JP2000078421A - Device, method and system for processing image - Google Patents

Abstract

PROBLEM TO BE SOLVED: To guarantee the gray density and gradation of a source image over detailed parts and to reproduce colors with fidelity even when calibration is performed to image data provided by reading the original image through an image input device. SOLUTION: A three-dimensional (3D) lookup table(LUT) 122 is prepared by an LUT preparing part 123 based on measured color data provided by measuring the colors of a chart equipped with the patches of plural colors and read data provided by reading that chart through a scanner 106. In that case, concerning the respective grid points of the 3D LUT 122, the prescribed number of the read data are extracted in order from the smallest color difference from these grid points and based on the prescribed number of read data, the output data of these grid points are prepared.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an image processing apparatus and method for reading an original image by image input means and correcting the input image data, and a method and an image processing system.

[0002]

2. Description of the Related Art With the recent development of image processing technology, image input devices such as scanners for optically reading a document image to generate image data have become widespread. Further, the spread of a color scanner or the like that reads a color original and generates color image data is remarkable.

Conventionally, in an image processing apparatus having a color image input device as image input means, a so-called calibration for correcting input / output characteristics of the color image input device in order to output image data faithful to an original image. Correction processing referred to as a correction processing.

In a calibration process in a conventional color image input device, first, a color of a calibration chart is measured in advance, and the colorimetric value is set as a target value. Then, the calibration chart is read by a color image input device, and since the input / output characteristics are close to linear characteristics, an operation using a matrix filter that minimizes an error between the read data and the target value is performed. Thus, the corrected output data is obtained.

[0005] Further, an image input device for inputting an image, such as a scanner, generally has a unique input characteristic, which exists as a so-called individual difference of the device. Therefore, in an image processing apparatus that performs calibration on color image data input by an image input device, it is necessary to absorb individual differences between image input devices and perform calibration processing independent of the image input device. . Therefore, in the conventional image processing apparatus, for example, a calibration chart of three gradations or less such as white / black or white / gray / black, or a calibration chart of continuous gradation is used for each solid state of the input device. By performing calibration with appropriate correction for each time, absorption of individual differences and correction of gray density have been performed.

[0006]

However, in the above-mentioned conventional image processing apparatus, when the image data obtained by reading the original image by the image input device is subjected to the calibration, the original image can be described in detail. It is difficult to guarantee the gray density and gradation of the color and to reproduce the color faithfully.

Further, in order to sufficiently absorb the individual differences and correct the gray density in the image input device, the conventional method using a calibration chart of three steps or less has insufficient accuracy.

Also, in the method using a continuous tone calibration chart, when a continuous tone chart is created, density unevenness is likely to occur in the patch. Is difficult to do,
It was also difficult to create a plurality of completely similar continuous tone charts. Therefore, even when a continuous tone chart is used, it is difficult to perform appropriate individual difference absorption and gray density correction processing.

SUMMARY OF THE INVENTION The present invention has been made to solve the above-mentioned problems, and an image processing apparatus and a method thereof capable of faithfully reproducing the gray density and color of an original image in detail. It is an object to provide an image processing system.

It is another object of the present invention to provide an image processing apparatus, a method thereof, and an image processing system capable of improving the accuracy of gray density correction while absorbing individual differences between image input apparatuses.

[0011]

As one method for achieving the above object, the image processing method of the present invention has the following arrangement.

That is, an image processing method in an image processing apparatus provided with an image input means for reading a document image and inputting color image data, wherein colorimetry is performed on a chart provided with patches of a plurality of colors to obtain colorimetric data A colorimetric step of obtaining, a reading step of reading the chart by the image input means to obtain read data, and a step of ensuring color reproducibility of the original image based on the colorimetric data and the read data. A three-dimensional table creating step of creating a three-dimensional table, and a correcting step of performing correction using the three-dimensional table on color image data obtained by reading the original image with the image input unit. In the three-dimensional table creation step, for each lattice point of the three-dimensional table, a predetermined number of the read data is extracted in ascending order of the color difference from the lattice point, Characterized by creating output data of lattice points on the basis of the collected data.

An image processing method in an image processing apparatus having an image input means for reading a document image and inputting image data, wherein colorimetric data is obtained by measuring a color of a chart provided with a plurality of gradation patches. A colorimetric step, a reading step of reading the chart with the image input means to obtain read data, and based on the colorimetric data and the read data,
1 for guaranteeing gray density and gradation of the original image
A one-dimensional table creation step of creating a dimension table; and a correction step of performing correction using the one-dimensional table on image data obtained by reading the original image with the image input unit, In the one-dimensional table creation step, a plurality of the one-dimensional tables are created according to input characteristics of the image input means.

