JP2003051944A - Image processing method, image processing system, program and storage medium - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide an image processing system that applies density correction for optimizing contrast to read image data. SOLUTION: The image processing system generates a density distribution histogram from read image data, generates a density correction curve on the basis of the ratio of data of both the light/dark extremes and corrects the density.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an image reading method and system for reading an original using an image sensor and performing density correction processing on the read image data, a program therefor, and a recording medium.

[0002]

2. Description of the Related Art Conventionally, an image read by an image reading device is subjected to shading correction processing for correcting light distribution variation of a light source based on correction data prepared in advance by reading a standard white member, and a monitor is provided. Gamma correction processing was performed using a gamma table on the image reading device side that matches the gamma characteristics of the display, and the result was displayed on the display.

[0003]

However, if the read original is an entirely bright original, conversely an entirely dark original, or an original with unclear light and dark, the read image is read accordingly. Became a bright image, a dark image, or an image with gray. For example, in the case of a character original, the characters become very difficult to read, which has also been a factor of reducing the recognition rate of OCR (optical character recognition).

Japanese Patent Laid-Open No. 4-35170 discloses a method for performing gamma correction processing according to the density characteristics of a read document.
It is disclosed in the publication. However, the information on the density characteristic needs to be set by the user, and it is not a proposal regarding a gamma correction means for enhancing the contrast of image data.

In view of the above points, the object of the present invention is to
An object of the present invention is to provide an image reading apparatus that can perform gamma correction processing with optimized contrast even on image data with unclear brightness and darkness.

[0006]

In order to achieve the above object, the present invention has the following constitution.

[Claim 1] A step of generating image data by reading light from a document, a step of creating a histogram of the density distribution from the image data, and a light and dark end of the density distribution with respect to the total number of data of the image data. An image reading method comprising: a step of generating a density correction curve based on the ratio of the number of data points closer to each other; and a step of correcting the density of image data with the density correction curve.

[Claim 2] In the step of generating the density correction curve according to claim 1, the density is divided into a plurality of areas based on an intermediate value between the shadow point and the highlight point of the image data, and each area is divided. The density correction curve is created based on the number of data of the histogram of the density distribution included in.

[Claim 3] In the step of generating the density correction curve according to claim 2, a signal of a density level darker than the intermediate value becomes a darker level, and a signal of a density level brighter than the intermediate value becomes brighter. It is characterized in that an S-shaped density correction curve such that

[Claim 4] In the step of generating the density correction curve according to claim 3, the S-shaped density correction curve having a small curvature is generated when the ratio of the number of data near the light and dark ends is large. When the ratio is small, an S-shaped density correction curve having a large curvature is generated.

[Claim 5] In the step of creating the histogram of the density distribution according to claim 1, when the original is a color image, each density data of R, G and B of the image data is combined. It is characterized in that a histogram of one density distribution is created.

[Claim 6] In the step of performing the density correction according to claim 1, when the original is a color image, the density correction common to the R, G and B density data of the image data is performed. It is characterized by using a curve.

[Claim 7] means for reading light from a document to generate image data, means for creating a histogram of the density distribution from the image data, and light and dark ends of the density distribution with respect to the total number of data of the image data. An image reading system comprising: a means for generating a density correction curve based on the ratio of the number of data points closer to each other; and a means for correcting the density of image data with the density correction curve.

[Claim 8] The means for generating the density correction curve according to claim 7 divides the density into a plurality of areas on the basis of an intermediate value between the shadow point and the highlight point of the image data, and each area is divided into a plurality of areas. The density correction curve is created based on the number of data of the histogram of the density distribution included in.

[Claim 9] In the means for generating the density correction curve according to claim 8, a signal of a density level darker than the intermediate value is darker and a signal of a density level brighter than the intermediate value is brighter. It is characterized in that an S-shaped density correction curve such that

[Claim 10] In the means for generating the density correction curve according to claim 9, the S-shaped density correction curve having a small curvature is used when the ratio of the number of data near the light and dark ends is large. When the ratio is small, an S-shaped density correction curve having a large curvature is generated.

[Claim 11] When the original is a color image, the means for creating the histogram of the density distribution according to claim 7 synthesizes the R, G and B density data of the image data. It is characterized in that a histogram of one density distribution is created.

[Claim 12] When the original is a color image, the means for performing the density correction according to claim 7 is a common density correction for the R, G and B density data of the image data. It is characterized by using a curve.

[Claim 13] A computer-executable program for realizing the image reading method according to any one of claims 1 to 5 by controlling the computer.

[Claim 14] A recording medium on which the program according to claim 13 is recorded.

[0021]

Preferred embodiments of the present invention will be described below with reference to the accompanying drawings.

FIG. 1 is a block diagram of a schematic configuration of an image reading apparatus according to the embodiment of the present invention, and FIG. 2 is a sectional view of the image reading apparatus according to the embodiment of the present invention. An embodiment for obtaining the density correction data based on dividing the density distribution into four will be described below.

