JPH11205596A - Image formation device and method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To avoid changes in contrast due to character attribute settings includ ing a type face, a character size, a stroke number and character modification, by converting binary image data to multi-valued image data depending on an inferred printing density. SOLUTION: The number of black or white picture elements present inside divided plural blocks into which generated raster image data are divided is detected, and the number of the picture elements and a threshold value are compared for the respective blocks so that the number of blocks provided with the number of the black or white picture elements equal to or more than the threshold value is calculated. Then, the block number and the printing density are related as a qualitative rule, degree of belonging to a set of the printing density is led out from a degree that the block number belongs to a prescribed set based on the above rule and the printing density is inferred based on the led-out degree. Then, depending on the inferred printing density, the binary image data are converted to multi-valued image data. In this device, an image generation processing program is stored in a ROM 213 and executed by a CPU 212.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

[0001] 1. Field of the Invention [0002] The present invention relates to an image forming apparatus such as a printer, a copying machine, a facsimile, and the like capable of printing light and shade.

[0002]

2. Description of the Related Art FIG. 23 is a block diagram showing a configuration of a conventional image forming apparatus. FIG. 24 is a flowchart showing an image forming processing procedure executed by the host computer.

Image forming apparatus and host computer 1
a is connected using a protocol such as RS-232C or Centronics, and transfers signals such as control signals and image data.

When the host computer 1a causes the image forming apparatus to start a new job, the operation mode of the image forming apparatus at that time is uncertain, and the image forming apparatus starts a job for forming an image in a specific operation mode. There are cases where the order is not accepted.

Therefore, the host computer 1a is in a state where the job of the image forming apparatus can be reliably started.
A text mode start command for setting an operation mode is issued (step S1001).

The host computer 1a declares a job start command for the image forming apparatus in which the operation mode is determined, specifies a resolution and a character code system used in the image forming apparatus (step S1002), and executes the job. A software reset command is issued to initialize a necessary printing environment (step S1003).

[0007] Then, a page description necessary for image formation, such as setting of a printing environment, control commands, and character data, is made (step S1004). When the page description for image formation is completed, the host computer 1a declares a job end command, initializes a printing environment for the next job, and releases the apparatus (step S1005).

FIG. 25 is a flowchart showing a page description processing procedure in step S1004. At the beginning,
A page format such as a paper size and a page orientation is set, and a printing environment such as the number of copies is set (step S1101).

Based on the page format information, the image forming apparatus sets the print location of the raster image data in a format of (m × n) × k dots and sets values of constants n and k. FIG. 26 is a diagram showing a format configuration of a print location.

Image memory 4 for storing image data
00a has an information capacity corresponding to one page composed of m-bit data. FIG. 27 is a diagram showing the arrangement of m-bit data in the image memory. Thus, the relative positional relationship between the address and the print location in the image memory 400a is determined.

Next, a character set to be used for printing is selected, and the character set is prepared in an assignment table (step S1102). By selecting this character set, the image forming apparatus sets a character font ROM 205a stored in an on-board ROM or the like, and a scalable font or bitmap allocation table to be used. Note that the font ROM 205a may be an external storage device such as a cartridge or an IC card.

After setting the character set to be used, a print position is designated (step S1103). By the designation of the print position, the image forming apparatus operates the image memory 400 described above.
The address is set based on the relative positional relationship between the address a and the print location.

Then, while describing the character data, switching of character sets, character modification, and the like are performed, and data for image formation is described (step S1104).

The image forming apparatus generates raster image data in the image memory 400a by referring to the character pattern data of the given character code according to the specified character set assignment table. When the description of the print data for one page is completed, a discharge command for discharging the recording material from the image forming apparatus is issued (step S110).
5).

The image forming apparatus that has completed the generation of the raster image data outputs a print signal for instructing the start of image formation to the MPU 12a provided in the engine controller. When the engine unit is ready for image formation, a vertical synchronization request signal requesting the output of a vertical synchronization signal for synchronizing vertical scanning is returned, and the control right of the image memory 400a is transferred from the CPU 202a to the memory controller 300.
a, and outputs a vertical synchronization signal.

The memory controller 300a transfers data corresponding to one horizontal scanning line of the image memory 400a to the FIFO memory 500a in accordance with the timing of a horizontal synchronizing signal for synchronizing horizontal scanning.
Address control and timing control for parallel-to-serial conversion of the data of 00a by the shift register 600a are performed.

The output of the shift register 600a is a laser modulation signal for modulating the semiconductor laser provided in the light source unit 8a, and is transmitted to the laser drive circuit 7a.

FIG. 28 is a block diagram showing the structure of the laser drive circuit 7a. The laser drive circuit 7a includes a switching circuit 706a for controlling on / off of the semiconductor laser 801a by a laser modulation signal, and a semiconductor laser 801a.
A light amount detection circuit 701a for detecting a light output current from a photodiode 802a for monitoring the light output of
A sampling circuit 702a that performs sampling when the semiconductor laser 801a is turned on and that is held when the semiconductor laser 801a is turned off, and a subtractor 703a that performs a subtraction operation between the output of the sampling circuit 702a and the reference voltage Vref.
APC (Auto Pow) comprising an adjuster 704a for determining an operation amount based on the output of the subtractor 703a, and a current control transistor 705a for controlling a laser drive current of the semiconductor laser 801a based on the operation amount of the adjuster 704a.
er Control) circuit. As a result, an optimum laser beam output for forming an electrostatic latent image is always obtained.

FIG. 29 is a diagram showing an optical configuration of the image forming apparatus. Laser light emitted from the semiconductor laser 801a provided in the light source unit 8a passes through a collimator lens 1301a and a cylindrical lens 1302a, and then reaches a deflection mirror of a rotary polygon mirror 1303a.

The laser light reflected by the deflecting mirror surface of the rotary polygon mirror 1303a is imaged on the surface of the photosensitive member 14a by an anamorphic scanning lens system including a spherical lens 1304a and a toric lens 1305a, and forms an electrostatic latent image. Form.

Further, a reflection mirror 1306a is provided at the tip of the scanning line, and guides laser light to the beam detector 9a.

The light output detection signal of the beam detector 9a is converted from an analog signal to a pulse signal by a horizontal synchronization detection circuit 10a, and outputs a horizontal synchronization signal indicating that the laser beam has reached a predetermined position.

Then, as described above, the raster image data is transferred in synchronization with the horizontal synchronizing signal, and an image corresponding to one page is formed.

