JP2009239530A - Correction value calculating method and printing method - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To calculate a correction value for suppressing the non-uniformity of density recognizable by a human being. <P>SOLUTION: A correction value acquiring method includes: a pattern forming step of forming a pattern constituted of a plurality of dot streams by forming on a medium the dot streams corresponding to data of pixel streams in print image data of a resolution matched to a printing resolution; a reading step of acquiring read data by reading an image of the pattern by means of a scanner; a filter applying step of applying a low-pass filter to the read data; and a correction value calculating step of calculating a correction value for correcting data of the pixel streams in the print image dat, for each pixel stream, respectively, in accordance with the read data to which the low-pass filter has been applied. <P>COPYRIGHT: (C)2010,JPO&INPIT

Description

  The present invention relates to a correction value calculation method and a printing method.

  Streaky density unevenness may occur in an image (printed image) printed on paper by an inkjet printer. The cause of this density unevenness is considered to be that a large number of dot rows constituting a print image are not formed as ideal due to the influence of the head manufacturing error, and the density of each dot row can be changed depending on the size of the dots. .

  Therefore, by correcting the image data (print image data) before printing so that the pixels of the darkly printed portion are lightly corrected and the pixels of the lightly printed portion are darkly corrected, the density unevenness of the printed image is corrected. (See Patent Document 1).

  Specifically, first, the printer prints a test pattern having a predetermined print resolution (for example, 720 × 720 dpi) based on print image data having a certain gradation value. The test pattern is read by the scanner, and the density of the row-like regions having a width corresponding to the printing resolution (for example, a width of 1/720 inch) is detected so as to match with the dot rows constituting the test pattern. Then, a correction value is calculated for each dot row in accordance with the difference between the detected density and the target density. The calculated correction value is stored in the printer memory.

Thereafter, when the printer prints an image under the user, the resolution of the print image data is converted in accordance with the print resolution. As a result, the pixel row on the print image data has a one-to-one correspondence with the dot row on the print image. It becomes a relationship. At this time, the gradation value of each pixel row on the print image data is corrected based on the correction value of the corresponding dot row. As a result, the pixel array printed dark is corrected lightly, and the pixel array printed light is corrected dark. When printing is performed based on the corrected print image data, the dot occurrence rate of each dot row is corrected according to the correction result of the gradation value of each pixel row. The density unevenness of the printed image is reduced by the correction.
JP 2005-206991 A

When a human sees a printed image, the person may not be able to recognize even if there is uneven density of high frequency components in the printed image. Further, when there is density unevenness of a frequency component in a predetermined band in the print image, a human recognizes that the print image has density unevenness.
When correcting density unevenness in a printed image, it is sufficient to correct density unevenness recognized by humans, and it is necessary to correct even density unevenness that is not recognized by humans (for example, density unevenness of high frequency components). There is no.
It is an object of the present invention to correct density unevenness that is visible to humans.

A main invention for achieving the above object is to form a pattern composed of a plurality of dot rows by forming dot rows on a medium in accordance with pixel row data of print image data having a resolution matching the print resolution. A pattern forming step to form, a reading step of reading an image of the pattern by a scanner to obtain read data, a filter applying step of applying a low-pass filter to the read data, and the application of the low-pass filter A correction value acquisition method comprising: a correction value calculation step for calculating, for each pixel column, a correction value for correcting the data of each pixel column of the print image data in accordance with the read data.
Other features of the present invention will become apparent from the description of the present specification and the accompanying drawings.

=== Summary of disclosure ===
At least the following matters will become clear from the description of the present specification and the accompanying drawings.

A pattern forming step for forming a pattern composed of a plurality of dot rows by forming dot rows on a medium according to pixel row data of print image data having a resolution that matches the print resolution, and the pattern by a scanner Each of the print image data according to the reading step of reading the image of the image and acquiring the read data, the filter applying step of applying a low pass filter to the read data, and the read data after the application of the low pass filter A correction value acquisition method having a correction value calculation step for calculating a correction value for correcting data of a pixel column for each pixel column is clarified.
According to such a correction value acquisition method, it is possible to acquire a correction value that can correct density unevenness visually recognized by humans.

  After the reading step, an inverse filter process for removing the influence of the scanner from the read data is performed, and in the filter applying step, the low-pass filter is applied to the read data after the inverse filter process. It is desirable. Thereby, a correction value that is not affected by the scanner can be calculated.

In the filter applying step, it is preferable that a weighting function is convolved with the read data, and the weighting function corresponds to an impulse response of a visual filter having a predetermined frequency characteristic. Thereby, it is possible to acquire a correction value that can correct density unevenness visually recognized by humans.

  In the filter applying step, a weight function is convolved with the read data, and the weight function is a spread function in which a positive range is set wider than a range corresponding to the width of the dot row. desirable. Thereby, it is possible to acquire a correction value that can correct density unevenness visually recognized by humans.

  In the filter applying step, a low pass filter is applied to the read data having a resolution higher than the print resolution, and in the correction value calculating step, the read data after applying the low pass filter is converted into the print resolution. Preferably, the correction value is calculated according to the read data after the resolution conversion. Thereby, a highly accurate correction value can be calculated.

  In the reading step, a representative value of each pixel column is calculated from the two-dimensional image data of the pattern, and the one-dimensional read data is constituted by the representative value of each pixel column. Preferably, a low pass filter is applied to the read data. Thereby, the load of the arithmetic processing for calculating a correction value can be reduced.