In FIGS. 1 and 2, reference numeral 101 denotes an image sensor, which irradiates the read original 202 with light emitted from a light source. The reflected light from the read document 202 is received by the image pickup element 204 via the lens 203 and photoelectrically converted. The image sensor 101 is moved in the sub-scanning direction along the original, and R, G, B line sequential (or dot sequential) is performed line by line.
Read the color image of.

The electric signal photoelectrically converted by the image pickup element 204 is sent to the electric substrate 205 of the image reading apparatus 201. 1 to 102 of FIG. 1 are provided on the electric board 205, and the following processing is performed on the electric signal sent from the image sensor. The AFE 102 performs processing such as amplifier amplification, DC offset correction, and A / D conversion on the electric signal output from the image sensor 101,
An analog preprocessor that finally outputs, for example, 12-bit digital image data.

The shading correction circuit 103 stores, as shading correction data, reference level data created by reading the white reference plate 206 provided outside the read original range using the image sensor 101, and based on this correction data. The shading correction of the image data generated by reading the read document is performed. The shading correction data is stored in the external device 106 after the data is acquired, and the data necessary for scanning is downloaded to the image reading device of the present embodiment and processed.

The data processing circuit 104 includes an external device 106.
Preset image reading mode (binary, 24
Packing processing according to (multi-valued bit etc.) is performed.

The interface circuit 105 transmits / receives a control signal to / from an external device 106, which is a host device of the image reading apparatus according to the present embodiment such as a personal computer, and outputs an image signal.

The external device 106 is a host computer and has a scanner driver for controlling the image reading device. The external device 106 forms an image processing system together with the image reading device.

The scanner driver has a user interface for designating an image reading mode, a resolution, a reading range, etc., and a control signal and a reading start command based on each designation are sent to the interface circuit 105 described above. To the image reading device. Also,
The scanner driver sequentially processes the image data read by the image reading device according to the control signal and displays the image on the screen. At this time, the gamma correction process of the present embodiment is performed by the scanner driver.

FIG. 3 shows a flow chart of image reading control in the image reading apparatus of this embodiment.
When the scanner driver is activated, first, step S30
At 1, wait for a determination as to whether or not to perform a preview scan. When the preview scan is started, step S30
In step 2, the read document is scanned at the minimum resolution and a preview image is displayed on the monitor. Then, in step S303, it is determined from the type of the original document whether or not to create a density correction curve for the character original of the image data. Step S303
When it is determined that the density correction curve for the text original is created in step S304, the density correction curve of the present invention is created, combined with the monitor gamma correction curve, and externally used as gamma correction data for the text original. Stored in device 106. If it is determined in step S303 that the density correction curve for the text original is not created, the process advances to step S305 to store the monitor gamma correction curve in the external device 106 as monitor gamma correction data. Next, when the main scan is started in step S306, step S304 or S305 is performed in step S307.
The original document is read while the image data is corrected according to the gamma correction data created in step 1, and the scan is completed.

If the main scan is not executed in step S306, it is determined in step S308 whether or not the scan operation is ended. When the scan operation is ended in step S308, the main scan is ended without being executed. If the scan operation is not ended in step S308, it is determined in step S309 whether to start the re-preview scan. Step S309
If re-preview is started in step S302
Then, the preview scan and the creation of the density correction curve for the text original are executed. If re-preview is not started in step S309, the process returns to step S306 and waits for a determination as to whether to start the main scan.

FIG. 4 shows a gamma correction data creation routine for character originals in step S304 in FIG.

First, in step S401, a histogram in which all R, G, and B colors are combined is generated in the color mode as shown in FIG. 5, and a histogram of only G color is generated in the gray mode. Next, in step S402, the shadow value s and the highlight value h are searched from the histogram, and the intermediate value m is calculated. Further, the shadow value-intermediate value and the intermediate value-highlight value are each divided into two, and [s, (s +
m) / 2], [(s + m) / 2, m], [m, (m +
h) / 2], [(m + h) / 2, h]. In step S403, the cumulative value a, b, c, d of the frequency of each section is obtained, and the density correction coefficient D = (a +
d) / (a + b + c + d) is calculated.

When the density correction coefficient D is obtained, step S
Output f to data x in the section [s, m] at 404
(X) = m × (x / m) ^ (1 / D), and output g (x) = N− for the data x in the section [m, h].
(N−m) × ((N−x) / (N−m)) ^ (1 / D)
Then, an S-shaped character original density correction curve (FIG. 6) is created. Here, N represents the number of bit gradations of a pixel, which can be represented by N = (2 ^ n) -1, and N = 255 when the number of gradations is 8 bits. In such a tone curve, as the density correction coefficient D is larger, S which is weaker than the original image data.
The character density correction is performed, and the smaller the density correction coefficient D is, the stronger the S-shaped density correction is applied.

Once the density correction curve for the text original is obtained,
In step S405, it is combined with the monitor gamma correction curve (FIG. 7), and the input / output table data is stored in the external device 106 as gamma correction data for the text original.
It should be noted that the gamma correction data for character originals created at the time of image data correction in the color mode is used as R, G, B common correction data to perform correction on each color data. Here, FIG.
Shows a composite curve when the monitor gamma is set to a γ value of 2.2.