[0024]

However, the conventional image forming apparatus has the following problems, and improvement thereof has been demanded. In other words, when printing various characters on the image forming apparatus, the typeface, size, number of strokes,
The contrast looks different due to differences such as character modification. This is due to the integral effect of human vision and cannot be avoided. For this reason, in the conventional image forming apparatus, the contrast is sharp in a typeface using a thick line or a large-sized character.

On the other hand, in a typeface using thin lines and small-sized characters, there is a trade-off relationship in which the characters are blurred and the contrast is reduced. However, there is a problem that the number increases.

SUMMARY OF THE INVENTION It is an object of the present invention to provide an image forming apparatus and method capable of avoiding a change in contrast due to a set of character attributes such as a font, a character size, the number of strokes, and character modification.

[0027]

To achieve the above object, an image forming apparatus according to a first aspect of the present invention is an image forming apparatus capable of performing density printing for each pixel. Image data generating means for generating binary raster image data of the stored pattern data; dividing means for dividing the generated raster image data into a plurality of blocks; and data existing in the divided blocks. Pixel number detecting means for detecting the number of black or white pixels; comparing means for comparing the detected number of black or white pixels with a threshold value for each of the blocks; as a result of the comparison, the threshold value A block number calculating means for calculating the number of blocks having the number of black or white pixels, and a rule for associating the calculated number of blocks with the print density as a qualitative rule. And means, in accordance with the rules, the degree to which the number of blocks belonging to a predetermined set, the degree derivation means for deriving a degree of belonging to the set of the printing density,
Inference means for inferring the print density based on the degree of belonging to the set of the derived print densities, and converting the binary image data into multi-valued image data by the inferred print density. I do.

According to a second aspect of the present invention, in the image forming apparatus according to the first aspect, the degree deriving means includes:
The degree of belonging to the set of print densities is derived from the degree to which the number of blocks belongs to a plurality of predetermined sets, and the inference means combines the derived degrees of belonging to the set of print densities. Means for calculating the inferred print density based on the degree of belonging to the synthesized print density set.

According to a third aspect of the present invention, in the image forming apparatus according to the first or second aspect, the ruler determines a qualitative rule between the number of blocks and the print density in the form of a fuzzy proposition. Characterized in that it is provided with a rule storage means for expressing and storing the same.

According to a fourth aspect of the present invention, in the image forming apparatus according to the first, second, or third aspect, the degree deriving means expresses the number of blocks and the print density by fuzzy sets. A membership function storing means for storing the membership function.

In the image forming apparatus according to a fifth aspect, in the image forming apparatus according to the fourth aspect, the degree deriving means includes:
A fitness calculation unit is provided for calculating the fitness of the number of blocks based on the membership function stored in the membership function storage unit.

In the image forming apparatus according to a sixth aspect, in the image forming apparatus according to the fifth aspect, the degree deriving means includes:
The inference result of the print density is obtained from the calculated conformity of the number of blocks in accordance with the rule stored in the rule storage means in the form of a fuzzy proposition.

In the image forming apparatus according to a seventh aspect, in the image forming apparatus according to the sixth aspect, the degree calculating means includes:
The inference result is obtained by a minimum value operation or a multiplication operation of the degree of conformity of the number of blocks and the membership function of the print density.

According to an eighth aspect of the present invention, in the image forming apparatus according to the seventh aspect, the inference means combines the inference result in each rule by a maximum value operation, a minimum value operation, or an addition operation. Features.

According to a ninth aspect of the present invention, in the image forming apparatus according to the eighth aspect, the calculating means determines the print density by obtaining a center of gravity of the synthesized result. .

According to a tenth aspect of the present invention, in the image forming method of performing grayscale printing for each pixel, pattern data is stored, and the stored pattern data is stored in the image data.
Generate value raster image data, divide the generated raster image data into a plurality of blocks, detect the number of black or white pixels present in the divided blocks,
The detected number of black or white pixels and a threshold value are compared for each of the blocks, and as a result of the comparison, the number of blocks having the number of black or white pixels equal to or greater than the threshold value is calculated. The calculated number of blocks and the print density are related as a qualitative rule, and according to the rule, the degree of belonging to the set of print densities is derived from the degree of the number of blocks belonging to a predetermined set. The print density is inferred based on the derived degree of belonging to the set of print densities, and the binary image data is converted into multi-valued image data based on the inferred print density.

[0037]

DESCRIPTION OF THE PREFERRED EMBODIMENTS An embodiment of the image forming apparatus and method of the present invention will be described. In the image forming apparatus according to the present embodiment, the number of gradations is set to 16 per pixel.

[First Embodiment] FIG. 1 is a block diagram showing the configuration of an image forming apparatus according to the first embodiment.
The image forming apparatus is connected to the host computer 1, and includes a host interface circuit 201, a CPU 21
2, ROM 213, RAM 214, font ROM 20
5, image memories 401 to 404, FIFO memory 501
, 504, shift registers 601-604, laser drive circuit 7, light source unit 8, memory controller 301,
It has a horizontal synchronization detector 10, a beam detector 9, and the like.

FIG. 2 is a flowchart showing an image forming processing procedure. This processing program is stored in the ROM 213 and is executed by the CPU 212.

The CPU 212 transfers the sequential data for image formation from the host computer 1 via the host interface (Host I / F) circuit 201 to the buffer 200 provided in the host interface circuit 201 (step S101). . After this,
The CPU 212 reads the transfer data from the buffer 200 (Step S102).

At this time, job start processing data for starting image formation is transferred as sequential data for image formation, followed by print environment setting data.

Then, it is determined whether or not the transfer data is a character code (step S103). If it is not a character code, it is determined whether or not it is a job end command (step S104). If the command is not a job end command, it is determined whether or not the command is a character set selection command (step S105). If it is not a character set selection command, other processing is executed (step S106). And when other processing is completed,
It is determined whether or not all the transfer data has been processed (step S
116) If not all have been processed, step S102
When the reading of the transfer data in step S101 is repeated and all the processing is performed, the host computer 1 in step S101
Return to the data transfer process from.

The CPU 212, which has received the page format selection command from the host computer 1, sets the correlation between the memory space of the image memories 401 to 404 and the print location on the recording material in the same manner as in the prior art (S102 → S1).
03 → S104 → S105 → S106). Image memory 4
Reference numerals 01 to 404 denote memories for storing raster image data of 4-bit image density data expressing 16 gradation densities. The least significant bit (bit 0) of the image density data is stored in the image memory 401, and the image memory 402 is stored in the image memory 402. Bit 1 of density data, bit 2 of image density data in image memory 403, bit 3 of image density data in image memory 404
Corresponds.

Subsequently, the host computer 1 which has completed the print environment setting transfers the print description data. The host computer 1 issues a character set selection command as a control command in order to set a character set used for printing. The character set selection command is a graphic set that specifies the correspondence between character codes and character patterns, a character pitch that specifies the character pitch, a character size that specifies the character size, and a character style that specifies a character style such as straight / italic. ,
Based on character set attributes such as stroke weight that regulates character thickness and typeface that regulates character design,
This sets the character set to be printed. An LUT (Look Up Tabl) that defines the correlation with the character set attribute
By providing e), it is also possible to set a character set by a specific command such as a character set name defining a specific name or a character set assign number defining a specific number.

CPU 21 receiving character set selection command
In step S105, when it is determined that the command is a character set selection command in step S105, the character set specified by the character set attribute and its character code correspond to one character pattern data stored in the font ROM 205. (Step S1)
07). Then, the CPU 212 executes the font ROM 205
Is read (step S108).

FIG. 3 is a diagram showing an outline of character set information of a bitmap font in which character pattern data is designed in a pixel matrix.

The character set information is roughly composed of three parameters. The first is a cell indicating the size of the outer frame of the character pattern data, and its value is indicated by the cell width / cell height of the number of pixels in the width and height directions. The second is a baseline indicating a reference line for aligning characters when writing characters horizontally, and the value is indicated by the number of pixels (including the baseline) from the lower side of the cell to the baseline. The third is an underline position indicating a default reference position when underlining is performed. The value is represented by the number of pixels from the baseline to the underline (not including the baseline but including the underline in the number). Is shown.

The CPU 212 secures a memory area in the RAM 214 for generating binary raster image data to be printed, based on at least the character size and cell width / cell height parameters of the character set attribute and character set information (step S109). And the parameter indicating the memory area is RA
It is stored in the register of M214 (step S110).

For example, the character set selection command is an ISO graphic set, and the character pitch is 10 cpi (Characte
r Per Inch), character size is 12 points, character style is 3D, stroke weight is a standard character set attribute, and a bitmap font designed with a resolution of 300 dpi (Dot Per Inch) is specified. In this case, as shown in FIG. 3, the cell width of the character set information is 30 pixels, and the cell height is 48 pixels. FIG. 4 is a diagram showing a bitmap font designated with a cell width of 30 pixels and a cell height of 48 pixels. Here, as shown in FIG. 4, the memory capacity reserved in the RAM 214 for the CPU 212 to generate binary raster image data from the character set information is 32 pixels in width of the image including byte bounding and the height of the image. Corresponds to 48 pixels.

FIG. 5 is a diagram showing a memory map of the RAM 214. FIG. 6 is a diagram showing a print location of raster image data on the RAM 214.

The CPU 212 performs byte access, and
When the data width of the AM 214 is 8 bits, the RAM 214
The parameters of the print location above are m = 8,
A memory capacity of 192 bytes consisting of n = 4 and k = 48 is secured.

Here, m is the data bit width of the RAM 214, n is the number of columns of the pixel matrix in m pixels, and k is the number of rows of the pixel matrix. Then, the CPU 212
The parameters of the character raster image data generation area secured on M214 are stored in the register of the RAM 214.

Subsequently, the CPU 212 performs a setting process of a block division parameter of the raster image data area on the RAM 214 (step S111). FIG. 7 is a flowchart showing the procedure of the block division parameter setting process in step S111.

First, the main scanning direction block division unit and the sub-scanning direction block division unit, which are the minimum units for dividing the raster image data area of the RAM 214, are equal in the main scanning direction block division unit and the sub-scanning direction block division unit. The settings are made so as to form a d × d pixel matrix (steps S401 and S402). The unit of division is 4 so that the access efficiency of the RAM 214 is improved.
Multiples are often used.

Then, the CPU 212 obtains the number of each divided block based on the division unit. The number of blocks Nw in the main scanning direction is obtained by dividing the pattern data width of (m × n) pixels by the main scanning direction division unit d, and obtaining the quotient as the operation result (step S403).

The number Nh of blocks in the sub-scanning direction is obtained as a quotient as a result of the division of the number k of rows of the pattern byte width by the sub-scanning direction division unit d (step S404).

If the square block division unit d is assumed to be 4 pixels again using the character set attribute bitmap font described above, the minimum block unit forms a 4 × 4 pixel matrix, and the number of blocks Nw in the main scanning direction is 8 , The number of blocks Nh in the sub-scanning direction is 12.

After allocating the character set, the host computer 1 transmits a print position designation command process in order to designate a print position for printing on a recording material. The CPU 212 that has read the print position designation command,
The relative position between the location of M214 and the image memories 401 to 404 is determined.

After the host computer 1 performs processing such as setting of a printing environment, assignment of a character set, and designation of a printing position, the host computer 1 transmits a character code of a character to be printed.
212 reads the character code. Then, read the character code according to the character set assignment table.
Referring to the character pattern data of the pixel matrix stored in the font ROM 205, binary raster image data is generated on the RAM 214 (step S11).
2). FIG. 8 is a diagram showing a block division state of raster image data when “A” is specified as a character code.

The CPU 212, which has generated the binary raster image data on the RAM 214, performs a process of detecting the number of pixels of the ON image (the pixel for recording black on the recording material) for each block (step S113).

FIGS. 9 and 10 are flowcharts showing the procedure for detecting the number of ON pixels in step S113. First, initialization is performed (steps S201 to S20).
4). In the initial setting, a block accumulation register NB that counts the number of blocks in which the number of ON pixels in the block is equal to or larger than a threshold value, and a variable K that indicates the number of repetitions in the sub-scanning direction
h, a variable Kw indicating the number of repetitions in the main scanning direction, and a variable Kr indicating the number of repetitions in the block,
The two operation registers Y0 and Y1 for storing the number of detected ON pixels in the block are reset.

Here, two registers are used because C
This is because the PU 212 performs byte access and the block division unit is set to four pixels, so that one access accesses image data of eight pixels, that is, two blocks. Therefore, upper 4 bits and lower 4 bits of data are distinguished as image data of each block.

The CPU 212, which has completed the initial setting, sets the RA
The address address AD is set to read the data of M214 (step S205). The setting of the address AD is performed by setting the number of main scanning blocks Nw and the intra-block repetition variable K
r, the block division unit d, the sub-scanning repetition variable Kh, and the main scanning direction repetition variable Kw are obtained by Expression (1).

