JP2021114750A - Image forming device - Google Patents

Abstract

PROBLEM TO BE SOLVED: To improve the identification accuracy of an identification image and appropriately adjust the print density for each screen type. A test chart 300 is output for each screen type. On the test chart 300, a correction pattern 303-2 composed of a plurality of correction images 201 is arranged, and an identification image 301 is arranged at a position corresponding to the sampling area 302. The screen type corresponding to the identification image identified in the sampling area 302 is specified, and the corresponding γLUT is updated based on the reading result of the correction pattern 303-2. Of the areas where the correction pattern 303-2 is arranged, all of the correction images arranged in the proximity area 601 are thinner than the identification image 301. [Selection diagram] FIG. 7

Description

The present invention relates to an image forming apparatus that adjusts the print density for each screen type.

The print density of an image forming apparatus such as a multifunction device changes due to changes in conditions such as the remaining amount of toner as printing is repeated. Adjusting the print density By performing the adjustment work with the print density adjustment function, the print density can be adjusted according to the current printing situation, and printing can be performed at an appropriate density. Generally, in the method of adjusting the print density, a test chart including correction images having different color density values is output, and this test chart is read by a scanner. Then, by comparing the density value calculated from the brightness value of the scanned image with the print density value of the set test chart, the excess or deficiency of the print density value is calculated, and the γLUT (γ look-up table) is created. Will be updated. γLUT is an adjustment condition for adjusting the print density. By correcting the gradation characteristics of the input image using γLUT and outputting the image, it is possible to keep the gradation characteristics of the output result constant even if the remaining amount of toner or the usage environment changes. ..

Since the print density adjustment differs depending on the screen, it is necessary to perform the same number of times as the number of screen types. The types of screens include, for example, for copying and for printing images / texts, but are not limited to these three types. Therefore, the image forming apparatus outputs the first test chart on the first screen, and the user (including the operator) puts the first test chart on the scanner. Similarly, the image forming apparatus outputs the test chart on the second screen, and the user places the second test chart on the scanner. The user repeats this operation for each type of screen (the number of test charts). Therefore, the usability is low because the user needs to place the test chart on the scanner as many times as the number of output sheets of the test chart.

Therefore, an adjustment method has been devised in which a plurality of test charts are printed continuously, a bundle of test charts is placed together in an automatic document feeder (ADF), and the test charts are continuously scanned. However, when the ADF scans a plurality of test charts in succession, the order of the test charts to be read depends on the order in which the user arranges them. Users do not always bundle test charts in the proper order. Therefore, since the test charts are not always arranged in the printing order, it is necessary to determine which screen the read test chart was printed on.

If there is a mechanism to automatically identify the type of test chart and execute processing according to the order of the test chart, the workload will be reduced. Therefore, in Patent Document 1, a mark identification image is added to the margin of the test chart, and the type of the test chart is specified by the color of the identification image. The identification image is formed as a color mark according to the chart type at a predetermined position in the chart margin.

Japanese Unexamined Patent Publication No. 2001-094801

However, the position of the identification image on the test chart may vary due to printing misalignment, skewing or misalignment in ADF reading (scanning). Therefore, the identification image may not be read properly and an error may occur. In that case, the user has to reread the test chart. In order to properly identify the identification image in consideration of the variation in the position of the identification image, the area (frame) for sampling the identification image is compared with the area where the identification image is formed. It is conceivable to set it large.

However, if the sampling area for the identification image is made too large, the area for the correction image is included, and there is a possibility that the identification image and the correction image are erroneously detected. In addition, the position of the correction image also shifts due to printing misalignment, skewing, misalignment, etc. Therefore, if the sampling area for the identification image is large, there is a high possibility that the correction image will enter the sampling area. .. If the correction image enters the sampling area for the identification image, the identification image cannot be properly identified depending on the shading of the correction image, and the test chart type, that is, the screen type cannot be correctly specified. If the type of the test chart cannot be properly specified, it becomes difficult to properly adjust the print density for each screen type.

An object of the present invention is to improve the identification accuracy of an identification image and appropriately adjust the print density for each screen type.

In order to achieve the above object, the present invention arranges a correction pattern composed of a plurality of correction images, and arranges an identification image corresponding to a screen type at a position corresponding to a preset first region. Based on the output means for outputting the test chart for each screen type, the reading means for reading the test chart output by the output means, and the reading result in the first region of the reading results by the reading means. Based on the identification means for identifying the identification image, the identification means for specifying the screen type corresponding to the identification image identified by the identification means, and the reading result of the correction pattern among the reading results by the reading means. The output means has a generation means for generating an adjustment condition for adjusting the print density corresponding to the screen type specified by the specific means, and the output means is out of an area in which the correction pattern is arranged. The test chart is output so that all of the correction images arranged in the second region close to the arrangement position of the identification image are made lighter or darker than the identification image. It is characterized by that.

According to the present invention, it is possible to improve the identification accuracy of the identification image and appropriately adjust the print density for each screen type.

It is a block diagram of an image forming apparatus. It is a schematic cross-sectional view of a reading device. It is a figure which shows the example of the test chart which is generally used. It is a figure which shows an example of the test chart which includes the image for identification. It is a figure which shows the example of the reading image of the test chart when the reading deviation occurs. It is a figure which shows an example of another test chart. It is a figure which shows an example of the test chart used in this embodiment. It is a figure which shows the example of the RGB luminance value acquired from the reading result in a sampling area. It is a flowchart of print density adjustment processing. It is a flowchart of the image sampling process for identification. It is a figure which shows an example of the test chart of the modification.

Hereinafter, embodiments of the present invention will be described with reference to the drawings.

FIG. 1 is a block diagram of an image forming apparatus according to an embodiment of the present invention. This image forming apparatus is configured as a multifunction device 100 having a plurality of functions such as a printer, copying, and scanning. In the multifunction device 100, the CPU 101 controls the entire multifunction device 100 by controlling each unit connected via the data bus 111. The eMMC 102 is composed of a flash memory and stores a control program or the like executed by the CPU 101. The DRAM 103 is a volatile memory that can store program control variables and the like, and temporarily store image data and the like to be processed.

The storage device 104 is composed of an HDD device or the like, and is a non-volatile memory for storing data such as image data. The operation unit 105 is an interface unit with a user, accepts user operations, and displays information in the device. The scanning device 106 scans a sheet (original document) and generates a scanned image. The sheet to be read also includes a test chart (FIG. 4, etc.) described later. The reading device 106 can read the sheet at a reading resolution of, for example, 300 dpi × 300 dpi. The scanned image is the brightness value of the light received through the red (R) filter, the brightness value of the light received through the green (G) filter, and the light received through the blue (B) filter. Contains information on the brightness value of the light.

The image processing unit 107 converts the signal value of the image data based on the adjustment table γLUT (γ look-up table), and the recording unit 108 forms the toner image based on the converted signal value. The relationship between the density of the image formed by the recording unit 108 and the signal value (density characteristic or gradation characteristic) changes depending on the remaining amount of toner, the usage environment, and the like. In order to correct the density characteristic to the ideal density characteristic, the image adjusting unit 109 holds the γLUT corresponding to the type of the screen, and converts the signal value of the image data using the γLUT. The image adjustment unit 109 updates the γLUT for each screen by the print density adjustment process (FIG. 9). As a result, the density of the image formed by the recording unit 108 based on the image data is controlled to the target density. The communication unit 110 is an interface unit between the multifunction device 100 and the external communication network.

FIG. 2 is a schematic cross-sectional view of the reading device 106. The scanning device 106 includes an automatic document feeder (ADF) 120 and an image reader 130. In the automatic document feeder 120, documents are loaded on the document tray 121. In the document feeding section of the automatic document feeder 120, a feeding roller (not shown) and a bundle of documents loaded on the document tray 121 are drawn into the separation unit 122. The top sheets of the original bundle are separated one by one, conveyed to the conveying rollers 123, 124, and the resist roller 125 in this order, and conveyed to the original reading unit.

In the document reading unit of the automatic document feeder 120, the conveyed document is conveyed to the reading position R1 at a predetermined speed by the resist roller 125 and the reading belt 126. When the tip of the document reaches the reading position R1, the optical unit 132 fixed to the reading position R1 performs an exposure operation, and the document is read while being conveyed. This operation is called ADF reading. When the reading of the original is completed, the original is conveyed to the original paper ejection section by the reading belt 126. In the document ejection section, the original is ejected to the output tray 128 by the output roller 127.

An optical unit 132 is provided in the image reader 130. When the original is placed on the platen glass 131 by the user, the optical unit 132 scans while exposing the original, so that the optical unit 132 reads the original while moving. This operation is called pressure plate reading.

Such a multifunction device 100 prints an image on printing paper based on the image data and outputs the image. The print density at the time of printing changes little by little due to changes in the situation such as the remaining amount of toner and the usage environment. In order to adjust the deviation of the print density to the correct density, there is a print density adjustment function.

FIG. 3 is a diagram showing an example of a test chart generally used for adjusting the print density. Pattern data including a plurality of correction images 201 is printed on the test chart 200. The plurality of correction images 201 are a plurality of gradation images having different gradations and different color density values.

In the print density adjustment, the brightness value read by the reading device 106 of the test chart 200 is converted into a density value. The γLUT is updated based on the difference between the density value and the actual density value set in each of the correction images 201. The value of γLUT is held for each screen type. Since this screen is used properly according to the printing mode, such as when printing a scanned image such as copy printing or when printing a digital data image such as a printed image, there are a plurality of types. Therefore, since it is necessary to adjust the print density for each screen, there are as many test chart types as there are screen types. The screens include screens having different numbers of lines and screens that are periodic or aperiodic. However, there is no limitation on the type of screen used in this embodiment. Generally, when adjusting the print density, it is necessary to repeat the work of printing and reading the test chart for the number of screen types.

The work procedure for general pressure plate reading is as follows. It is assumed that the number of screen types is n.
(A) Recording unit 108 prints chart 1 → User (including operator) places chart 1 on reading device 106 → Reading (b) Recording unit 108 prints chart 2 → User reads chart 2 Place on 106 → Read (c) The recording unit 108 prints the chart n → The user places the chart n on the reading device 106 → Read That is, the user performs the work of placing the chart n on the reading device 106 each time the test chart is printed. As a result, the procedure becomes very complicated as the number of screen types increases. Therefore, a method has been proposed in which reading is continuously performed by the ADF so that the user's procedure does not increase even if the number of screens increases. The procedure for adjusting the print density by this method is as follows.
(A) Recording unit 108 prints chart 1 (b) Recording unit 108 prints chart 2 (c) Recording unit 108 prints chart n (d) User bundles n charts and reads them. Place at 106 → Continuous read This simplifies the user's work. Moreover, even if the number of test charts increases, the load on the user hardly increases.

In the pressure plate reading, since the printed test charts are read one by one, it is not necessary to determine on which screen the test chart to be read is printed. On the other hand, in the adjustment using the ADF, the test charts are read in the order in which the users arrange them, so that the readings are not always performed in the correct order. Therefore, it is necessary to determine which screen the read test chart was printed on.

FIG. 4 is a diagram showing an example of a test chart including an image for identification. A correction pattern 303 is printed on the test chart 300. The correction pattern 303 is composed of a plurality of correction images 201 in the test chart 200 (FIG. 3). The correction pattern 303 is an image group used for adjusting the print density in the test chart 300. In addition to the correction pattern 303, an identification image 301 is printed on the test chart 300. The identification image 301 is arranged at a fixed position from the paper edge in the margin portion where the correction pattern 303 is not arranged in the test chart 300.

The identification image 301 is a mark for specifying the type of the test chart 300, and by extension, the corresponding screen type. Therefore, the identification image 301 is provided (correspondingly) for each screen type. Specifically, the color of the identification image 301 differs depending on the corresponding screen type. The CPU 101 identifies the identification image 301 according to the difference in the color (luminance value of each color) of the identification image 301, and identifies the type of the corresponding test chart 300 or the screen type.

