Image forming device
By integrating actual measurement and predictive methods to calculate weighted average image forming conditions, the image forming apparatus achieves high-precision density correction, overcoming surface roughness and environmental variability challenges.
Patent Information
- Application Number
- JP2021115829
- Authority / Receiving Office
- JP · JP
- Patent Type
- Patents
- Current Assignee / Owner
- Filing Date
- 2021-07-13
- Publication Date
- 2025-04-07
- Estimated Expiration
- 2041-07-13
AI Technical Summary
Existing image forming apparatuses face challenges in achieving high-precision density correction due to variations in the surface roughness of the intermediate transfer belt and the limitations of predictive models in handling unexpected environmental changes.
The image forming apparatus employs a combination of actual measurement and predictive methods to determine image forming conditions. It uses a generation unit to calculate image forming conditions based on a weighted average of first and second density information, where the first density information is acquired from correlated variations, and the second density information is measured from the formed image.
This approach enables high-accuracy density correction control, effectively addressing the issues of surface roughness and environmental variability, thereby stabilizing the density and gradation of output images.
Smart Images

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Abstract
Description
[Technical field]
[0001] The present invention relates to an image forming apparatus, for example, an image forming apparatus using an electrophotographic process. [Background technology]
[0002] In an image forming apparatus, the density and density gradation of an output image may differ from the desired density and gradation due to short-term fluctuations caused by fluctuations in the environment in which the apparatus is installed or in the environment inside the apparatus, and long-term fluctuations caused by changes over time (deterioration over time) of a photoconductor or developer, etc. Therefore, in order to match the density and gradation of an output image to the desired density and gradation, the image forming apparatus must correct the image formation conditions as needed, taking into account these various fluctuations.
[0003] Such a process of appropriately correcting changes in density and color is generally called calibration. In calibration, for example, several pattern images with uniform density are formed on paper, a photoconductor, or an intermediate transfer body, the density of the formed patterns is measured and compared with a target value, and various conditions for forming the image are appropriately adjusted based on the comparison results.
[0004] Conventionally, in order to stabilize the density and gradation of the output image, a specific correction pattern such as a gradation pattern is formed on paper, as in Patent Document 1. The formed pattern is read by an image reading unit, and the read gradation pattern information is fed back to image formation conditions such as γ (gamma) correction, thereby improving the stability of image quality.
[0005] As described above, the timing when calibration is required is when the environment changes or when the printer is left unused for a long time, and when the gradation needs to be corrected appropriately in various situations. For example, when the power is turned on first thing in the morning or when the printer is returned from the power saving mode, when the environment changes easily, when the output image duty is high and the toner supply amount is large, or when jobs with low output image duty are continuously performed. As a technique for performing such calibration, a method such as that in Patent Document 2 has been proposed. In Patent Document 2, a method is used in which a density patch image of each color is formed on an intermediate transfer body or a transfer belt, read by a density detection sensor, and fed back to the high voltage conditions and image processing conditions to adjust the maximum density and halftone gradation characteristics of each color.
[0006] In recent years, there has been an increasing demand for improved usability, particularly improved productivity by reducing waiting time and downtime, in addition to stable image quality, and there is a strong demand for calibration control for stabilizing image quality to be performed in a shorter time. As a technology that meets such demands, for example, Patent Document 3 shows a technology that creates a model using the external environment, image output conditions, and fluctuations in various sensor values as input values, and predicts the fluctuations in patches for calibration from the model. In this way, a technology has been proposed that omits the patch imaging process, which takes up much of the time required for calibration. [Prior art documents] [Patent documents]
[0007] [Patent Document 1] JP 2000-238341 A [Patent Document 2] JP 2003-167394 A [Patent Document 3] JP 2017-37100 A Summary of the Invention [Problem to be solved by the invention]
[0008] However, the method of actually measuring the color tone and density fluctuations using a density detection sensor in this way gives rise to the following problems.
[0009] There are two methods for forming a density patch image on the intermediate transfer belt and reading it with an optical sensor, which is a density detection sensor: diffuse reflection detection and specular reflection detection. The diffuse reflection detection method detects the change in the amount of diffusely reflected light from the density patch in response to light irradiated from the optical sensor. The specular reflection detection method detects the change in the amount of specularly reflected light from the intermediate transfer belt. The diffuse reflection detection method is widely used for density patches of color toners such as cyan, magenta, and yellow, which exhibit the characteristic of diffusively reflecting incident light, while the specular reflection detection method is widely used for black, which absorbs light and does not diffusely reflect it.
[0010] One of the problems of the conventional technology is that the method of detecting the density patch by the diffuse reflection light detection method is affected by the surface shape of the transfer belt. If the surface of the intermediate transfer belt is uniform and has few irregularities at the beginning of use, the light incident on the gaps between the toners of the density patch is not diffusely reflected from the surface of the intermediate transfer belt. However, during the middle to end of use, the surface of the intermediate transfer belt is roughened by friction with the contact member and the transfer paper, causing minute irregularities, which begin to show the characteristic of diffusing and reflecting the incident light. The minute irregularities existing as irregularities on the intermediate transfer belt reduce the measurement accuracy of the density patch, which results in a deterioration in the accuracy of various corrections, which may cause density variations in the printed matter.
[0011] On the other hand, calibration methods that predict color and density fluctuations using a model rather than actually measuring them can lead to the following problems:
[0012] In the density prediction model, a model is created by machine learning from the results of data collected under conditions such as the usage environment, the usage status of parts, and the image to be printed. Here, the conditions are conditions within an assumed average range. Then, the prediction accuracy is high within the range of the assumed conditions, but the prediction accuracy may decrease if the image is used in a manner that deviates from the assumed conditions. This is because it is common to use an average model that covers a certain degree of usage environment and situation, and it is not necessarily optimal for each individual usage environment. Factors that reduce the prediction accuracy include internal factors inside the device and external disturbance factors. An example of an internal disturbance factor is when the parts of the image forming device are in an initial state or a final state under conditions that are likely to cause individual differences. In addition, an example of an external disturbance factor is a sudden change in the temperature and humidity environment, or a sudden change in the image density of the image to be printed.
