JP2000004362A - Image forming device - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide an image forming device capable of notifying the correction state of gradation correction. SOLUTION: This image forming device decides an operation coefficient, that is used for γ-correction which performs image processing so as to obtain the desired gradation characteristics (step S7 to S11). When the correction of the operation coefficient to be used for the γ-correction is instructed (steps S13 and S14), a test pattern and an original image on a platen are composited and are subjected to copy output, when it is not an test pattern reading mode (step S17 to S19). When it is test pattern mode, a test pattern is read and the correction of the operation coefficient, a correction situation, removing number of corrections, etc., are notified (step S20).

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an image forming apparatus, and more particularly, to an image forming apparatus for copying a document.

[0002]

2. Description of the Related Art Conventionally, as a tone correction technique by an image forming apparatus, Japanese Patent Publication No. 7-46379 and Japanese Patent Application Laid-Open
Conventional techniques such as Japanese Patent No. 47458 are disclosed. According to the technique disclosed in Japanese Patent Publication No. 7-46379, a color patch is output and read, and color correction characteristics are calculated and determined from data at the time of output and at the time of reading. According to the technique disclosed in Japanese Patent Application Laid-Open No. 9-247458, a color patch is output and read, a coefficient for the next and subsequent gamma correction calculations is determined and changed based on the read data and the recording medium read data. A technique for performing this is disclosed. The calculation of the image forming parameter and the γ correction at the time of the gradation correction disclosed in these prior arts is difficult to converge to the target value at a time, and the accuracy deteriorates, and it does not readily converge to the target value. Approach the goal
By performing the correction operation a plurality of times, the correction calculation is performed such that the correction value falls within the range of the target value, that is, the threshold value.

[0003]

However, in the technology disclosed in Japanese Patent Publication No. 7-46379 and Japanese Patent Application Laid-Open No. 9-247458, the number of correction operations required to reach a target allowable range depends on the environmental and environmental conditions. The operator did not know how many times the correction operation should be performed because of differences due to machine differences and the like. In addition, the operator can be notified of the predetermined recommended number of operations, but if the target is reached with the number of operations less than the recommended number of times, the correction operation is performed up to the recommended number of times, so that the correction operation continues unnecessarily. There was a problem that would be done.

SUMMARY OF THE INVENTION The present invention has been made to solve the above-described problem, and has as its object to provide an image forming apparatus that allows an operator to easily confirm the correction state of gradation correction.

[0005]

According to an aspect of the present invention, there is provided an image forming apparatus comprising: a reading unit for reading a document as image data; and a unit for forming a test pattern for correcting an operation coefficient for processing an image. And a printer unit for combining and outputting the read image data and the test pattern.

According to another aspect of the present invention, there is provided an image forming apparatus for forming a test pattern based on an operation coefficient, a printer unit for outputting the test pattern, and reading the output test pattern as image data. Correction means for correcting the operation coefficient based on the obtained image data, wherein the correction means includes a correction number notification means for notifying the number of corrections of the calculation coefficient based on the number of corrections made in the past. I do.

According to another aspect of the present invention, there is provided an image forming apparatus for forming a test pattern based on an operation coefficient, a printer for outputting the test pattern, and reading the output test pattern as image data. Correction means for correcting the operation coefficient based on the image data obtained, the correction means including a correction status notifying means for notifying the correction convergence degree of the operation coefficient.

According to another aspect of the present invention, there is provided an image forming apparatus for forming a test pattern based on an operation coefficient, a printer for outputting the test pattern, and reading the output test pattern as image data. Correction means for correcting the operation coefficient based on the obtained image data, the correction means predicting the number of times necessary for the correction operation from the obtained image data and the desired gradation characteristic and reporting the number of remaining corrections It is characterized by including notification means.

According to the present invention, it is possible to notify the user of the state of the gradation adjustment, so that it is possible to provide an image forming apparatus that allows the operator to easily confirm the correction state of the gradation correction.

[0010]

FIG. 1 is a sectional view showing the overall configuration of an image forming apparatus according to an embodiment of the present invention. Referring to FIG. 1, the image forming apparatus includes an image reader unit 2 for reading a document image, and a printer unit 1 for reproducing the read image.

In the image reader section 2, a document table 4
The original placed on the original 0 is exposed by a scanner 41, and the reflected light is detected by a reading optical unit 43 including a CCD sensor 42, and R, G, and B of each pixel are obtained by photoelectric conversion.
It is read as a multi-valued electrical signal of color. The multi-valued electric signal is converted into analog data of the reflectance by the image signal processor 44.
Is input to

FIG. 2 is a block diagram showing the configuration of the image signal processing section 44. Referring to this figure, the CCD sensor 4
The flow of processing of an image signal from the second through the image signal processing unit 44 to the printer unit will be described. Image signal processing unit 44
Represents the reflectance data of R, G, and B from the CCD sensor 42 after the offset and gain correction,
The data is converted into a multi-value digital value by the D converter 100, and then the shading correction unit 102 performs shading correction. The corrected digital value is converted into density data by the log conversion circuit 104. Next, in order to improve black reproduction by the under color removal and black printing circuit 106,
The common part of the three color data is calculated as black data, and the black data is subtracted from the three color data. And
In the masking processing circuit 108, R, G, and B data are converted into Y, M, C, and Bk signals. Then, the density correction circuit 110 corrects the density by multiplying the data of Y, M, C, and Bk by a predetermined coefficient, and performs smoothing of the data by the spatial frequency correction circuit 112, and the like.
The processed data is sent to the printer unit 1 as print data.

Returning to FIG. 1, the description will be continued. In the printer section 1, a photosensitive drum 10 is mounted on the right side of the central portion so as to be rotatable in the direction of arrow f. Around the photosensitive drum 10, a transfer drum 20 is installed so as to be rotatable in the direction of arrow g. Further, a charging charger 11, magnetic brush type developing devices 12 to 15, a transfer charger 23, a residual toner cleaning device 16, and an eraser lamp 17 are sequentially arranged around the photosensitive drum 10. The image is exposed on the photosensitive drum 10 by the print head unit 50 immediately after the charging process. On the other hand, the sheet suction chargers 24 and 25 and the separation claw 26 are arranged around the transfer drum 20.

The print head unit 50 performs gradation correction, that is, γ correction, on the input signal in accordance with image reproducibility such as a photoconductor and development characteristics, and then generates exposure data by D / A conversion. Based on the exposure data, the laser is driven by the print head unit 50 to expose the rotatably driven photosensitive drum 10. The photosensitive drum path 10
Before being exposed to light, it is irradiated by an eraser lamp 17 and is charged by a charger 11. When exposure is performed in this state, an electrostatic latent image of the document is formed on the photosensitive drum 10. The developing devices 12 to 15 contain a two-component developer composed of a toner and a carrier, and face the photosensitive drum 10 to visualize the electrostatic latent image with a toner of a corresponding color.