[0014]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS An embodiment according to the present invention will be described below in detail with reference to the drawings.

[First Embodiment] In the present embodiment,
It has two LUTs, a one-dimensional look-up table (hereinafter, one-dimensional LUT) and a three-dimensional look-up table (hereinafter, three-dimensional LUT), and performs a correction process using the LUT to guarantee the gray density and gradation of the original image. It is characterized by realizing guarantee and guarantee of color reproducibility.

<Configuration of Image Processing System> FIG. 1 shows an example of a system according to the present embodiment. The host computer 100 is connected to a printer 105 such as an inkjet printer, a scanner 106, a monitor 110, and an external storage device FD109 such as a floppy disk or a compact disk.

The host computer 100 includes application software 101 such as a word processor, a spreadsheet, and an Internet browser, and an operating system (OS).
em) 102, OS 10 by application 101
2, a printer driver 103 for processing various drawing commands (image drawing command, text drawing command, graphics drawing command) indicating an output image to generate print data, and image data input from the scanner 106. A scanner driver 104 that converts the data into an appropriate format so that the OS 102 can refer to the data, a monitor driver 108 that processes various drawing commands issued by the application 101 and displays the data on a monitor 110, and an FD that controls data input / output to and from the FD 109. It has a driver 107 as software.

The host computer 100 includes a central processing unit CPU 113 and a hard disk driver HD1 as various hardware on which the software can operate.
12, a random access memory RAM 114, a read only memory ROM 115, and the like. An external I / F 111 enables data communication with an external device.

As an example of the image processing system shown in FIG. 1, for example, PC-A manufactured by IBM, which is widely spread, is used.
Microsoft Windows for T-compatible personal computers
A form in which a desired application capable of performing image input and printing is installed using ws95 as an OS, and a scanner or a printer is connected can be considered.

The host computer 100 provides the image data input from the scanner 106 to the application 101 as image data. The application 101 creates output image data using text data classified as text such as characters, graphics data classified as graphics such as figures, image image data classified as natural images, and the like, When the output image data (drawing command group) is passed to the printer driver 103 via the OS 102,
The print output by the printer 105 is performed.

<Calibration Processing> The calibration processing in the present embodiment will be described below. FIG. 2 shows a schematic functional configuration for performing the calibration process in the present embodiment. In the present embodiment, a one-dimensional lookup table (hereinafter, one-dimensional LU) is used.
T) 121 and a three-dimensional lookup table (hereinafter, three-dimensional LUT) 122 are provided. These LUTs are generated by the LUT creation unit 123.
It is generated by the procedure described later.

In FIG. 2, image data input by the scanner 106 first passes through a one-dimensional LUT 121 to assure gray density and tonality, and then passes through a three-dimensional LUT 122 to produce color data. Reproducibility is improved. Therefore, a high-quality image can be output to the printer 105. Before output to the printer 105,
It goes without saying that various types of image processing are performed on the image data, but they are not particularly described here.

In this embodiment, the three-dimensional LUT 122
Controls the mathematical operation for converting the coordinate system of the input image to the RGB coordinate system, color calibration on the RGB coordinate system, the mathematical operation for converting the RGB coordinate system to the output signal coordinate system, and the like. . Here, the number of grid points in the three-dimensional LUT 122 is 8 bits (0 to 2).
16 × 16 × 16 409 in 17 steps on 55 gradations)
Assume that there are six points.

Each of the LUTs shown in FIG.
The application 101 may be provided on the M114 so that the application 101 can refer to the LUT, or may be provided on the scanner driver 104. In addition, the LU
It is also possible to transfer T to the scanner 106 and execute calibration on the scanner 106 side.

<Overview of LUT Creation Method> Hereinafter, one-dimensional LUT used in the calibration process of this embodiment will be described.
A method for creating the UT 121 and the three-dimensional LUT 122 will be described.

FIG. 3 is a flowchart showing an outline of the LUT creation processing executed by the LUT creation section 123. This processing is realized, for example, by the CPU 113 executing the predetermined application 101.

In the figure, first, a gray chart is measured by a color measuring device (not shown) (step S101), the measured data is normalized (step S102), and gray chart read data by the scanner 106 (step S103). Then, a one-dimensional LUT 121 is created (step 4). The one-dimensional LUT 121 realizes the guarantee of gray density and the guarantee of gradation in the calibration of the present embodiment.

Next, based on the measurement of the color chart by a colorimeter (not shown) (step S105), the normalization of the data (step S106), and the read data of the color chart by the scanner 106 (step S107). Create the three-dimensional LUT 122 (step S
108). The three-dimensional LUT 122 can improve color reproducibility in the calibration of the present embodiment.

