Inkjet printing method, device, equipment and storage medium for image segmentation conversion

Abstract

The present invention discloses an inkjet printing method, device, equipment and storage medium for segmented image transformation, and relates to the field of inkjet printing technology. The inkjet printing method for segmented image transformation of the present invention comprises: solving a forward transformation matrix; determining the most edge point, width and height of a target image; solving an inverse transformation matrix; converting the original image into a target image in segments; and printing the target image in segments. The printing device comprises: a forward transformation matrix solving module, a target image parameter determining module, an inverse transformation matrix solving module, an original image segmented conversion module, and a target image segmented printing module. The printing device comprises a processor, a memory and computer program instructions stored in the memory. The storage medium stores computer program instructions. The inkjet printing method, device, equipment and medium for segmented image transformation of the present invention can correct the placement error of the printing object, shorten the printing time and improve the printing efficiency.

Description

Technical Field

[0001] The present invention relates to the field of inkjet printing technology, and in particular to an inkjet printing method, device, equipment and storage medium for image segmentation conversion. Background Art

[0002] Inkjet printing technology refers to the technology of spraying ink droplets onto the printing object through a nozzle to obtain images or text. This technology is non-contact printing and has the characteristics of fast printing speed, low pollution and high printing accuracy.

[0003] In some printing scenarios, due to the placement error of the printing object, the actual target image to be printed is different from the original image as the source of the printing data in terms of position, size, angle, etc. In this case, the original image needs to be transformed to obtain the target image before printing. For example, when printing a PCB, the actual position or posture of the PCB board is different from the original image. In this case, the original image needs to be converted into a target image with the same position or posture as the actual PCB board before printing to correct the error caused by the board placement.

[0004] However, when the original image data volume is large, the process of converting the original image into the target image takes too long, and directly printing the original image without conversion cannot correct the board placement error. Summary of the invention

[0005] The present invention provides an inkjet printing method, device, equipment and storage medium for image segment conversion, which are used to solve the technical problem that the existing inkjet printing method cannot shorten the printing time and improve the printing efficiency when correcting the placement error of the printing object.

[0006] In a first aspect, the present invention provides an inkjet printing method for image segmentation conversion, which is used to convert an original image into a target image for printing, comprising the following steps:

[0007] S1: solving a forward transformation matrix according to original image information and actual positioning point data and / or conversion information;

[0008] S2: Determine the edge point, width and height of the target image according to the original image information and the forward transformation matrix;

[0009] S3: solving an inverse transformation matrix according to the original image information and the most edge points of the target image;

[0010] S4: transforming the original image into the target image in segments according to the inverse transformation matrix;

[0011] S5: Printing the target image in sections.

[0012] Preferably, the step S4: converting the original image into a target image by segmentation according to the inverse transformation matrix further comprises:

[0013] S41: dividing the original image into a plurality of sub-original images according to the inverse transformation matrix, each sub-original image corresponds to a sub-target image, and the target image includes the sub-target image;

[0014] S42: Allocating a first storage area for storing data of a sub-original image and a second storage area for storing data of a sub-target image corresponding to the sub-original image;

[0015] S43: Read the data of the sub-original image into the first storage area;

[0016] S44: converting the data of the sub-original image into data of a corresponding sub-target image and storing the data in a second storage area;

[0017] S45: Repeat steps S43 to S44 until the conversion of data of all sub-original images is completed.

[0018] Preferably, the step S44: converting the data of the sub-original image into data of a corresponding sub-target image and storing the data in the second storage area further comprises:

[0019] S441: determining the corresponding coordinate positions of pixels at each coordinate position in the target image in the original image according to the inverse transformation matrix;

[0020] S442: Obtain the storage location of the sub-target image data corresponding to the pixel at each coordinate position in the sub-target image in the second storage area;

[0021] S443: Obtain the storage location of the sub-original image data corresponding to the pixels at each coordinate position of the sub-original image in the first storage area;

[0022] S443: determining a storage position in the first storage area corresponding to the storage position in the second storage area according to the corresponding coordinate position, the storage position of the sub-target image data in the second storage area, and the storage position of the sub-original image data in the first storage area;

[0023] S444: extracting the sub-original image data in the first storage area according to the corresponding storage position in the first storage area and performing data processing to obtain the sub-target image data, and storing the processed sub-target image data in the corresponding storage position in the second storage area.

[0024] Preferably, between S41 and S42: the following steps are also included:

[0025] S410: Determine the maximum storage capacity C1 required to store a single sub-original image according to the number of rows N of the sub-target image, the inverse transformation matrix, the width of the original image and the height of the target image, and determine the maximum storage capacity C2 required to store a single sub-target image according to the number of rows N of the sub-target image and the width of the target image;

[0026] In S42:, the storage capacity of the first storage area applied for is C1, and the storage capacity of the second storage area applied for is C2.