AD = Nw ÷ 2 × (Kr + d × Kh) + K
w (1) The CPU 212 reads the data at the set address AD (step S206), and calculates the number of ON pixels X0 of the upper 4 bits and the number of ON pixels X1 of the lower 4 bits of the read data (step S207). ,
S208). Then, the calculated numbers of ON pixels X0 and X1 are added to the operation registers Y0 and Y1, respectively, and the result is stored in the operation registers Y0 and Y1 again (step S209).

It is determined whether or not the above processing is repeated for d pixel rows as a block division unit (step S21).
0), if not repeated, increment the in-block repetition variable Kr (step S211), return to step S205, repeat the above processing from the setting of address AD, and calculate the number of ON pixels in the block.

On the other hand, if the above processing is repeated for d pixel rows, which is a unit of block division, two operation registers Y
A comparison is made between the values of 0 and Y1 and the threshold value Vth (step S212). If both of the operation registers Y0 and Y1 are equal to or larger than the threshold value, the block accumulation register N
After adding the value 2 to the value of B, it is stored again in the block accumulation register NB (step S213), and the operation register Y
If any one of 0 and Y1 is equal to or greater than the threshold value, the value of the block accumulation register NB is added with the value 1 and then stored in the block accumulation register NB again (step S214). Further, when both of the operation registers Y0 and Y1 are smaller than the threshold value, the block accumulation register NB is held as it is, and the process proceeds to step S215.

After the comparison of the operation registers Y0 and Y1 is completed, it is determined whether or not the main scanning direction repetition variable Kw has reached a value obtained by decrementing the half value of the number Nw of blocks in the main scanning direction by 1 (step S215). . If the main scanning direction repetition variable Kw does not reach a value obtained by decrementing the half value of the number Nw of blocks in the main scanning direction by one, there are blocks in the main scanning direction for which the number of ON pixels has not been calculated, compared, or counted. The main scanning direction repetition variable Kw is incremented (step S216), and the above-described processing (S203 to S215) is repeated.

When the main scanning direction repetition variable Kw reaches a value obtained by decrementing the half value of the number Nw of blocks in the main scanning direction by 1, the calculation, comparison, and counting of the number of ON pixels are performed in the blocks in the main scanning direction. Judgment is made and block search in the sub-scanning direction is performed.

In the block search in the sub-scanning direction, the number of blocks Nh in the sub-scanning direction is set to 1
It is determined whether the value has reached the decremented value (step S217). If the sub-scanning direction repetition variable Kh does not reach a value obtained by decrementing the number of blocks Nh in the sub-scanning direction by 1, calculation of ON pixels in the sub-scanning direction;
Since there is a block that has not been compared and counted, the variable Kh in the sub-scanning direction is incremented (step S218), and the above-described processing (S202 to S2) is performed.
Repeat 17).

When the sub-scanning direction repetition variable Kh reaches a value obtained by decrementing the number of blocks Nh in the sub-scanning direction by one, the calculation, comparison, and counting of the number of ON pixels are performed for all the blocks in the sub-scanning direction. Run,
For all the raster image data in the RAM 212, it is determined that the cumulative block number NB having the number of ON pixels equal to or larger than the threshold value in the divided blocks has been calculated, and the processing is terminated. In step S114, the print density data is set. The process returns to the print density determination processing.

In setting the print density data, the image forming apparatus of the present embodiment uses fuzzy logic. FIG.
1 is a graph showing a membership function of the block accumulation register NB stored in the ROM 213 as the antecedent part membership function.

In the membership function of the block accumulation register NB, 3
Two fuzzy sets are defined. The fuzzy sets indicated by fuzzy labels S, M, and L are as follows, and the degree of belonging to each fuzzy set takes an arbitrary value from 0 to 1.

S (Small): Fuzzy set indicating that the value of the block accumulation register is small M (Middle): Fuzzy set indicating that the value of the block accumulation register is medium L (Large): Value of the block accumulation register Fuzzy set showing that there are many ROM213 as a consequent part membership function
5 is a graph showing a membership function of print density stored in the printer. In the print density membership function, three fuzzy sets are defined for the print density.
The fuzzy sets indicated by fuzzy labels L, M, and D are as follows.

L (Light): Fuzzy set indicating that print density is light M (Middle): Fuzzy set indicating that print density is medium D (Dark): Fuzzy set indicating that print density is high Fuzzy rules R1, R2, and R3 for regulating the correlation between the block accumulation register NB and the print density are defined as follows, and are stored in the ROM 213.

R1: IF (X = S) then (Y = D) R2: IF (X = M) then (Y = M) R3: IF (X = L) then (Y = L) Rule 1 of fuzzy rule In (R1), if the value of the block accumulation register NB is small, the print density is increased. Rule 2
In (R2), if the value of the block accumulation register NB is medium, the print density is set to medium. Rule 3 (R
3) specifies that if the value of the block accumulation register NB is large, the print density is reduced.

FIG. 13 is a diagram showing an outline of a calculation process for determining a print density by fuzzy inference. FIG. 14 is a flowchart showing a print density determination processing procedure for setting print density data by fuzzy inference in step S114.

The CPU 212 reads out the block accumulation register NB indicating the number of blocks in which the number of ON pixels is equal to or larger than the threshold value (step S301), and based on the value of the block accumulation register NB, each fuzzy in the membership function of the block accumulation register described above. The fitness ω of the set is calculated (step S302).

For example, the value of the block accumulation register NB is X1, and the fitness ω of each fuzzy set is shown in FIG.
Assuming that the values shown in (b) and (c) are taken, the degree of conformity ω to the fuzzy set S is 0.5 (see FIG. 13).
(A)), the fitness ω to the fuzzy set M has a value of 0.5 (FIG. 13B), and the fitness ω to the fuzzy set L has a value of 0 (FIG. 13C).

The CPU 212, which has calculated the degree of conformity of the membership function of the antecedent part, infers the print density according to the fuzzy rules described above (step S304). Here, as means for estimating the print density, an AND operation for finding a common set of the fitness ω of the block accumulation register and the fuzzy set of the print density, that is, a MIN (minimum value) operation is used.

In the inference of the print density in the fuzzy rule 1, the MIN operation of the fitness ω of the fuzzy set S and the fuzzy set of the print density D is performed, and the result shown by the trapezoidal hatched portion in FIG. As a result of inferring the print density in the fuzzy rule 2, the MIN operation of the fitness ω of the fuzzy set M and the fuzzy set of the print density M is performed.
The result shown by the trapezoidal hatched portion (e) is obtained. Further, as a result of the inference of the print density in the fuzzy rule 3, since the fitness ω of the fuzzy set L is a value of 0, when the MIN operation is performed with the fuzzy set of the print density D, the value 0 (FIG. 13F)
See). In this way, the inference of the print density is repeated until all the fuzzy rules are executed (step S3).
03, S304).

When the print density inference for all fuzzy rules is completed, the CPU 212 synthesizes the print density inference result for each rule. At this time, the synthesis rule for synthesizing the print density inference result for each rule is used. Are added to each inference result (step S305). That is, the inference results of FIGS. 13 (d), (e), and (f) are added, and
The inference synthesis result shown in FIG.

The result of the inference synthesis (FIG. 13)
(G)) is calculated (step S306), and an optimum print density is obtained as a result of the calculation.

At this time, if the image forming apparatus can obtain a sufficient number of quantizations in consideration of the visual characteristics, step S30
Although it is possible to use the optimum print density obtained in No. 3 as it is as the image density, when it is limited by the image memory capacity or the like (16 gradations), the print density is not always completely equal to the optimum print density. . Therefore, the CPU 212
Sets the print density data closest to the optimum print density,
The data is stored in the print density register (step S307).

The CPU 212 having set the print density data in the print density register performs a masking process with the raster image data in the RAM 212, and
4 stores print density data and generates multi-valued image density data (step S115).

Then, the CPU 212 determines whether or not the buffer 200 is empty (empty) and has processed all of the transfer data (step S116). If not, the CPU 212 reads the transfer data from the buffer 200 and executes the above processing. repeat. When the buffer 200 is empty and processes all data, the host computer 1
, Requesting data transfer again, and repeating the above processing until a job end command is received.

The image forming apparatus which has completed the raster image data generation processing instructs an MPU (not shown) provided in the engine controller to start image formation via an engine interface (not shown). Output print signal. When the engine unit is ready for image formation, a vertical synchronization request signal requesting the output of a vertical synchronization signal for synchronizing vertical scanning is returned, and the image memory 40
The control right of 1 to 404 is released from the CPU 212 to the memory controller 301, and a vertical synchronization signal is output.

The memory controller 301 responds to the timing of a horizontal synchronizing signal for synchronizing horizontal scanning.
The data corresponding to one horizontal scanning line of the image memories 401 to 404 is transferred to the FIFO memories 501 to 504,
The data in the memories 501 to 504 is stored in the shift register 601.
At steps 604 to 604, address control and timing control for performing parallel-serial conversion are performed. Shift register 60
The image density data, which is the output of 1 to 602, is transferred to the laser drive circuit 7.

FIG. 15 is a block diagram showing the configuration of the laser drive circuit. The laser drive circuit 7 includes a shift register 6
Image density data b0 to b3 output from 01 to 604
Is input to a logical sum circuit 707 that performs a logical sum operation to generate a laser modulation signal for performing laser on / off control. Further, the image density data is stored in a reference voltage control circuit 708.
And a reference voltage Vref based on the image density data.
Voltage switching.

Further, the laser drive circuit 7 detects a light output current from the photodiode 802 for monitoring the light output of the semiconductor laser 801 and a light amount detection circuit 701 for sampling when the semiconductor laser 801 is turned on.
A sampling / hold (S / H) circuit 702 that performs hold control when the light is off, a subtractor 703 that performs a subtraction operation between the sampling / hold circuit 702 and the output voltage of the reference voltage control circuit 708, and a subtractor 703. An adjuster 704 for determining an operation amount based on the output;
APC from the current control transistor 705 for controlling the laser drive current of the semiconductor laser 801 based on the operation amount of the APC
A circuit is configured to output an optimal laser beam for forming an electrostatic latent image according to the image density data.

As described above, the image forming apparatus generates print density data from character pattern data, and performs print density correction by performing laser intensity modulation based on multi-valued image density data. Contrast can be obtained.

In addition to the above laser intensity modulation, the present invention is also effective in the case where the laser light output is fixed and the pulse width modulation of the laser is performed based on the image density data.
The present invention is also effective for an image forming apparatus other than the electrophotographic type, for example, an image forming apparatus of an ink jet type.

[Second Embodiment] The image forming apparatus according to the second embodiment has the same configuration as that of the first embodiment except for the print density determination process in step S114. The same components as those in the first embodiment will be described using the same reference numerals.

FIG. 16 is a flowchart showing a print density determination processing procedure in the second embodiment. FIG. 17 is a diagram showing an outline of a calculation process for determining a print density by fuzzy inference.

The CPU 212 sets a block accumulation register NB indicating the number of blocks in which the number of ON pixels is equal to or larger than the threshold value.
Is read (step S301), and the fitness ω of each fuzzy set in the membership function of the block accumulation register is obtained from the value of the block accumulation register NB (step S302).

For example, assuming that the value of the block accumulation register NB is X1 and takes the values shown in FIGS. 17A, 17B and 17C, the degree of conformity ω to the fuzzy set S is 0.
5 (FIG. 17A), the fitness ω to the fuzzy set M is 0.5 (FIG. 17B), and the fitness ω to the fuzzy set L
Is 0 (FIG. 17C).

The CPU 212, which has calculated the degree of conformity of the membership function of the antecedent part, infers the print density according to the same fuzzy rules R1, R2, R3 as in the first embodiment (steps S303, S304). Here, as means for estimating the print density, an AND operation for finding a common set of the fitness ω of the block accumulation register and the fuzzy set of the print density, that is, a MIN (minimum value) operation is used.

As a result of inferring the print density in the fuzzy rule 1 (R1), the MIN operation of the fitness ω of the fuzzy set S and the fuzzy set of the print density D is performed, and FIG.
The result shown by the trapezoidal hatched portion in (d) is obtained. Further, as a result of inferring the print density in the fuzzy rule 2 (R2), the MIN calculation of the fitness ω of the fuzzy set M and the fuzzy set of the print density M is performed, and the result indicated by the trapezoidal hatched portion in FIG. obtain. Further, as an inference result of the print density in the fuzzy rule 3 (R3), the fitness ω of the fuzzy set L
Is the value 0, the MI with the fuzzy set of print density D
As a result of the N operation, a value 0 (FIG. 17F) is obtained. This inference of the print density is repeated until all the fuzzy rules are executed (steps S303 and S304).

After completing the inference of the print density in all the fuzzy rules, the CPU 212 synthesizes the inference result of the print density for each rule. As a synthesis rule for synthesizing the inference result of the print density for each rule, A logical sum operation for obtaining a union set of the inference results, that is, a MAX (maximum value) operation is performed (step S305A). That is, FIG.
MAX calculation of the inference results of 7 (d), (e) and (f),
The inference synthesis result shown in FIG.

Then, the center of gravity of the inference synthesis result (FIG. 17 (g)) is calculated (step S306), and the optimum print density is obtained as the calculation result.