Once the one-dimensional LUT 121 and the three-dimensional LUT 122 are completed as described above,
Using T, it is possible to perform appropriate correction processing on input image data by the scanner 106.

Hereinafter, a method of creating the one-dimensional LUT 121 and the three-dimensional LUT 122 will be described in more detail with reference to specific examples.

<Method of Creating One-Dimensional LUT>
A method for creating the UT 121 will be described.

FIG. 6 is a diagram showing an example of a gray chart having 20 patches. For example, "Kodak Gray Scale" generally available from Eastman Kodak Company is used. In step S101 described above, the gray chart is measured in a L * a * b * color space by a colorimeter (not shown), and the colorimetric values are input from, for example, the external I / F 111. Then, in step S102, the colorimetric value is
Is converted to an RGB color space by normalization in accordance with the γ characteristic of. Hereinafter, the colorimetric values of the gray chart in the RGB color space will be referred to as gray calibration data.

Then, in step S103, the scanner 10
6, the gray chart shown in FIG. 6 is read, and in step S104, a one-dimensional LUT 121 is created based on the input signal data and the calibration data.

Thus, a one-dimensional LUT 121 taking into account the input characteristics of the scanner 106 is created, and the one-dimensional LU
By using T121, the gray density and gradation of the original image can be guaranteed.

<Method of Creating Three-Dimensional LUT>
A method for creating the UT 122 will be described in detail with reference to the flowchart shown in FIG.

FIG. 7 is a diagram showing an example of a color chart having 256 patches. In the present embodiment, a plurality of color charts having different levels are prepared to prepare a total of 4096 patches.

First, in step S201 of FIG.
This color chart is converted into L * a * by a colorimeter (not shown).
The colorimetry is performed in the b * color space, and the colorimetric values are normalized in accordance with the γ characteristic of the printer 105 and converted to the RGB color space. Hereinafter, the colorimetric values of the color chart in the RGB color space are referred to as color calibration data.

Then, in step S202, the scanner 10
The input signal data is obtained by reading the color chart shown in FIG.

Next, in step 203, the three-dimensional LU
In order to obtain output image data of the grid point of interest at T122, three points are extracted in order from the input image data closest to the grid point of interest on the L * a * b * coordinate system. Then, in step S204, a 3 × 3 matrix filter to be multiplied with the image data of the grid point of interest by a three-dimensional linear equation based on the input signal data of the three points and the corresponding color calibration data. Is calculated.

Here, in the present embodiment, the boundary condition of each element of the matrix filter is set in the range of -0.6 to 1.5, and the element is not allowed to have any other numerical value.
That is, all elements of the matrix filter must satisfy the boundary conditions. Therefore, in step S205,
It is determined whether all the elements of the matrix calculated in step S204 are within the range satisfying the boundary condition. If not, the process returns to step S203 and the selection of the extraction point is performed again.
The details of the process of obtaining the three extraction points and calculating the matrix filter in steps S203 to S205 will be described later with reference to FIG.

If the matrix filter satisfies the boundary condition, the flow advances to step S206 to determine the calculated number of matrix filters. If the number of obtained matrix filters is two or less, in step S207,
1 to finally determine the average value of each element of the matrix
Each element of one matrix filter. On the other hand, when three or more sets of matrix filters are obtained, in step S208, an average value is calculated for each element of the matrix except for the maximum value and the minimum value, and each of the matrix filters to be finally determined is calculated. Element.

Next, in step S209, the three-dimensional L is calculated using the matrix filter obtained as described above.
By performing a matrix operation on each grid point on the UT 122, output data at the grid point is obtained.

In step S210, it is determined whether or not processing has been completed for all grid points in the three-dimensional LUT 122, that is, whether or not the processed grid point is the 4096th point. Proceed to S211. On the other hand, if the processing has not been completed, the process proceeds to step S203, and processing for the next grid point of interest is started.

In step S211, linear interpolation is performed on the grid points for which the matrix filter has not been calculated based on other nearby grid points, thereby obtaining output data at the grid points.

<Details of Matrix Calculation Process> The details of the process of calculating a matrix filter by obtaining three extraction points in steps S203 to S205 of FIG. 4 will be described below with reference to the flowchart of FIG.

First, in step S301, L * a * b
* 100 points are extracted in order from the input signal data closest to the grid point of interest on the coordinate system. In step S302, the color difference between the 100 points and the lattice point is 13.0.
The number of data within the range is determined, and the process branches in step S303 according to the number of data.