[0027] Preferably, the step S410: determining the maximum storage capacity C1 required to store a single sub-original image according to the number of rows N of the sub-target image, the inverse transformation matrix, the width of the original image and the height of the target image, and determining the maximum storage capacity C2 required to store a single sub-target image according to the number of rows N of the sub-target image and the width of the target image further comprises:

[0028] S4111: Obtain the number of rows N of the sub-target image;

[0029] S4112: Calculating the maximum storage capacity required to store a single sub-target image according to the width of the target image and the number of rows N of the sub-target images;

[0030] S4113: Determine the end row and the start row of each sub-original image according to the number of rows N of the sub-target image and the inverse transformation matrix;

[0031] S4114: Calculate the storage capacity required for reading each sub-original image according to the width of the original image, the height of the target image, and the end row and the start row of each sub-original image;

[0032] S4115: Select the largest one from the memory values ​​required to read each sub-original image as the maximum storage capacity required to obtain a single sub-original image.

[0033] Preferably, the original image information includes the coordinates of the outermost points of the original image, and the step S2: determining the outermost points, width and height of the target image according to the original image information and the forward transformation matrix further includes:

[0034] S21: Perform a forward transformation on the coordinates of the most edge point of the original image according to the forward transformation matrix to obtain the most edge point of the target image;

[0035] S22: determining the minimum outer bounding positive moment of the target image according to the most edge point of the target image;

[0036] S23: Determine the outermost point, width and height of the target image according to the minimum outer bounding positive moment of the target image.

[0037] Preferably, the original image information includes the coordinates of the outermost points of the original image, and S3 includes:

[0038] S31: performing a translation transformation on the target image to align with the origin according to the outermost point of the target image to obtain the coordinates of the outermost point of the aligned target image;

[0039] S32: Determine an inverse transformation matrix according to the coordinates of the most edge points of the aligned target image and the coordinates of the most edge points of the original image.

[0040] In a second aspect, the present invention provides an inkjet printing device for image segmentation conversion, the device comprising:

[0041] A forward transformation matrix solving module, wherein the forward transformation matrix solving module is used to solve the forward transformation matrix according to the original image information and the actual positioning point data and / or the conversion information;

[0042] A target image parameter determination module, the target image parameter determination module is used to determine the edge point, width and height of the target image according to the original image information and the forward transformation matrix;

[0043] An inverse transformation matrix solving module, wherein the inverse transformation matrix solving module is used to solve the inverse transformation matrix according to the original image information and the most edge point of the target image;

[0044] The original image segmentation conversion module is used to convert the original image segmentation into the target image according to the inverse transformation matrix;

[0045] The target image segment printing module is used to print the target image in segments.

[0046] In a third aspect, the present invention provides an inkjet printing device for image segmentation conversion, comprising at least one processor, at least one memory, and computer program instructions stored in the memory, and when the computer program instructions are executed by the processor, the method described in the first aspect is implemented.

[0047] In a fourth aspect, the present invention provides a storage medium having computer program instructions stored thereon, and when the computer program instructions are executed by a processor, the method described in the first aspect is implemented:

[0048] Beneficial effects: In summary, the inkjet printing method, device, equipment and storage medium for image segmentation conversion provided by the present invention utilize an inverse transformation matrix to segment the original image into a target image, and then perform segmented printing on the converted target image. In this way, the placement error of the printing object can be corrected in the process of converting the original image into the target image, and the image to be printed can be accurately printed on the printing object even when the printing object is not placed accurately. Since the present invention adopts the method of segmented conversion and segmented printing, it is not necessary to wait until the entire image to be printed is converted before printing, which greatly shortens the overall printing time and significantly improves the printing efficiency. Since each segment is converted before printing, the printing efficiency is improved while the placement error of the printing object is corrected. In addition, the segmented conversion not only shortens the overall time of image printing, but also reduces the demand for storage resources during the conversion process. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] In order to more clearly illustrate the technical solution of the embodiment of the present invention, the following briefly introduces the drawings required for use in the embodiment of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0050] Figure 1 is a flow chart of an inkjet printing method for image segmentation conversion according to Embodiment 1 of the present invention;

[0051] Figure 2 It is a schematic diagram of forward transformation using the positioning points of the original image and the positioning points of the target image;

[0052] Figure 3 is a schematic diagram of the present invention using four corner points of the original image as positioning points;

[0053] Figure 4 Schematic diagram of the minimum outer bounding positive moment of the target image of the present invention;

[0054] Figure 5 is a schematic diagram of aligning a target image toward an origin according to the present invention;

[0055] Figure 6 It is a flow chart of converting the original image into the target image by segmentation according to the present invention;

[0056] Figure 7 is a flow chart of the present invention for converting the data of the sub-original image into the data of the corresponding sub-target image and storing the data in the second storage area;

[0057] Figure 8 It is a schematic diagram of assigning values ​​one by one according to the present invention;

[0058] Fig. 9is a schematic diagram of converting an original image into a target image according to the present invention;

[0059] Fig.10 is a structural block diagram of an inkjet printing device for image segmentation conversion in Embodiment 3 of the present invention;

[0060] Fig.11 It is a structural block diagram of the inkjet printing device for image segmentation conversion in Example 4 of the present invention. DETAILED DESCRIPTION

[0061] The features and exemplary embodiments of various aspects of the present invention will be described in detail below. In order to make the purpose, technical solutions and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and Examples. It should be understood that the specific embodiments described herein are only configured to explain the present invention and are not configured to limit the present invention. For those skilled in the art, the present invention can be implemented without the need for some of these specific details. The following description of the embodiments is only to provide a better understanding of the present invention by illustrating examples of the present invention.