Therefore, the CPU 212 sets print density data closest to the optimum print density and stores it in the print density register (step S307).

[Third Embodiment] The image forming apparatus according to the third embodiment is the same as the first embodiment except that the print density determination process in step S114 is different. The same components as those in the first embodiment will be described using the same reference numerals.

FIG. 18 is a flowchart showing a print density determination processing procedure in the third embodiment. FIG. 19 is a diagram showing an outline of a calculation process for determining a print density by fuzzy inference.

The CPU 212 sets a block accumulation register NB indicating the number of blocks in which the number of ON pixels is equal to or larger than the threshold value.
Is read (step S301), and the fitness ω of each fuzzy set in the membership function of the block accumulation register is obtained from the value of the block accumulation register NB (step S302).

For example, assuming that the value of the block accumulation register NB is X1 and takes the values shown in FIGS. 19A, 19B, and 19C, the degree of conformity ω to the fuzzy set S is 0.
5 (FIG. 19A), the fitness ω to the fuzzy set M is a value 0.5 (FIG. 19B), and the fitness ω to the fuzzy set L
Is a value 0 (FIG. 19C).

The CPU 212, which has calculated the degree of conformity of the membership function of the antecedent part, infers the print density according to the same fuzzy rules R1, R2, R3 as in the first embodiment (steps S303, S304). Here, as means for estimating the print density, an AND operation for finding a common set of the fitness ω of the block accumulation register and the fuzzy set of the print density, that is, a MIN operation is used.

As a result of inferring the print density in the fuzzy rule 1 (R1), the MIN operation of the fitness ω of the fuzzy set S and the fuzzy set of the print density D is performed, and FIG.
The result shown by the trapezoidal hatched portion in (d) is obtained. Further, as a result of inferring the print density in the fuzzy rule 2 (R2), the MIN operation of the fitness ω of the fuzzy set M and the fuzzy set of the print density M is performed. obtain. Further, as an inference result of the print density in the fuzzy rule 3 (R3), the fitness ω of the fuzzy set L
Is the value 0, the MI with the fuzzy set of print density D
As a result of the N operation, a value 0 (FIG. 19 (f)) is obtained. This inference of the print density is repeated until all the fuzzy rules are executed (steps S303 and S304).

After finishing the inference of the print density in all the fuzzy rules, the CPU 212 synthesizes the inference result of the print density for each rule. As a synthesis rule for synthesizing the inference result of the print density for each rule, An AND operation for finding a common set of the inference results, that is, a MIN operation is performed (step S305B). That is, FIG.
The MIN operation is performed on the inference results of (e) and (f), and FIG.
An inference synthesis result shown in (g) is obtained.

Then, the center of gravity of the inference synthesis result (FIG. 19 (g)) is calculated (step S306), and the optimum print density is obtained as the calculation result.

Therefore, the CPU 212 sets print density data closest to the optimum print density and stores it in the print density register (step S307).

[Fourth Embodiment] The image forming apparatus according to the fourth embodiment differs from the first embodiment only in the means for estimating the print density in the print density determination processing in step S114, except for the print density. Is the same as that in the first embodiment. Therefore, the same components as those in the first embodiment will be described using the same reference numerals.

FIG. 20 is a diagram showing an outline of a calculation process for determining a print density by fuzzy inference in the fourth embodiment.

The CPU 212 reads out the block accumulation register NB indicating the number of blocks in which the number of ON pixels is equal to or larger than the threshold value (step S301), and based on the value of the block accumulation register NB, each fuzzy in the membership function of the block accumulation register described above. The fitness ω of the set is calculated (step S302).

For example, the value of the block accumulation register NB is X1, and the fitness ω of each fuzzy set is shown in FIG.
Assuming that the values shown in (b) and (c) take values, the degree of conformity ω to the fuzzy set S is 0.5 (see FIG. 20).
(A)), the degree of conformity ω to the fuzzy set M is 0.5 (FIG. 20B), and the degree of conformity ω to the fuzzy set L is 0 (FIG. 20C).

The CPU 212 that has calculated the degree of conformity of the membership function of the antecedent part performs inference of the print density in accordance with the fuzzy rules described above (step S304). Here, as means for estimating the print density, a multiplication operation of the fitness ω of the block accumulation register and the fuzzy set of the print density is used.

In the inference of the print density in the fuzzy rule 1, a multiplication operation of the fitness ω of the fuzzy set S and the fuzzy set of the print density D is performed, and a result indicated by a hatched portion in FIG. 20D is obtained. As a result of inferring the print density in the fuzzy rule 2, a multiplication operation of the fitness ω of the fuzzy set M and the fuzzy set of the print density M is performed.
The result shown by the hatched triangle in (e) is obtained. Further, as a result of the inference of the print density in the fuzzy rule 3, since the fitness ω of the fuzzy set L is a value of 0, when the multiplication operation with the fuzzy set of the print density D is performed, the value 0 (FIG. 20 (f))
See). In this way, the inference of the print density is repeated until all the fuzzy rules are executed (step S3).
03, S304).

When the printing density inference for all the fuzzy rules is completed, the CPU 212 synthesizes the printing density inference result for each rule. At this time, the synthesis rule for synthesizing the printing density inference result for each rule is used. Then, an addition operation of each inference result is performed (step S305). That is, the inference results of FIGS. 20 (d), (e), and (f) are added to obtain the inference synthesis result shown in FIG. 20 (g).

The result of the inference synthesis (FIG. 20)
(G)) is calculated (step S306), and an optimum print density is obtained as a result of the calculation. The CPU 212 sets the print density data closest to the optimum print density and stores it in the print density register (step S307).

[Fifth Embodiment] The image forming apparatus according to the fifth embodiment differs from the second embodiment only in the means for estimating the print density in the print density determination processing in step S114, except for the print density. Is the same as that of the second embodiment. Also, the same components as those in the first embodiment will be described using the same reference numerals.

FIG. 21 is a diagram showing an outline of a calculation process for determining a print density by fuzzy inference in the fifth embodiment.

The CPU 212 reads out the block accumulation register NB indicating the number of blocks in which the number of ON pixels is equal to or larger than the threshold value (step S301), and uses each value of the block accumulation register NB to determine the fuzzy function in the membership function of the block accumulation register. The fitness ω of the set is calculated (step S302).

For example, the value of the block accumulation register NB is X1, and the fitness ω of each fuzzy set is shown in FIG.
Assuming the values shown in (b) and (c), the degree of conformity ω to the fuzzy set S is 0.5 (see FIG. 21).
(A)), the fitness ω to the fuzzy set M has a value of 0.5 (FIG. 21B), and the fitness ω to the fuzzy set L has a value of 0 (FIG. 21C).