[0013] The present invention has been made in consideration of the above-mentioned circumstances, and an object of the present invention is to provide an image forming apparatus that enables highly accurate density correction control. [Means for solving the problem]
[0014] The present invention has been made to achieve the above object, and has the following configuration. That is, according to one aspect of the present invention, an image forming unit that forms an image based on image forming conditions; an acquisition means for acquiring information correlated with a change in density of an image formed by the image forming means; a measuring means for measuring the measurement image formed by the image forming means; An image forming apparatus is provided, characterized by having a generation means for determining first density information from the information acquired by the acquisition means, determining second density information from the measurement results of the measurement image by the measurement means, and generating the image forming conditions based on a weighted average of the first density information and the second density information. Effect of the Invention
[0015] According to the present invention, it becomes possible to perform density correction control with high accuracy. [Brief description of the drawings]
[0016] [Figure 1] Overall schematic diagram of an image forming apparatus [Diagram 2] Print system configuration diagram [Diagram 3] Block diagram of concentration prediction unit [Figure 4] FIG. 13 is a diagram showing a flow of automatic tone correction in the present embodiment. [Diagram 5] Conceptual diagram of two-point electrical control in this embodiment [Figure 6] FIG. 13 is a diagram showing an example of a maximum toner application amount correction chart in the present embodiment; [Figure 7] FIG. 13 is a conceptual diagram illustrating exposure intensity determination during maximum toner application amount correction in the present embodiment; [Figure 8] FIG. 13 is a diagram showing a gradation correction table at the time of automatic gradation correction in the embodiment; [Figure 9] FIG. 13 is a flow chart showing a process for forming a patch image and calculating a density in the embodiment; [Figure 10] FIG. 13 is a flow chart showing a flow of calculating a predicted density from an image density prediction model in the present embodiment. [Figure 11] FIG. 1 is a diagram showing the implementation timing and effect of actual measurement control and predictive control in this embodiment. [Figure 12] FIG. 13 is a flow chart showing a process for creating a correction LUT from density calculation values in the first embodiment. [Figure 13] FIG. 13 is a diagram showing the relationship between the basic correction LUT and the basic density curve and the final density curve in this embodiment. [Figure 14] FIG. 13 is a diagram showing a correction time LUT created from a final density curve in this embodiment; [Figure 15] FIG. 13 is a diagram showing the relationship between the basic correction LUT, the correction LUT, and the composite correction LUT in this embodiment. [Figure 16] FIG. 11 is a flow chart showing a process for creating a correction LUT from density calculation values in the second embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS
[0017] [Embodiment 1] Hereinafter, the embodiments will be described in detail with reference to the attached drawings. Note that the following embodiments do not limit the invention according to the claims. Although the embodiments describe a number of features, not all of these features are essential to the invention, and the features may be combined in any manner. Furthermore, in the attached drawings, the same reference numbers are used for the same or similar configurations, and duplicated descriptions are omitted.
[0018] First, a first embodiment of the present invention will be described. In this embodiment, a method for solving the above problem will be described using an image forming apparatus of the electrophotographic type (or electrophotographic process). Although the explanation will be given using an electrophotographic type, the characteristic points of control, particularly the matters described in the claims, also have the same problem in inkjet printers and dye-sublimation printers, and the problem can be solved using the method described below. Therefore, it is asserted that each image forming apparatus is also included in the invention according to the above claims.
[0019] (Image forming device) (Leader) As shown in FIG. 1, the image forming apparatus 100 has a reader unit A. A document placed on a document table glass 102 of the reader unit A is illuminated by a light source 103, and the reflected light from the document forms an image on a CCD sensor 105 via an optical system 104. The CCD sensor 105 is composed of a group of red, green, and blue CCD line sensors arranged in three rows, and generates red, green, and blue color component signals for each line sensor. These reading optical system units are moved in the direction of an arrow R103 shown in FIG. 1, and convert the image of the document into an electrical signal for each line. On the document table glass 102, a positioning member 107 is arranged to abut one side of the document to prevent the document from being obliquely placed, and a reference white plate 106 is arranged to determine the white level of the CCD sensor 105 and perform shading correction in the thrust direction of the CCD sensor 105. The image signal obtained by the CCD sensor 105 is subjected to A / D conversion by the reader control unit 108, shading correction using the read signal of the reference white plate 106, color conversion, and is sent to the printer unit, where it is processed by the printer control unit. Also connected to the reader unit A are an operation unit 20 and a display unit 218 that allow an operator to start copying and perform various settings. The reader unit A may also be equipped with a CPU, RAM 215, and ROM 216 for control purposes. These control the reader unit A.
[0020] (Printer section) As shown in FIG. 1, image forming apparatus 100 is a tandem intermediate transfer type full-color printer in which yellow, magenta, cyan and black image forming units PY, PM, PC and PK are arranged along intermediate transfer belt 6.
[0021] In the image forming station PY, a yellow toner image is formed on the photosensitive drum 1Y and is primarily transferred to the intermediate transfer belt 6. In the image forming station PM, a magenta toner image is formed on the photosensitive drum 1M and is primarily transferred and superimposed on the yellow toner image on the intermediate transfer belt 6. In the image forming stations PC and PK, a cyan toner image and a black toner image are formed on the photosensitive drums 1C and 1K, respectively, and are similarly primarily transferred and superimposed in order onto the intermediate transfer belt 6.
[0022] The four-color toner image that has been primarily transferred onto the intermediate transfer belt 6 is transported to a secondary transfer section T2 and is then collectively (secondarily) transferred onto a recording material P. The recording material P onto which the four-color toner image has been secondarily transferred is transported by a transport belt 10, and is heated and pressurized by a fixing device 11 to fix the toner image on the surface, and then is discharged outside the apparatus body.
[0023] The intermediate transfer belt 6 is supported by being stretched across a tension roller 61, a drive roller 62, and an opposing roller 63, and is driven by the drive roller 62 to rotate in the direction of arrow R2 at a predetermined process speed.