(Other Embodiments) In the above embodiment, the density distribution is divided into four to obtain the density correction coefficient D. However, the density correction coefficient D is not limited to four, and [s, s + (hs)). / 3],
[S + (h−s) / 3, s + (h−s) × 2/3],
[S + (h−s) × 2/3, h] is divided into three, and the cumulative values of the frequencies of the respective sections are set to e, f, and g, and D = (e +
g) / (e + f + g). Further, in the case of 5 divisions or more, similarly, the density correction coefficient D can be obtained from the ratio of the total number of data and the frequency of the outer side to create the density correction curve.

In the above embodiment, the image processing system is configured by the image reading apparatus 201 and the host computer of the external apparatus 106, but it is also possible to implement it in an apparatus in which these are integrated.

[0038]

As described above, according to the present invention,
It is possible to perform the gamma correction process that optimizes the contrast even on image data with unclear brightness and darkness.

[Brief description of drawings]

FIG. 1 is a block diagram of a schematic configuration of an image reading apparatus according to an embodiment of the present invention.

FIG. 2 is a sectional view of the image reading apparatus according to the embodiment of the present invention.

FIG. 3 is a flowchart of a document reading operation of the image reading device according to the embodiment of the present invention.

FIG. 4 is a flowchart for creating gamma correction data for a character original in the image reading apparatus according to the embodiment of the present invention.

FIG. 5 is an example of a histogram of a character original image according to the embodiment of the present invention.

FIG. 6 is an example of a tone curve for a character original according to the embodiment of the invention.

FIG. 7 is a curve of gamma correction data for a character original according to the embodiment of the present invention.

Continued front page    F term (reference) 5B057 CE11 CE17 CH01 CH11 DA08                       DB02 DB06 DB09 DC23                 5C077 MP01 MP08 PP15 PP32 PP37                       PP52 PP53 PQ12 PQ19 PQ22                 5C079 HB01 LA10 LA12 LB01 MA01                       MA11

Claims (14)

[Claims] 1. A step of reading light from a document to generate image data, a step of creating a histogram of a density distribution from the image data, and data of the density distribution near both the light and dark sides with respect to the total number of data of the image data. An image processing method comprising: a step of generating a density correction curve based on a number ratio; and a step of correcting the density of image data with the density correction curve. 2. The step of generating the density correction curve according to claim 1, wherein the density is divided into a plurality of areas based on an intermediate value between the shadow value and the highlight value of the image data, and the density correction curve is included in each area. The density correction curve is created based on the number of data in the histogram of the density distribution. 3. The step of generating the density correction curve according to claim 2, wherein a signal having a density level darker than the intermediate value becomes a darker level, and a signal having a density level brighter than the intermediate value becomes brighter. It is characterized in that an S-shaped density correction curve is generated. 4. The step of generating the density correction curve according to claim 3, wherein when the ratio of the number of data near the light and dark ends is large, the density correction curve having an S-shape with a small curvature is used, and the ratio is small. It is characterized in that an S-shaped density correction curve with a large curvature is sometimes generated. 5. The step of creating a histogram of the density distribution according to claim 1, wherein when the original is a color image, one density obtained by combining the R, G, and B density data of the image data is combined. It is characterized by creating a histogram of the distribution. 6. The step of performing the density correction according to claim 1, when the original is a color image, a common density correction curve is used for each R, G, B density data of the image data. It is characterized by 7. A means for generating image data by reading light from a document, a means for creating a histogram of the density distribution from the image data, and data for the density distribution near both ends of the density distribution with respect to the total number of data of the image data. An image processing system comprising: a unit for generating a density correction curve based on the ratio of numbers; and a unit for correcting the density of image data with the density correction curve. 8. The means for generating the density correction curve according to claim 7, wherein the density is divided into a plurality of areas based on an intermediate value between the shadow value and the highlight value of the image data, and the density is included in each area. The density correction curve is created based on the number of data in the histogram of the density distribution. 9. The means for generating a density correction curve according to claim 8, wherein a signal having a density level darker than the intermediate value becomes a darker level, and a signal having a density level brighter than the intermediate value becomes brighter. It is characterized in that an S-shaped density correction curve is generated. 10. The means for generating the density correction curve according to claim 9, wherein when the ratio of the number of data near the light and dark ends is large, the density correction curve having an S-shape with a small curvature is used, and the ratio is small. It is characterized in that an S-shaped density correction curve with a large curvature is sometimes generated. 11. The means for creating the histogram of the density distribution according to claim 7, wherein when the original is a color image, one density obtained by combining the R, G, and B density data of the image data is combined. It is characterized by creating a histogram of the distribution. 12. The means for performing density correction according to claim 7, when the original is a color image, uses a common density correction curve for each R, G, B density data of the image data. It is characterized by 13. A computer-executable program for realizing the image reading method according to claim 1 by controlling the computer. 14. A recording medium on which the program according to claim 13 is recorded.