  In the filter applying step, a low-pass filter is applied to the read data that is two-dimensional image data, and in the correction value calculating step, a representative value of each pixel column is calculated from the read data after the low-pass filter is applied. Preferably, the correction value is calculated according to the representative value of each pixel column. Even with such processing, it is possible to obtain a correction value that can correct density unevenness visually recognized by humans.

A pattern forming step for forming a pattern composed of a plurality of dot rows by forming dot rows on a medium according to pixel row data of print image data having a resolution that matches the print resolution, and the pattern by a scanner Each of the print image data according to the reading step of reading the image of the image and acquiring the read data, the filter applying step of applying a low pass filter to the read data, and the read data after the application of the low pass filter A correction value calculation step for calculating a correction value for correcting the pixel column data for each pixel column, and each pixel data of the print image data having a resolution matching the print resolution corresponds to the pixel column of the pixel data. An image forming step is performed in which an image is formed according to the corrected pixel data and according to the corrected pixel data. An image forming method and a flop reveals.
According to such an image forming method, it is possible to correct the density unevenness visually recognized by humans and form an image.

=== Explanation of terms ===
First, the meanings of terms used in describing this embodiment will be described.
FIG. 1 is an explanatory diagram of terms.

A “printed image” is an image printed on paper. A print image of an ink jet printer is composed of countless dots formed on paper.
A “raster line” is a row of dots arranged in the direction in which the head and paper move relative to each other (movement direction). In the case of a line printer as in the embodiments described later, “raster line” means a row of dots arranged in the paper transport direction. On the other hand, in the case of a serial printer that prints with a head mounted on a carriage, “raster line” means a row of dots arranged in the carriage movement direction. A print image is formed by arranging a large number of raster lines in a direction perpendicular to the moving direction. As shown in the figure, the raster line at the nth position is referred to as an “nth raster line”.

“Image data” is data indicating a two-dimensional image. In an embodiment described later, there are 256 gradation image data, 4 gradation image data, and the like.
“Print image data” is image data used when printing an image on paper. When the printer controls dot formation with four gradations (large dot, medium dot, small dot, no dot), the four gradation print image data indicates the formation state of dots constituting the print image. .
“Read image data” is image data read by a scanner.

A “pixel” is a minimum unit that constitutes an image. An image is formed by arranging these pixels two-dimensionally. Mainly means a pixel on the image data.
A “pixel column” is a column of pixels arranged in a predetermined direction on image data. As shown in the figure, the nth pixel column is referred to as an “nth pixel column”.

“Pixel data” is data indicating the gradation value of a pixel. The image data is composed of a large number of pixel data. “Pixel data” is sometimes referred to as “pixel gradation value”. In the case of four-tone print image data, each pixel data is 2-bit data, and indicates the dot formation state (large dot, medium dot, small dot, no dot) of a certain pixel.
“Pixel column data” is pixel data of a plurality of pixels included in a pixel column. A raster line is formed by forming dots according to the pixel data in the pixel column data. The “pixel column data” is sometimes referred to as “pixel column gradation value”.

  A “pixel area” is an area on paper corresponding to a pixel on image data. For example, when the resolution of the print image data is 720 × 720 dpi, the “pixel area” is a square area having one side of 1/720 inch.

  A “row area” is an area on paper corresponding to a pixel row. For example, when the resolution of the print image data is 720 × 720 dpi, the row area is an elongated area having a width of 1/720 inch. The “row area” may mean an area on paper corresponding to a pixel line on print image data, or may mean an area on paper corresponding to a pixel line on read image data. In the lower right part of the figure, a row region in the former case is shown. The “row area” in the former case is also a raster line formation target position. The “row area” in the latter case is also a measurement position (measurement range) on the paper where the pixel row on the read image data is read. In other words, the position on the paper where the image (image piece) indicated by the pixel row exists. But there is. As shown in the figure, the row region at the nth position is referred to as an “nth row region”. The nth row region is the target position for forming the nth raster line.

  “Image piece” means a part of an image. On the image data, an image indicated by a certain pixel row is an “image piece” of the image indicated by the image data. In the print image, an image represented by a certain raster line is an “image piece” of the print image. In the print image, an image represented by color development in a certain row region also corresponds to an “image piece” of the print image.

Incidentally, in the lower right of FIG. 1, the positional relationship between the pixel region and the dots is shown. As a result of the deviation of the second raster line from the second row region due to the influence of the head manufacturing error, the density of the second row region becomes light. Further, in the fourth row region, the density of the fourth row region becomes light as a result of the dot becoming smaller due to the influence of the head manufacturing error. Since it is necessary to explain such density unevenness and the density unevenness correction method, in this embodiment, the meaning and relationship of “raster line”, “pixel column”, “column region”, and the like are described along the above contents. is doing.
However, the meanings of general terms such as “image data” and “pixel” may be appropriately interpreted in accordance with not only the above description but also common technical common sense.

=== Configuration of Printer ===
FIG. 2 is a block diagram of the overall configuration of the printer 1. FIG. 3 is a perspective view for explaining the conveyance process and the dot formation process of the printer 1.

The printer 1 includes a transport unit 20, a head unit 40, a detector group 50, and a controller 60. The printer 1 that has received the print data from the computer 110 as an external device controls each unit (the transport unit 20 and the head unit 40) by the controller 60. The controller 60 controls each unit based on the print data received from the computer 110 and prints an image on paper. The situation in the printer 1 is monitored by a detector group 50, and the detector group 50 outputs a detection result to the controller 60. The controller 60 controls each unit based on the detection result output from the detector group 50.