On the other hand, the printer section 1 is provided with three automatic paper feed units 61, 62 and 63. The size of the paper loaded in each unit is detected by sensors SE11 to SE13, respectively. The paper fed and conveyed from the automatic paper feed units 61, 62 and 63 is fed onto the transfer drum 20 in synchronization with the suction position, and the paper suction roller 22, the paper suction charger 21
Is electrostatically attracted onto the transfer film. The developed image on the photoconductor drum 10 is transferred to the sheet adsorbed on the transfer drum 20 by outputting the transfer charger 23.

After the process operations of image reading, latent image formation, development, and transfer as described above are repeated for the required number of colors (four times in the case of normal full-color image formation), the paper is transferred from the transfer drum 20. Separation chargers 24 and 25, Separation claw 2
6 separated. Then, the toner image is conveyed to the fixing device 30 via the conveyance device 27, where the toner image is heated and fixed on the paper and discharged to the paper discharge tray 31.

Referring to FIG. 3, the image forming apparatus further includes a printer control unit 201, a control ROM (Read Only Me
mory) 202, data ROM 203, RAM (Random A)
ccessMemory) 204, an operation panel 205 including a reset key 206 and a mode setting section 250, etc., a V sensor (surface potential sensor) 207, a photoconductor driving counter 208, an environment sensor 209, a developing device driving counter 210, a developing device driving circuit 211, Toner supply driving device 212, Vb generation unit 213, AIDC sensor (density sensor) 21
4. Light source 216, light source driving unit 217, D / A conversion circuit 2
18, γ correction unit 219, light emission signal generation circuit 220, Vg
Includes a generation unit 221.

FIG. 4 is a plan view of the operation panel 205. The mode setting unit 250 is a liquid crystal display touch panel, and switches the display according to an instruction from the operator. Numeric keypad 25
The 1 and clear keys 252 are keys for inputting numerical values such as the number of copies. The start key 253 is a key for starting a printing operation or a correction operation, and the like, and the stop key 254 is a key for stopping these operations.

The printer control unit 201 includes a control ROM 2
02, a data ROM 203 and a RAM 204 are respectively connected. The control ROM 202 stores various control programs. The data ROM 203 stores various data necessary for automatic density control and γ correction control described later. The printer control unit 201 controls the control RO.
The print operation is controlled based on various data stored in the M202, the data ROM 203, and the RAM 204, and an automatic density control, a γ correction control, and the like, which will be described later, are performed.

The printer control unit 201 is further connected with an operation panel 205, a photosensitive member drive counter 208, and an environment sensor 209. Printer control unit 20
Reference numeral 1 further connects an AIDC sensor 214, a developing device drive counter 210, and a V sensor 207. Various operation commands are input from the operation panel 205 to the printer control unit 201, a reset signal is input from the reset button 206, and the photoconductor 1 is input from the V sensor 207.
The detection signal of the surface potential of 0 is input and the AIDC sensor 2
A detection signal indicating that the amount of toner adhering to the surface of the photoconductor 10 is optically detected is input from 14, a signal indicating the number of times the photoconductor 10 has been driven is input from the photoconductor drive counter 208, and an environment sensor 209 is input. A signal indicating environmental characteristics such as temperature and humidity is input, and the developing device driving counter 21
From 0, a signal indicating the number of driving of the developing devices 12 to 15 is input, and reflectance data is input from the CCD sensor 42.

The printer control unit 201 performs automatic density control and γ correction control, which will be described later, based on the various types of input information. Therefore, a Vg generation unit 221 for generating a grid potential Vg of the charger 8 and each of the developing devices 12 to
The Vb generation unit 213 that generates 15 development bias potentials Vb is controlled. In addition, the printer control unit 201
The light emission data for γ correction calculated by a predetermined process described later is output to the γ correction unit 219. The γ correction unit 219 performs γ correction on the 8-bit image data output from the image signal processing unit 4 based on the input γ-correction emission data, and outputs the corrected image data to a D / A conversion circuit. The signal is converted into an analog signal by 218 and output to the light source driving unit 217. The light source drive unit 217 causes the light source 216 to emit light according to the input analog signal based on the control of the light emission signal generation circuit 220 controlled by the printer control unit 201. In the test pattern reading mode, the printer control unit 201 corrects the γ correction calculation coefficient based on the reflectance data from the CCD sensor 42.

The image forming apparatus of the present embodiment is configured as described above, and performs gamma correction control (image density stabilization control) by calculating the gamma correction emission data used for gamma correction of image data as needed within the apparatus. ). In the present embodiment, sensing is performed by multipoint input of the V sensor and the AIDC sensor, and γ correction light emission data is calculated and created for each image forming operation. Further, in the present embodiment, the coefficient for the γ correction calculation is corrected in the test pattern reading mode. Hereinafter, the gamma correction control according to the present embodiment will be described in detail using a flowchart.

FIG. 5 is a main flowchart of the printer control system of the image forming apparatus shown in FIG. Referring to FIG. 5, when the power of the image forming apparatus is turned on, first, in step S1, an AIDC calibration process is executed.

Next, the AIDC calibration process will be described in more detail. FIG. 6 is a flowchart for explaining the AIDC calibration process.

Referring to FIG. 6, first, in step S21, the AID at a solid level at which the amount of adhered toner is maximized.
A grid potential Vg for obtaining the output Vab of the C sensor,
Each maximum output of the developing bias potential Vb and the exposure amount LD is set.

Next, in step S22, a photoreceptor background level and solid level detection process is executed. First, a test toner image is created under the conditions set in step S21,
The output Vab of the AIDC sensor at this time is detected. Also, the AI at the photoconductor background level without the toner image
The output Van of the DC sensor is detected. Next, based on this, the relationship between the output of the sensor and the toner adhesion amount (output characteristic of the AIDC sensor) is standardized and stored in the RAM 204. In step S23, five types of test toner images are created for each color, that is, two colors, based on the predetermined grid potential Vg and the developing bias potential Vb and five different exposure levels. FIG. 6 shows the exposure level at this time.
1 (32 gray levels), 3 (64 gray levels), 5 (96 gray levels), 9 (160 gray levels), 10 (192 gray levels) A test toner image is created with the five gradations.

Next, in step S24, the output Vab of the AIDC sensor for the test toner image created for each color is detected, and step S2 is performed on the detected output Vab and the output Van of the AIDC sensor at the background level.
The toner adhesion amount is obtained from the relationship between the sensor output and the adhesion amount created in step 2.

Next, in step S25, based on the amount of adhered toner obtained at step S24, the amount of adhered three exposure in 0.05mg / cm ² ~0.5mg / cm ² in the region for each color The quantity level is selected from FIG. 7 and stored.