The CPU 212, which has calculated the degree of conformity of the antecedent membership function, infers the print density according to the fuzzy rules described above (step S304). Here, as means for estimating the print density, a multiplication operation of the fitness ω of the block accumulation register and the fuzzy set of the print density is used.

In the inference of the print density in the fuzzy rule 1, a multiplication operation of the fitness ω of the fuzzy set S and the fuzzy set of the print density D is performed, and the result indicated by the hatched triangle in FIG. 21D is obtained. As a result of inference of the print density in the fuzzy rule 2, a multiplication operation of the fitness ω of the fuzzy set M and the fuzzy set of the print density M is performed, and FIG.
The result shown by the hatched triangle in (e) is obtained. Furthermore, as a result of the inference of the print density in the fuzzy rule 3, the fitness ω of the fuzzy set L is a value of 0.
See). In this way, the inference of the print density is repeated until all the fuzzy rules are executed (step S3).
03, S304).

When print density inference for all fuzzy rules is completed, the CPU 212 synthesizes print density inference results for each rule. At this time, a synthesis rule for synthesizing print density inference results for each rule is used. As a logical OR operation for finding the union of the inference results, ie, MAX
An operation is performed (step S305A). That is, FIG.
MAX calculation is performed on the inference results of (d), (e), and (f) to obtain the inference synthesis result shown in FIG.

The result of the inference synthesis (FIG. 21)
(G)) is calculated (step S306), and an optimum print density is obtained as a result of the calculation. The CPU 212 sets the print density data closest to the optimum print density and stores it in the print density register (step S307).

[Sixth Embodiment] The image forming apparatus according to the sixth embodiment differs from the third embodiment only in the means for estimating the print density in the print density determination processing in step S114, except that the print density is different. Is the same as that of the third embodiment. Also, the same components as those in the first embodiment will be described using the same reference numerals.

FIG. 22 is a diagram showing an outline of an arithmetic processing for judging print density by fuzzy inference in the sixth embodiment.

The CPU 212 reads out the block accumulation register NB indicating the number of blocks in which the number of ON pixels is equal to or larger than the threshold value (step S301), and uses each value of the block accumulation register NB in the fuzzy membership function of the block accumulation register. The fitness ω of the set is calculated (step S302).

For example, the value of the block accumulation register NB is X1, and the fitness ω of each fuzzy set is shown in FIG.
Assuming that the values shown in (b) and (c) take values, the degree of conformity ω to the fuzzy set S is 0.5 (see FIG. 22).
(A)), the degree of conformity ω to the fuzzy set M is 0.5 (FIG. 22B), and the degree of conformity ω to the fuzzy set L is 0 (FIG. 22C).

The CPU 212, which has calculated the degree of conformity of the antecedent membership function, infers the print density in accordance with the fuzzy rules described above (step S304). Here, as means for estimating the print density, a multiplication operation of the fitness ω of the block accumulation register and the fuzzy set of the print density is used.

In the inference of the print density in the fuzzy rule 1, a multiplication operation of the fitness ω of the fuzzy set S and the fuzzy set of the print density D is performed, and a result indicated by a hatched portion in FIG. 22D is obtained. As a result of inferring the print density in the fuzzy rule 2, a multiplication operation of the fitness ω of the fuzzy set M and the fuzzy set of the print density M is performed.
The result shown by the hatched triangle in (e) is obtained. Further, as a result of inferring the print density in the fuzzy rule 3, since the degree of conformity ω of the fuzzy set L is 0, when the multiplication operation with the fuzzy set of the print density D is performed, the value 0 (FIG. 22F)
See). In this way, the inference of the print density is repeated until all the fuzzy rules are executed (step S3).
03, S304).

When the print density inference for all fuzzy rules is completed, the CPU 212 synthesizes the print density inference result for each rule. At this time, the synthesis rule for synthesizing the print density inference result for each rule is used. AND operation for finding a common set of the inference results, that is, MI
An N operation is performed (step S305B). That is, FIG.
MIN operation is performed on the inference results of (d), (e), and (f) to obtain an inference synthesis result shown in FIG.

The result of the inference synthesis (FIG. 22)
(G)) is calculated (step S306), and an optimum print density is obtained as a result of the calculation. The CPU 212 sets the print density data closest to the optimum print density and stores it in the print density register (step S307).

Note that the present invention may be applied to a system including a plurality of devices, or may be applied to an apparatus including a single device. Needless to say, the present invention can be applied to a case where the present invention is achieved by supplying a program to a system or an apparatus. In this case, by reading out a storage medium storing a program represented by software for achieving the present invention into a system or an apparatus, the system or the apparatus can enjoy the effects of the present invention.

The storage medium is not limited to ROM, for example, but may be a floppy disk, hard disk, optical disk, magneto-optical disk, CD-ROM, CD-R, DV, or the like.
D, a magnetic tape, a nonvolatile memory card, or the like can be used.

[0136]

According to the image forming apparatus of the first aspect of the present invention, when grayscale printing is performed for each pixel, the pattern data is stored in the storage means, and the stored pattern data is stored in the image data generating means. , And divides the generated raster image data into a plurality of blocks by a dividing unit, and detects the number of black or white pixels present in the divided block by a pixel number detecting unit. The number of black or white pixels detected by the comparing means is compared with a threshold value for each of the blocks. As a result of the comparison, the number of black or white pixels equal to or greater than the threshold value is calculated by the block number calculating means. Is calculated by the rule means, and the calculated number of blocks and the print density are related as a qualitative rule, and the degree is derived by the degree deriving means. Therefore, the degree of belonging to the set of print densities is derived from the degree to which the number of blocks belongs to the predetermined set, and the print density is determined based on the degree of belonging to the set of print densities derived by the inference means. The binary image data is converted to the multi-valued image data based on the inferred print density, so that the typeface, character size, number of strokes,
It is possible to avoid a change in contrast due to a character attribute setting value such as character modification.

Therefore, it is possible to control the print density of any character, to always obtain the optimum contrast in view, and to reduce eye fatigue, and as a result, to obtain customer satisfaction (CS). )) Can be improved.

In addition, the density of toner and ink can be further increased, and the printing quality of small characters can be further improved without increasing the contrast of large characters.

Further, the occurrence of gloss due to toner can be reduced, and the printing quality of the apparatus can be improved. The same effect can be obtained in the image forming method according to the tenth aspect.