[0062] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the statement "include..." do not exclude the presence of other identical elements in the process, method, article or device including the elements.

[0063] Example 1

[0064] See also Figure 1 This embodiment provides an inkjet printing method for image segmentation transformation, which is used to convert an original image into a target image for printing, and mainly includes the following steps:

[0065] S1: solving a forward transformation matrix according to original image information and actual positioning point data and / or conversion information;

[0066] S2: Determine the edge point, width and height of the target image according to the original image information and the forward transformation matrix;

[0067] S3: solving an inverse transformation matrix according to the original image information and the most edge points of the target image;

[0068] S4: transforming the original image into the target image in segments according to the inverse transformation matrix;

[0069] S5: Printing the target image in sections.

[0070] When printing PCB, the PCB board is first placed on the printing platform of the printing device, and then the pattern to be printed is printed on the corresponding position of the PCB board using the original image sent to the printing device in advance. However, errors often occur when the PCB board is placed, such as deviations in the placement position and posture. In order to accurately print the pattern on the corresponding position of the printed PCB board even when there are placement errors, the image segmentation transformation inkjet printing method of this embodiment converts the original image into a target image with the same position or posture as the actual PCB board before printing. For example, Fig. 9 The original image on the left is converted to Fig. 9 The target image on the right.

[0071] Among them, the forward transformation matrix refers to the transformation matrix that converts the original image into the target image, and the inverse transformation matrix refers to the transformation matrix that converts the target image into the original image.

[0072] like Figure 2 As shown, before converting the original image into the target image, multiple positioning points 3 can be set on the original image 1, and positioning points corresponding to the positioning points of the original image are set on the printing object. After the printing object is placed on the printing platform, the positioning points are used as actual positioning points, and the actual positioning points are translated to obtain the positioning points of the target image 2. The forward transformation matrix is ​​solved based on the positioning points 3 of the original image 1 and the actual positioning points 3. The specific solution method is:

[0073] Let AX = b

[0074] Then X=((A t A) -1 A t b)) t

[0075] Where A is the matrix composed of the coordinates of the original image's positioning points (u0, v0), (u1, v1), (u2, v2), ... (vn, un), X is the forward transformation matrix, and b is the matrix composed of the target image's positioning points (x0, y0), (x1, y1), (x2, y2), ... (xn, yn).

[0076] in

[0077] In addition to the corresponding positioning points between the original image and the target image, the corresponding forward transformation matrix can also be solved based on the transformation information, such as the scaling from the original image to the target image, the rotation angle from the original image to the target image, and other information.

[0078] The original image information includes the coordinates of the most edge points of the original image, as shown in FIG3 . The most edge points of the original image may be four corner points of the original image. The step S2: determining the most edge points, width and height of the target image according to the original image information and the forward transformation matrix also includes:

[0079] S21: Perform a forward transformation on the coordinates of the most edge point of the original image according to the forward transformation matrix to obtain the most edge point of the target image;

[0080] S22: determining the minimum outer bounding positive moment of the target image according to the most edge point of the target image;

[0081] S23: Determine the outermost point, width and height of the target image according to the minimum outer bounding positive moment of the target image.

[0082] After obtaining the forward transformation matrix, forward transformation is performed on each edge point of the original image to obtain the edge point of the target image. For example, the four corner points of the original image are used as the four edge points of the original image (see Figure 3 ), the coordinate value of each edge point (u, v) is composed of the u coordinate value and the v coordinate value. The coordinate values ​​of the four edge points of the original image are (0, 0), (-1, 0), (-1, -1), (0, -1) respectively. Let the vector composed of the u coordinate values ​​of the four edge points of the original image be srcP.u, the vector composed of the v coordinate values ​​be srcP.v, the vector composed of the x coordinate values ​​of the four edge points of the target image be srcP.x, the vector composed of the y coordinate values ​​be srcP.y, and the forward transformation matrix be X, then after transformation

[0083] dstP.x=X(0,0)*srcP.u+X(0,1)*srcP.v+X(0,2)

[0084] dstP.y=X(1,0)*srcP.x+X(1,1)*srcP.y+X(1,2)

[0085] X(i,j) represents the value of the i-th row and j-th column.

[0086] in

[0087] like Figure 4 As shown, according to the transformed edge point, the corresponding minimum outer bounding square 4 can be determined. The minimum outer bounding square 4 refers to the smallest rectangle that can surround the image.

[0088] The upper left corner point P_tl(x a ,y a )=(min(x),min(y))

[0089] The right upper corner point P_tl(x b ,y b )=(max(x),max(y))

[0090] The width and height of the minimum outer bounding square 4 are the width and height of the transformed target image.

[0091] The width of the target image w = x b -x a , the height of the target image h = y b -y a .

[0092] Where min(x) represents the minimum x-coordinate value of the transformed edge point coordinates, min(y) represents the minimum y-coordinate value of the transformed edge point coordinates, max(x) represents the maximum x-coordinate value of the transformed edge point coordinates, and max(y) represents the maximum y-coordinate value of the transformed edge point coordinates.