Exposure is performed so that the toner adhesion amount falls within the above range.
The choice of quantity level is based on the following reasons. With toner
Specularly reflected light on the surface of the photoreceptor 10 as the deposition amount increases
The output of the AIDC sensor 214 becomes
descend. Therefore, the detection sensitivity of the sensor also decreases,
When the adhesion of the toner exceeds a certain amount, the AIDC sensor 2
The output of 14 is completely saturated. As a result, the sensor
In order to improve the detection accuracy of
Means that the toner adhesion amount is about 0.05 mg / cm ^Two~ 0.
5mg / cm^TwoIt is preferable to use a region that becomes

Referring again to FIG. 5, after the AIDC calibration processing, in step S2, the AIDC detection processing is executed. This process is a subroutine for obtaining the toner adhesion amount using the AIDC sensor 214.

First, 12 kinds of test toner images of three levels of exposure amount × 4 colors are prepared under predetermined grid potential Vg and developing bias potential Vb. The three exposure levels are the three exposure levels selected in step S25. The amount of toner attached to each of the test toner images created is detected using the AIDC sensor 214.
That is, the toner adhesion amount corresponding to the output of the AIDC sensor 214 is obtained using the output characteristics of the AIDC sensor obtained in step S22.

Hereinafter, the AIDC detection processing will be described in more detail. FIG. 8 is a flowchart illustrating the AIDC detection process.

Referring to FIG. 8, first, in step S51, a predetermined grid potential Vg (the same potential as in step S23), a developing bias potential Vb (a potential switched for each color based on the predicted dark decay rate), and Under the conditions of the three exposure levels selected in S25, three test toner images (low-density side test toner image M1, middle-density level test toner image M)
2. The test toner M3) on the high density side is created for each color.

Next, in step S52, the photosensitive member 1
The density of the test toner image is detected by an AIDC sensor 214 provided near 0. The output value Va detected for each color is processed in the same manner as in step S1.
The output characteristics of the AIDC sensor stored in the RAM 22 are stored in the RAM 20.
4, the output Va of the AIDC sensor is converted into a toner adhesion amount using the output characteristics.

Next, in step S53, the process of determining and updating the next exposure level of the launch of the test toner image is performed based on the result of step S52. That is, from the next time, the three exposure levels of the test toner image created in step S51 are set in step S51 for each color.
It is determined by the data updated at 53. Therefore, as will be described later, after the copy is completed, the process in step S1 is always performed.
Instead of performing the AIDC calibration process, the process returns to the AIDC detection process of step S2, and determines the next three exposure levels when the normal test toner is detected in step S2.

Referring again to FIG. 5, in step S3, V (photoconductor surface potential) detection processing is performed. The V detection process is a process of detecting the surface potential of the photoconductor 10 using the V sensor 207. More specifically, a latent image pattern (test pattern) is created at ten exposure levels (different from the exposure steps shown in FIG. 7) under the conditions of a predetermined exposure and a grid potential Vg. The surface potential of each latent image pattern formed on the photoconductor 10 is detected by 207. In addition, in order to improve the detection accuracy of the surface potential, when the power is turned on, the exposure amount and the grid potential Vg are switched in three stages, and in each stage, a latent image pattern is formed at ten exposure levels, and 3 × 10 The surface potential of the point is detected. Also,
When the power is turned on, the surface of the photoreceptor is erased by the eraser lamp 17 after detecting the surface potential of 3 × 10 points, and the surface potential Vr after the erase is detected. In other cases, after the surface potential of 10 points is detected, the erase is performed. The detected photoconductor surface potential Vr is detected. In this process, the surface potential is detected using the V sensor 207, but the surface potential may be directly predicted by a predetermined calculation without directly detecting the surface potential.

The detection operation is completed by the above-described steps S1 to S3, and the arithmetic processing is performed thereafter.

Next, the photoconductor sensitivity characteristic calculation processing in step S4 shown in FIG. 5 will be described in detail. FIG. 9 is a flowchart illustrating the photoconductor sensitivity characteristic calculation process. Referring to FIG. 9, first, in step S161, a photoconductor sensitivity characteristic approximate expression creating process is performed. Next, in step S162, a charging efficiency calculation process is executed. Next, in step S163, prediction processing of each position of the photoconductor sensitivity characteristic is executed, and the process proceeds to step S5.

Next, the above-described process for creating the approximate expression of the photoreceptor sensitivity characteristic will be described in more detail. FIG. 10 is a flowchart for explaining the photoconductor sensitivity characteristic approximation formula creation processing.

First, in step S171, the sensitivity characteristics of the photoconductor 10 are calculated. Specifically, the photoconductor light attenuation curve is approximated using the data of the surface potential of the photoconductor 10 with respect to the ten-level latent image pattern detected in step S3. Since the photoreceptor light attenuation curve has a simple attenuation characteristic, it can be approximated in the form of V × ea ^{* x + b} , and each coefficient is obtained by the least square method.

Next, a method of forming an approximate expression of the photosensitive member light attenuation curve will be described below. Step S as described above
Based on the surface potential V of the photoreceptor detected by the detection data of No. 3, an approximation including a ripple of exposure is performed so that an effective development potential can be calculated. That is, what can be detected by the electrometer is considered to be the average potential due to the exposure ripple, and here, the coefficient of the following approximate expression is obtained by the least square method in the form of the average potential of the maximum value and the minimum value of the ripple.

V = (Vbi−Vr) × (e ^{(−B * E (n) * D / Ks)} + e
^{(−A * E (n) * D / Ks)} ) / 2 + Vr (1) B = 2-A + 0.18 × (A-1) ³ (2) where Vbi: surface potential under bias exposure ( ≠
V ₀ ), Vr: residual potential, E (n): average exposure amount minus bias light amount (modulation exposure amount for each gradation), A: local maximum value (coefficient) under average exposure, B: average exposure amount , Ks: sensitivity coefficient of the photoconductor, D: exposure lighting ratio with respect to the modulation time, n: gradation for the test pattern (n = 1 to 10), and “*” in the exponent part is “ Multiplication "
Is shown. In this embodiment, a semiconductor laser (laser diode) is used as a light source for image writing. In order to improve the response of laser diode emission,
The bias current is constantly applied, and the laser diode emits light spontaneously. Therefore, Vbi described above indicates the photoconductor surface potential under the exposure of the spontaneous light emission.

In the above approximate expression, the surface potential Vbi under bias exposure is set as the initial value of the attenuation due to ease of detection and reliability. Using the coefficient obtained by the above approximate expression, it is possible to calculate the surface potential V of the photoconductor at an arbitrary grid potential Vg and an exposure amount under an actual use environment.

Next, in order to obtain the coefficients A, B, and Ks of the above-described approximate expression using the least squares method, it is necessary to first determine an initial value. The initial value Ks0 of Ks is determined by the following equation.