  The transport unit 20 is for transporting a medium (for example, paper S) in a predetermined direction (hereinafter referred to as a transport direction). The transport unit 20 includes an upstream roller 22A and a downstream roller 22B, and a belt 24. When a conveyance motor (not shown) rotates, the upstream roller 22A and the downstream roller 22B rotate, and the belt 24 rotates. The fed paper S is conveyed by the belt 24 to a printable area (area facing the head). When the belt 24 transports the paper S, the paper S moves in the transport direction with respect to the head unit 40. The paper S that has passed through the printable area is discharged to the outside by the belt 24. The paper S being conveyed is electrostatically attracted or vacuum attracted to the belt 24.

  The head unit 40 is for ejecting ink onto the paper S. The head unit 40 ejects ink onto the paper S being conveyed, thereby forming dots on the paper S and printing an image on the paper S. The printer 1 of this embodiment is a line printer, and the head unit 40 can form dots for the paper width at a time.

  FIG. 4 is an explanatory diagram of an arrangement of a plurality of heads on the lower surface of the head unit 40. As shown in the figure, a plurality of heads 41 are arranged in a staggered pattern along the paper width direction. In each head, a black ink nozzle row, a cyan ink nozzle row, a magenta ink nozzle row, and a yellow ink nozzle row are formed. Each nozzle row includes a plurality of nozzles that eject ink. The plurality of nozzles in each nozzle row are arranged at a constant nozzle pitch along the paper width direction. That is, a nozzle group corresponding to the paper width is constituted by the nozzle row of each head.

FIG. 5 is an explanatory diagram of the nozzle arrangement and the dot formation for simplified explanation. Here, in the head unit 40, it is assumed that a nozzle group having a predetermined nozzle pitch is configured by the nozzle row of each head. As shown in FIG. 4, the actual nozzle positions are different in the transport direction, but by changing the ejection timing, the nozzle groups composed of the nozzle rows of each head are arranged in a row as shown in FIG. Can be thought of as nozzles lined up in For the sake of simplicity, it is assumed that only the black ink nozzle group is provided. Further, to simplify the explanation, it is assumed that the nozzle group of black ink is composed of 24 nozzles. In the following description, the transport direction may be referred to as “X direction”, and the paper width direction may be referred to as “Y direction”.
This nozzle group is composed of 24 nozzles arranged in the paper width direction (y direction) at intervals of 1/720 inch. Each nozzle is numbered sequentially from the top in the figure.

  Note that the nozzle group forms 24 raster lines on the paper by intermittently ejecting ink droplets from each nozzle to the paper S being transported. For example, nozzle # 1 forms a first raster line on the paper, and nozzle # 2 forms a second raster line on the paper. Each raster line is formed along the transport direction (x direction).

  The detector group 50 includes a rotary encoder (not shown) that detects the amount of rotation of the upstream roller 22A. Based on the detection result of the rotary encoder, the transport amount of the paper S can be detected.

  The controller 60 is a control unit (control unit) for controlling the printer 1. The controller 60 includes an interface unit 61, a CPU 62, a memory 63, and a unit control circuit 64. The CPU 62 is an arithmetic processing unit for controlling the entire printer. The memory 63 is for securing an area for storing a program of the CPU 62, a work area, and the like, and includes storage elements such as a RAM and an EEPROM. The CPU 62 controls each unit via the unit control circuit 64 in accordance with a program stored in the memory 63. A correction value (described later) for correcting density unevenness is stored in the memory 63.

=== Correction Value Acquisition Processing of this Embodiment ===
<Overview>
In the inspection process of the printer manufacturing factory, for each manufactured printer, a correction value reflecting the density unevenness characteristic of each printer is calculated, and the correction value is stored in the memory of each printer.

  FIG. 6A to FIG. 6C are explanatory views of a state from when the test pattern is printed until the correction value is stored in the printer 1. The inspector connects the printer 1 to be inspected to the computer 110 in the factory, and the printer 1 prints a test pattern on the test sheet TS (see FIG. 6A). Next, the inspector sets the test sheet TS on the scanner 150, and the computer 110 acquires image data (read image data) of the test pattern (see FIG. 6B). Next, the computer 110 analyzes the test pattern image data to calculate a correction value, and stores the correction value in the memory of the printer 1 (see FIG. 6C).

  FIG. 7 is an explanatory diagram of how image data is analyzed. The read image data acquired by the computer 110 from the scanner 150 is data affected by the characteristics of the scanner. Therefore, the computer 110 obtains original image information by removing the characteristics of the scanner from the read image data, and corrects the read image data by applying a visual filter to the original image information. By this processing, the read image data acquired from the scanner can be corrected to image data indicating an image that a person feels when viewing the test pattern. Then, the computer 110 calculates a correction value for correcting density unevenness using the corrected read image data.

  7 may be applied to the two-dimensional read image data, but in the present embodiment described below, the processing of FIG. 7 is applied to the one-dimensional data (luminance distribution data). Yes.

<Before the correction value acquisition process>
First, the inspector connects the printer 1 to be inspected to the computer 110 in the factory (see FIG. 6A). A scanner 150 is also connected to the computer 110. The computer 110 includes a printer driver for printing the test pattern on the printer 1, a scanner driver for controlling the scanner 150, and image data (read image data) acquired from the scanner 150 by performing image processing and correcting values. A correction value acquisition program for calculating is installed in advance.

  Test printer image data (print image data) is prepared in advance in the printer driver. The print image data of this test pattern is image data having a resolution (720 × 720 dpi) that matches the print resolution.