If there are three or more input signal data within the color difference 13.0, the flow advances to step S304 to limit the input signal data closest to the grid point of interest to the input signal data group within the color difference. Then, the remaining two points are selected in order from the input signal data group having a color difference of 13.0 or less. That is, all three points become input signal data within the predetermined color difference. Then, in step S305, a 3 × 3 matrix filter to be multiplied with the image data of the grid point of interest is obtained by a three-dimensional linear equation based on the input signal data of the three points and the corresponding color calibration data. Then, in step S306, it is determined whether or not each element of the matrix filter is within a predetermined range (-0.6 to 1.5). still,
Steps S308 and S309 to be described later, step S3
11 and S312 are also performed in step S30.
5 and S306.

In step S306, at least one element in the matrix filter is out of the predetermined range, that is, when the matrix filter cannot be calculated, or when the number of data within the predetermined color difference is two in step S303. , The process proceeds to step S307.

In step S307, the input signal data at two points within the predetermined color difference is fixed, and as the remaining one point, the closest point is selected from the other 100 input image data groups. Then, in step S308, a matrix filter is calculated, and in step S309, it is determined whether the matrix filter is within a predetermined range.

If at least one element in the matrix filter is out of the predetermined range in step S309, or if the number of data within the predetermined color difference is one or less in step S303, step S3
Go to 10.

In step S310, the input image data closest to the grid point of interest is fixed from the input image data group of 100 points, and the remaining two points are sequentially selected. Then, a matrix filter is calculated in step S311.
In step S312, it is determined whether the matrix filter is within a predetermined range.

Step S306 or S309 or S31
In FIG. 4, it is assumed that the matrix filter is within a predetermined range, that is, the calculation of the matrix filter is successful.
Go to step S206. On the other hand, if the matrix filter cannot be calculated in step S312, the process returns to step S203 in FIG.

As described above, the scanner 106
The three-dimensional LUT 122 is created in consideration of the input characteristics, and by using the three-dimensional LUT 122, the colors of the original image can be faithfully reproduced.

The output signal data of the lattice point near the gray of the three-dimensional LUT 122 is used as the one-dimensional LUT 12
One input signal data can be applied as it is.
Thereby, even in the three-dimensional LUT 122, further assurance of gray density and gradation can be performed.

Although the description has been made on the assumption that the grid points of the three-dimensional LUT are 4096, the present invention is not limited to this example.
It may be a point.

As described above, according to the present embodiment,
By using the one-dimensional LUT 121 and the three-dimensional LUT 122, it is possible to perform high-precision calibration in consideration of the input characteristics of the scanner 106, to assure the gray density and gradation of the original image, and to maintain the color fidelity Reproduction is possible.

[Second Embodiment] Hereinafter, a second embodiment according to the present invention will be described.
An embodiment will be described. Note that the configuration of the image processing system according to the second embodiment is the same as that of FIG. 1 according to the first embodiment described above, and therefore, the same reference numerals are referred to and description thereof will be omitted.

<Configuration of Image Processing System> FIG.
2 shows a schematic functional configuration for performing a calibration process in the embodiment. In the second embodiment, LU
It is characterized in that it includes a plurality of one-dimensional LUTs 801 and 802 created by a T creating unit 810 according to a procedure described later. The one-dimensional LUTs 801 and 802 respectively
It is created according to the input mode of the scanner 106 (reflective original mode, transparent original mode, etc.). In FIG. 8, the image data input by the scanner 106 passes through one of the one-dimensional LUTs 801 or 802 according to the input mode, thereby guaranteeing the gray density and the gradation. Therefore, a high-quality image can be output to the printer 105. It is needless to say that various types of image processing are performed on the image data before output to the printer 105, but this is not particularly described here.

Each of these LUTs is, for example, a RAM 11
4, the application 101 may refer to the LUT, or the scanner driver 1
04 can also be provided. It is also possible to transfer the LUT into the scanner 106 and execute calibration on the scanner 106 side.

<Overview of LUT Creation Method> FIG. 9 shows an LUT executed by the LUT creation unit 810 in the second embodiment.
It is a flowchart which shows the outline | summary of UT preparation processing. This processing is realized, for example, by the CPU 113 executing the predetermined application 101.

In the figure, first, in step S901, the calibration chart is measured with L * a * b * values by a colorimeter (not shown), and the colorimetric values are input from, for example, the external I / F 111.

Here, the calibration chart in the second embodiment is composed of patches of four or more steps having a linear characteristic with respect to the density value, and is prepared according to the input mode of the scanner 106. For example, for a mode for a reflection original such as a print image on plain paper, a gray chart as shown in FIG. 6 also shown in the first embodiment is used. For example, "Kodak Gray Scale" consisting of 20 steps (gradation) generally available from Eastman Kodak Company can be used. FIG. 1 shows a mode for a transparent original (hereinafter referred to as a positive original) such as a positive film (reversal film).
A chart as shown in FIG. FIG. 10 is a diagram showing a color chart and a gray chart for a positive film. For example, a color chart of “Fuji IT8” generally marketed by Fuji Photo Film Co., Ltd. is used. In the chart for the positive film shown in FIG.
The gray chart portion having 24 steps (gradations) below it can be used as a calibration chart for a positive document in the second embodiment.

The values obtained by measuring the color of the calibration chart are normalized to the γ characteristics of the printer 105 and converted into the RGB color space, that is, the colorimetric values of the gray chart in the RGB color space are converted. Is obtained. Hereinafter, this is referred to as calibration data. When the chart of “Fuji IT8” is used as a calibration chart, for example, the calibration data of the positive document is provided by a floppy disk or the like attached to the chart. L * a * b * data to FD109
It is also possible to read from it and use it as it is.

Then, in step S902, the scanner 1
In step 06, the calibration charts of the reflection original and the positive original are read to obtain input signal data.

Next, in step S 903, the one-dimensional LUTs 80 for the reflection original and the positive original based on the calibration data and the input signal data of the scanner 106.
1, 802 are respectively created.

Thus, the one-dimensional LUTs 8 for the reflection original and the positive original in consideration of the input characteristics of the scanner 106 are provided.
01 and 802 are created and selectively used according to the input document, so that the gray density and gradation of the original image can be guaranteed.

<Details of LUT Creation Method> Hereinafter, the one-dimensional LUT creation method in step S903 shown in FIG. 9 will be described in detail with reference to FIGS.

FIG. 11 is a diagram for explaining an outline of one-dimensional LUT creation, FIG. 12 is a diagram showing an example of an LUT used for simple gradation conversion, and FIG.
FIG. 3 is a diagram showing an example of a one-dimensional LUT created in FIG.

First, the number of gradations of the scanner 106 (10 bits) and the number of gradations of the host computer 100 (8 bits)
10 bits prepared in advance to match
A calibration chart is read from the scanner 106 using an 8-bit LUT. This LUT may be simply converted from 10 bits to 8 bits and multiplied by gamma, or simply logarithmically converted. An example of this LUT is shown in FIG.
It is shown in FIG. FIG. 12A shows a correspondence between each 10-bit value and an 8-bit value, and FIG. 12B shows a logarithmically converted 10-bit value.
This shows an example of a LUT of 8 bits → 8 bits.

Then, based on the obtained 8-bit scanner input signal data and calibration data,
Create an 8-bit to 8-bit LUT. This example is shown in FIG.
1 (a). FIG. 11A is a table showing the correspondence between calibration data and scanner input signal data each having 8 bits.

Next, a 10-bit to 8-bit LUT shown in FIG. 12 is applied to the 8-bit scanner input signal data.
, 10-bit scanner input signal data is obtained. As a result, a default conversion curve shown in FIG. 11B is obtained. Then, a 10-bit → 8-bit one-dimensional LUT is created by associating the 10-bit input signal data with the calibration data. The one-dimensional LUT thus obtained is a curve of the LUT in FIG. 11B, and FIG.
Is a numerical representation of it.

In the example shown in FIG. 11, in the R component, 1
When the 0-bit input signal data is “300”, the corresponding 8
The case where the bit input signal data is “200” and the calibration data at this time is “170” is shown. That is, when the R component of the 10-bit input signal data from the scanner 106 is “300”, the one-dimensional L
It can be seen that the UT is corrected to an 8-bit value of “170”. This makes it possible to absorb the individual difference of the scanner 106 and appropriately correct the gray density.

FIG. 13 is a diagram showing an example of a one-dimensional LUT obtained corresponding to FIG. 12. In FIG. 13 (b), a dotted line corresponds to FIG. 12 (b), and a solid line Shows the obtained one-dimensional LUT.

In the second embodiment, the scanner 106
One-dimensional LUs corresponding to the type of input and its input mode, etc.
T is created and stored in, for example, the RAM 114 or the like. The plurality of one-dimensional LUTs and the respective calibration data are all managed by a predetermined application on the host computer 100 side. That is, each time an input operation is performed, the input means is determined, an appropriate one is selected from a plurality of one-dimensional LUTs, and the selected one is set in the scanner driver 104.

FIG. 14 is a flowchart of a correction process for image data input from the scanner 106 in the second embodiment. Here, as the scanner 106,
It is assumed that a scanner for reading a normal reflection original and a film scanner for reading a positive film can be connected to the host computer 100, respectively. Host computer 1
When the scanner 106 is connected, the OS 102 can obtain various kinds of information such as the device type of the scanner 106 via the scanner driver 104.

In step S1401, the scanner 10
When image data is input from step 6, step S1402
It is determined whether the image data is a reflection original or a positive original. This determination can be made based on the device type of the scanner 106 without actually referring to the image data. If the original is a positive original, the process proceeds to step S1403 to select the one-dimensional LUT 802 created for the positive original. If the original is a reflective original, the process proceeds to step S1404 to select the one-dimensional LUT 802 created for the reflective original.
Select UT801. Then, in step S1405, optimal correction processing, that is, calibration, is performed on the input image data.

As described above, the one-dimensional LUT 801 created for the reflection original and the one-dimensional LU created for the positive original are described.
By selectively using T802, in any case, the gray density can be appropriately corrected while absorbing the individual difference of the scanner 106.

By providing the function of the scanner driver 104 directly to the scanner 106, an appropriate one-dimensional LUT can be provided from the host computer 100 to the scanner 10.
6 can also be transferred to the storage unit.

In the second embodiment, two types of one-dimensional LUTs 8 corresponding to a reflective original and a transparent original, respectively, are used.
Although an example of creating 01, 802 has been described,
It is of course possible to create three or more one-dimensional LUTs according to the type of the image input device or the input mode and selectively use them.

In the second embodiment, an image processing system having one scanner 106 as an image input device has been described. However, a plurality of scanners having different input characteristics can be connected at the same time, and the input of each scanner can be performed. Correspondingly, a plurality of one-dimensional LUTs can be selectively used.

As described above, according to the second embodiment, it is possible to improve the gray density and the gradation correction accuracy while absorbing the individual differences of the scanner 106.

[Other Embodiments] Even if the present invention is applied to a system composed of a plurality of devices (for example, a host computer, an interface device, a reader, a printer, etc.), an apparatus (a single device) may be used. For example, the present invention may be applied to a copying machine, a facsimile machine, and the like.

An object of the present invention is to provide a storage medium storing a program code of software for realizing the functions of the above-described embodiments to a system or an apparatus, and to provide a computer (or CPU) of the system or apparatus.
And MPU) read and execute the program code stored in the storage medium.

In this case, the program code itself read from the storage medium implements the functions of the above-described embodiment, and the storage medium storing the program code constitutes the present invention.

Examples of the storage medium for supplying the program code include a floppy disk, hard disk, optical disk, magneto-optical disk, CD-ROM, and CD.
-R, a magnetic tape, a nonvolatile memory card, a ROM, or the like can be used.

When the computer executes the readout program code, not only the functions of the above-described embodiment are realized, but also the OS (Operating System) running on the computer based on the instruction of the program code. ) May perform some or all of the actual processing, and the processing may realize the functions of the above-described embodiments.

Further, after the program code read from the storage medium is written into a memory provided in a function expansion board inserted into the computer or a function expansion unit connected to the computer, based on the instructions of the program code, It goes without saying that the CPU included in the function expansion board or the function expansion unit performs part or all of the actual processing, and the processing realizes the functions of the above-described embodiments.

[0088]

As described above, according to the present invention, it is possible to faithfully reproduce the gray density and color of the original image in detail.

Further, it is possible to improve the accuracy of gray density correction while absorbing individual differences of the image input device.

[0090]

[Brief description of the drawings]

FIG. 1 is a block diagram illustrating a configuration of an image processing system according to an embodiment of the present invention.

FIG. 2 is a block diagram illustrating a functional configuration for performing a calibration process according to the embodiment;

FIG. 3 is a flowchart illustrating an outline of an LUT creation process according to the embodiment.

FIG. 4 is a flowchart illustrating a three-dimensional LUT creation process according to the present embodiment.

FIG. 5 is a flowchart illustrating a three-dimensional LUT creation process according to the embodiment.

FIG. 6 is an example of a gray chart used in the present embodiment.

FIG. 7 is an example of a color chart used in the present embodiment.

FIG. 8 is a block diagram showing a functional configuration for performing a calibration process according to a second embodiment of the present invention.

FIG. 9 is a flowchart illustrating an LUT creation process according to the second embodiment.

FIG. 10 is a gray chart for a positive document used in the second embodiment.

FIG. 11 is a diagram for explaining an outline of LUT creation in a second embodiment.

FIG. 12 is a diagram illustrating an example of an LUT used for simple gradation conversion in the second embodiment.

FIG. 13 shows a one-dimensional LU created in the second embodiment.
It is a figure showing T example.

FIG. 14 is a flowchart illustrating a calibration process according to the second embodiment.

[Explanation of symbols]

 REFERENCE SIGNS LIST 100 host computer 101 application 102 OS 103 printer driver 104 scanner driver 105 printer 106 scanner 107 FD driver 108 monitor driver 109 FD 110 monitor 111 communication I / F 112 HD 113 CPU 114 RAM 115 ROM

Claims (33)

[Claims] 1. An image processing method in an image processing apparatus having image input means for reading a document image and inputting color image data, wherein the colorimetric data is obtained by measuring the color of a chart having patches of a plurality of colors. A color measurement step for obtaining; a reading step for reading the chart with the image input means to obtain read data; and 3 for ensuring color reproducibility of the document image based on the color measurement data and the read data. A three-dimensional table creating step of creating a three-dimensional table; and a correcting step of performing correction using the three-dimensional table on color image data obtained by reading the original image with the image input unit. In the three-dimensional table creation step, for each lattice point of the three-dimensional table, a predetermined number of the read data is extracted in ascending order of the color difference from the lattice point, and the predetermined number of read data is extracted. Image processing method characterized by creating the output data of the grid points based on the data. 2. The color difference from the grid point is a color difference on L * a * b * color space coordinates.
The image processing method described in the above. 3. The three-dimensional table creating step includes: extracting a predetermined number of image data closest to a grid point of interest on L * a * b * color space coordinates from the read data; A matrix creation step of creating a matrix based on the predetermined number of read data and the colorimetric data extracted in the above, and by multiplying the matrix by the read data corresponding to the grid point of interest, 3. The image processing method according to claim 2, further comprising a matrix operation step of calculating output data. 4. The image processing method according to claim 3, wherein the predetermined number is three points, and the matrix is a 3 × 3 matrix. 5. The method according to claim 1, wherein in the extracting step, the second color difference within a predetermined color difference from a grid point of interest on L * a * b * color space coordinates.
5. The image processing method according to claim 4, wherein said three points of image data are extracted with priority from said image data. 6. The image processing method according to claim 3, wherein in the matrix creation step, each element of the matrix is created within a predetermined range. 7. An interpolation step of calculating output data at a grid point for which a matrix has not been created in the matrix creation step by linear interpolation based on another neighboring grid point. The image processing method according to claim 3, wherein 8. In the matrix creation step, when a plurality of sets of a predetermined number of image data are extracted in the extraction step, a matrix is created for each of the plurality of sets,
4. The image processing method according to claim 3, wherein one matrix is created based on the plurality of matrices. 9. In the matrix creation step, when three or more sets of a predetermined number of image data are extracted in the extraction step, a plurality of matrices created for each set are extracted. The average value of the values excluding the maximum value and the minimum value of each element is used. When less than three sets of the predetermined number of image data are extracted,
9. The image processing method according to claim 8, wherein an average value of each element of a plurality of matrices created for each set is used. 10. The image processing method according to claim 9, wherein the chart has 4096 color patches. 11. The image processing method according to claim 1, wherein the three-dimensional table has 4096 grid points. 12. A gray color measurement step of measuring a gray chart provided with a plurality of gradation patches to obtain gray color measurement data, and reading the gray chart by the image input unit to obtain gray read data. A gray reading step; a one-dimensional table creating step of creating a one-dimensional table for guaranteeing gray density and gradation of the document image based on the gray colorimetric data and the gray read data; 2. The image processing method according to claim 1, further comprising: a gray correction step of correcting the color image data using a table. 13. The gray chart has at least 20
13. The image processing method according to claim 12, further comprising a gradation patch. 14. The image processing method according to claim 13, wherein the gray chart is a commercially available gray chart. 15. The image according to claim 12, wherein the three-dimensional table creating step further uses output data of the one-dimensional table as output data of a lattice point near gray in the three-dimensional table. Processing method. 16. Image input means for reading a document image and inputting color image data, colorimetric data obtained by measuring a chart provided with a plurality of color patches, and read data obtained by reading the chart with the image input means. A three-dimensional table creating means for creating a three-dimensional table for guaranteeing the color reproducibility of the original image, based on the above, and for color image data obtained by reading the original image with the image input means. Correction means for performing correction using the three-dimensional table, wherein the three-dimensional table creation means determines a predetermined number of the grid points in the three-dimensional table in ascending order of color difference from the grid points. An image processing apparatus for extracting read data and generating output data of the grid point based on the predetermined number of read data. 17. The image processing apparatus according to claim 16, wherein the color difference from the grid point is a color difference on L * a * b * color space coordinates. 