[0045]

(Equation 1)

Here, Vs (n): average surface potential (detection potential of each gradation), m: grid potential V of the charged charger
g, where the initial value of A is 1.4.

According to the above-described processing, when the power is turned on, the exposure amount and the grid potential Vg are switched three times to detect the surface potential of the photoreceptor. A characteristic curve is created. FIG.
FIG. 4 is a diagram illustrating sensitivity characteristics of the photoconductor when power is turned on. Since the surface potential is detected only once except when the power is turned on, a sensitivity characteristic curve of one photosensitive member is created.
Note that Ks and A obtained by the above processing are V
Since it is a coefficient for obtaining the surface potential of the photoconductor at the position of the sensor, it is referred to as Ksv and Av in the following description.

Referring again to FIG. 10, next, in step S172, the calculation processing of coefficient A is executed as described above. Next, in step S173, it is determined whether or not there is a coefficient A between a predetermined maximum value Amax and a predetermined minimum value Amin. If the coefficient A is between Amin and Amax, the process proceeds to step S174; otherwise, the process proceeds to step S176. Next, in step S176, the coefficient A is changed to a predetermined value As. As As, the coefficient A calculated last time or a predetermined set value is used.

Next, in step S174, the calculation process of the coefficient Ks is executed as described above. Next, in step S175, a predetermined minimum value Ksm
It is determined whether or not there is a coefficient Ks between in and the maximum value Ksmax. If the coefficient Ks is within the above range, the process proceeds to step S162; otherwise, the process proceeds to step S177.
Move to. Next, in step S177, the coefficient K
s is changed to a predetermined value Kss. As Kss, the coefficient Ks calculated last time or a predetermined value set in advance is used.

As described above, the result of the previous calculation or the set value of the initial is compared, and if the difference or ratio differs by more than the set threshold value, the value is regarded as irregular, and Or the initial set value may be adopted to proceed to the next stage. Further, when the irregular calculation result continues for the set threshold value more than a predetermined number of times, the photoconductor 10, the charging charger 11, the V
It may be displayed that one of the g generation unit 221 and the V sensor 207 is defective. further,
The above calculation result may be reset automatically by the reset button 206 or by exchanging the photoconductor 10, the developer, the AIDC sensor 214, the V sensor 207, and the like.

Next, the charging efficiency calculation process will be described in detail. FIG. 12 is a flowchart illustrating the charging efficiency calculation process. First, step S181
In, a charging efficiency calculation process is executed. That is,
The charging efficiency of the photoconductor 10 is calculated using the surface potential detected in step S3. The charging efficiency is used to calculate a grid potential Vg for obtaining a desired surface potential described later. The calculation of the charging efficiency is based on the grid potential Vg.
Is obtained as a linear expression.
This linear function is a function that does not originally have an intercept or a function that has the post-erase potential Vr as an intercept, but is approximated by the following expression in a form having an intercept to improve the accuracy near actual use.

Vbi = α × Vg + β (4) where α is the charging efficiency and β is the intercept. From the above equation, for example, the relationship between the surface potential and the grid potential shown in FIG. 13 is obtained. Α and β determined by the above equation
Are coefficients at the position of the V sensor 207, and are referred to as αv and βv in the following description.

Referring again to FIG. 12, next, in step S182, it is determined whether or not the calculated charging efficiency α is larger than a preset minimum value αmin and smaller than a maximum value αmax. If this condition is satisfied, the flow shifts to step S186 to determine that the charging efficiency α is a normal value, and shifts to step S163.

On the other hand, if the above condition is not satisfied, the flow shifts to step S183, where it is determined that charging or laser emission is abnormal. Next, the process shifts to step S184 to execute a service call process. Next, step S185
In, the device is stopped.

According to the above processing, when there is an abnormality in the data used for generating the light emission characteristic data for γ correction such as the coefficient A, Ks, charging efficiency α, etc., it is possible to change the data to predetermined data and maintain the data. Is warned to the user that it is necessary, and the device can be stopped. As a result, the user does not use the apparatus in an abnormal state, but can always use the apparatus in a good state.

Also, the result of the previous calculation or the set value of the initial is compared, and if the difference or ratio differs by more than the set threshold value, the value is regarded as irregular and the result of the previous calculation is determined. Alternatively, the initial set value may be adopted to proceed to the next stage. Further, if the calculated result of the irregularity continues more than the set threshold value for a predetermined number of times, it is displayed that any one of the photoconductor 10, the charging charger 11, the Vg generating unit 221, and the V sensor 207 is defective. It may be. Further, the above calculation result is obtained based on the photoconductor 10, the developer, the AIDC sensor 21.
4. Reset may be performed automatically or by reset button 206 by replacing V sensor 207 or the like.

Referring again to FIG. 9, next, in step S
In 163, the photosensitive characteristic curves of the photoconductor 10 at the respective developing positions of the developing devices 12 to 15 are predicted. Each coefficient obtained in the above processing is a coefficient at the position of the V sensor. Therefore, the coefficient at each development position is calculated by a proportional calculation with respect to the coefficient at the position of the V sensor. The calculation of the photosensitive characteristic of the photoconductor at each development position cannot be directly calculated in a series of γ correction control, and therefore is calculated using an empirical rule described below.

Regarding the empirical rule, analysis of variance was conducted by experiment using environment, film thickness, paper passing mode, pause mode, beam diameter and the like as control factors. As a result, the contribution rate is high (5%
The above effect is stored in the data ROM 203 as a look-up table for each control factor as predetermined data, and the position of the V sensor 207, Av,
The respective ratio of each development position to Ksv, αv, βv can be obtained.

FIG. 14 is a diagram showing the sensitivity characteristics of the photoconductor at each developing position obtained by the above calculation. In FIG. 14, the uppermost curve is a curve showing the sensitivity characteristic of the photoconductor at the position of the V sensor 207.
Curves indicating the sensitivity characteristics of the photoconductor at each of the developing positions Nos. To 15 are sequentially shown. By the above processing, the V sensor 207
The coefficients at each developing position are obtained by using the coefficients at the positions (1) and (2), and finally the sensitivity characteristics of the photoconductor at each developing position can be obtained.

Referring again to FIG. 4, next, in step S
In 5, the amount of LD power (maximum exposure during image formation) is optimized. The LD power light amount is uniquely determined by the condition of the photoconductor regardless of the developing condition. The LD power light amount Pmax (i) is determined to be about 2.5 times the half-reduced light amount Eh (i) at each development position based on the photoconductor sensitivity characteristics predicted at each development position. The half light quantity Eh (i) is obtained by exposing a photoconductor charged at a certain potential at an exposure position, and thereafter, when the photoconductor reaches each developing position,
This is the exposure amount at which the potential of the photoconductor is reduced by half.