FIG. 8A is an explanatory diagram of print image data of a test pattern. The test pattern is composed of five correction patterns. The five correction patterns are arranged along the x direction. Note that when the test pattern is printed, the x direction on the print image data is determined so that five correction patterns are arranged along the X direction (conveyance direction).
Each correction pattern has a different reference gradation value (reference gradation value). The reference gradation values of the correction patterns are 76, 102, 128, 153, and 179 in order from the first correction pattern on the right, and the darker the correction pattern is on the left. These five types of reference gradation values are represented by symbols Sa (= 76), Sb (= 102), Sc (= 128), Sd (= 153), and Se (= 179).

FIG. 8B is an explanatory diagram of print image data of the third correction pattern. Although the third correction pattern will be described here, the other correction patterns have substantially the same configuration.
The third correction pattern is configured by arranging 24 pixel rows in the y direction. Each pixel column is composed of several tens of pixels arranged in the x direction. Each pixel data represents a reference gradation value (here, Sc).

<Halftone processing (S101)>
FIG. 9 is a flowchart of correction value acquisition processing performed in the inspection process after manufacturing the printer.
First, the printer driver of the computer 110 converts the above-described 256-tone test pattern print image data (FIG. 8A) into 4-tone print image data by performing halftone processing on the test pattern print image data. (S101). On the four-tone print image data, each pixel column data indicates a dot formation state of each raster line.

<Print test pattern (S102)>
After the halftone process, the printer driver transmits print data including print image data of 4 gradations to the printer 1, and the printer 1 ejects ink droplets from each nozzle according to the 4 gradation pixel data in the print data. The test pattern is printed (S102, see FIG. 6A). In the present embodiment, the printer 1 prints a test pattern with a print resolution of 720 × 720 dpi.

  Due to head manufacturing errors, the dots constituting the print image do not all have the same size, and the raster line may be formed with a deviation from a predetermined row region. When the test pattern is viewed macroscopically, the test pattern includes a density unevenness, but becomes a print image as shown in print image data (FIG. 8A and FIG. 8B).

<Reading test pattern (S103)>
Next, the test pattern printed by the printer 1 is set on the scanner 150 by the inspector, and the scanner driver of the computer 110 causes the scanner 150 to read the test pattern (see S103, FIG. 6B). In this embodiment, the scanner 150 moves an image sensor by moving a line sensor (for example, a CCD sensor) along the main scanning direction in the sub-scanning direction. Direction) and the main scanning direction of the scanner 150 (line direction of the line sensor) are set in the scanner 150 so as to match. In this embodiment, the scanner 150 reads the test pattern at 1440 × 1440 dpi. That is, the scanner 150 reads the test pattern at a reading resolution higher than the print resolution of the test pattern, which is 720 × 720 dpi.

  The correction value acquisition program of the computer 110 extracts a test pattern portion from the image data (read image data) acquired from the scanner 150. Therefore, the read image data is rotated or trimmed as necessary. Etc. may be given.

  In the present embodiment, since the test pattern composed of 24 raster lines of 720 dpi is read at 1440 × 1440 dpi, the read image data is composed of about 48 pixel columns. The raster line interval is not accurate due to head manufacturing errors, and the movement of the line sensor of the scanner 150 in the sub-scanning direction is not always accurate. Therefore, when the number of pixel columns arranged in the y2 direction is exactly 48. Is not limited.

  Each pixel column data (a column of pixels arranged in the x direction) on the read image data indicates an image piece of a column region having a width of about 1/1440 inch on the paper on which the test pattern is printed. In other words, each pixel column data of the read image data indicates an image piece at a measurement position with an interval of about 1/1440 inch.

<Calculation of luminance distribution data (S104)>
Next, the correction value acquisition program of the computer 110 calculates the luminance distribution of each pixel column of each correction pattern on the read image data (S104). The luminance of each pixel column is considered to indicate the density of each column region on the printed test pattern.

  FIG. 10 is an explanatory diagram of how the luminance of each pixel column is calculated. On the left side of the figure, image data of the third correction pattern is shown. In the image data of the third correction pattern, pixel rows made up of a predetermined number of pixels are arranged in the y direction. The correction value acquisition program calculates an average luminance for each pixel column based on pixel data of a plurality of pixels arranged in the x direction, and uses the average luminance as a luminance of the pixel column (a representative value of the pixel column). . For example, the luminance of the first pixel column is calculated based on the pixel data in the thick line on the left side in the drawing. On the right side of FIG. 10, a graph of the luminance of each pixel column is shown. In the present embodiment, luminance distribution data like the graph on the right side of FIG. 10 is obtained for each correction pattern.

  In the following description, the luminance distribution data in the y direction of the correction pattern on the read image data is represented as Y (y). The correction value acquisition program acquires the luminance distribution data of each of the five correction patterns. The luminance distribution data corresponds to read data obtained by reading a pattern with the scanner 150.

<Removal of Scanner Characteristic (S105)>
The read image data acquired by the computer 110 from the scanner 150 is data deteriorated from the original image because it is affected by the characteristics of the scanner. For this reason, the luminance distribution data Y (y) calculated in S104 is also data deteriorated from the luminance distribution of the original image because it is affected by the characteristics of the scanner. Therefore, the correction value calculation program of the computer 110 removes the characteristics of the scanner from the luminance distribution data Y (y) according to the procedure shown in FIG. 7, and restores the luminance distribution data S (y) on the original image (S105). ).