18. A recording medium on which a program code for image processing in an image processing apparatus provided with an image input means for reading a document image and inputting color image data is recorded, wherein the program code comprises a plurality of color patches. A code of a colorimetric data input step of inputting colorimetric data obtained by measuring the color of a chart, a code of a read data input step of obtaining the read data by reading the chart with the image input means, and the colorimetric data. A code for a three-dimensional table creation step of creating a three-dimensional table for guaranteeing color reproducibility of the original image based on the read data; and a color obtained by reading the original image by the image input unit. And a code for a correction step of performing correction on the image data using the three-dimensional table. Extracting, for each grid point of the three-dimensional table, a predetermined number of the read data items in ascending order of color difference from the grid point, and creating output data of the grid point based on the predetermined number of read data items Recording medium characterized by the above-mentioned. 19. An image processing method in an image processing apparatus having image input means for reading a document image and inputting image data, wherein colorimetric data is obtained by measuring a color of a chart provided with a plurality of gradation patches. A color measuring step, a reading step of reading the chart with the image input unit to obtain read data, and a step of guaranteeing a gray density and a gradation of the original image based on the color measuring data and the read data. A one-dimensional table creating step of creating a one-dimensional table; and a correcting step of performing correction using the one-dimensional table on image data obtained by reading the original image by the image input unit. The image processing method according to claim 1, wherein in the one-dimensional table creating step, a plurality of the one-dimensional tables are created according to input characteristics of the image input means. 20. The image processing method according to claim 19, wherein the chart is a gray chart including at least four gradation patches. 21. The image input device, wherein a plurality of types of originals can be input, and in the reading step, a plurality of types of gray charts corresponding to a plurality of types of the originals are read by the image input unit, 21. The image processing method according to claim 20, wherein in the table creating step, a plurality of the one-dimensional tables are created according to a plurality of types of gray charts read in the reading step. 22. The image processing method according to claim 21, wherein the plurality of types of originals are a reflective original and a transparent original. 23. The gray chart according to claim 22, wherein the gray chart has at least 20 gradation patches for the reflection original and at least 24 gradation patches for the transparent original. Image processing device. 24. The image processing method according to claim 23, wherein the gray chart is a commercially available gray chart for both the reflection original and the transparent original. 25. The image processing method according to claim 22, wherein the transparent original is a positive film. 26. In the correcting step, according to characteristics of image data read by the image input unit,
The image processing method according to claim 19, wherein the plurality of one-dimensional tables are selectively used. 27. The one-dimensional table creating step, wherein the one-dimensional table is corrected so that the number of tones when reading an original image by the image input means is corrected to the number of tones that can be processed by the image processing apparatus. 20. The image processing method according to claim 19, wherein the image is created. 28. Image input means for reading a document image and inputting image data, colorimetric data obtained by measuring a chart provided with a plurality of gradation patches, and read data obtained by reading the chart with the image input means A one-dimensional table creating means for creating a one-dimensional table for guaranteeing the gray density and gradation of the original image, based on the image data obtained by reading the original image by the image input means. Correction means for performing correction using the one-dimensional table. The one-dimensional table creation means creates a plurality of the one-dimensional tables in accordance with input characteristics of the image input means. Image processing device. 29. The image processing apparatus according to claim 28, wherein the chart is a gray chart including at least four gradation patches. 30. An image processing system in which an image input device that reads a document image and inputs image data is connected to an image processing device that corrects the image data, wherein the image processing device comprises: A one-dimensional image for guaranteeing gray density and gradation of the original image based on colorimetric data obtained by measuring the color of a chart having a gradation patch and read data obtained by reading the chart with the image input device. A one-dimensional table creating means for creating a table; and a correcting means for performing correction using the one-dimensional table on image data obtained by reading the original image with the image input device, An image processing system, wherein the one-dimensional table creating means creates a plurality of one-dimensional tables according to input characteristics of the image input device. 31. The image processing system according to claim 30, wherein the chart is a gray chart including at least four-tone patches. 32. The image processing apparatus further comprises: a memory for holding the plurality of one-dimensional tables and information for creating the one-dimensional tables; and the memory according to characteristics of image data read by the image input device 31. One of the plurality of one-dimensional tables stored in the image input device is selected, and the selected one-dimensional table is transferred to the image input device.
The image processing system described in the above. 33. A recording medium on which a program code for image processing in an image processing apparatus having an image input means for reading an original image and inputting image data is recorded,
The program code includes a code of a colorimetric data input step of inputting colorimetric data obtained by measuring the color of a chart having a plurality of gradation patches; A code of a one-dimensional table creating step of creating a one-dimensional table for guaranteeing gray density and gradation of the original image based on the colorimetric data and the read data; And a code of a correction step of performing correction using the one-dimensional table on image data obtained by reading the image data by the image input means. In the one-dimensional table creation step, the image input means A plurality of the one-dimensional tables are created according to the input characteristics of the storage medium.