[0024] The recording material P drawn from the recording material cassette 65 is separated one by one by a separation roller 66 and sent to a registration roller 67. The registration roller 67 receives the recording material P in a stopped state and keeps it waiting, and sends the recording material P to a secondary transfer portion T2 in synchronization with the toner image on the intermediate transfer belt 6.
[0025] The secondary transfer roller 64 contacts the intermediate transfer belt 6 supported by the opposing roller 63 to form a secondary transfer portion T2. When a positive DC voltage is applied to the secondary transfer roller 64, the toner image, which is negatively charged and carried on the intermediate transfer belt 6, is secondarily transferred to the recording material P.
[0026] The image forming units PY, PM, PC, and PK are substantially identical in configuration, except that the colors of toner used in the developing devices 4Y, 4M, 4C, and 4K are different: yellow, magenta, cyan, and black. In the following, unless a particular distinction is required, the suffixes Y, M, C, and K added to the reference numerals to indicate a color will be omitted, and the image forming units will be generally described.
[0027] As shown in FIG. 1, the image forming section includes a photosensitive drum 1, a charging device 2, an exposure device 3, a developing device 4, a primary transfer roller 7, and a cleaning device disposed therearound.
[0028] The photosensitive drum 1 is an aluminum cylinder with a photosensitive layer with a negative charge formed on the outer surface thereof, and rotates in the direction of the arrow at a predetermined process speed. The photosensitive drum 1 is an OPC photosensitive body with a reflectance of approximately 40% for near-infrared light (960 nm). However, it may be an amorphous silicon photosensitive body with a similar reflectance.
[0029] The charging device 2 uses a scorotron charger, which irradiates the photosensitive drum 1 with charged particles generated by corona discharge, thereby charging the surface of the photosensitive drum 1 to a uniform negative potential. The scorotron charger has a wire to which a high voltage is applied, a shield portion connected to earth, and a grid portion to which a desired voltage is applied. A predetermined charging bias is applied to the wire of the charging device 2 from a charging bias power supply (not shown). A predetermined grid bias is applied to the grid portion of the charging device 2 from a grid bias power supply (not shown). Although it depends on the voltage applied to the wire, the photosensitive drum 1 is charged to approximately the voltage applied to the grid portion.
[0030] The exposure device 3 scans a laser beam with a rotating mirror to write an electrostatic image on the charged surface of the photosensitive drum 1. A potential sensor (not shown), which is an example of a potential detection means, can detect the potential of the electrostatic image formed on the photosensitive drum 1 by the exposure device 3. The development device 4 attaches toner to the electrostatic image on the photosensitive drum 1 to develop it into a toner image.
[0031] The primary transfer roller 7 presses against the inner surface of the intermediate transfer belt 6 to form a primary transfer portion between the photosensitive drum 1 and the intermediate transfer belt 6. When a positive DC voltage is applied to the primary transfer roller 7, the negative toner image carried on the photosensitive drum 1 is primarily transferred to the intermediate transfer belt 6 passing through the primary transfer portion.
[0032] The image density sensor (patch detection sensor) 400 is disposed facing the intermediate transfer belt and measures the image density of unfixed toner. Note that, although the image density sensor is disposed facing the intermediate transfer belt in this embodiment, it can be disposed appropriately, including facing the photosensitive drum. The image density sensor disposed on the photosensitive drum or intermediate transfer belt is a sensor that measures the image density of unfixed toner. It is also possible to dispose an image density sensor that measures a fixed pattern image downstream of the fixing device, and is not limited to the image density sensor described in this embodiment.
[0033] The cleaning device rubs a cleaning blade against the photosensitive drum 1 to collect the transfer residual toner that has escaped transfer onto the intermediate transfer belt 6 and remains on the photosensitive drum 1 .
[0034] The belt cleaning device 68 rubs a cleaning blade against the intermediate transfer belt 6 to collect the transfer residual toner that has escaped from being transferred to the recording material P and passed through the secondary transfer portion T2 and remains on the intermediate transfer belt 6.
[0035] (Image processing unit) 2 is a diagram showing the configuration of a print system according to the present invention. In the diagram, 301 is a host computer and 100 is an image forming apparatus. The host computer 301 and the image forming apparatus 100 are connected by a communication line such as USB 2.0 High-Speed, 1000Base-T / 100Base-TX / 10Base-T (IEEE 802.3 compliant), etc.
[0036] In the image forming apparatus 100, a printer controller 300 controls the overall operation of the printer. The printer controller 300 has the following configuration. A host I / F unit 302 that controls input / output with a host computer 301 . an input / output buffer 303 for transmitting and receiving control codes from the host I / F unit 302 and data from each communication means; A printer controller CPU 313 controls the overall operation of the controller 300 . A program ROM 304 that stores control programs and control data for the printer controller CPU 313 . A RAM 309 is used as a work memory for the control codes, calculations required for interpreting data and printing, or processing print data. An image information generating unit 305 generates various image objects based on the settings of the data received from the host computer 301 . A RIP (Raster Image Processor) unit 314 develops an image object into a bitmap image. A color processing unit 315 performs color conversion processing for multi-colors. A tone correction unit 316 performs tone correction for a single color. A pseudo-halftone processing unit 317 executes pseudo-halftone processing such as a dither matrix or an error diffusion method. An engine I / F unit 318 transfers the converted image to the image forming engine unit. An image forming engine unit 101 forms an image from the converted image data. The above is the basic image processing flow of the printer controller during image formation, which is indicated by the thick solid line.
[0037] The printer controller 300 not only controls image formation but also various control calculations. The control programs for this purpose are stored in a program ROM 304. The control programs and data include the following: A maximum density condition determination unit 306 that performs maximum density adjustment. A predicted concentration calculation unit 307 that predicts the concentration based on the output value from the sensor, etc. A tone correction table generating unit (γLUT) 308 that performs density tone correction. The generated tone correction table includes, as correction values, output density values corresponding to input density values, for example. A prediction model correction unit 350 that corrects a model for calculating a predicted density. Note that a detailed explanation of various control calculations in the printer controller will be given later. Note that the tone correction table is also called an image correction condition.
[0038] In addition, it has a table storage unit 310 that temporarily stores the adjustment results from the maximum density condition determination unit 306 to the gradation correction table generation unit 308. It also has an operation panel 218 that operates the printing device and issues instructions to execute the correction process, and a panel I / F unit 311 that connects the printer controller 300 and the operation panel 218. It also has an external memory unit 181 that is used to store print data and various pieces of information about the printing device, a memory I / F unit 312 that connects the controller 300 and the external memory unit 181, and a system bus 319 that connects each unit.
[0039] (Concentration correction / potential control) The density correction used in this embodiment is performed using an output image (toner image after fixing) formed on a paper sheet at the user's discretion, as shown in Fig. 4. Note that, in this embodiment, a system having a potential sensor that measures the potential on the drum surface is described, but the present invention is not limited to this. Note that, although the procedure in Fig. 4 is at the user's discretion, it is performed at least once before the device is put into service, and may be performed at any time thereafter.
[0040] When the automatic tone correction control is performed at the user's discretion, first, the potential control process (S201) starts. The engine control unit 102 determines the target charging potential (VdT), grid bias (Y) and developing bias (Vdc) by potential control before printing on paper. The potential control process can determine the charging potential and the like according to the environmental conditions (including temperature and humidity conditions) in which the image forming apparatus 100 is installed.
[0041] In this embodiment, the engine control unit 102 performs potential control called two-point electrification control. FIG. 5 is a diagram for explaining the concept of potential control by two-point electrification control. In FIG. 5, the horizontal axis indicates the grid bias, and the vertical axis indicates the photoconductor surface potential. VD1 indicates the charging potential under the first charging condition (grid bias 400V), and Vl1 indicates the exposed portion potential formed with the standard laser power. Vd2 indicates the charging potential under the second charging condition (grid bias 800V), and Vl2 is the exposed portion potential formed with the standard laser power at that time. In this case, the contrast potentials (Cont1, Cont2) at the grid biases of 400V and 800V can be calculated from the formulas (1) and (2).
[0042] (Cont1) = (Vd1 - Vl1) (1) (Cont2) = (Vd2 - Vl2) (2) Here, the increase in contrast potential (Cont Δ) for every 1 V of the charging potential can be calculated by equation (3) based on the results of equations (1) and (2).
[0043] (ContΔ)=((Cont2-Cont1) / (Vd2-Vd1))...(3) Meanwhile, an environmental sensor (not shown) is provided inside the image forming apparatus 100, and the environmental sensor measures environmental conditions such as temperature and humidity inside the image forming apparatus 100. The engine control unit 102 obtains the environmental conditions (e.g., absolute moisture content) inside the image forming apparatus 100 based on the measurement results of the environmental sensor. Then, the engine control unit 102 refers to a preregistered environmental table to find a target contrast potential (ContT) corresponding to the environmental condition.
[0044] The relationship between the target contrast potential (ContT) and the increase in contrast potential (ContΔ) can be calculated by equation (4).
[0045] ContT=Cont1+X·ContΔ···(4).
[0046] By calculating the parameter "X" that satisfies the relationship in equation (4), the target charged potential (VdT) (hereinafter also referred to as "target potential") can be calculated using equation (5).
[0047] VdT = Vd1 + X (5).
[0048] The charge potential change (VdΔ) per 1 V of grid bias can be calculated using equation (6).
[0049] (VdΔ)=(Vd2-Vd1) / (800-400) ···(6).
[0050] The grid bias (Y) that gives the target potential (VdT) can be calculated from equation (7).
[0051] Target VdT = 400 + Y VdΔ (7).
[0052] In equation (7), VdΔ can be calculated from equation (6), and VdT can be calculated from equation (5). Therefore, by substituting the known potentials from equations (5) and (6), the grid bias (Y) that satisfies the relationship in equation (7) can be finally determined.
[0053] The above process makes it possible to determine the target potential (VdT) and grid bias (Y) according to the environmental conditions. The developing bias (Vdc) has a specified potential difference with respect to the target potential (VdT), and can be calculated by subtracting the specified potential from the determined target potential (VdT). Subsequent image formation is performed with the determined developing bias (Vdc). Note that the potential on each drum is negative, but the negative potential is omitted here to make the calculation process easier to understand. The above process ends the potential control process of step S201 in FIG. 4.
[0054] (Maximum toner load adjustment) Next, the process proceeds to step S202, where a patch image for adjusting the maximum toner loading amount is formed using the grid bias (Y) and the development bias (Vdc) determined by the potential control in the previous step S201 (S202).
[0055] For printers that prioritize productivity, the following flow is omitted, and a flow for adjusting the maximum toner amount by potential control alone is also disclosed. However, the colorant charge retention amount in the developer and the mixture ratio of toner and carrier change depending on the environment and durability, so control by potential alone has low accuracy. Therefore, in this embodiment, patch images with several levels of exposure light intensity (hereinafter LPW) are formed, and the LPW to be used for normal image formation is determined.
[0056] The image forming apparatus 100, in which the grit bias (Y) and the developing bias (Vdc) have been determined, forms five patch images ((1) to (5)) for each color, black, cyan, yellow, and magenta, as shown in FIG. 6, in order to adjust the maximum toner amount. Note that the number of patches is not limited to this. The formation conditions for the five patch images are different LPWs, which are LPW1, LPW2, LPW3 (corresponding to the standard laser power when used for potential control), LPW4, and LPW5 from the left. The laser power increases from LPW1 to LPW5. The number of colors of the patches is not limited to four colors as long as it follows the number of color components used in the image forming apparatus 100.
[0057] The output image is set in the reader by the user, and the density of the image pattern is automatically detected (S203). Fig. 7 is a diagram showing the relationship between the density value of each patch image and the LPW. It is possible to adjust the amount of applied toner by controlling the LPW according to a density target value (hereinafter also referred to as the "maximum applied amount target density value") that targets the detected density value.
[0058] (tone correction and basic value acquisition) After the adjustment of the maximum toner loading amount is completed, the next step is to correct the gradation. Here, the previously determined grid bias (Y), developing bias (Vdc), and LPW level are used to form an image pattern with 64 gradations for each color, and output it onto paper (S204). Note that the number of gradations is not limited to this. The output image is set in the reader by the user, and the density of the image pattern is automatically detected (S205).
[0059] From the density obtained from the image pattern, interpolation and smoothing processes are performed to obtain engine γ (gamma) characteristics for the entire density range. Next, using the obtained engine γ characteristics and a preset gradation target, a gradation correction table is created for converting an input image signal into an output image signal (S206). In this embodiment, as shown in FIG. 8, an inverse conversion process is performed to match the gradation target, and a gradation correction table is created. When this process is completed, the density on the paper will match the gradation target over the entire density range.
[0060] The target LPW determined by the above procedure is applied, and a toner image pattern including test images of multiple gradations for each color component is formed using the gradation correction table (S207). If the density of the test image is detected on the intermediate transfer body using the image density sensor 400 (S208), the density value becomes the target density on the intermediate transfer body and is stored as the basic density in the density storage unit 331 (see FIG. 3) (S209). In this embodiment, after the gradation correction table is created, test images of 10 gradations for each color are formed, the test images are measured using the image density sensor 400, and the results are stored as the basic density in the density storage unit 331. The measurement results of the image density sensor 400, which vary depending on the density of the test image, are stored in the density storage unit 331. The data stored in the density storage unit 331 are, for example, the density values of the test images. Note that the density values may be stored together with the density values before or after gradation correction corresponding to the densities. However, it is necessary to determine which one to use. Also, if the test images to be formed are determined in advance, the density values for each detected test image may be stored without being linked to the density values. The base density values are referenced during calibration.
[0061] Furthermore, the sensor, counter, and timer values when this automatic tone correction is performed and the basic density is obtained, as well as image forming conditions such as the grid bias, development bias, and LPW level, are stored as basic signal values in the signal value storage unit 321 (S210). With reference to the basic density, engine γ characteristics, and basic signal values thus obtained, the tone correction table is updated as described below. Note that, although the automatic tone correction process in FIG. 4 has been described above as forming a test image on a recording medium such as paper, it may also be configured to measure the density of a test image formed on an intermediate transfer belt by the image density sensor 400.
[0062] (Concentration calculated from actual measurements) First, a flow for actually measuring density values in the current image forming apparatus in normal image correction control is shown in FIG.
[0063] When this process is started, information such as environmental values at the time of startup, the amount of time left unattended, and the number of times toner has been replenished, as well as information on the image formation conditions for forming an image, are obtained as input signal values from sensors, timers, and counters provided in the image forming device (S901).
[0064] Next, a toner image pattern is formed under image forming conditions according to the acquired information (S902). In this embodiment, a pattern with 10 gradations for each color is formed, but this is not limited to this. This toner image pattern may be the same as the test image formed in S207 of FIG. 4. In other words, the density value of each toner image pattern is the same as that of the test image formed in S207.
[0065] Next, the density of the formed toner image pattern is detected on the intermediate transfer body by using the image density sensor 400 (S903), and the density value (γ characteristic) at the time of correction is obtained. Then, the tone correction table is updated based on the density value (also called second density information) or gamma characteristic (output gamma characteristic) obtained by the procedure of Fig. 9, which will be described with reference to Figs. 12 to 15.
[0066] In this embodiment, the actual measurement control or the prediction control of the image density is a model that measures the image density on the intermediate transfer body, so the density value measured on the intermediate transfer body is stored as the density value that serves as the reference for prediction. However, for example, when the image density on a recording medium is actually measured or predicted, the image density on the recording medium is measured and stored as the density value that serves as the reference for the prediction model. The measurement position of the base density can be appropriately selected depending on the position at which the density of the image formed is to be handled in the adopted image density prediction model, and is not limited to the above.
[0067] (Concentration calculation based on prediction) Next, a flow for predicting density in the predicted density calculation section in the printer controller will be described with reference to FIG. 3 and FIG.
[0068] The image forming apparatus has a sensor 200 for detecting the external environment such as temperature, a timer 201, and a counter 202 in the image forming engine. Various signal values from these, and image forming conditions 203 such as the current exposure intensity (hereinafter referred to as LPW) / charge potential (hereinafter referred to as Vd) in the image forming apparatus are input to a predicted density calculation unit 307 in the printer controller. At this time, the signal value is first input to an input signal value processing unit 320 in the predicted density calculation unit 307. The input signal value processing unit 320 has a signal value storage unit 321 that stores a basic signal value, and a difference calculation unit 322 that calculates the difference between the input signal value and the signal value stored in the signal value storage unit 321. Here, information indicating the environment inside and outside the image forming apparatus is called environmental conditions, and the environmental conditions and image forming conditions may be collectively called condition information.
[0069] The signal value processed by the input signal value processing unit 320 is input to a density prediction unit 330. The density prediction unit 330 has a density memory unit 331 that stores a basic density, and a prediction function unit 332 that predicts a density from an input value from the input signal processing unit 320. The prediction function unit 332 has an image density prediction model that calculates a density change amount from a basic density from an input value, and calculates a current predicted density by adding the density change amount calculated here to the basic density stored in the density memory unit 331. The acquisition of the basic signal value and the acquisition of the basic density will be described later.
[0070] The calculated predicted density is input to a tone correction table generating unit 308, which creates a γLUT for input to a tone correction unit 316. The tone correction method will be described later.
[0071] The flow for calculating the predicted concentration value is shown in Figure 10. Here, we will explain the flow for predicting the concentration when the main body is started up in a state in which the basic signal value and basic concentration have been acquired in advance in the above-mentioned method.
[0072] First, when this process is started, information indicating the environment inside and outside the image forming apparatus, such as environmental values such as temperature and humidity at the time of start-up, the time left standing, the number of times toner is replenished, and information on the image forming conditions for performing image formation are acquired as input signal values (S1001). These pieces of information may be acquired, for example, from a sensor, a timer, a counter, and the like provided in the image forming apparatus. The image forming conditions include, for example, exposure intensity (hereinafter LPW) / charge potential (hereinafter Vd), and the like. LPW and Vd can also be said to be information correlated with the density of the image to be formed. There is other information correlated with the density of the image, such as the temperature inside the machine and the paper quality, which may also be correlated with the density of the image, in which case these pieces of information can also be said to be information correlated with the density of the image. Of course, there may be other information correlated with the density of the image. A difference between the acquired signal value and a basic signal value previously stored in step S210 is extracted (S1002).
[0073] Next, the extracted difference value is substituted into an image density prediction model formula that has been created based on a study in advance (S1003), and a predicted value of the difference value from the basic density of the current density is calculated (S1004). A predicted density value (also called first density information) at the current time is calculated from the sum of this difference prediction value and the basic density value stored in the density storage unit 331, and the gamma characteristic is obtained (S1005). The gradation correction table is updated based on the density value or gamma characteristic obtained by the procedure of Fig. 10, which will be described with reference to Figs. 12 to 15.
[0074] As described above, this embodiment is provided with the configuration and functions for performing both calibration of density gradations based on actual measurement values and calibration of density gradations using a prediction model.
[0075] (Control timing of actual measurement control and predictive control) The density correction sequence by actual measurement control, in which an image pattern is formed on the intermediate transfer belt and the image pattern is read by an image density sensor, is generally performed by interrupting the image formation sequence, which is a printing operation. Therefore, the control time required for one density correction sequence directly reduces productivity. However, performing actual measurement control infrequently out of concern for reduced productivity leads to worsening color and density fluctuations. In light of this background, the control timing of actual measurement control was set in conventional image forming devices, taking into account the balance between color and density fluctuations and productivity. Depending on the main body configuration, it is possible to increase the frequency of actual measurement control by forming an image pattern outside the image formation range, but performing actual measurement control frequently can lead to increased toner consumption, which means increased costs, so it is currently difficult to increase the frequency of actual measurement control.
[0076] However, by implementing predictive control, it is possible to compensate for density correction between actual measurement controls and suppress color and density fluctuations. Because predictive correction does not require processes such as image formation and reading, the required time is short and no consumables such as toner or sheets are consumed.
[0077] Fig. 11 shows an overview of the control timing of actual measurement control and predictive control. Fig. 11(a) shows the density correction control timing when control is performed using only conventional actual measurement control, and the actual color fluctuation at that time. Meanwhile, Fig. 11(b) shows the density correction control timing and actual color fluctuation when control is performed by interweaving actual measurement control and predictive control as performed in this embodiment. As a result, the density correction control shown in Fig. 11(b) can perform density correction more frequently, thereby achieving greater suppression of color fluctuation.
[0078] In this embodiment, predictive control is also performed at the same time as actual measurement control. The purpose of this is to compensate for the deterioration in accuracy by predictive control, since the accuracy of actual measurement control deteriorates depending on the surface condition of the intermediate transfer belt that forms the image pattern. For example, if the surface condition of the intermediate transfer body deteriorates or the sensor 400 becomes dirty, the accuracy of the density measurement value may decrease. In that case, the deterioration in accuracy of the measurement value appears as a fluctuation in density. Therefore, the deterioration in accuracy is compensated for by predictive control. Therefore, if predictive control is performed only for the purpose of supporting actual measurement control, it is acceptable to supplement predictive control only at the same timing as actual measurement control.
[0079] (LUT creation method) Next, a method for reflecting the calculated density values (or gamma characteristics) in the LUT in this embodiment will be described. First, during automatic gradation correction performed arbitrarily by the user, a gradation correction table (hereinafter, basic correction LUT) is formed in accordance with the engine gamma characteristics so as to match a preset gradation target (hereinafter, gradation LUT). After that, as described above, basic density values of 10 gradations for each color are obtained as a comparison standard for density calculation by actual measurement or prediction. The density curve created from these basic density values is set as the reference density curve.
[0080] Thereafter, at preset timings, such as when the power is turned on, when the printer returns from sleep mode, and when the environment changes, the density value at that timing is calculated by actual measurement control and predictive control, and the calculated density value is used to create an LUT at the time of image output (hereinafter, a composite correction LUT). As described with reference to FIG. 11, when actual measurement control is performed, predictive control is also performed at the same time. In FIG. 12 and subsequent figures, a procedure for performing predictive control at the same time as actual measurement control is described. This calibration by actual measurement control and predictive control may be performed under preset conditions, for example, under the condition that a predetermined number of pages have been printed since the last calibration was performed by actual measurement control. In that case, calibration by predictive control alone may be performed when other factors occur, such as when the power is turned on, when the printer returns from sleep mode, and when the environment changes.
[0081] A composite correction LUT creating method will be described with reference to FIGS.
[0082] FIG. 12 is a flow diagram for creating a composite correction LUT from the calculation results of the actual measured density and the predicted density. First, the usage history of the current intermediate transfer belt (intermediate transfer body 6) is grasped. This usage refers to the number of sheets printed using the intermediate transfer belt and the rotation time of the intermediate transfer belt, which are obtained from information from a usage measurement unit such as a parts counter. For example, when the intermediate transfer belt is replaced, the initial count value at that time is stored, and by subtracting the initial count value from the current count value, it is possible to know the usage amount indicating the degree of use from the new state. Here, it is determined whether the usage amount of the intermediate transfer belt is less than a predetermined amount, for example, less than 80%, of the usage amount assumed to be the lifespan (for example, the number of sheets printed that is assumed to be the lifespan) (S1201).
[0083] If it is determined that the usage is less than 80% of the lifespan, the reflection rate of actual measurement control to density correction is determined to be 50%, and the reflection rate of predictive control to density correction is determined to be 50% (S1202).Also, if it is determined in S301 that the usage amount of the intermediate transfer belt is a predetermined amount or more, for example, 80% or more, the reflection rate of actual measurement control to density correction is determined to be 30%, and the reflection rate of predictive control to density correction is determined to be 70% (S1203).
[0084] The reason for lowering the reflection rate of the actual measurement value here is as described above. For example, this is because the detection accuracy of the image pattern deteriorates due to minute irregularities or unevenness that occur on the surface of the intermediate transfer belt due to its usage history. However, the reason for not setting the correction reflection rate of the actual measurement to 0% is to detect through actual measurement that the actual image pattern has changed to a state that cannot be predicted by the density prediction model, and to reflect this in the density correction. For example, this may occur in a situation where the photosensitive drum or developing unit has been replaced but the counter information has not been set correctly, or when there is an error between the detection value and the actual state due to individual differences in the various sensors that detect the information required for density prediction.
[0085] 9 and 10, the concentration by actual measurement control, i.e., the actual measurement concentration calculated value, and the concentration by predictive control, i.e., the predictive control calculated value are calculated (S1204). Then, each of these calculated concentration values is multiplied by the reflection rate calculated in S1202 or S1203, respectively, to calculate the final concentration value (S1205).
[0086] For example, consider a case where the reflection rate of actual measurement control on density correction is set to 30% and the reflection rate of predictive control on density correction is set to 70% as in S1203. In this case, if the actual measurement concentration calculated value obtained in S1204 is a reflection concentration of 0.7 and the predictive concentration calculated value is a reflection concentration of 0.8, the final concentration value is calculated by the calculation method shown in the following formula 1. 0.8×(30÷100)+0.7×(70÷100)=0.73 (Formula 1) Here, the density value of one gradation is shown as an example, but similar calculations are performed for the other nine gradations to calculate the final density value for all 10 gradations. This calculation is also performed for each color component. In this way, the density value is calculated by taking the weighted average of the actual measured value and the predicted value, using a weight determined according to the amount of use of the intermediate transfer body.
[0087] In this way, in a situation where the density calculation values differ between actual measurement control and predictive control, and it is assumed that the detection accuracy of the image pattern in actual measurement control has decreased, the density correction reflection rate is changed so that a value close to the density calculation value in predictive control is calculated as the final density value. This correction reflection rate is determined at each actual measurement control timing shown in Figure 11(b), and the reflection rate is reviewed each time according to the usage status of the image forming apparatus.
[0088] Also, as shown in FIG. 11(b), the correction reflection rate of the predictive control performed at the timing when the actual measurement control is not performed indicates the color variation result of always fixing the density value predicted by the predictive control at 100%. The correction reflection rate of the predictive control at this timing may be the reflection rate determined in the determination flow of the density correction reflection rate. In that case, since there is a possibility that the correction amount of the color variation may be reduced, it is better to determine the content according to the prediction accuracy of the density predictive control and the actual ability of the color variation. Either configuration does not limit the scope of the present claim. However, since the density value is not actually measured at this timing, the measurement value measured last by the actual measurement control may be saved and used.
[0089] Next, the obtained final density values are plotted for each gradation, and a density curve (current engine γ characteristic: dashed line) is created for the density values shown by the circles in FIG. 13 (S1206).
[0090] In order to correct this final density curve to the basic density curve created during the automatic tone correction shown in Fig. 4, an inverse conversion is performed to create a correction LUT as shown by the long dashed line in Fig. 14 (S1207). The gamma characteristic of the final density is converted to the gamma characteristic of the basic density by this correction LUT.
[0091] Finally, a composite correction LUT is created (S1208) as shown by the long two-dot chain line in Fig. 15, which is a combination of the correction LUT and the basic correction LUT (tone correction table in Fig. 8) during automatic tone correction. This composite correction LUT becomes the tone correction table to be used when forming images from now on. In other words, the input image signal is corrected using this composite correction LUT, and an output image is formed and output.
[0092] The concentration curve may be created by a commonly used approximation method, such as by using an approximation formula that connects 10 points.
[0093] In addition, if the concentration is calibrated using only predictive control between concentration calibrations in the procedure of FIG. 12, after performing the procedure of FIG. 10, the concentration value obtained in that procedure can be treated as the final concentration in FIG. 12 and steps S1206 and thereafter in FIG. 12 can be performed.
[0094] According to the present embodiment, in the calibration for color / density gradation stabilization control, two density calculation methods are used in combination: a method for calculating color / density values by measuring a formed image pattern, and a method for calculating color / density values by using a prediction model. In this case, by changing the reflection rate of each density calculation value in the correction according to the situation, it becomes possible to accurately grasp the actual density change situation and provide highly accurate density correction control.
[0095] In this embodiment, a machine learning density prediction model is used to predict the density, but a model other than machine learning may be used. That is, a table specifying predicted values of density fluctuations may be prepared in advance, and predictions may be made by referring to the table. For example, the table may output parameters such as the environment inside the image forming apparatus, the degree to which a developing unit including a photosensitive drum and a developing device has been used, and the area ratio of the area where toner is placed to the image area, and the like, and the amount of density fluctuation corresponding to the values of these parameters.
[0096] [Embodiment 2] In the first embodiment, the reflection rate of the actual measurement result and the predicted result in the creation of the LUT was determined according to the usage amount of the intermediate transfer body 6 (intermediate transfer belt). In this embodiment, by adding a conditional branch that determines the reflection rate (or weighting) of the actual measurement result and the predicted result, it becomes possible to continue to execute highly accurate density prediction. Fig. 16 is a flow diagram for creating a composite correction LUT from the calculation results of the actual measurement density and the predicted density in this embodiment.
[0097] First, the temperature and humidity conditions in which the image forming apparatus is currently used are grasped. A common method is a detection method using an environmental sensor installed in the image forming apparatus that can detect temperature and humidity. The environmental sensor determines whether the temperature inside the apparatus is within a predetermined range, for example, 15°C to 35°C, and whether the relative humidity is within a predetermined range, for example, 10% to 70% (S1601). Here, the object of the determination may be either temperature or humidity. If the conditions are met, it is determined that the accuracy of the predicted control is likely to be higher than the accuracy of the actual control, and the process proceeds to the determination flow of S1602. In S1602, it is determined whether the usage amount of the drum or the developer is both within a predetermined range, for example, between 5% and less than 80% (S1602). When the drum or the developer is replaced as a unit, they are collectively called a developing section or a developing unit. If it is determined in S1602 that the usage amount is within the predetermined range, it is determined that the accuracy of the predicted control is likely to be higher than the accuracy of the actual control, as in the previous step, and the process proceeds to the determination flow of S1603.
[0098] In S1603, it is determined whether the average image duty per 10 sheets of the printed image data is less than a predetermined value, for example, 30% (S1603). If it is determined in S1603 that the duty is less than the predetermined value, it is determined that the criteria set in S1601, S1602, and S1603 are achieved and the usage situation is one in which the accuracy of the predictive control is higher than the accuracy of the actual measurement control. Then, as shown in S1605, the reflection rate of the actual measurement control is determined to be 30% and the reflection rate of the predictive control is determined to be 70% (S1605). The criteria set in S1601, S1602, and S1603 are whether the usage conditions are included in the learning data acquisition conditions when creating the concentration prediction model. That is, the learning when creating the concentration prediction model is performed in an environment that satisfies all of the conditions in S1601 to S1603. If it is within the range of the learning data acquisition conditions, the accuracy of the concentration prediction control tends to be high because it is a learned usage condition. Therefore, it is possible to increase the reflection rate of the predictive control.
[0099] On the other hand, if it is determined in each of the determination steps S1601, S1602, and S1603 that the amount of use of the intermediate transfer belt is not within any of the predetermined ranges, the process proceeds to the determination flow of S1604. The steps of S1604, S1606, and S1607 are similar to the steps of S1201, S1202, and S1203 in FIG. 12 described in the first embodiment, and therefore will not be described here. However, the reflection rate is different from that in FIG. 12, and if it is determined in S1604 that the amount of use of the intermediate transfer belt is less than 80%, then in S1606, 70% is weighted to the actual measurement control and 30% is weighted to the predictive control. On the other hand, if it is determined in S1604 that the amount of use of the intermediate transfer belt is 80% or more, then in S1607, 50% is weighted to the actual measurement control and 50% is weighted to the predictive control.
[0100] In the steps up to this point, the reflection rates of the actual measurement control and the predictive control in the density correction have been determined, so the process moves to the flow shown in S1608 to S1612. This flow from S1608 to S1612 is similar to the flow from S1204 to S1208 in FIG. 12 described in the first embodiment, so a detailed description will be omitted. In steps S1608 and after, the density by the predictive control and the density by the actual measurement control are weighted-averaged with weights determined according to whether the tested conditions are met or not, and the final density (or gamma characteristic) is determined. Then, the gradation correction table is updated according to the final density or gamma characteristic.
[0101] The duty factor referred to in S1603 may be, for example, in the case of an electrophotographic method, the ratio of the time that the light source that exposes the photoconductor is on to the time required for image formation, or the ratio of the area on which toner is placed to the area of the recording region. In the case of full-color image formation, it may be the duty factor for each color component, or the total duty factor for all colors. In any case, it is sufficient if it is the same as the condition during learning.
[0102] In addition, in steps S1601 to S1603, it is determined whether the conditions when the concentration prediction model by machine learning was created are satisfied, but other conditions may be added, or at least one of the conditions tested here may be satisfied.
[0103] According to this embodiment, in the calibration for the color and density gradation stabilization control, two density calculation methods are used in combination: one is to measure the formed image pattern and calculate the color and density values, and the other is to calculate the color and density values using a prediction model. In this case, by providing a judgment step for changing the reflection rate of each density calculation value in the correction depending on the situation in addition to the judgment conditions of the first embodiment, it is possible to more accurately grasp the actual density change situation and provide a highly accurate density correction control.
[0104] [Other embodiments] The above embodiment has been described by taking an electrophotographic image forming apparatus as an example. However, as long as the gamma characteristics of the image forming apparatus are corrected using a tone correction table, the present invention can be applied regardless of the image forming mechanism. However, in the case of a method that does not use an intermediate transfer body like the electrophotographic method, such as an inkjet method, the actual measurement control requires measuring an image for measurement formed on a recording medium such as paper, and therefore requires a configuration for this purpose.
[0105] The present invention can also be realized by a process in which a program for implementing one or more of the functions of the above-described embodiments is supplied to a system or device via a network or a storage medium, and one or more processors in a computer of the system or device read and execute the program. The present invention can also be realized by a circuit for implementing one or more of the functions, such as an ASIC.
[0106] The invention is not limited to the above-described embodiments, and various modifications and variations are possible without departing from the spirit and scope of the invention. Accordingly, the following claims are appended to apprise the public of the scope of the invention. [Explanation of symbols]
[0107] 1: photoconductor drum, 2: charging device, 3: exposure device, 4: developing device, 6: transfer device, 200: intermediate transfer image density sensor, 300: printer controller
Claims
1. an image forming means for forming an image based on image forming conditions; an acquisition means for acquiring information correlated with a change in density of an image formed by the image forming means; a measuring means for measuring the measurement image formed by the image forming means; a generation means for determining first density information from the information acquired by the acquisition means, determining second density information from the measurement results of the measurement image by the measurement means, and generating the image formation conditions based on a weighted average of the first density information and the second density information.
2. the image forming conditions are a gradation correction table used to convert image data, 2. The image forming apparatus according to claim 1, wherein said image forming means forms said image based on said image data converted based on said gradation correction table.
Citation Information
Patent Citations
Image processor and control method therefor
JP2000238341A
Image forming apparatus
JP2003167394A
Image forming apparatus and method of controlling the same
JP2017037100A
Image formation device, tone correction method, and tone correction program
JP2017123605A
Image processing system, image processing method and image processing program
JP2020152030A