[0093] like Figure 4 and Figure 5 As shown, the edge points of the target image refer to the four corner points of the target image. The original image information includes the coordinates of the edge points of the original image. S3: solving the inverse transformation matrix according to the original image information and the edge points of the target image includes:

[0094] S31: performing a translation transformation on the target image to align with the origin according to the outermost point of the target image to obtain the coordinates of the outermost point of the aligned target image;

[0095] S32: Determine an inverse transformation matrix according to the coordinates of the most edge points of the aligned target image and the coordinates of the most edge points of the original image.

[0096] This embodiment offsets the coordinates of the outermost point of the target image obtained after the forward transformation. The offset value is the coordinate value of the upper left corner of the minimum outermost normal moment of the transformed outermost point, so that the transformed outermost point is aligned with the origin, and the coordinates of the aligned outermost point of the target image after the transformation are obtained.

[0097] At this time, the aligned edge points of the target image and the edge points of the original image are used as positioning points to solve the inverse transformation matrix from the edge points of the aligned target image to the edge points of the original image. For the specific solution process, please refer to the solution process of the forward transformation matrix, which will not be repeated here.

[0098] like Figure 6 As shown, in this embodiment, the step S4: converting the original image into a target image by segmentation according to the inverse transformation matrix further includes:

[0099] S41: dividing the original image into a plurality of sub-original images according to the inverse transformation matrix, each sub-original image corresponds to a sub-target image, and the target image includes the sub-target image;

[0100] S42: Allocating a first storage area for storing data of one of the sub-original images and a second storage area for storing data of the sub-target image corresponding to the sub-original image;

[0101] S43: Read the data of the sub-original image into the first storage area;

[0102] S44: converting the data of the sub-original image into data of a corresponding sub-target image and storing the data in a second storage area;

[0103] S45: Repeat steps S43 to S44 until the conversion of data of all sub-original images is completed.

[0104] The present embodiment first divides the original image into a plurality of sub-original images, and then converts the divided sub-original images into sub-target images one by one. When all sub-target images are converted, these sub-target images can form a completed target image. In order to save storage resources, the present embodiment converts only one sub-original image at a time, so that in the conversion process, only storage resources that can accommodate one sub-original image and one sub-target image need to be provided. After the current sub-original image is converted into the sub-target image, the current storage resources can be released for the conversion of the next sub-original image. The present embodiment applies two storage areas, namely the first storage area and the second storage area, wherein the first storage area is used as a memory buffer for storing the sub-original image to be converted, and the second storage area is used as a memory buffer for storing the target image of the data of the sub-target image obtained after the sub-original image is converted.

[0105] like Figure 8 As stated, Figure 8The left rectangle in the figure represents the target image, and the right rectangle represents the original image. The storage scheme of the conversion process of this embodiment is to convert one sub-original image at a time, that is, extract the data of a sub-original image from the print file and store it in the first storage area, then convert the sub-original image, store the converted sub-target image in the second storage area, and then the printing device extracts the print data from the second storage area for printing. In the conversion process of the sub-original image, the first storage area and the second storage area can be used repeatedly, so the storage capacity of the first storage area and the second storage area only needs to meet the conversion of a single sub-original image, and there is no need to provide a storage capacity that can meet the conversion of the entire original image. In specific implementation, the starting line 5 and the ending line 6 of the original image required for this transformation can be calculated based on the starting line and the ending line of the target image currently required. Then the data read from the file is cached in the first storage area applied in advance. Finally, the sub-original image is converted into a sub-target image by assigning the image data in the first storage area to the second storage area. The sub-original images are converted one by one in the above manner until all the sub-original images of the original image are converted into sub-target images. The specific assignment conversion process is:

[0106] The step S44 of converting the data of the sub-original image into data of the corresponding sub-target image and storing the data in the second storage area also includes:

[0107] S441: determining the corresponding coordinate positions of pixels at each coordinate position in the target image in the original image according to the inverse transformation matrix;

[0108] S442: Obtain the storage location of the sub-target image data corresponding to the pixel at each coordinate position in the sub-target image in the second storage area;

[0109] S443: Obtain the storage location of the sub-original image data corresponding to the pixels at each coordinate position of the sub-original image in the first storage area;

[0110] S443: determining a storage position in the first storage area corresponding to the storage position in the second storage area according to the corresponding coordinate position, the storage position of the sub-target image data in the second storage area, and the storage position of the sub-original image data in the first storage area;

[0111] S444: extracting the sub-original image data in the first storage area according to the corresponding storage position in the first storage area and performing data processing to obtain the sub-target image data, and storing the processed sub-target image data in the corresponding storage position in the second storage area.

[0112] In order to facilitate conversion, the data of the sub-original image is stored in the corresponding position of the first storage area according to the coordinate position of each pixel of the sub-original image in the original image. The specific conversion process is to convert the pixels of the sub-target image one by one. The data of the sub-target image is composed of the data corresponding to each pixel of the sub-target image. The storage position of the sub-target image data is determined according to the coordinate position of each pixel on the sub-target image, that is, the coordinate position of each pixel of the sub-target image on the sub-target image corresponds to the storage position of the corresponding sub-target image data.

[0113] Therefore, the conversion process is to first find the coordinate position of the sub-original image corresponding to each pixel in the sub-target image, and then find the storage position of the sub-original image data related to the coordinate value in the first storage area according to the coordinate value of the sub-original image, extract the data at the relevant storage position, and calculate the corresponding sub-target image data, and then store the calculated sub-target image in the corresponding storage position in the second storage area.