According to the image forming apparatus of the present invention,
The degree deriving unit derives the degree of belonging to the set of print densities from the degree that the number of blocks belongs to a plurality of predetermined sets, and the degree of belonging to the set of print densities derived by the combining unit. Are synthesized, and the inferred print density is determined based on the degree of belonging to the set of print densities synthesized by the arithmetic means, so that the print density can be inferred more accurately.

According to the image forming apparatus of the present invention, the print density can be inferred by fuzzy inference, and the print density of any character can be easily controlled.

[Brief description of the drawings]

FIG. 1 is a block diagram illustrating a configuration of an image forming apparatus according to a first embodiment.

FIG. 2 is a flowchart illustrating an image forming processing procedure.

FIG. 3 is a diagram showing an outline of character set information of a bitmap font in which character pattern data is designed in a pixel matrix.

FIG. 4 is a diagram showing a bitmap font designated with a cell width of 30 pixels and a cell height of 48 pixels.

FIG. 5 is a diagram showing a memory map of a RAM 214.

FIG. 6 is a diagram showing a print location of raster image data on a RAM 214.

FIG. 7 is a flowchart illustrating a block division parameter setting processing procedure in step S111.

FIG. 8 is a diagram illustrating a block division state of raster image data when “A” is specified as a character code.

FIG. 9 is a flowchart showing a procedure for detecting the number of ON pixels in step S113.

FIG. 10 is a flowchart illustrating a procedure for detecting the number of ON pixels following FIG. 9;

FIG. 11: ROM 21 as antecedent membership function
4 is a graph showing a membership function of a block accumulation register NB stored in No. 3;

FIG. 12 shows ROM 21 as a membership function of the consequent part.
6 is a graph showing a print density membership function stored in No. 3;

FIG. 13 is a diagram illustrating an outline of a calculation process for determining a print density by fuzzy inference.

FIG. 14 is a flowchart showing a print density determination processing procedure for setting print density data by fuzzy inference in step S114.

FIG. 15 is a block diagram illustrating a configuration of a laser driving circuit.

FIG. 16 is a flowchart illustrating a print density determination processing procedure according to the second embodiment.

FIG. 17 is a diagram illustrating an outline of a calculation process for determining a print density by fuzzy inference.

FIG. 18 is a flowchart illustrating a print density determination processing procedure according to the third embodiment.

FIG. 19 is a diagram illustrating an outline of a calculation process for determining a print density by fuzzy inference.

FIG. 20 is a diagram illustrating an outline of a calculation process of determining a print density by fuzzy inference in the fourth embodiment.

FIG. 21 is a diagram illustrating an outline of a calculation process for determining a print density by fuzzy inference in the fifth embodiment.

FIG. 22 is a diagram illustrating an outline of a calculation process for determining a print density by fuzzy inference in the sixth embodiment.

FIG. 23 is a block diagram illustrating a configuration of a conventional image forming apparatus.

FIG. 24 is a flowchart illustrating an image forming processing procedure executed by a host computer.

FIG. 25 is a flowchart showing a page description processing procedure in step S1004.

FIG. 26 is a diagram illustrating a format configuration of a print location.

FIG. 27 is a diagram showing an arrangement of m-bit data in an image memory.

FIG. 28 is a block diagram showing a configuration of a laser drive circuit 7a.

FIG. 29 is a diagram illustrating an optical configuration of an image forming apparatus.

[Explanation of symbols]

 205 Font ROM 212 CPU 213 ROM 214 RAM 401 to 404 Image memory

Claims (10)

[Claims] 1. An image forming apparatus capable of performing grayscale printing for each pixel, a storage unit for storing pattern data, an image data generation unit for generating binary raster image data of the stored pattern data, Dividing means for dividing the raster image data into a plurality of blocks, a pixel number detecting means for detecting the number of black or white pixels present in the divided blocks, and a pixel number detecting means for detecting the number of black or white pixels. Comparing means for comparing a threshold value with each of the blocks; and, as a result of the comparison, a block number calculating means for calculating the number of blocks having the number of black or white pixels equal to or larger than the threshold value; Means for relating the number of blocks and the print density as a qualitative rule, and according to the rule, the degree of the number of blocks belonging to a predetermined set, A degree deriving unit that derives a degree belonging to the set of print densities; and inference means that infers the print density based on the derived degree belonging to the set of print densities. An image forming apparatus for converting binary image data into multilevel image data. 2. The degree deriving means derives the degree of belonging to the set of print densities from the degree of the number of blocks belonging to a plurality of predetermined sets, and the inference means comprises: Combining means for combining the degree of belonging to the set of print densities; and calculating means for determining the inferred print density based on the combined degree of belonging to the set of print densities. The image forming apparatus according to claim 1. 3. A rule storing means for storing a qualitative rule between the number of blocks and the print density in the form of a fuzzy proposition. Item 3. The image forming apparatus according to Item 2. 4. The apparatus according to claim 1, wherein said degree deriving means includes membership function storing means for storing a membership function in which said number of blocks and said print density are respectively expressed by fuzzy sets. The image forming apparatus according to claim 2 or 3. 5. The degree deriving means includes a degree of fitness calculating means for calculating the degree of fitness of the number of blocks based on a membership function stored in the membership function storing means. Item 5. The image forming apparatus according to Item 4. 6. The degree deriving means obtains an inference result of the print density from the fitness of the calculated number of blocks in accordance with rules stored in the rule storage means in the form of fuzzy propositions. The image forming apparatus according to claim 5, wherein 7. The image according to claim 6, wherein the degree calculating means obtains the inference result by a minimum value operation or a multiplication operation of the degree of conformity of the number of blocks and the membership function of the print density. Forming equipment. 8. The image forming apparatus according to claim 7, wherein the inference unit combines the inference results in each rule by a maximum value operation, a minimum value operation, or an addition operation. 9. The image forming apparatus according to claim 8, wherein the calculating unit determines the print density by obtaining a center of gravity of the synthesized result. 10. An image forming method for performing grayscale printing for each pixel, wherein pattern data is stored, binary raster image data of the stored pattern data is generated, and the generated raster image data is stored in a plurality. The number of black or white pixels present in the divided block is detected, and the detected number of black or white pixels is compared with a threshold value for each of the blocks. As a result, the number of the blocks having the number of black or white pixels equal to or larger than the threshold value is calculated, and the calculated number of blocks and the print density are related as a qualitative rule. Derives the degree of belonging to the set of print densities from the degree to which the number of blocks belongs to a predetermined set, and based on the derived degree of belonging to the set of print densities, An image forming method, comprising inferring a print density and converting binary image data into multi-valued image data based on the inferred print density.