The sampling area 302 (first area) in FIG. 4 is an area preset as an area to be sampled in order to identify the identification image 301. The sampling area 302 is set at a fixed position from the edge of the scanned image. The relative positions of the correction pattern 303 and the identification image 301 are constant, but the relative positions of the sampling area 302 and the identification image 301 are due to skewing or misalignment in ADF reading (scanning). Can change. The size of the sampling area 302 is set to be equal to or larger than the size of the identification image 301.

Ideally, the entire identification image 301 fits in the sampling area 302, and the correction pattern 303 does not enter the sampling area 302. However, it may not be ideal. This will be described with reference to FIG.

5 (a) and 5 (b) are diagrams showing an example of a read image of the test chart 300 when a reading deviation occurs in the ADF.

When the print density is adjusted by ADF reading (scan reading), if skewing or misalignment occurs, the edges of the paper and the edges of the scanned image do not match. For example, FIG. 5A shows a state in which skew occurs. FIG. 5B shows a state in which misalignment occurs in the longitudinal direction of the paper. In these cases, a part or all of the identification image 301 may not fit in the sampling area 302. In addition to this, a part of the correction pattern 303 may enter the sampling area 302. In these cases, the identification image 301 cannot be identified from the reading result of the sampling area 302, and a reading error may occur. When this happens, the user must again place the test chart 300 and start reading.

FIG. 6 is a diagram showing an example of another test chart 300. In this test chart 300, the size of the sampling area 302 is larger than that of the test chart 300 shown in FIG. Since the sampling area 302 is large, the identification image 301 can be easily accommodated in the sampling area 302 (FIG. 6A). From this point of view, it contributes to avoiding read errors. However, on the other hand, a part of the correction pattern 303 is likely to enter the sampling area 302. From this point of view, a reading error of the identification image 301 is likely to occur. For example, in the example of FIG. 6B, although the identification image 301 is contained in the sampling area 302, the correction pattern 303 is contained in the sampling area 302. Especially when the color of the correction pattern 303 included in the sampling area 302 is different from that of the identification image 301, the identification image 301 may be erroneously determined as another identification image 301. The degree of risk of erroneous determination also differs depending on the density of the correction pattern 303 included in the sampling area 302. Therefore, in the present embodiment, as described with reference to FIG. 7, erroneous determination is suppressed by devising the arrangement of the correction pattern 303.

FIG. 7 is a diagram showing an example of the test chart 300 used in the present embodiment. In this test chart 300, the size of the sampling area 302 is the same as the example of FIG. 6 and is larger than the identification image 301. However, it is not essential that the sampling area 302 is larger than the identification image 301. In the test chart 300 shown in FIG. 7, unlike the example of FIG. 6, the correction pattern 303-2 is printed.

In FIG. 7, the proximity region 601 (second region) is an region in which the correction pattern 303-2 is arranged, which is close to the arrangement position of the identification image 301. The proximity region 601 is set to include the entire region that may enter the sampling region 302 in the event of maximum skew or misalignment. When the recording unit 108 outputs the test chart 300, the CPU 101 controls all of the correction images 201 arranged in the proximity region 601 so as to be thinner than the identification image 301. Preferably, the CPU 101 is arranged in the proximity region 601 in order from the thinnest of the correction images 201 included in the correction pattern 303-2. On the other hand, it is desirable that the identification image is output at the maximum density.

In other words, the identification image 301 may be an image darker than the luminance value determination threshold value, and all of the correction images 201 arranged in the proximity region 601 may be an image thinner than the luminance value determination threshold value. In this case, for example, for each of the RGB luminance values (R luminance value, G luminance value, and B luminance value) of the identification image 301, each of the RGB luminance values (RGB) of the correction image 201 in the proximity region 601. All of the brightness values) may be large values.