[0114] For example, first calculate the position of a certain pixel from the starting row to the ending row of the target image in the corresponding sub-original image, that is, the coordinate value of the sub-target image corresponding to the pixel point is transformed by the inverse transformation matrix and then rounded to the integer coordinate position. Then obtain the position of the point of the sub-target image in the second storage area, that is, x remains unchanged, y minus the size of the starting row (where x, y are the coordinate values ​​of the pixel point in the x direction and y direction on the sub-target image). Then calculate the position of the sub-original image corresponding to the middle position in the first storage area, that is, u remains unchanged, v minus the size of the starting row. Finally, the pixel value corresponding to the position in the first storage area is added to the corresponding position in the second storage area. In this way, the pixels of the original image are assigned values ​​one by one according to the above method until every pixel from the starting row to the ending row is traversed. Since the above pixel position is transformed into an inverse transformation when taking the value, it can be ensured that there is no situation where there is no corresponding value with the original image when the image is enlarged.

[0115] When the coordinate position of the original image corresponding to certain pixels obtained by the inverse transformation matrix is ​​not an integer, there is no definite storage position in the first storage area corresponding to the coordinate position. At this time, the sub-target image data can be calculated based on the data of the corresponding storage position in the first storage area corresponding to the integer coordinate positions around the non-integer coordinate position. At this time, the aforementioned extraction of the corresponding sub-original image data from the first storage area and processing to obtain the data of the sub-target image corresponding to each pixel is to extract the corresponding sub-original image data and then calculate the corresponding sub-target image data based on the extracted sub-original image data.

[0116] The specific calculation method can be a nearest neighbor interpolation algorithm, a bilinear interpolation algorithm, a cubic convolution interpolation algorithm, etc.

[0117] The nearest neighbor interpolation algorithm selects the grayscale value of the input pixel closest to the position it is mapped to as the interpolation result. For a two-dimensional image, the grayscale value of the nearest neighboring point among the four neighboring pixels around the sample point to be tested is taken as the pixel value of the sample point to be tested. For example, when the coordinate position of the original image corresponding to a certain pixel obtained by the inverse transformation matrix is ​​not an integer, the sub-original image data corresponding to the integer coordinate position closest to the non-integer coordinate position is taken as the data of the corresponding sub-target image.

[0118] Among them, the bilinear interpolation algorithm, the cubic convolution interpolation algorithm, and the cubic interpolation rule take the sub-original image data corresponding to multiple integer coordinate positions near the non-integer coordinate position as the interpolation input data, obtain the interpolated data according to a certain interpolation method, and then use the interpolated data as the sub-target image data.

[0119] Among them, bilinear interpolation is also called first-order interpolation. It takes three interpolations to get the final result. It is an improvement on the nearest neighbor interpolation method. First, first-order linear interpolation is performed in the two horizontal directions, and then first-order linear interpolation is performed in the vertical direction.

[0120] Among them, cubic convolution interpolation is also called bicubic interpolation, which is an improvement on bilinear interpolation. It not only takes into account the influence of the grayscale values ​​of the four directly adjacent pixels around it, but also takes into account the influence of their grayscale value change rate. This method uses the grayscale values ​​of 16 pixels near the sampling point for cubic interpolation calculation.

[0121] The segmented printing can be printing each sub-target image obtained by conversion. If the conversion speed is faster than the printing speed, the remaining sub-original images can be converted while the converted target images are continuously printed after the first sub-original image is converted.

[0122] Example 2

[0123] This embodiment is a further improvement on the basis of the embodiment 1. For the case where only storage resources for storing a sub-original image currently being converted and a sub-target image obtained after the conversion are applied for at one time in some examples of the embodiment 1, this embodiment further includes the following between S41: dividing the original image into a plurality of sub-original images according to the inverse transformation matrix, each sub-original image corresponds to a sub-target image, and the target image is composed of the sub-target images, and S42: applying for a first storage area for storing data of one of the sub-original images and a second storage area for storing data of the sub-target image corresponding to the sub-original image:

[0124] S410: Determine the maximum storage capacity C required to store a single sub-original image according to the number of rows N of the sub-target image, the inverse transformation matrix, the width of the original image, and the height of the target image.1 According to the number of rows N of the sub-target image and the width of the target image, the maximum storage capacity C required to store a single sub-target image is determined. 2 ;

[0125] In S42: applying for a first storage area for storing data of one of the sub-original images and a second storage area for storing data of the sub-target image corresponding to the sub-original image, the storage capacity of the applied first storage area is C 1 The storage capacity of the second storage area applied for is C 2 .

[0126] The number of rows N of the sub-target image can be set by the user, and the number of rows N of the sub-target image can be consistent with the number of rows of a segment printing performed by the printing device. Since the storage capacity required for the conversion of each sub-original image is not exactly the same, the present embodiment first calculates the storage capacity required for the conversion of each sub-original image before starting the image conversion, and finds the largest storage capacity, that is, the maximum storage capacity C required to store a single sub-original image. 1 and the maximum storage capacity C2 required to store a single sub-target image, and then directly apply for a storage capacity of C 1 and C2's storage resources, and the entire conversion process is satisfied by repeatedly using the requested storage resources. This can greatly reduce the number of storage resource applications, greatly reduce the number of memory applications and releases, and significantly improve the utilization efficiency of the system and storage resources.

[0127] The specific conversion process is:

[0128] S4111: Obtain the number of rows N of the sub-target image;

[0129] S4112: Calculating the maximum storage capacity required to store a single sub-target image according to the width of the target image and the number of rows N of the sub-target images;

[0130] Since N rows of sub-target image data need to be obtained each time, the maximum data memory block required for the transformed image is: N*the width of the target image.

[0131] S4113: Determine the end row and the start row of each sub-original image according to the number of rows N of the sub-target image and the inverse transformation matrix;

[0132] like Figure 8 ( Figure 8 The left rectangle represents the target image, and the right rectangle represents the original image), where the process of determining the end row and the start row of each sub-original image is as follows:

[0133] S41131: Obtain the four edge coordinate points of rows t*N to (t+1)*N of the target image, where t is a positive integer.

[0134] S41132: Perform an inverse transformation matrix transformation on the four edge coordinate points to obtain the inverse transformed edge coordinate points.

[0135] S41133: Obtain the minimum outer bounding normal moment of the most edge coordinate point of the inverse transformation, and round the pixel position to the nearest integer. The coordinate value of the upper left corner of the minimum outer bounding normal moment in the v direction is the starting row srcLs read from the original image for this transformation, and the coordinate value of the lower right corner of the minimum outer bounding normal moment in the v direction is the ending row srcLe read from the original image for this transformation.

[0136] S4114: Calculate the storage capacity required for reading each sub-original image according to the width of the original image, the height of the target image, and the end row and the start row of each sub-original image;

[0137] Assume the original image width is W, height is H, and record the maximum data memory block requirement as (srcLe-srcLs)*W

[0138] The required storage capacity of each sub-original image is calculated one by one according to the above method until the number of remaining rows is less than N, and the required storage capacity of the last original image is calculated in the range of t*N~h.

[0139] S4115: Select the largest one from the memory values ​​required to read each sub-original image as the maximum storage capacity required to obtain a single sub-original image.

[0140] Example 3

[0141] See also Fig. 9 The embodiment of the present invention provides an inkjet printing device for image segmentation conversion, the device comprising:

[0142] A forward transformation matrix solving module, wherein the forward transformation matrix solving module is used to solve the forward transformation matrix according to the original image information and the positioning point data and / or the conversion information;

[0143] A target image parameter determination module, the target image parameter determination module is used to determine the edge point, width and height of the target image according to the original image information and the forward transformation matrix;

[0144] An inverse transformation matrix solving module, wherein the inverse transformation matrix solving module is used to solve the inverse transformation matrix according to the original image information and the most edge point of the target image;

[0145] The original image segmentation conversion module is used to convert the original image segmentation into the target image according to the inverse transformation matrix;

[0146] The target image segment printing module is used to print the target image in segments.

[0147] The inkjet printing device for image segmentation conversion also includes a maximum storage capacity determination module, which is used to determine the maximum storage capacity C required to store a single sub-original image according to the number of rows N of the sub-target image, the inverse transformation matrix, the width of the original image and the height of the target image. 1 According to the number of rows N of the sub-target image and the width of the target image, the maximum storage capacity C required to store a single sub-target image is determined. 2 .

[0148] The target image segmentation conversion module also includes:

[0149] A sub-original image division submodule, the sub-original image division submodule is used to divide the original image into a plurality of sub-original images according to the inverse transformation matrix, each sub-original image corresponds to a sub-target image, and the target image is composed of the sub-target images;

[0150] a storage area application submodule, the storage area application submodule being used to apply for a first storage area for storing data of one of the sub-original images and a second storage area for storing data of a sub-target image corresponding to the sub-original image;

[0151] A sub-original image data reading sub-module, wherein the sub-original image data reading sub-module is used to read the data of the sub-original image into the first storage area;

[0152] A sub-target image data storage sub-module, the sub-target image data storage sub-module is used to convert the data of the sub-original image into data of a corresponding sub-target image and store it in a second storage area;

[0153] The repeated execution submodule is used to repeatedly execute the functions of the sub-original image data reading submodule and the sub-target image data storage submodule until the conversion of the data of all sub-original images is completed.

[0154] Example 4

[0155] In addition, combined Figure 1 The inkjet printing method for image segmentation conversion according to the embodiment of the present invention described above can be implemented by an inkjet printing device for image segmentation conversion. Fig.11 A schematic diagram of the hardware structure of an inkjet printing device for image segmentation conversion provided by an embodiment of the present invention is shown.

[0156] The inkjet printing device for image segment conversion may include a processor 401 and a memory 402 storing computer program instructions.

[0157] Specifically, the processor 401 may include a central processing unit (CPU), or an application specific integrated circuit (ASIC), or may be configured to implement one or more integrated circuits of the embodiment of the present invention.