The following equation was used in calculating the LD power light amount. V = (Vbi−Vr) × (e ^{(−B (i) * Eh (i) * D / Ks (i))} +
e ^{(−A (i) * Eh (i) * D / Ks (i))} ) / 2 + Vr (5) V = (Vbi−Vr) / 2 + Vr (6) V = (Vbi−Vr) × (e ^{(-A (i) * Eha (i) * D / Ks (i))} )
+ Vr (7) V = (Vbi−Vr) × (e ^{(−B (i) * Ehb (i) * D / Ks (i))} )
+ Vr (8) V = (Vbi-Vr) / 2 + Vr (9) where i = 1 to 4 (where i = 1 is the yellow developing device 12, i = 2 is the magenta developing device 13, i = 3
Indicates the cyan developing device 14, i = 4 indicates the black developing device 15, and Eh (1) to Eh (4) indicate the half-decrease light amount at each of the yellow, magenta, cyan, and black developing positions. A (1) to A (4), B (1)
B (4) and Ks (1) to Ks (4) indicate coefficients at the respective development positions. ). To calculate the LD power light amount, Eh (i) that satisfies Expression (6) of Expression (5) may be obtained. Eha (i) and Ehb that are Expressions (9) of Expressions (7) and (8) are used. (I) was determined, and the average of these values was designated as Eh (i), and the product obtained by multiplying 2.5 times was designated as Pmax (i). That is, Pmax (i) was calculated by the following equation.

Pmax (i) = 2.5 × (−Ks (i)) × ln (1/2) × (1 / A (i) + 1 / B (i)) / 2 (10) Accordingly, the LD power light amount Pmax (i) having a value of about 2.5 times the half light amount at each developing position (i = 1 to 4)
To determine.

When the system speed differs between detection and image formation, for example, when the system speed is increased only during mono-color copying, the integrated light amount per time unit is equivalent to the light amount obtained under the above conditions. The LD light amount is determined as described above.

Next, the development efficiency calculation processing shown in step S6 of FIG. 5 will be described in detail. FIG. 15 is a flowchart for explaining the development efficiency calculation process. First, in step S191, an effective development potential calculation process is performed.

More specifically, the effective developing potential of the test pattern of 3 tones × 4 colors (hereinafter referred to as AIDC pattern) created in step S2 is determined. Here, the calculation is performed by inputting the conditions at the time of pattern creation using the predicted sensitivity characteristics of the photoconductor at each development position.

First, the average developing potential Ve (i, n) is determined by the following equation. Ve (i, n) = (Vbi (i) −Vr) × (Ks (i)) / {(B (i) −A (i)) × E (n)} × (e ^{(−B (i) * E (n) * D / Ks (i))-} e ^{(-A (i) * E (n) * D / Ks (i))} ) + Vr (11) Next, each developing position in uniform exposure V (C) = Vb + V
The light quantity C (i) in mg is obtained by the following equation.

C (i) = Ks (i) × ln {(Vbi (i) −Vr) / (Vb (i) + Vmg (i) −Vr)} (12) where Vmg is the fogging potential ( (Development start potential) correction coefficient, the initial value of which is 0.

Next, the effective development potential ΔVe (i, n) of the AIDC pattern is calculated. In the calculation, when the exposure ripple is sufficiently larger than the developing bias potential Vb,
It is divided into three cases: when it is over the developing bias potential Vb, or when it is sufficiently small.

First, (C (i) / B (i)) <E (n)
At the time of × D (when the ripple is sufficiently larger than Vb), it is calculated by the following equation.

ΔVe (i, n) = Vb (i) + Vmg (i) −Ve (i, n) (13) Next, (C (i) / A (i)) <E (n) × D <(C
When (i) / B (i)) (when straddling Vb), it is obtained by the following equation.

ΔVe (i, n) = [− 1 / {(A (i) −B (i)) × E (n) × D}] × {Ks (i) × (Vbi (i) −Vr) × e ^{(−A (i) * E (n) * D / Ks (i))} + (A (i) × E (n) × DC (i) −Ks (i)) × (Vb (i + Vmg (i) −Vr)｝ (14) Finally, when (C (i) / A (i))> E (n) × D (when it is sufficiently smaller than Vb), it is obtained by the following equation.

ΔVe (i, n) = 0 (15) Referring again to FIG. 15, in step S 192, a development efficiency calculation process is performed for each color, and the flow advances to step S 7.

More specifically, the developing efficiency is obtained from the toner adhesion amount obtained in step S2 and the effective developing potential obtained by calculating the effective developing potential. The relationship between the adhesion amount and the effective development potential is approximated by a linear equation, and the slope and intercept thereof are obtained. The inclination at this time is defined as the development efficiency. Originally, the intercept of the primary equation should be 0, but it does not always fog out from the level of the developing bias potential Vb.
It will have some value. Therefore, the intercept is used as the fog potential correction coefficient Vmg.

The actual fog potential correction coefficient Vmg is calculated from the slope (developing efficiency η (i)) and the intercept (ν (i)). FIG. 16 is a diagram showing the relationship between the surface potential and the amount of adhesion. As shown in FIG. 16, the fog potential correction coefficient Vmg (i) can be obtained by the following equation: Vmg (i) = ν (i) / η (i) (16) Vmg calculated here
By recalculating the above-described process of calculating the effective development potential using (i), the development efficiency can be calculated in a form without intercept (ν (i) = 0).

Referring again to FIG. 5, next, in step S
7, the effective developing potential ΔV required for each color
e is calculated. First, the development characteristic curve is approximated. The development characteristics should be a straight line (a linear relationship between the potential and the amount of adhesion), but it is not necessarily linear at the time of high adhesion such as low temperature and low humidity, and low T / C (when the content of the toner to the carrier is low). May not be the case. Therefore, here, the developing characteristic curves of the respective colors are approximated using the developing efficiencies obtained by the above-described processing of calculating the developing efficiencies of the respective colors, with the high-adhesion side slightly dulled.

Next, the effective development potential ΔVe required for each color to obtain a desired maximum adhesion amount (maximum density) is determined based on the LD power light amount obtained in step S5 and the development characteristic curve obtained by the above processing. calculate. First, the transfer characteristics are predicted and calculated in order to make the desired maximum amount of adhesion on the transfer material. Here, the transfer characteristic is predicted by the data RO
At least one of environmental information such as humidity input from the environmental sensor 209, transfer material information input from the operation panel 205, and counter information input from the developing device drive counter 210, using a predetermined coefficient stored in advance in M 203. The correction is performed based on one or more pieces of information. Further, transfer efficiency coefficients d1, d2, d3 for each information are based on environment information input from the environment sensor 209, transfer material information input from the operation panel 205, and counter information input from the photoconductor drive counter 210 at that time. Is read. Next, an effective development potential ΔVe ₍₂₅₅₎ required for each color is calculated using the following equation.

