cell printing image processing method as described in any one of claims 1-5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer program instructions, which, when executed by a processor, implement the cell printing image processing method as described in any one of claims 1-5.

9. An inkjet printer, characterized in that, Includes the electronic device as described in claim 7.

Images