[0158] Memory 402 may include a large capacity memory for data or instructions. For example, but not limitation, memory 402 may include a hard disk drive (HDD), a floppy disk drive, a flash memory, an optical disk, a magneto-optical disk, a magnetic tape, or a universal serial bus (USB) drive or a combination of two or more of these. In appropriate cases, memory 402 may include a removable or non-removable (or fixed) medium. In appropriate cases, memory 402 may be inside or outside a data processing device. In a specific embodiment, memory 402 is a non-volatile solid-state memory. In a specific embodiment, memory 402 includes a read-only memory (ROM). In appropriate cases, the ROM may be a mask-programmed ROM, a programmable ROM (PROM), an erasable PROM (EPROM), an electrically erasable PROM (EEPROM), an electrically rewritable ROM (EAROM) or a flash memory or a combination of two or more of these.

[0159] The processor 401 reads and executes computer program instructions stored in the memory 402 to implement any one of the data addressing methods for random area printing in the above embodiments.

[0160] In one example, the inkjet printing device for image segment conversion may also include a communication interface 403 and a bus 410. Fig.11 As shown, the processor 401, the memory 402, and the communication interface 403 are connected via a bus 410 and communicate with each other.

[0161] The communication interface 403 is mainly used to implement the communication between the modules, devices, units and / or equipment in the embodiment of the present invention.

[0162] Bus 410 includes hardware, software or both, and the components for the output of small multiples of ink volume are coupled to each other. For example, but not limitation, bus may include accelerated graphics port (AGP) or other graphics bus, enhanced industrial standard architecture (EISA) bus, front-side bus (FSB), hypertransmission (HT) interconnection, industrial standard architecture (ISA) bus, infinite bandwidth interconnection, low pin count (LPC) bus, memory bus, micro channel architecture (MCA) bus, peripheral component interconnection (PCI) bus, PCI-Express (PCI-X) bus, serial advanced technology attachment (SATA) bus, video electronics standard association local (VLB) bus or other suitable bus or two or more of these combinations. In appropriate cases, bus 410 may include one or more buses. Although the embodiment of the present invention describes and shows a specific bus, the present invention considers any suitable bus or interconnection.

[0163] Example 5

[0164] In addition, in combination with the inkjet printing method for image segmentation conversion in the above embodiments, the embodiments of the present invention can provide a computer-readable storage medium for implementation. The computer-readable storage medium stores computer program instructions; when the computer program instructions are executed by a processor, any inkjet printing method for image segmentation conversion in the above embodiments is implemented.

[0165] The above is a detailed introduction to the inkjet printing method, device, equipment and storage medium for image segmentation conversion provided by the embodiments of the present invention.

[0166] It should be clear that the present invention is not limited to the specific configuration and processing described above and shown in the figures. For the sake of simplicity, a detailed description of the known method is omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of the present invention is not limited to the specific steps described and shown, and those skilled in the art can make various changes, modifications and additions, or change the order between the steps after understanding the spirit of the present invention.

[0167] The functional blocks shown in the above-described block diagram can be implemented as hardware, software, firmware or a combination thereof. When implemented in hardware, it can be, for example, an electronic circuit, an application specific integrated circuit (ASIC), appropriate firmware, a plug-in, a function card, etc. When implemented in software, the elements of the present invention are programs or code segments that are used to perform the required tasks. The program or code segment can be stored in a machine-readable medium, or transmitted on a transmission medium or a communication link by a data signal carried in 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, optical fiber media, radio frequency (RF) links, etc. The code segment can be downloaded via a computer network such as the Internet, an intranet, etc.

[0168] It should also be noted that the exemplary embodiments mentioned in the present invention describe some methods or systems based on a series of steps or devices. However, the present invention 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 from the embodiments, or several steps can be performed simultaneously.

[0169] The above is only a specific implementation of the present invention. Those skilled in the art can clearly understand that for the convenience and simplicity of description, the specific working process of the system, module and unit described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here. It should be understood that the protection scope of the present invention is not limited to this. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed by the present invention, and these modifications or replacements should be covered within the protection scope of the present invention.

Claims

1. Inkjet printing method for image segmentation conversion, It is characterized in that The method is used to convert an original image into a target image for printing, including the following steps: S1: solving a forward transformation matrix according to original image information and actual positioning point data and / or conversion information; S2: Determine the edge point, width and height of the target image according to the original image information and the forward transformation matrix; S3: solving an inverse transformation matrix according to the original image information and the most edge points of the target image; S4: transforming the original image into the target image in segments according to the inverse transformation matrix; S5: Printing the target image in sections; Among them, the forward transformation matrix refers to the transformation matrix that converts the original image into the target image, and the inverse transformation matrix refers to the transformation matrix that converts the target image into the original image; The original image information includes the coordinates of the outermost points of the original image; S4: converting the original image into a target image by segmentation according to the inverse transformation matrix, comprises the following steps: S41: dividing the original image into a plurality of sub-original images according to the inverse transformation matrix, each sub-original image corresponds to a sub-target image, and the target image includes the sub-target image; S42: Allocating a first storage area for storing data of a sub-original image and a second storage area for storing data of a sub-target image corresponding to the sub-original image; S43: Read the data of the sub-original image into the first storage area; S44: converting the data of the sub-original image into data of a corresponding sub-target image and storing the data in a second storage area; S45: Repeat steps S43 to S44 until the conversion of data of all sub-original images is completed.