First, the correction value calculation program Fourier transforms the luminance distribution data Y (y) to calculate luminance distribution data G (f) on the Fourier transform region (frequency region). Here, f represents a spatial frequency.
Next, the correction value calculation program multiplies G (f) by an inverse filter obtained from the MTF of the scanner 150 to calculate F (f). Assuming that the MTF of the scanner 150 is H (f), F (f) is obtained by the following equation.
F (f) = G (f) × H (f) / | H (f) | ²
Next, the correction value calculation program calculates S (y) by performing Fourier inverse transform on F (f). The calculated S (y) is estimated to be luminance distribution data on the original image. In other words, it can be estimated that S (y) is data obtained by removing the influence of the MTF of the scanner from the luminance distribution data Y (y) of the read image data.
The correction value acquisition program calculates S (y) from each luminance distribution data of the five correction patterns.

<Application of visual filter (S106)>
Next, the correction value calculation program applies a visual filter to the luminance distribution data S (y) on the original image (S106).

The Dooley VTF filter is adopted as the visual filter. When the spatial frequency in the x direction is fx (cycle / degree) and the spatial frequency in the y direction is fy, the VTF filter is expressed by the following equation.

FIG. 11 is a graph of Dooley's VTF filter. As shown in the figure, the VTF filter has a function of a low-pass filter that removes components in a high frequency band.
FIG. 12 is a graph of the impulse response h (y) of the filter having the frequency characteristics of FIG. The impulse response h (y) is a spread function that can be obtained by the inverse Fourier transform of the above equation. As will be described later, h (y) is used as a weighting function when performing convolution integration.

  Here, the filtering process is performed for a range in which h (y) is positive (between two points where h (t) = 0). The position where h (y) = 0 is approximately ± 37.5 μm, and the range where h (y) is positive is a width of approximately 75 μm. Since the interval between the pixel columns on the read image data is 1/1440 inch (17.64 μm), for example, when the i-th pixel column on the read image data is centered, as shown in FIG. The range from the −2 pixel column to the (i + 2) th pixel column is within the positive range of h (y). In other words, when the filter process is performed, it is affected by two adjacent pixel columns on both sides.

  Here, the value of h (y) at the position of the i-th pixel column is set to h0 (= h (0)), and the value of h (y) at the position of the i−1th pixel column and the i + 1th pixel column is It is assumed that h1 is the value of h (y) at the positions of the (i-2) th pixel column and the (i + 2) th pixel column.

First, the correction value acquisition program performs visual filter processing by convolving h (y) with luminance distribution data S (y) on the original image, and calculates Y ′ (y). For example, the luminance value Y ′ (i) after the filter processing of the i-th pixel column is calculated as follows.
Y ′ (i) = Y ′ (i−2) × h2 + Y ′ (i−1) × h1 + Y ′ (i) × h0 + Y ′ (i + 1) × h1 + Y ′ (i−2) × h2
It can be assumed that the calculated Y ′ (y) indicates a luminance distribution that is felt when a correction pattern is viewed by a human. For this reason, in the following description, Y ′ (y) is referred to as “visual luminance distribution data”.

By the way, the visual luminance distribution data can be calculated by another method. Hereinafter, a description will be given with reference to FIG.
It is the same as the above until G (f) is calculated by Fourier transforming the luminance distribution data Y (y), and F (f) is calculated by multiplying this G (f) by an inverse filter. . G ′ (f) can be calculated by applying the VTF filter of FIG. 11 to the F (f) in the Fourier transform domain (frequency domain). This G ′ (f) can also be calculated by applying a VTF filter to F (f) obtained by Fourier transforming the luminance distribution data S (y) on the restored original image. If G ′ (f) is subjected to inverse Fourier transform, visual luminance distribution data Y ′ (y) can be calculated.

Further, the correction value calculation program calculates two-dimensional luminance image data Y (x, y) from the two-dimensional read image data, and Fourier transforms Y (x, y), thereby obtaining 2 on the Fourier transform region. Dimensional image data G (u, v) can be calculated. If this image data G (u, v) is multiplied by an inverse filter, F (u, v) can be calculated, and if F (u, v) is inversely Fourier transformed, an original that is estimated as a two-dimensional original image is obtained. Image data S (x, y) can be calculated. If visual filter processing is performed on the two-dimensional original image data S (x, y), two-dimensional visual luminance data Y ′ (x, y) can be calculated. If the y-direction luminance distribution data is extracted from the two-dimensional visual luminance data Y ′ (x, y) as shown in FIG. 10, similar visual luminance distribution data Y ′ (y) is obtained. However, since it is necessary to perform Fourier transform and inverse Fourier transform on the two-dimensional data, the calculation process takes time compared to the calculation process for the one-dimensional data such as S104 to S106 of the present embodiment.
The correction value acquisition program calculates the respective visual luminance distribution data Y ′ (y) for each of the five correction patterns.

<Resolution conversion process (S107)>
The viewing luminance distribution data Y ′ (y) is considered to indicate a luminance distribution with a resolution of 1440 dpi. Therefore, the correction value acquisition program converts the resolution of the visible luminance distribution data Y ′ (y), and calculates 720 dpi luminance distribution data composed of 24 luminance data (S107). As a result, the 24 pieces of luminance data of the luminance distribution data indicate the luminance of the row region having a width (1/720 inch) corresponding to the print resolution. For example, the first luminance data after resolution conversion indicates the luminance of the first column region, the second luminance data indicates the luminance of the second column region, and the i-th luminance data indicates the luminance of the i-th column region. Can be considered.

  In the present embodiment, the visual luminance distribution data Y ′ (y) is calculated by applying a visual filter to the luminance distribution data S (y) having a resolution of 1440 dpi, and then the resolution is converted into luminance distribution data having a resolution of 720 dpi. ing. That is, after applying a visual filter to high resolution data, resolution conversion is performed to a low resolution. If the visual filter is applied after the luminance conversion data S (y) having the resolution of 1440 dpi is converted to the resolution of 720 dpi, the visual filter is applied to the data deteriorated by the resolution conversion. The value correction accuracy is poor.