ΔVe ₍₂₅₅₎ = (0.7 + R _0.7 × d1 × d2 × d3) / η (i) (17) Next, in step S8, the grid potential Vg and the developing bias potential Vb, which are image forming parameters, are changed. decide. Specifically, first, the approximate expression of the photoconductor sensitivity characteristic at each developing position obtained in step S163 shown in FIG. 9 is calculated backward to satisfy the necessary effective developing potential ΔVe for each color obtained in the above processing. Bias potential Vb is calculated for each color. At this time, the fog potential correction coefficient obtained in the development efficiency calculation process is also considered.

Next, the sum of the determined developing bias potential Vb and the set fog margin is applied to the surface potential Vbi of each color.
Then, the grid potential Vg for obtaining this Vbi is calculated using the charging efficiency obtained in step S181. At this time,
If either of the ranges of the settable grid potential Vg and the developing bias potential Vb is exceeded, the closest value within the settable range is set, and the other is recalculated according to the values (Vb +
Fog margin or Vbi-fogging margin).

Next, in step S9, a correction potential at the time of multicopy is obtained. That is, the potential for correcting the sensitivity change at the time of multicopy is obtained. Assuming that the charging efficiency does not significantly change during multicopy, the change in the latent image forming system is considered to be due to a change in the sensitivity of the photoconductor 10. Since the LD power light amount is determined based on the sensitivity of the photoconductor, it is considered that the LD power amount can be corrected by normalizing the exposure amount and the potential. When geometrically standardized, the standardization may be performed at the maximum value or the minimum value. However, in this case, since the halftone portion having higher sensitivity has a greater impact on the image, the standardization is performed in the vicinity of the half light amount or at a certain fixed gradation. Is performed. That is, feedback is applied to the LD power light amount so that the potential of the gradation is always constant. However, since the actual detection is performed by the V sensor 207, the V sensor 2
If the potential at the position 07 can be corrected, it is assumed that the potential at the developing position has been corrected.

Specifically, in this process, the potential V1 at the time of irradiation of the exposure amount E1 is calculated by the following equation.

V1 = (Vbi−Vr) × (e ^{(−Bv * E1 * D / Ksv)} + e ^{(−Av * E1 * D / Ksv} )) / 2 + Vr (18) This is the exposure when the γ correction curve is created. It becomes the potential at the time of irradiation of the amount E1.

Next, in step S10, the gamma characteristic during linear light emission is predicted. First, a light amount divided into 255 from the bias light amount to the set LD power light amount is obtained.
Here, for example, a relationship between light emission data and light emission intensity as shown in FIG. 17 is obtained.

Next, for each light quantity, the approximate expression of the photoconductor sensitivity characteristic at each developing position obtained in step S4 and the set grid potential Vg, developing bias potential Vb, and fogging potential correction coefficient are used. Thus, the effective developing potential ΔVe for the 256 gradations is obtained. The relationship between the exposure amount obtained here and the effective development potential ΔVe is, for example, as shown in FIG.
As shown in FIG.

Next, for each of the effective development potentials ΔVe, the toner adhesion amount on the photoreceptor is determined using the development efficiency. The relationship between the effective development potential ΔVe obtained here and the toner adhesion amount on the photoconductor is, for example, as shown in FIG.

Next, the estimated transfer remaining amount is subtracted from the toner adhesion amount on each photoreceptor to obtain the paper adhesion amount. Here, the estimated remaining transfer amount is stored in a look-up table in advance, and is fed back based on information from the environment sensor 209. Assuming that the adhesion amount on paper is PT (n, i) and the adhesion amount of toner on the photoreceptor is PA (n, i), the adhesion amount on paper is expressed by the following equation.

PT (n, i) = PA (n, i) −R (n) × d1 × d2 × d3 (19) Next, the relationship between the amount of adhesion on paper and the density based on the characteristics of the toner is determined. In this process, characteristics measured in advance are stored in a look-up table. For example, the relationship between the amount of adhesion on paper and the density shown in FIG. 20 is stored in advance. Therefore, by obtaining the density on paper using this look-up table, the density for 256 gradations can be calculated. As a result, for example, a γ characteristic curve as shown in FIG. 21 can be obtained.

Next, in step S11, light emission characteristic data for γ correction is created using the γ characteristic curve created by the above processing. In this calculation method, when the γ characteristic curve has a linear characteristic, the γ correction light emission characteristic data to be calculated can be calculated by XY conversion of the γ characteristic curve.

First, the target density (density of the target adhesion amount) and the level 0 of the γ characteristic curve obtained in step S10 are set.
Are standardized by 8 bits. At this time, if the maximum density of the γ characteristic curve does not reach the target density, the standardization gain is adjusted according to the shortage. As a result, for example, density data and light emission data as shown in FIG. 22 are obtained.

Next, the 8-bit data is converted into 10 bits (4 times), and the XY axis is converted. After that, the missing data is linearly complemented. As a result, data shown in FIG. 23 is obtained.

Finally, the data obtained by using the moving average filter is subjected to a smoothing process. As a result, gamma correction light emission characteristic data for linearly converting the gamma characteristic curve created in step S10 is created.

The γ correction control is performed as described above. After step S11, in step S12, various correction state displays described later are displayed on the mode setting unit 250 in the operation panel 205. Then, step S1
In step 3, the operator makes an input through various keys in the mode setting section 250, and in step S14, whether or not to perform a correction operation is set and input. If "no" is input for the correction operation, the gamma correction control is terminated.
If "YES" is input for the correction operation, it is determined in step S15 whether the start key 253 has been turned on. If the start key 253 is not turned on,
Steps S13 and S14 are repeated until turned on. If it is determined that the start key 253 has been turned on, it is determined in step S16 whether or not the test pattern reading mode has been set in the key input process of step S13. If the test pattern reading mode has not been set, the flow advances to step S17 to form an image of a test pattern.

Then, in the next step S18, the original on the original plate is read, and the copying operation is performed by synthesizing the test pattern and the original image. FIG. 26 shows the result. The test pattern is printed on the test pattern printing unit 301 and the document image is printed on the document image printing unit 302. By copying and outputting the machine image state at that time simultaneously with the output of the test pattern in this way, the operator can determine whether or not an acceptable image is output by looking at the copied output. When the operator determines that an acceptable image has been output and determines that no more correction operation is necessary, the correction operation can be terminated when the process reaches step S13.

After the copy is completed in step S19, the process returns to step S1. If it is determined in step S16 that the test pattern reading mode is set, the pattern reading operation described in detail below is performed, and the correction data of the γ correction calculation coefficient obtained here is calculated in step S7 and subsequent steps. To adopt.

Next, a description will be given of the operation of adjusting the coefficient for γ correction calculation using the test pattern reading mode.

FIG. 24 is a flowchart illustrating step S20 in detail. These are the flow from reading the reflectance data of the target pattern of the test pattern printed from the test pattern document, determining the maximum density correction coefficient and the highlight correction coefficient, and transferring the data to the γ calculation unit. It is shown.