2. The inkjet printing method for image segmentation conversion according to claim 1, It is characterized in that The step S44: converting the data of the sub-original image into the data of the corresponding sub-target image and storing the data in the second storage area comprises the following steps: S441: determining the corresponding coordinate positions of pixels at each coordinate position in the target image in the original image according to the inverse transformation matrix; S442: Obtain the storage location of the sub-target image data corresponding to the pixel at each coordinate position in the sub-target image in the second storage area; S443: Obtain the storage location of the sub-original image data corresponding to the pixels at each coordinate position of the sub-original image in the first storage area; S444: determining a storage position in the first storage area corresponding to the storage position in the second storage area according to the corresponding coordinate position, the storage position of the sub-target image data in the second storage area, and the storage position of the sub-original image data in the first storage area; S445: extracting the sub-original image data in the first storage area according to the corresponding storage position in the first storage area and performing data processing to obtain the sub-target image data, and storing the processed sub-target image data in the corresponding storage position in the second storage area.

3. The inkjet printing method for image segmentation conversion according to claim 1, It is characterized in that Between S41 and S42 include: S410: Determine the maximum storage capacity C required to store a single sub-original image according to the number of rows N of the sub-target image, the inverse transformation matrix, the width of the original image, and the height of the target image. 1； According to the number of rows N of the sub-target image and the width of the target image, the maximum storage capacity C required to store a single sub-target image is determined. 2 ; In S42, the storage capacity of the allocated first storage area is C 1 The storage capacity of the second storage area applied for is C 2 .

4. The inkjet printing method for image segmentation conversion according to claim 3, It is characterized in that S410: Determine the maximum storage capacity C required to store a single sub-original image according to the number of rows N of the sub-target image, the inverse transformation matrix, the width of the original image, and the height of the target image. 1 According to the number of rows N of the sub-target image and the width of the target image, the maximum storage capacity C required to store a single sub-target image is determined. 2 , including the following steps: S4111: Obtain the number of rows N of the sub-target image; S4112: Calculating the maximum storage capacity required to store a single sub-target image according to the width of the target image and the number of rows N of the sub-target images; S4113: Determine the end row and the start row of each sub-original image according to the number of rows N of the sub-target image and the inverse transformation matrix; S4114: Calculate the storage capacity required for reading each sub-original image according to the width of the original image, the height of the target image, and the end row and the start row of each sub-original image; S4115: Select the largest one from the memory values ​​required to read each sub-original image as the maximum storage capacity required to obtain a single sub-original image.

5. The inkjet printing method for image segmentation conversion according to any one of claims 1 to 4, It is characterized in that S2: determining the edge point, width and height of the target image according to the original image information and the forward transformation matrix, comprises the following steps: S21: Perform a forward transformation on the coordinates of the most edge point of the original image according to the forward transformation matrix to obtain the most edge point of the target image; S22: determining the minimum outer bounding positive moment of the target image according to the most edge point of the target image; S23: Determine the outermost point, width and height of the target image according to the minimum outer bounding positive moment of the target image.

6. The inkjet printing method for image segmentation conversion according to any one of claims 1 to 4, It is characterized in that The S3 includes: S31: performing a translation transformation on the target image to align with the origin according to the outermost point of the target image to obtain the coordinates of the outermost point of the aligned target image; S32: Determine an inverse transformation matrix according to the coordinates of the most edge points of the aligned target image and the coordinates of the most edge points of the original image.

7. Inkjet printing device for image segmentation conversion, It is characterized in that include: A forward transformation matrix solving module, wherein the forward transformation matrix solving module is used to solve the forward transformation matrix according to the original image information and the actual positioning point data and / or the conversion information; A target image parameter determination module, the target image parameter determination module is used to determine the edge point, width and height of the target image according to the original image information and the forward transformation matrix; An inverse transformation matrix solving module, wherein the inverse transformation matrix solving module is used to solve the inverse transformation matrix according to the original image information and the most edge point of the target image; The original image segmentation conversion module is used to convert the original image segmentation into the target image according to the inverse transformation matrix; A target image segment printing module, the target image segment printing module is used to print the target image in segments; Among them, the forward transformation matrix refers to the transformation matrix that converts the original image into the target image, and the inverse transformation matrix refers to the transformation matrix that converts the target image into the original image; The original image information includes the coordinates of the outermost points of the original image; The step of converting the original image into a target image by segmentation according to the inverse transformation matrix comprises the following steps: S41: dividing the original image into a plurality of sub-original images according to the inverse transformation matrix, each sub-original image corresponds to a sub-target image, and the target image includes the sub-target image; S42: Allocating a first storage area for storing data of a sub-original image and a second storage area for storing data of a sub-target image corresponding to the sub-original image; S43: Read the data of the sub-original image into the first storage area; S44: converting the data of the sub-original image into data of a corresponding sub-target image and storing the data in a second storage area; S45: Repeat steps S43 to S44 until the conversion of data of all sub-original images is completed.

8. Inkjet printing equipment for image segmentation conversion, It is characterized in that The method comprises at least one processor, at least one memory and computer program instructions stored in the memory, and when the computer program instructions are executed by the processor, the method according to any one of claims 1 to 6 is implemented.

9. A storage medium having computer program instructions stored thereon, It is characterized in that When the computer program instructions are executed by a processor, the method according to any one of claims 1 to 6 is implemented.

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