  In the following description, the i-th luminance data of the luminance distribution data after resolution conversion is represented as Yi. Further, since the luminance data is provided for every five correction patterns, the subscripts a to b are added according to the reference gradation value to represent the luminance data. For example, the i-th luminance data of the luminance distribution data (luminance distribution data after resolution conversion) for the third correction pattern having the reference gradation value Sc is Yi_c.

<Calculation of Correction Value (S108)>
Next, the correction value acquisition program calculates a correction value ΔC for each pixel column based on the difference between the luminance data and the target luminance. Here, a method for calculating the correction value of the i-th pixel column will be described.

  13A and 13B are explanatory diagrams of the correction value ΔCi_b of the reference gradation value Sb of the i-th pixel column. In the figure, the horizontal axis indicates the gradation value indicated by the pixel data, and the vertical axis indicates the luminance value. In the drawing, the target luminance Yt_b at the reference gradation value Sb is shown. Here, the target luminance Yt_b is an average value of the 24 luminance data Y1_b to Y24_c obtained in S107.

  As shown in FIG. 13A, when the luminance Yi_b of the i-th pixel column of the reference gradation value Sb is smaller than the target luminance Yt_b, the correction value acquisition program uses linear interpolation based on the straight line BC to correspond to the target luminance Yt_b. The gradation value Sbt to be calculated is calculated. Then, the difference between the gradation value Sbt and the reference gradation value Sb is calculated as a correction value ΔCi_b. The correction value in this case is a positive value.

  As shown in FIG. 13B, when the luminance Yi_b of the i-th pixel column of the reference gradation value Sb is larger than the target luminance Yt_b, the correction value acquisition program uses the linear interpolation based on the straight line AB to correspond to the target luminance Yt_b. The gradation value Sbt to be calculated is calculated. Then, the difference between the gradation value Sbt and the reference gradation value Sb is calculated as a correction value ΔCi_b. The correction value in this case is a negative value.

  In this way, the correction value acquisition program calculates a correction value for each pixel column for each of the five types of reference gradation values. When calculating the correction value of the reference gradation value Sa, linear interpolation may be performed based on two points (0, 0) and (Sa, Yi_a). Further, when calculating the correction value of the reference gradation value Se, linear interpolation may be performed based on two points (Se, Yi_e) and (255, 255).

  In the present embodiment, five correction values respectively corresponding to five reference gradation values are calculated for one pixel column. Further, such a correction value is calculated for every 24 pixel columns.

  By the way, when the dot diameter is larger than 1/720 inch (when the dot diameter is larger than the pixel area), even if the pixel column data of 720 × 720 dpi print image data is corrected by the correction value (described later). The effect of the correction will extend over a wider area than the 1/720 inch wide row area. For this reason, when the dot diameter is larger than 1/720 inch, when calculating the correction value corresponding to a certain pixel column, the luminance information (1/720 inch) of the column region corresponding to the pixel column is calculated. It is considered desirable to reflect not only the luminance information of the width area) but also the luminance information in a wider range than the pixel column. On the other hand, in this embodiment, the positive range of the weighting function h (y) in S106 is wider than about 70 μm, which is the dot diameter (or raster line width). As a result, the luminance value after filtering is information reflecting luminance information in a wider range than the dot diameter. For this reason, the calculated correction value is for correcting the pixel column data of the print image data of 720 × 720 dpi (described later), but corrects the density in a range wider than the width of 1/720 inch. The value is suitable for.

  FIG. 14 is an explanatory diagram of a table of calculated correction values. Each of the calculated correction values is stored in the correction value table in association with the reference gradation value and the pixel column. In the figure, subscripts a to e are attached to the correction value ΔCi corresponding to the i-th pixel column for each reference gradation value.

<Storing correction values>
The correction value acquisition program of the computer 110 stores the correction value table in the memory 63 of the printer 1 (S109, see FIG. 6C).
In the above description, only black (black ink nozzle row) has been described, but correction values are similarly calculated for other colors (cyan, magenta, yellow) and stored in the memory of the printer 1. A correction value table is stored.
After the correction value table is stored in the memory in this way, the printer 1 is packed and shipped from the factory.

=== Print processing ===
<Processing before Density Unevenness Correction (S201 to S203)>
FIG. 15 is a flowchart of print processing performed by the printer driver under the user. A user who has purchased the printer 1 installs a printer driver (or a printer driver downloaded from the homepage of a printer manufacturer) stored in a CD-ROM included with the printer 1 in a computer. This printer driver is provided with code for causing a computer to execute each process in the drawing. The user connects the printer 1 to the computer.

First, the printer driver acquires a correction value table (see FIG. 14) stored in the memory of the printer 1 from the printer 1 (S201).
When the user instructs printing from the application program, the printer driver is called, receives image data (print image data) to be printed from the application program, and performs resolution conversion processing on the print image data (S202). . The resolution conversion process is a process for converting image data (text data, image data, etc.) to a resolution (printing resolution) for printing on paper. Here, the print resolution is 720 × 720 dpi, and each pixel data after the resolution conversion processing is data of 256 gradations represented by the RGB color space.

  Next, the printer driver performs color conversion processing (S203). The color conversion process is a process of converting image data in accordance with the color space of the ink color of the printer 1. Here, image data (256 gradations) in the RGB color space is converted into image data (256 gradations) in the CMYK color space.

  As a result, image data of 256-tone CMYK color space is obtained. In the following description, for simplification of description, the image data of the black plane among the image data of the CMYK color space will be described.