The test pattern original is, for example, as shown in FIG.
6 is a gradation pattern of a plurality of colors as shown in FIG. This test pattern is cyan,
The pattern density increases in the order of magenta, yellow, and black, and from left to right. An edge signal detection pattern for automatically detecting the position of the test pattern is provided on the right side of the leading end of the sheet. Then, place the document on the platen 40 and press the start key 2
When 53 is turned on, the test pattern is printed on the test pattern printing unit 301 in steps S17, S18 and S19 in FIG.
The original image obtained by reading the original on the document
Is printed out and printed out. When the test pattern is read (step S20), the document table 4
The reading of the original on 0 is not performed.

Next, the printed test pattern is placed on the document table 40. It is determined that the reading mode is set in step S13 of FIG.
At 20, a pattern is read.

In step S201 of FIG. 24, the test pattern position on the document table is automatically detected. When the above-described edge signal detection pattern is not detected within the predetermined time, it is recognized in step S203 that the test pattern is not correctly placed, the reading mode is stopped, and an error message is displayed on the operation panel. If it is placed correctly, the image is read in step S202 described later with reference to FIG.

Next, image reading will be described in detail with reference to FIG. After a predetermined time from the edge signal detection position as a reference position, the reflectance data of the recording paper itself is read in step S212, and an average value is calculated in step S213. The reading of the reflectance data is shown in FIG.
2 is performed by the image reader unit 2 described with reference to FIG.

Next, in step S214, cyan test pattern data is read. The data reading is set to be performed for each gradation level (a to d) of each test pattern. First, data is read for the gradation level a. In step S215, a threshold value of the reflectance data of the cyan gradation level a is set. In step S216, each read reflectance data is compared with a threshold value. In step S217, data exceeding the threshold value is regarded as irregular, and in step S218, the irregular data is deleted. By doing so, the influence of image noise and the like can be eliminated, and the accuracy of data detection can be increased. In step S219, the average value of the data read in the above-described step is calculated.

Steps S214 to S219 are similarly performed for the cyan test pattern gradation levels b to d, and subsequently, magenta, yellow, and black are repeated.

Referring back to FIG. 24, steps after step S204 will be described. In step S204 and subsequent steps, the maximum density and highlight fog are calculated using the data of the respective gradation levels for each color obtained in step S202. See].

In step S204, the maximum density correction coefficient is determined. Here, data of the gradation level a of each color is used. Since the test pattern in the high density portion is hardly affected by the reflection of the recording paper, the reflectance data of the recording paper obtained in step S213 is not considered. When the data of the recording paper is subtracted from the test pattern data, Lo is obtained.
The error after the g conversion increases.

FIG. 27 is a table for maximum density correction of each color. For example, if the high density part data of cyan is 32, the cyan maximum density correction table indicates
It is determined that the read test pattern density is high, the maximum density correction table is set to +3, and the development efficiency obtained in step S6 in FIG. 4 is corrected using the following equation.

Η (i) ′ = (100 + ts) * η (I) / 100 (20) ts: maximum density correction value of each color obtained from the maximum density correction table η (i): color development efficiency Step S205 In, a highlight portion correction coefficient is determined. Here, data of the gradation level d of each color is used. The read data difference value is calculated in consideration of the reflectance data of the recording paper for the test pattern of the highlight portion.

FIG. 28 is a cyan highlight portion correction table. For example, if the cyan highlight portion data is 37, it is determined that the density of the read test pattern is low, the highlight portion correction table is set to +2, and the fogging potential correction is performed using the following equation. Modify the coefficient.

As described above, the actual fogging potential correction coefficient Vmg was obtained by the equation (16). In this processing, instead of the equation (16), the following equation (16) is used with a slight modification. Equation (21) is used.

Vmg (i) ′ = Vmg (i) + Kmg (i) / η (i) ′ * Vsp (i) (21) where Vmg (i) ′: fogging potential correction to be used in future calculations Coefficient Vmg (i): Fogging potential correction coefficient obtained by calculation Kmg (i): Constant set for each color η (I) ′: Development efficiency of each color obtained by correction of high density portion Vsp (i): Each color highlight correction value is converted to the correction coefficient obtained in steps S204 and S205 by the γ correction calculation unit of the printer control unit 201 in step S204.
7 (step S206).

In step S207, the current number N of correction operations is incremented. In step S208, the degree of correction convergence and the number of remaining necessary correction operations are determined. The degree of correction convergence and the number of remaining necessary correction operations will be described later. Next, step S2
In step 09, the maximum density correction value of each color and the highlight part correction coefficient for the current number of correction operations are stored in the RAM 204.

Here, the determination of the degree of correction convergence and the number of remaining necessary correction operations will be described. The degree of correction convergence can be calculated by a change in η (i) ′ and Vmg (i) ′ with respect to the number N of correction operations. For example, each value is the table No. of each color table in FIGS. Is closer to a value of 0, the degree of correction convergence becomes higher. Thus, for example, the following correction convergence degree is calculated. FIG.
Now, consider the value M (N) for the number N of correction operations. The value at the time of one correction is M (1), and M (2), M (3),... At that time are predicted. here,
The target value of the value is Mt, and the allowable range of the value is Mr- to Mr +. The predicted value of M (2) is represented by the sum of half the difference between the target value Mt and M (1) and the target value Mt. The predicted value of M (3) is represented by the sum of a half value of the difference between the target value Mt and M (2) and the target value Mt. Hereinafter, similarly, the value of N when the predicted value falls within the allowable range (Mr− to Mr +) is set as the number of times of the prediction end correction. Here, the predicted value M (N) is M (N) = ((Mt−M (N−1)) / 2 + Mt.

Using the above calculation method, step S208
Of the correction convergence degree and the number of remaining necessary correction operations are calculated. FIG. 30 is a flowchart illustrating Step S208 in detail. In step S301, predicted values of the maximum density correction value and the highlight correction value of each color obtained from the maximum density correction table shown in FIG. 27 are calculated. For example, looking at the cyan maximum density correction table of FIG. 27, the target value of the cyan maximum density correction pattern data read average value is 16.5, and the allowable range is 14 to 19.
It is. Until it converges within this allowable range, the prediction value is calculated according to the above-described calculation formula, and the number of correction operations is predicted. For other colors, the number of correction operations is similarly predicted. Step S
In 302, the number of correction operations N at which the predicted value falls within the allowable range is calculated for the maximum density correction value and the highlight portion correction value of each color, and is set as the prediction end correction operation number. Then, the remaining necessary number of correction operations is calculated based on the prediction end correction operation number and the current correction operation number N.

In step S209, the maximum density correction value and the highlight portion correction value of each color for the current number of correction operations are stored.