In the identification image sampling process (described later) of FIG. 10, if any one of the luminance values (R luminance value, G luminance value, and B luminance value) is equal to or less than the corresponding luminance value determination threshold value, the proximity is approached. The image in the area 601 is determined to be the identification image 301. On the other hand, if any of the luminance values is larger than the corresponding luminance value determination threshold value, the image in the proximity region 601 is determined to be the correction image 201 or the margin portion. Here, the luminance value is, for example, an 8-bit signal value, and the luminance value determination threshold value is, for example, 150.

FIG. 8 is a diagram showing an example of RGB luminance values acquired from the reading result in the sampling area 302 (in the first area). The acquired RGB luminance value is an 8-bit signal value and is shown in the range of 0 to 255. The identification of the identification image 301 is performed based on the brightness value acquired from the reading device 106. The luminance value determination threshold determines whether or not the pixels in the sampling area 302 have the set color characteristics. Specific processing will be described later with reference to FIG.

In FIG. 8, the region 601a is a region of the proximity region 601 that has entered the sampling region 302. Of the sampling area 302, an area that is neither the area 601a nor the identification image 301 corresponds to the margin of the paper. The brightness value of each pixel in the margin is very high. Since the thin image is located in the region 601a, the luminance value of each pixel in the region 601a is sufficiently far from the luminance value of each pixel in the identification image 301 and is close to the luminance value of each pixel in the margin portion. Therefore, by excluding the pixels having a high luminance value using a certain threshold value, it is easy to extract only the pixels of the identification image 301 that do not include the pixels of the margin portion and the region 601a. That is, the identification image 301 can be appropriately identified without being affected by the correction pattern 303-2 that has entered the sampling area 302.

FIG. 9 is a flowchart of the print density adjustment process. This process is realized by the CPU 101 deploying the program stored in the eMMC 102 on the DRAM 103 and executing it. This process is started every time the number of printed sheets reaches a certain number. Note that this process may be started by an instruction from the user.

First, in step S101, the CPU 101 generates chart data for forming the identification image 301 and the correction pattern 303-2. In step S102, the CPU 101 outputs the test chart 300 (FIG. 7) by controlling the recording unit 108 as an output means to print the chart data on paper. The processes of steps S101 and S102 are performed for the number of screen types. Therefore, as many test charts 300 as the number of screen types are output. When the plurality of test charts 300 required for the print density adjustment are output, the user bundles the plurality of test charts 300 and places them on the document tray 121 of the reading device 106. After that, the user instructs the start of reading by operating the operation unit 105.

In step S103, the CPU 101 waits for a reading start instruction, and when there is a reading start instruction, the CPU 101 starts continuous reading (ADF reading) of a plurality of test charts 300 by the reading device 106 as a reading means. The processes of steps S104 to S107 are executed for each test chart 300.

First, in step S104, the CPU 101 executes an identification image sampling process (FIG. 10), which will be described later, on the read data of the test chart 300 this time. As will be described later, in this identification image sampling process, it is determined whether or not the identification image 301 exists in the sampling area 302, and the color of the existing identification image 301 is specified. .. Further, when the identification image 301 of the test chart 300 can be identified, the screen type corresponding to the type of the identification image 301 is also specified.

In step S105, the CPU 101 determines whether or not the identification image 301 exists in the sampling area 302 as a result of the identification image sampling process. Then, when the identification image 301 exists in the sampling area 302, the CPU 101 advances the process to step S106. However, if the identification image 301 does not exist in the sampling area 302, the CPU 101 ends the process shown in FIG.

In step S106, the CPU 101 controls the image adjusting unit 109 to perform sampling processing of the correction pattern 303-2. In step S107, the CPU 101 controls the image adjusting unit 109 as a generation means to perform γLUT based on the comparison result between the sampling result in step S106 and the actual density value set in the test chart 300. Update. The γLUT to be updated in step S107 corresponds to the identification image 301 whose existence is recognized in the test chart 300 this time. That is, the γLUT corresponding to the screen type specified by the identification of the identification image 301 this time is the update target. As a result, γLUT, which is an adjustment condition, is generated for each screen type. After that, the CPU 101 ends the process shown in FIG.

FIG. 10 is a flowchart of the identification image sampling process executed in step S104 of FIG. In step S201, the CPU 101 controls the image adjustment unit 109 to determine the brightness value read in 1-pixel units in the sampling area 302, and whether the current pixel corresponds to the pixel of the identification image 301. Determine if not. Here, the CPU 101 determines whether or not the current pixel has the characteristics of the identification image 301. For that purpose, it is necessary to distinguish the identification image 301 from the margin portion and the correction pattern 303-2. Therefore, the CPU 101 excludes the pixel having the luminance feature determined to be the margin portion or the correction pattern 303-2. ..

Specifically, the CPU 101 determines whether or not at least one of the RGB luminance values of the pixel this time is smaller than the corresponding luminance value determination threshold value. That is, if at least one of the R brightness value <the brightness value determination threshold value for R, the G brightness value <the brightness value determination threshold value for G, and the B brightness value <the brightness value determination threshold value for B is satisfied, the CPU 101 is used. It is determined that the pixel corresponds to the pixel of the identification image 301. In other words, when the CPU 101 does not satisfy any of the R brightness value <R brightness value determination threshold value, G brightness value <G brightness value determination threshold value, and B brightness value <B brightness value determination threshold value. Determines that the pixel is a margin or a pixel of the correction pattern 303-2. By this processing, the identification image 301 can be identified from the pixel group excluding not only the margin portion but also the plurality of correction images 201 constituting the correction pattern 303-2 that has entered the sampling area 302. can. That is, it is possible to identify the identification image 301 based on the image excluding the image thinner than the luminance value determination threshold value from the reading results in the sampling area 302.

As a result of the determination in step S201, if the pixel this time does not correspond to the pixel of the identification image 301, the CPU 101 proceeds to the process in step S203. When the current pixel corresponds to the pixel of the identification image 301, the CPU 101 determines the color of the current pixel in step S202.

Here, the CPU 101 determines that the pixel color is "cyan" if, for example, the luminance value R: 0 to 80 and the luminance value B: 96 to 255. Similarly, the CPU 101 determines that the pixel color is "magenta" if the luminance value G: 0 to 80 and the luminance value R: 96 to 255. Further, the CPU 101 determines that the pixel color is "yellow" if the luminance value B: 0 to 80 and the luminance value G: 96 to 255.

After step S202, the CPU 101 advances the process to step S203. In step S203, the CPU 101 determines whether or not the scanning for all the pixels in the sampling area 302 is completed. Then, if there are unscanned pixels, the CPU 101 returns the process to step S201. When scanning for all pixels is completed, the CPU 101 identifies the type (color in this case) of the identification image 301 this time and also specifies the screen type corresponding to the identified identification image 301 in step S204. .. In this process, the CPU 101 corresponds to the identification means and the identification means in the present invention.

For example, the CPU 101 may determine the color of the determined pixel having the largest number as the color of the identification image 301. If the number of the determined pixel colors is less than a certain percentage, it may be determined that the pixels cannot be identified. After that, the CPU 101 ends the process shown in FIG.

By the processing of steps S201 to S203, the type of the identification image 301 is identified from the pixel group excluding the pixels determined not to correspond to the pixels of the identification image 301. Therefore, the type of the identification image 301, and by extension, the screen type can be accurately specified. If the type of the identification image 301 cannot be identified, an error may be notified.

In the method described with reference to FIG. 10, the identification image 301 is identified by the brightness value acquired by the reading device 106. After converting the brightness value into a density value, the converted value is compared with the density threshold value. The identification image 301 may be identified with. In this case, the CPU 101 converts the reading brightness value into a density value (yellow density, magenta density, cyan density, black density) of each color component based on the brightness density conversion table. Then, if the largest value among the density values of each color component is equal to or more than the density threshold value, the CPU 101 determines that the color identification image 301 corresponds to the largest value.

According to the present embodiment, the test chart is set so that all of the correction images arranged in the proximity area 601 of the areas where the correction pattern 303-2 is arranged are thinner than the identification image 301. It is output. As a result, even if the correction pattern 303-2 enters the sampling area 302, the identification accuracy of the identification image 301 does not decrease, so that the sampling area 302 can be easily set large. Therefore, the identification accuracy of the identification image can be improved, and the print density can be appropriately adjusted for each screen type.

Further, the identification accuracy of the identification image can be further improved by arranging the image including the thinnest image 201 among the correction images 201 included in the correction pattern 303-2 in the proximity region 601.

In the example shown in FIG. 7, the identification image was output at the maximum density, and among the correction images included in the correction pattern, the images were arranged in the proximity region 601 in order from the thinnest one. However, the relationship of shading may be reversed.

FIG. 11 is a diagram showing an example of a modified example test chart 300. The proximity area 602 is an area in which the correction pattern 303-3 is arranged and is close to the arrangement position of the identification image 301. The proximity region 602 may be the same as the proximity region 601. When the test chart 300 is output, the CPU 101 controls all of the correction images 201 arranged in the proximity region 602 to be darker than the identification image 301. In particular, in the proximity region 602, the correction image included in the correction pattern 303-3 may be arranged in the proximity region 602 in order from the darkest one. The identification image 301 may be output at the lowest density.

In other words, the identification image 301 may be an image thinner than the luminance value determination threshold value, and all of the correction images 201 arranged in the proximity region 602 may be an image darker than the luminance value determination threshold value. In this case, for example, for each of the RGB luminance values (R luminance value, G luminance value, and B luminance value) of the identification image 301, each of the RGB luminance values (RGB) of the correction image 201 in the proximity region 602. All of the brightness values) may be small values. When the configuration shown in FIG. 11 is adopted, it is preferable that the margin portion of the paper has a color closer to black than white. Therefore, the test chart 300 may be output using dark paper that is close to black.

The present invention can also be applied to an inkjet image forming apparatus.

Although the present invention has been described in detail based on the preferred embodiments thereof, the present invention is not limited to these specific embodiments, and various embodiments within the scope of the gist of the present invention are also included in the present invention. included.

101 CPU
106 Reading device 108 Recording unit 201 Correction image 300 Test chart 302 Sampling area 301 Identification image 303-2, 303-3 Correction pattern 601, 602 Proximity area

Claims (8)

A test chart in which a correction pattern composed of a plurality of correction images is arranged and an identification image corresponding to the screen type is arranged at a position corresponding to a preset first area is output for each screen type. Output means and
A reading means for reading the test chart output by the output means, and
An identification means for identifying an identification image based on the reading result in the first region among the reading results by the reading means, and
A specific means for specifying the screen type corresponding to the identification image identified by the identification means, and
It has a generation means for generating adjustment conditions for adjusting the print density corresponding to the screen type specified by the specific means based on the reading result of the correction pattern among the reading results by the reading means. ,
The output means makes all the correction images arranged in the second area close to the arrangement position of the identification image in the area where the correction pattern is arranged thinner than the identification image. An image forming apparatus, characterized in that the test chart is output so as to obtain a dark image. The output means makes the identification image darker than the threshold value, and makes all the correction images arranged in the second region lighter than the threshold value.
The image forming according to claim 1, wherein the identification means identifies the identification image based on an image excluding an image thinner than the threshold value among the reading results in the first region. Device. The image forming apparatus according to claim 2, wherein the thinnest image among the plurality of correction images constituting the correction pattern is arranged in the second region. The image forming apparatus according to any one of claims 1 to 3, wherein the identification means identifies the identification image by determining the color of the identification image. The image forming apparatus according to any one of claims 1 to 3, wherein the identification means identifies the identification image based on a luminance value as a reading result in the first region. The image forming apparatus according to any one of claims 1 to 5, wherein the identification image is arranged in a margin portion where the correction pattern is not arranged in the test chart. The image forming apparatus according to any one of claims 1 to 6, wherein the first region is larger than the identification image. The image forming apparatus according to any one of claims 1 to 7, wherein the reading means continuously reads a plurality of test charts output for each screen type.

Images