<Density unevenness correction process (S204)>
Next, the printer driver performs density unevenness correction processing (S204). The density unevenness correction process is a process of correcting the gradation values of the pixel data belonging to each pixel column based on the correction value for each pixel column. Here, correction of gradation values of pixel data belonging to the i-th pixel column will be described.

FIG. 16 is an explanatory diagram of correction of gradation values of pixel data. The horizontal axis in the figure indicates the gradation value before correction, and the vertical axis in the figure indicates the gradation value after correction.
If all the pixel data of the print image data before correction is the reference gradation value Sb, the printer driver uses the correction value ΔCi_b corresponding to the reference gradation value Sb to change the gradation value Sb of the pixel data to Sb + ΔCi_b. It is considered that it is preferable to correct it (thus, if a print image is formed according to the corrected gradation value Sb + ΔCi_b, it is considered that a print image without density unevenness as in the original print image data is obtained). Similarly, if all the pixel data of the print image data before correction is the reference gradation value Sc, the printer driver uses the correction value ΔCi_c corresponding to the reference gradation value Sc to set the gradation value Sc of the pixel data. It is considered good to correct to Sc + ΔCi_c.

  On the other hand, when the gradation value S_in before correction is different from the reference gradation value, for example, when the gradation value S_in before correction is between Sb and Sc as shown in the figure, the printer driver performs the correction value ΔCi_b and the correction value. Straight line interpolation is performed using the value ΔCi_c, and the gradation value S_out is calculated.

  According to the graph in the figure, the correction value ΔCi_a is a negative value. Therefore, if the gradation value S_in before correction is a value close to the reference gradation value Sa, the printer driver corrects the gradation value of the pixel data so that the gradation value is lowered. Further, according to the graph in the figure, the correction value ΔCi_b, the correction value ΔCi_c, the correction value ΔCi_d, and the correction value ΔCi_b are positive values. Therefore, if the gradation value S_in before correction is a value close to the reference gradation values Sb to Se, the printer driver corrects the gradation value of the pixel data so as to increase the gradation value.

Although the correction of the gradation value of the pixel data belonging to the i-th pixel column has been described here, the gradation value is similarly corrected for the pixel data belonging to the other pixel columns. As a result, the printer driver can correct the print image data in advance before printing so as to lightly correct the pixels in the darkly printed portion and to darken the pixels in the lightly printed portion.
The print image data after density unevenness correction is image data in a 256-tone CMYK color space.

<Processing after Density Unevenness Correction (S205 to S208)>
After the density unevenness correction processing, the printer driver performs halftone processing. Halftone processing is processing for converting high gradation number data into low gradation number data. Here, the 256 gradation print image data is converted into the four gradation print image data that can be expressed by the printer 1. As a halftone processing method, a dither method, an error diffusion method, and the like are known, and this embodiment also performs such a halftone processing. The halftone process performed in S101 (FIG. 9) and the halftone process here are the same type.

  In the present embodiment, the printer driver performs halftone processing on pixel data that has been subjected to density unevenness correction processing. As a result, the tone value of the pixel data in the dark and easily visible portion is corrected to be low, so the dot generation rate in that portion is low. On the contrary, the dot generation rate is high in a portion that is faint and easily visible.

  Next, the printer driver performs rasterization processing (S206). The rasterization process is a process of changing the order of arrangement of pixel data on the print image data to the order of data to be transferred to the printer 1. Thereafter, the printer driver generates print data by adding control data for controlling the printer 1 to the pixel data (S207), and transmits the print data to the printer 1.

  The printer 1 performs a printing operation according to the received print data. Specifically, the controller 60 of the printer 1 controls the transport unit 20 and the like according to the received print data control data, and controls the head unit 40 according to the pixel data of the print data to eject ink from each nozzle. When the printer 1 performs printing processing based on the print data generated in this way, the dot generation rate of each raster line is changed, the density of the image pieces in the row area on the paper is corrected, and the density of the print image Unevenness is suppressed.

=== Other Embodiments ===
The above-described embodiment is mainly described for a printer. Among them, a printing apparatus, a recording apparatus, a liquid ejection apparatus, a printing method, a recording method, a liquid ejection method, a printing system, a recording system, and a computer system are included. Needless to say, the disclosure includes a program, a storage medium storing the program, a display screen, a screen display method, a printed material manufacturing method, and the like.

  Moreover, although the printer etc. as one embodiment were demonstrated, said embodiment is for making an understanding of this invention easy, and is not for limiting and interpreting this invention. The present invention can be changed and improved without departing from the gist thereof, and it is needless to say that the present invention includes equivalents thereof. In particular, the embodiments described below are also included in the present invention.

<About the printer 1>
In the above-described embodiment, the printer has been described. However, the present invention is not limited to this. For example, color filter manufacturing apparatus, dyeing apparatus, fine processing apparatus, semiconductor manufacturing apparatus, surface processing apparatus, three-dimensional modeling machine, liquid vaporizer, organic EL manufacturing apparatus (particularly polymer EL manufacturing apparatus), display manufacturing apparatus, film formation The same technique as that of the present embodiment may be applied to various recording apparatuses to which an ink jet technique is applied such as an apparatus and a DNA chip manufacturing apparatus. These methods and manufacturing methods are also within the scope of application.

<About the printer 2>
The printer 1 described above is a printer in which paper moves relative to the head. However, other types of printers may be used. For example, there is a serial printer in which a head is mounted on a carriage that moves in a moving direction, and an ejection operation that ejects ink from the head that moves in the moving direction and a transport operation that transports paper in the transport direction are repeated alternately. Also good. Further, the printer may print an image on paper by moving the head in two directions on a plane parallel to the paper surface.

<About raster lines>
Each of the aforementioned raster lines is formed from one nozzle. However, the raster line forming method is not limited to this. A raster line may be formed by a plurality of nozzles.

<About brightness>
In the above-described embodiment, the luminance Yi is obtained as the representative value of each pixel column on the read image data, and the correction value is calculated using the luminance distribution data. However, the representative value of each pixel column is not the luminance, and other data may be used as the representative value. For example, gradation values in the RGB color space, gradation values in the Lab color space, and the like may be obtained as representative values of each pixel column, and the distribution data may be configured by the representative values.

<About filters>
In the above-described embodiment, filtering is performed using the Dooley visual filter VTF. However, the filter used for the filter process may be another visual filter. Further, instead of the visual filter, for example, an average value filter (a filter that performs weighting with the same value) may be used (in this case, moving average processing is performed on the luminance distribution data S (y) on the restored original image. The visual luminance distribution data Y ′ (y) is calculated.
In short, if a low-pass filter such as a visual filter VTF or an average value filter is applied to the luminance distribution data, and the correction value of each pixel column is calculated based on the luminance distribution data after applying the low-pass filter, it is visible to humans. Such density unevenness can be corrected.

It is explanatory drawing of a term. 1 is a block diagram of an overall configuration of a printer 1. FIG. FIG. 6 is a perspective view for explaining a conveyance process and a dot formation process of the printer. 4 is an explanatory diagram of an arrangement of a plurality of heads on the lower surface of the head unit 40. FIG. It is explanatory drawing of the mode of the nozzle arrangement | positioning for simple description, and dot formation. FIG. 6A to FIG. 6C are explanatory views of a state from when the test pattern is printed until the correction value is stored in the printer 1. It is explanatory drawing of the mode of an analysis of image data. FIG. 8A is an explanatory diagram of print image data of a test pattern. FIG. 8B is an explanatory diagram of print image data of the third correction pattern. It is a flowchart of a correction value acquisition process. It is explanatory drawing of the mode of the calculation of the brightness | luminance of each pixel column. It is a graph of Dooley's VTF filter. 12 is a graph of an impulse response h (t) of a filter having the frequency characteristic of FIG. 13A and 13B are explanatory diagrams of the correction value ΔCj_b of the reference gradation value Sb of the i-th pixel column. It is explanatory drawing of a correction value table. FIG. 10 is a flowchart of print processing performed by a printer driver. It is explanatory drawing of correction | amendment of the gradation value of pixel data.

Explanation of symbols

1 printer, 20 transport unit,
22A upstream roller, 22B downstream roller, 24 belt,
40 head units, 41 heads, 41A first head, 41B second head,
411 first nozzle group, 412 second nozzle group, 50 detector group,
60 controller, 61 interface unit, 62 CPU, 63 memory,
64 unit control circuit, 110 computer, 150 scanner

Claims (8)

A pattern forming step of forming a pattern composed of a plurality of the dot rows by forming a dot row on a medium according to the pixel row data of the print image data having a resolution matched to the print resolution;
A reading step of reading an image of the pattern by a scanner to obtain read data;
Applying a low-pass filter to the read data;
A correction value calculating step for calculating, for each pixel column, a correction value for correcting the data of each pixel column of the print image data in accordance with the read data after application of the low-pass filter;
A correction value acquisition method. The correction value acquisition method according to claim 1,
After the reading step, an inverse filter process for removing the influence of the scanner from the read data is performed,
In the filter application step, the low-pass filter is applied to the read data after the inverse filter process. The correction value acquisition method according to claim 1 or 2,
In the filter applying step, a weight function is convolved with the read data,
The correction value acquisition method, wherein the weight function corresponds to an impulse response of a visual filter having a predetermined frequency characteristic. The correction value acquisition method according to claim 1 or 2,
In the filter applying step, a weight function is convolved with the read data,
The correction value acquisition method, wherein the weighting function is a spread function in which a positive range is set wider than a range corresponding to the width of the dot row. A correction value acquisition method according to any one of claims 1 to 4,
In the filter applying step, a low pass filter is applied to the read data having a resolution higher than the print resolution,
In the correction value calculating step, the read data after application of the low-pass filter is subjected to resolution conversion to the print resolution, and the correction value is calculated according to the read data after resolution conversion. Acquisition method. A correction value acquisition method according to any one of claims 1 to 5,
In the reading step, a representative value of each pixel column is calculated from the two-dimensional image data of the pattern, and the one-dimensional read data is configured by the representative value of each pixel column,
In the filter application step, a low-pass filter is applied to the one-dimensional read data. A correction value acquisition method according to any one of claims 1 to 5,
In the filter applying step, a low-pass filter is applied to the read data that is two-dimensional image data,
In the correction value calculation step, a representative value of each pixel column is calculated from the read data after application of a low-pass filter, and the correction value is calculated according to the representative value of each pixel column. Acquisition method. A pattern forming step of forming a pattern composed of a plurality of the dot rows by forming a dot row on a medium according to the pixel row data of the print image data having a resolution matched to the print resolution;
A reading step of reading an image of the pattern by a scanner to obtain read data;
Applying a low-pass filter to the read data;
A correction value calculating step for calculating, for each pixel column, a correction value for correcting the data of each pixel column of the print image data in accordance with the read data after application of the low-pass filter;
An image forming step of correcting each pixel data of the print image data having a resolution matched to the print resolution according to the correction value corresponding to the pixel column of the pixel data and forming an image according to the corrected pixel data; Method.