Returning to FIG. 5, the image read by the image reader unit 2 is reproduced by the printer unit 1 in step S21. Based on the calculation result, the current state is displayed on the mode setting section 250 of the operation panel 205 (step S12). FIG. 31 shows a display example of step S12.

The average value of the number of correction operations required for the correction performed in the past, which is stored in advance as an empirical value, is displayed as the recommended number of corrections. For example, when the average value of the number of correction operations required for the correction performed in the past is four, the display is as shown in FIG. Assuming that the number of correction operations performed at this time is one, the degree of convergence at this time is calculated as shown in FIGS.
8 of the correction table shown in FIG. Display as Table No. Table No. indicates that the maximum density correction value and the highlight portion correction value of each color correspond to the table No. in FIGS. It is. The convergence degree is based on the displayed eight table Nos. Among them, it can be determined from how much is 0. Further, the number of remaining necessary correction operations calculated as described above is displayed. At this point, the operator confirms that the table No. Is determined to be within an acceptable range, even if the remaining required number of correction operations has not become zero,
The correction operation can be ended in step S14 (FIG. 5). To end the correction operation in step S14 of FIG. 5, the stop key 254 is pressed. In addition, as shown in FIG. 31, when the recommended number of correction operations is four and the calculated number of remaining necessary correction operations is two, if the operation ends when the number of remaining necessary correction operations becomes zero, a total of three times And the unnecessary correction operation can be omitted once. In this way, when the target is reached with a number of times smaller than the recommended number of times of operation, it is not necessary to perform an extra number of correction operations.

In the present embodiment, the recommended number of corrections, the number of correction operations, the number of remaining necessary operations, and the degree of convergence are displayed on the operation panel 205. However, these are output by printing or voice. It may be. For example, when the number of correction operations is two and the number of recommended corrections is four, "2/4" can be printed on the right shoulder of the sheet.

[Brief description of the drawings]

FIG. 1 is a cross-sectional view illustrating an overall configuration of an image forming apparatus according to an embodiment of the present invention.

FIG. 2 is a block diagram illustrating a configuration of an image signal processing unit of the image forming apparatus illustrated in FIG.

FIG. 3 is a block diagram illustrating a configuration of a printer control system of the image forming apparatus illustrated in FIG.

FIG. 4 is a plan view of an operation panel.

FIG. 5 is a main flowchart of a printer control system of the image forming apparatus shown in FIG.

FIG. 6 is a flowchart illustrating an AIDC calibration process.

FIG. 7 is a diagram illustrating a relationship between an exposure amount step and an exposure amount level.

FIG. 8 is a flowchart for explaining AIDC detection processing.

FIG. 9 is a flowchart illustrating a photoconductor sensitivity characteristic calculation process.

FIG. 10 is a flowchart illustrating an approximate expression creation process of a photoconductor sensitivity characteristic.

FIG. 11 is a diagram illustrating sensitivity characteristics of a photoconductor when power is turned on.

FIG. 12 is a flowchart illustrating a charging efficiency calculation process.

FIG. 13 is a diagram showing a relationship between a surface potential and a grid potential.

FIG. 14 is a diagram illustrating sensitivity characteristics of a photoconductor at each developing position.

FIG. 15 is a flowchart illustrating a development efficiency calculation process.

FIG. 16 is a diagram showing the relationship between the surface potential and the amount of adhesion.

FIG. 17 is a diagram showing a relationship between light emission data and light emission intensity.

FIG. 18 is a diagram illustrating a relationship between an exposure amount and an effective developing potential.

FIG. 19 is a diagram showing the relationship between the amount of adhesion on a photosensitive member and the effective development potential.

FIG. 20 is a diagram showing the relationship between the amount of adhesion on paper and the density.

FIG. 21 is a diagram showing a γ correction characteristic curve.

FIG. 22 is a diagram showing a relationship between density data and light emission data.

FIG. 23 is a diagram showing XY-axis converted data.

FIG. 24 is a flowchart illustrating a gamma correction operation coefficient adjustment mode.

FIG. 25 is a flowchart illustrating the image reading of FIG. 23;

FIG. 26 is a diagram showing a configuration of a test pattern.

FIG. 27 is a diagram showing a maximum density correction table.

FIG. 28 is a diagram illustrating a correction table for a highlight portion.

FIG. 29 is a diagram for describing a correction convergence degree.

FIG. 30 is a flowchart showing the flow of a process of calculating the degree of correction convergence and the number of remaining necessary correction operations.

FIG. 31 is a diagram illustrating an example of a display screen displayed on a mode setting unit of the operation panel.

[Explanation of symbols]

 DESCRIPTION OF SYMBOLS 10 Photoconductor 11 Charging charger 12-15 Developing device 20 Transfer drum 27 Conveying device 30 Fixing device 31 Discharge tray 40 Document table 42 CCD sensor 44 Image signal processing unit 50 Print head unit 201 Printer control unit 202 Control ROM 203 Data ROM 204 RAM 205 Operation panel 206 Reset button 207 V sensor 208 Photoconductor drive counter 209 Environment sensor 210 Developing device drive counter 211 Developing device drive circuit 212 Toner replenishment drive 213 Vb generation unit 214 AIDC sensor 216 Light source 217 Light source drive 218 D / A Conversion circuit 219 γ correction unit 220 Light emission signal generation circuit 221 Vg generation unit

Continued on the front page F term (reference) 2H027 EB01 EC03 FD01 HA07 2H030 AA03 AD12 5C077 LL16 MM27 MP08 NN02 PP00 PP05 PP23 SS06 TT03 TT06 5C079 LA00 LA40 MA10 MA17 NA17 PA02 PA03

Claims (4)

[Claims] A reading unit configured to read a document as image data; a unit configured to form a test pattern for correcting an operation coefficient for processing an image; and combining the read image data with the test pattern An image forming apparatus comprising: 2. A means for forming a test pattern based on a calculation coefficient; a printer unit for outputting the test pattern; reading the output test pattern as image data; and calculating the calculation coefficient based on the obtained image data. Correction means for correcting the number of corrections, wherein the correction means includes correction number notification means for notifying the number of corrections of the operation coefficient based on the number of corrections made in the past. Means for forming a test pattern based on a calculation coefficient; a printer unit for outputting the test pattern; reading the output test pattern as image data; and calculating the calculation coefficient based on the obtained image data. Correction means for correcting the correction coefficient, wherein the correction means includes a correction status notifying means for notifying the correction convergence degree of the operation coefficient. 4. A means for forming a test pattern based on a calculation coefficient, a printer unit for outputting the test pattern, reading the output test pattern as image data, and performing the calculation based on the obtained image data. Correction means for correcting a coefficient, wherein the correction means includes a correction remaining number notification means for predicting and notifying the number of times required for a correction operation from the obtained image data and a desired gradation characteristic, and notifying. An image forming apparatus, characterized by: