JP4442665B2 - Image processing apparatus and image processing program - Google Patents

Description

The present invention relates to an image processing apparatus capable of correcting an image with an easy operation.

  With the popularization of digital cameras and the like, it has become popular to print images taken by individuals using a home printing device. In addition, printing (copying) an image stored on a print medium with a home printing apparatus is also widespread. In such a case, if the acquired image does not have a desired color or tone, it is desired to correct the image before printing.

  Here, for example, Patent Document 1 below discloses a printing apparatus capable of image adjustment. In this printing apparatus, it is necessary to input adjustment data in order to adjust the image quality of the acquired image.

JP 2007-89179 A

  In the printing apparatus as described above, it is necessary to input specific data in order to adjust the image, so knowledge about the image is required, and sensory color adjustment cannot be performed. Further, in the above document, since it is necessary to select or set adjustment data, it is not a simple operation. Furthermore, it is desirable to be able to confirm what kind of image correction is performed before printing or before image correction.

  Accordingly, an object of the present invention is to provide an image processing apparatus that can confirm what kind of image correction is performed and can perform desired image correction sensuously in order to solve the above-described problems.

In order to achieve the above object, an invention according to claim 1 is an image processing apparatus comprising first image input means, second image input means, creation means, feature amount extraction means, image correction means, display means, and print control means. The first image input means inputs a first image, the second image input means inputs a second image, and the creation means creates the second image as a second display image. The feature quantity extraction unit extracts a first feature quantity from the first image and a second feature quantity from the second image or the second display image, and the image correction unit extracts the first feature quantity and the second feature quantity. Based on the second feature amount, the second display image and the second image are corrected, the display means displays the image-corrected second display image, and the print control means includes: Based on the display result of the display means, the image correction means Performs processing for printing the second image that is an image correction, the image correction unit performs image correction on a predetermined region of the second display image, said display means being the image correction The display image is displayed as an image in which a boundary line is drawn at the boundary between the image-corrected region and the region that has not been image-corrected, and the color of the boundary line is based on color information of the image-corrected region. Determined .

According to a second aspect of the present invention, there is provided an image processing apparatus including a first image input unit, a second image input unit, a creation unit, a feature amount extraction unit, an image correction unit, and a display unit. One image is input, the second image input means inputs a second image, the creating means creates the second image as a second display image, and the feature quantity extracting means is a first image. The first feature amount is extracted from the second image or the second display image, and the image correction unit is configured to extract the first feature amount based on the first feature amount and the second feature amount. 2 The image for display is corrected, the display means displays the second image for display corrected, and the image correction means converts the second image into an image based on the display result of the display means. corrected, performs image correction on a predetermined region of the second display image The display means displays the image for which the image is corrected, an image in which a boundary line is drawn at a boundary between the image-corrected region and a region where the image correction is not performed, and the color of the boundary line is It is determined based on the color information of the image-corrected area .

According to a third aspect of the present invention, there is provided an image processing apparatus comprising a first image input unit, a second image input unit, a creation unit, a feature amount extraction unit, an image correction unit, a display unit, and a print control unit. The means inputs a first image, the second image input means inputs a second image, the creation means creates the second image as a second display image, and the feature quantity extraction means includes Extracting a first feature quantity from the first image and a second feature quantity from the second image or the second display image, and the image correcting means is based on the first feature quantity and the second feature quantity. The second display image and the second image are image-corrected, the display means displays the image-corrected second display image, and the print control means displays the display result of the display means. On the basis of the second image corrected by the image correcting means, A process for printing, the image correction unit performs image correction on a predetermined area of the second display image, and the display unit converts the image corrected display image into the image correction unit. The area that has not been converted is converted to an achromatic color, and the gradation of the area that has been converted to the achromatic color is displayed smaller than the other areas.

According to a fourth aspect of the present invention, there is provided an image processing apparatus including a first image input unit, a second image input unit, a creation unit, a feature amount extraction unit, an image correction unit, and a display unit. One image is input, the second image input means inputs a second image, the creating means creates the second image as a second display image, and the feature quantity extracting means is a first image. The first feature amount is extracted from the second image or the second display image, and the image correction unit is configured to extract the first feature amount based on the first feature amount and the second feature amount. 2 The image for display is corrected, the display means displays the second image for display corrected, and the image correction means converts the second image into an image based on the display result of the display means. And correct the image on a predetermined area of the second display image. The display means displays the image-corrected display image by converting the area that has not been image-corrected into an achromatic color, and displaying the gradation of the area that has been converted to the achromatic color smaller than other areas. It is characterized by that.

The invention according to claim 5 is the image processing apparatus according to any one of claims 1 to 4, further comprising correction data creating means for creating correction data based on the first feature quantity and the second feature quantity, The image conversion means performs image correction of the second display image and the second image based on the correction data.

According to a sixth aspect of the present invention, in the image processing apparatus according to the fifth aspect, the feature amount extraction unit extracts a feature amount related to a hue from the first image, and the feature amount extraction unit includes the second image. Alternatively, a feature amount related to hue is extracted from the second display image, and the first image, the second image, or the second display image is divided into a plurality of regions based on the feature amount related to the hue, and A feature value related to other than the hue is extracted for each divided area, and the correction data generation unit is configured to output the hue for each divided area of the first image and the second image or the second display image. A representative value of the feature amount relating to, and creating hue correction data based on the representative value, for each of the divided areas of the first image and the second image or the second display image, in front A representative value of a feature amount related to other than hue is extracted, and the image correction unit corrects a feature amount related to a hue for each pixel of the second image and the second display image based on the hue correction data, and A feature amount related to a hue other than a hue for each pixel of the second image and the second display image is corrected based on a representative value for each region.

According to a seventh aspect of the present invention, in the image processing apparatus according to the sixth aspect, the feature quantity related to the hue is calculated based on an H value in the HSV space.

The invention according to claim 8 is a first image input step for inputting a first image to a computer, a second image input step for inputting a second image, a creation step for creating the second image as a second display image, A first feature amount extracting step for extracting a first feature amount from the first image; a second feature amount extracting step for extracting a second feature amount from the second image or the second display image; and the first feature amount. And a first image correcting step for correcting the second display image and the second image based on the second feature amount, a first display step for displaying the image corrected second display image, Based on the display result of the first display step, a print control step for executing a process for printing the second image with the image corrected, and a second for performing image correction on a predetermined area of the second display image. Image correction step A second display step of displaying the image-corrected display image in an image in which a boundary line is drawn at a boundary between the image-corrected region and a region that has not been image-corrected; A line color determining step for determining a color of the boundary line based on color information is executed.

The invention according to claim 9 is a first image input step for inputting a first image to a computer, a second image input step for inputting a second image, a creation step for creating the second image as a second display image, A first feature amount extracting step for extracting a first feature amount from the first image; a second feature amount extracting step for extracting a second feature amount from the second image or the second display image; and the first feature amount. And a first image correction step for correcting the second display image based on the second feature amount, a first display step for displaying the image corrected second display image, and a first display step. A second image correction step of correcting the second image based on a display result and performing image correction on a predetermined area of the second display image; Area and image A second display step of displaying an image in which a boundary line is drawn at the boundary with the uncorrected region; a line color determining step of determining a color of the boundary line based on color information of the image-corrected region; It is made to perform.

The invention according to claim 10 is a first image input step for inputting a first image to a computer, a second image input step for inputting a second image, a creation step for creating the second image as a second display image, A first feature amount extracting step for extracting a first feature amount from the first image; a second feature amount extracting step for extracting a second feature amount from the second image or the second display image; and the first feature amount. And a first image correcting step for correcting the second display image and the second image based on the second feature amount, a first display step for displaying the image corrected second display image, Based on the display result of the first display step, a print control step for executing a process for printing the second image with the image corrected, and a second for performing image correction on a predetermined area of the second display image. Image correction The second display for displaying the image for which the image has been corrected, by converting the non-image-corrected area to an achromatic color and lowering the gradation of the area to which the achromatic color has been converted to other areas. The step is executed.

The invention according to claim 11, the computer, the first image input step of inputting first image, the second image input step of inputting a second image, creating step of creating a second image as a second display image, A first feature amount extracting step for extracting a first feature amount from the first image; a second feature amount extracting step for extracting a second feature amount from the second image or the second display image; and the first feature amount. And a first image correction step for correcting the second display image based on the second feature amount, a first display step for displaying the image corrected second display image, and a first display step. A second image correction step of correcting the second image based on a display result and performing image correction on a predetermined area of the second display image; Was not Converts the frequency to an achromatic color, and said second display step of the gray scale of the region converted to achromatic display with less than other regions, is executed.

According to the first aspect of the present invention, image correction can be performed sensuously based on the feature amount extracted from the image input by the image input means. In addition, by performing image correction on the display image (thumbnail image) in the image to be image-corrected based on the pre-stored feature amount and displaying the image that has been subjected to image correction, in the stage before printing, It is possible to clearly confirm how much correction is performed on which part of the image to be corrected. Then, if printing is started based on a confirmation operation by the user, it is possible to obtain an image that is sensuously subjected to desired image correction while preventing unnecessary printing processing. Various parameters can be used to specify the hue.
Further, according to the present invention, image correction is performed only for the area having the largest area among the divided areas, and the image-corrected area is displayed in a manner that is easily perceived. It is possible to clearly confirm whether image correction is performed.
According to the invention, since a boundary line is drawn at the boundary between the image-corrected region and the non-image-corrected region, it is more clearly confirmed which image correction is applied to which region. can do.
Further, according to the present invention, since the color of the boundary line is determined based on the color information of the image corrected region, it is more clearly confirmed which image correction is applied to which region. be able to.

According to the second aspect of the invention, image correction can be performed sensuously based on the feature amount extracted from the image input by the image input means. In addition, image correction is performed on the display image (thumbnail image) in the image to be image-corrected based on the pre-stored feature amount, and the image that has been subjected to image correction is displayed. Thus, it is possible to clearly check how much correction is performed on which part of the image to be corrected. Then, if printing is started based on a confirmation operation by the user, it is possible to obtain an image that is sensuously subjected to desired image correction while preventing unnecessary printing processing.
Further, according to the present invention, image correction is performed only for the area having the largest area among the divided areas, and the image-corrected area is displayed in a manner that is easily perceived. It is possible to clearly confirm whether image correction is performed.
According to the invention, since a boundary line is drawn at the boundary between the image-corrected region and the non-image-corrected region, it is more clearly confirmed which image correction is applied to which region. can do.
Further, according to the present invention, since the color of the boundary line is determined based on the color information of the image corrected region, it is more clearly confirmed which image correction is applied to which region. be able to.

According to the invention of claim 3, it is possible to perform image correction sensuously based on the feature amount extracted from the image input by the image input means. In addition, by performing image correction on the display image (thumbnail image) in the image to be image-corrected based on the pre-stored feature amount and displaying the image that has been subjected to image correction, in the stage before printing, It is possible to clearly confirm how much correction is performed on which part of the image to be corrected. Then, if printing is started based on a confirmation operation by the user, it is possible to obtain an image that is sensuously subjected to desired image correction while preventing unnecessary printing processing. Various parameters can be used to specify the hue.
Further, according to the present invention, image correction is performed only for the area having the largest area among the divided areas, and the image-corrected area is displayed in a manner that is easily perceived. It is possible to clearly confirm whether image correction is performed.
According to the invention, since the area that has not been subjected to image correction is converted to an achromatic color, it is possible to more clearly confirm which area is subjected to image correction.
Further, according to the present invention, since the gradation of the region converted to the achromatic color is displayed smaller than other regions, it can be confirmed more clearly which region is subjected to image correction. .

According to the invention which concerns on Claim 4, based on the feature-value extracted from the image input by the image input means, image correction can be performed sensuously. In addition, image correction is performed on the display image (thumbnail image) in the image to be image-corrected based on the pre-stored feature amount, and the image that has been subjected to image correction is displayed. Thus, it is possible to clearly check how much correction is performed on which part of the image to be corrected. Then, if printing is started based on a confirmation operation by the user, it is possible to obtain an image that is sensuously subjected to desired image correction while preventing unnecessary printing processing.
Further, according to the present invention, image correction is performed only for the area having the largest area among the divided areas, and the image-corrected area is displayed in a manner that is easily perceived. It is possible to clearly confirm whether image correction is performed.
According to the invention, since the area that has not been subjected to image correction is converted to an achromatic color, it is possible to more clearly confirm which area is subjected to image correction.
Further, according to the present invention, since the gradation of the region converted to the achromatic color is displayed smaller than other regions, it can be confirmed more clearly which region is subjected to image correction. .

According to the invention which concerns on Claim 5 , there can exist the effect mentioned above.

According to the sixth aspect of the invention, since different image conversion processing is performed separately for the feature value related to hue and the feature value related to other than hue, desired image correction processing can be performed with high accuracy. Various parameters can be used to specify the hue.

According to the invention which concerns on Claim 7 , the feature-value regarding a hue is computable based on H value in HSV space.

The inventions according to claims 8 to 11 can also achieve the effects described above.

[First embodiment of the present invention]
First, an example of the appearance of the image processing apparatus according to the present invention is shown in FIG. An example of the internal configuration of the image processing apparatus 1 is shown in FIG.

  The image processing apparatus 1 is an example of a multi-function printer or the like, and has a scanner 2 for reading image information from a photograph or the like on the upper part (in FIG. 1, the scanner is in a covered state). .) Image information read by the scanner is used as sample information for correcting the color and the like of image information read from the memory slot shown below. Details of the image correction process will be described later.

  The image processing apparatus 1 has a memory slot 3 that functions as an IC card reader for reading image information recorded in an external memory that is a recording medium such as an SD card (trademark) or a CF card (trademark). Here, as the external memory (storage medium), a known medium and format can be appropriately selected. Further, it may be configured to have a plurality of memory slots so as to be applied to a plurality of types of media. In addition, a communication function (for example, a LAN card, not shown) that can be connected to a network such as a LAN to which a PC storing image information is connected is added to the signal line to which the CPU, ROM, RAM, etc. shown in FIG. 2 are connected. Thus, instead of the external memory, desired image information may be read from a network to which the PC is connected. In that case, the image processing apparatus 1 has a communication function.

  The image processing apparatus 1 has an operation panel 4 for performing various operations. Various buttons and the like are arranged on the operation panel 4.

  The image processing apparatus 1 includes a printer 10 illustrated in FIG. The image information subjected to the image correction is printed by the printer 10. The printed paper is discharged from the discharge port 5, for example.

  The image processing apparatus 1 has display means 6. Various character information and images can be displayed. Further, a transparent touch panel may be provided on the front surface of the display unit 6 and a part or all of the functions of the operation panel 4 may be substituted. Moreover, you may comprise so that a touch panel and the operation panel 4 can be used together.

  The image processing apparatus 1 is entirely controlled by a processor (CPU 9). In addition, there are a RAM 7 for temporarily storing information and a ROM 8 for storing predetermined information. Moreover, you may have mass storage means, such as HDD, as needed.

  Each element mentioned above is mutually connected by the signal wire | line.

  Further, various functions (for example, FAX) can be added to the image processing apparatus 1. Further, an interface for connecting to a personal computer or the like and an interface for connecting to another printing apparatus may be provided.

In addition, the said external appearance is only an example, and it cannot be overemphasized that this invention is not limited to the said external appearance. Moreover, in the above-mentioned external appearance, an apparatus in which all functions are integrated is shown, but some functions may be realized by an external apparatus. Furthermore, the internal configuration is merely an example, and it goes without saying that the present invention is not limited to the internal configuration.

  Next, an outline of an image correction process using the image processing apparatus 1 according to the present invention will be described with respect to a user operation and an apparatus main body process. FIG. 3 shows an outline of the processing. First, the user sets a memory in which an image to be corrected is stored in a memory slot of the image processing apparatus. As described above, as this memory, a known storage medium such as a memory card can be appropriately employed.

  When the memory is set in the memory slot 3 (1), the image processing apparatus recognizes the set memory and causes the user to select an image to be corrected from the images stored in the memory. (2). In addition, the process for selecting an image can employ | adopt suitably a well-known technique (For example, switching and displaying an image sequentially, etc.). Further, the display means 6 may be used.

  When an image to be corrected is determined (3), the image processing apparatus reads the image into, for example, a RAM (4). Hereinafter, the image may be referred to as an “original image”.

  Next, the user installs (5) an image (hereinafter, also referred to as “example image”) as a sample for image correction of the image on the scanner, and presses a predetermined button or the like to The processing apparatus reads the model image into, for example, the RAM 7 (6).

  Next, the image processing apparatus 1 generates and displays a display image (7). The generation of the display image will be described later.

  The user confirms whether the display image has been subjected to desired image correction, and performs an instruction operation for printing (8). At this time, the operation panel 4 or the touch panel is used.

  When receiving the print instruction, the image processing apparatus 1 performs image correction processing (9). Thereafter, the original image after the image correction is printed (10).

  In the process of FIG. 3 described above, an image is read using a scanner after reading an image from a memory. However, a model image is first read using a scanner, and then an image is read from a memory. It may be configured.

  Next, basic processing in the image processing apparatus 1 will be described. FIG. 4 is a flowchart showing an outline of basic processing in the present embodiment.

In S <b> 11, the original image and the model image are written in the RAM 7 of the image processing apparatus 1. Here, the format of the read image is not limited.
In S12, each pixel of the read model image is converted into an HSV parameter. The conversion process to the HSV parameter will be described later.

  In S13, a first feature value is extracted as a feature value of the model image based on the HSV parameter. Specific processing for extracting the first feature amount will be described later.

  In S14, each pixel of the read original image is converted into an HSV parameter. In S15, the second feature value is extracted as the feature value of the original image based on the HSV parameter. Specific processing for extracting the second feature amount will be described later.

  In S16, a display image is generated. The display image is generated by converting the resolution of the original image to a specified size. Here, the specified size is, for example, a size capable of displaying the entire image on the display means 6. Further, when the original image is used as it is as a display image, the process of S16 is not executed. Here, as the resolution conversion method, a nearest neighbor method, a bilinear method, or a bicubic method may be employed. In the case of reduction by resolution conversion, the average pixel method may be employed. Furthermore, another processing method may be adopted.

  In S17, the display image is corrected using the first feature value and the second feature value. Details of the correction processing will be described later.

  In S18, the corrected display image is displayed on the display means 6. At this time, the display mode of the corrected display image may be changed. The display mode changing process will be described later. At this time, the display unit 6 displays a display image and a message as to whether or not to print the display image. In accordance with this message, for example, the user performs a print instruction or an end instruction by operating the touch panel of the display unit 6.

  In S19, it is determined whether there is a print instruction by a user operation. If there is no print instruction (S19: NO), the basic process is terminated. If there is a print instruction (S19: YES), the process proceeds to S20.

  In S20, the original image is color-corrected based on the first feature value and the second feature value. Specific processing contents of color correction will be described later.

  In S21, the corrected original image is printed. At this time, the HSV parameters are converted into other parameters (for example, RGB parameters) as necessary. The conversion process to RGB parameters will be described later. Note that the process of S20 may be performed in advance before confirming the print instruction. That is, the original image is color corrected together with the display image and stored in the RAM 7. When there is a print instruction from the user, the original image subjected to color correction stored in the RAM 7 is printed. The processing load of the image processing apparatus 1 can be reduced by performing the process of S20 after receiving the print instruction.

  In the above-described processing, the second feature amount is extracted after extracting the first feature amount. However, the first feature amount may be extracted after extracting the second feature amount. Further, L * c * h * parameters may be extracted instead of HSV parameters. Further, the present invention can be realized even with known parameters such as RGB parameters. In the following, a case where HSV parameters are extracted will be described.

  Next, an example of converting the model image pixels in S12 of FIG. 4 into HSV parameters will be described. In the following, it is assumed that the model image and the original image are in the RGB format. Conversion from the RGB format to the HSV format can be performed as follows. Moreover, the process of S14 of FIG. 4 can be performed similarly. In addition, the conversion formula shown below is an example, and it cannot be overemphasized that you may convert with another conversion formula.

[RGB → HSV conversion formula]
max (a, b, c) represents the largest value among a, b, and c.
min (a, b, c) represents the smallest value among a, b, and c.
V = max (R ÷ 255, G ÷ 255, B ÷ 255)
When V is not 0
S = {V-min (R, G, B)} ÷ V
When V is 0
S = 0
When {V-min (R, G, B)} is not 0,
r = (V-R ÷ 255) ÷ (V-min (R, G, B)
g = (V-G ÷ 255) ÷ (V-min (R, G, B)
b = (V-B ÷ 255) ÷ (V-min (R, G, B)
When {V-min (R, G, B)} is 0,
r = 0
g = 0
b = 0
When V = R ÷ 255
H = 60 × (bg)
When V = G ÷ 255
H = 60 × (2 + rg)
When V = B ÷ 255
H = 60 × (4 + gr)
However, when H <0
H = H + 360

  Next, the process for extracting the first feature amount in S13 will be described with reference to FIG. FIG. 5 is a flowchart of the first feature amount extraction process. In the following processing, the H value takes a value of −30 to less than 330. If the H value is not within the above range, the H value is appropriately converted (for example, “H value + 360 × n” or “H value−360 × n”, where n is an integer), so that the value in the above range is taken. adjust.

In S31, the sample image is divided into a plurality of regions. Here, the image is divided based on six commonly used hues. Specifically, based on the H value of each pixel,
-R region: -30 or more and less than 30-Y region: 30 or more and less than 90-G region: 90 or more and less than 150-C region: 150 or more and less than 210-B region: 210 or more and less than 270-M region: Divide into 270 or more and less than 330. That is, a process of classifying the constituent pixels of the model image into six classification items according to the classification standard corresponding to the hue value is performed. Here, the correspondence relationship between the region and the H value is an example and can be changed as appropriate.

In S32, “representative value (HSV value) of each region” and “ratio of each region in the model image” are calculated for each region divided in S31. Here, the representative value (HSV value) of each region is defined as follows.
-Typical values of R region: sHr, sSr, sVr
-Typical values in the G region: sHg, sSg, sVg
-Typical values of the B region: sHb, sSb, sVb
-Typical value of C region: sHc, sSc, sVc
-Typical values in the M region: sHm, sSm, sVm
-Typical values of the Y region: sHy, sSy, sSy

  Here, the representative value can be an average value of each HSV value in each region. Moreover, an intermediate value can be used.

Further, the ratio of each area in the model image is defined as follows.
The ratio of the R region in the model image: sRateR
-Ratio of the G area in the model image: sRateG
-Ratio of area B in the model image: sRateB
-Ratio of the C area in the model image: sRateC
-Ratio of M area in the model image: sRateM
The ratio of the Y area in the model image: sRateY

Here, the ratio is, for example, for the R region,
Although it can be defined as sRateR = (number of pixels in the R region in the model image) / (total number of pixels in the model image), it may be defined by another formula.

  Next, the process for extracting the second feature value in S15 of FIG. 4 will be described with reference to FIG. FIG. 6 is a flowchart of the second feature amount extraction process.

  In S41, the original image is divided into six regions. Since the content of the process is the same as the process for the model image, the description is omitted.

In S42, the same process as S32 in FIG. 5 is performed on the original image. Further, the representative value (HSV value) of each region is defined as follows.
・ Representative value of R region: iHr, iSr, iVr
・ Representative value of G region: iHg, iSg, iVg
・ Representative value of B area: iHb, iSb, iVb
-Typical value of C region: iHc, iSc, iVc
-Typical values in the M region: iHm, iSm, iVm
・ Representative value of Y area: iHy, iSy, iSy

The proportion of each area in the original image is defined as follows.
-Ratio of R area in original image: iRateR
-Ratio of the G area in the original image: iRateG
-Ratio of B area in original image: iRateB
-Ratio of the C area in the original image: iRateC
-Ratio of M area in original image: iRateM
The ratio of the Y area in the original image: iRateY

  In the above-described processing, the algorithm for extracting the first feature quantity and the algorithm for extracting the second feature quantity have been described as being the same. However, each feature quantity is configured to be extracted by a different algorithm. Also good.

  Next, details of the process of converting the display image based on the first feature value and the second feature value, which are executed in S17 of FIG. 4, will be described. This process is performed by converting the H value, S value, and V value of each pixel of the display image.

  First, the conversion process for the H value will be described. The representative value of the H value of the original image is plotted on the X axis and the representative value of the H value of the model image is plotted on the Y axis, and the representative value of the H value for each region is plotted. Then, a hue correction table shown in FIG. 7 is created by linear interpolation between the plotted points, for example. Here, when H ′> 360, H ′ = H′-360.

  Then, the H value is corrected by applying the hue correction table to the H value of each pixel of the display image. More specifically, the corrected H ′ can be defined by the following equation.

H ′ = (y2−y1) / (x2−x1) × H− (y2−y1) / (x2−x1) × x2 + y2
... (Formula 1)
Here, x1, x2, y1, and y2 are defined as follows.

When H <iHr,
(X1, y1) = (iHm-360, sHm-360)
(X2, y2) = (iHr, sHr)

When iHr ≦ H <iHy,
(X1, y1) = (iHr, sHr)
(X2, y2) = (iHy, sHy)

When iHy ≦ H <iHg,
(X1, y1) = (iHy, sHy)
(X2, y2) = (iHg, sHg)

When iHg ≦ H <iHc,
(X1, y1) = (iHg, sHg)
(X2, y2) = (iHc, sHc)

When iHc ≦ H <iHb,
(X1, y1) = (iHc, sHc)
(X2, y2) = (iHb, sHb)

When iHb ≦ H <iHm,
(X1, y1) = (iHb, sHb)
(X2, y2) = (iHm, sHm)

When iHm ≦ H,
(X1, y1) = (iHm, sHm)
(X2, y2) = (iHr + 360, sHr + 360)

Next, conversion in the S value and V value of each pixel of the display image will be described. The S value and the Y value are converted for each area divided by the H value. For example, for the R region:
When S ≦ iSr,
S ′ = S × (sSr ÷ iSr) (Formula 2)
When S> iSr,
S ′ = 1 + (S−1) × {(1-sSr) ÷ (1-iSr)} (Formula 3)
When V ≦ iVr,
V ′ = V × (sVr ÷ iVr) (Formula 4)
When V> iVr,
V ′ = 1 + (V−1) × {(1−sVr) ÷ (1−iVr)} (Formula 5)
It can be calculated by the following formula. Further, other areas can be similarly calculated. In the following, the conversion table defined by the S value conversion formula may be referred to as a saturation correction table, and the conversion table defined by the V value conversion formula may be referred to as a brightness correction table. .
The same processing is performed for the conversion of the original image in S20.

  Next, a conversion formula for converting into a format (for example, RGB value) suitable for the printer 10 in S21 of FIG. 4 will be described. In addition, the conversion formula shown below is an example, and it cannot be overemphasized that you may convert with another conversion formula.

[HSV-> RGB conversion formula]
(In, fl, m, and n shown below are parameters used in the process of calculating RGB from HSV)
Let in be the integer part of (H / 60) and fl be the decimal part of (H / 60).
If in is an even number
fl = 1-fl
m = V × (1-S)
n = V × (1-S × fl)
When in is 0
R = V × 255
G = n × 255
B = m × 255
When in is 1
R = n × 255
G = V × 255
B = m × 255
When in is 2
R = m × 255
G = V × 255
B = n × 255
When in is 3
R = m × 255
G = n × 255
B = V × 255
When in is 4
R = n × 255
G = m × 255
B = V × 255
When in is 5
R = V × 255
G = m × 255
B = n × 255

  According to the first embodiment of the present invention, the correction result can be confirmed at a stage before printing. Further, as described above, when the display image is relatively small, the color correction process for the display image can be performed at high speed. In addition, by performing the above-described image correction processing, it is possible to correct the hue of the original image to the hue of the model image for each region divided based on the H value.

[Second Embodiment of Image Correction Processing]
In the second embodiment of the image correction process described below, for each divided area, a part of the image correction process can be stopped and the amount of change can be controlled based on the size of the area. . Thereby, the user can reflect only a part of the hue of the model image in the hue of the original image.

FIG. 8 shows a flowchart of basic processing of this embodiment. The basic processing flow of this embodiment is the same as that in FIG. 4, but a representative value resetting process (S56) is added after the second feature amount extraction process. Hereinafter, the representative value resetting process will be described with reference to the drawings.

  FIG. 9 is a flowchart of the representative value resetting process in the present embodiment. In S71, it is determined whether or not the divided area is a correction target. In this process, it is determined whether or not the area satisfies a predetermined condition.

  When it is determined that it is a correction target (S71: YES), the process proceeds to S73. When it is determined that it is not a correction target (S71: NO), the process proceeds to S72. In S72, the representative value is reset, and then the process proceeds to S73. A method of resetting the representative value will be described later.

  In S73, it is determined whether or not all the regions (six regions when divided into six) are determined as correction targets. If an unidentified area remains (S73: NO), the process returns to S71 and is repeated. When the determination for all the areas is completed (S73: YES), the representative value resetting process is terminated.

[Method using threshold Thre]
As the predetermined condition described above, the magnitude relationship between the size of the divided area and the threshold value Thre can be used. When the ratio of the original image or the model image is smaller than the threshold value Thre, the representative value of the original image and the model image related to the region is changed to the same value, and the above-described changed representative value is used for each pixel described above. The correction process is performed. Hereinafter, this process will be described. The representative value can be reset as follows.

When sRateR <Thre or iRateR <Thre,
sHr = 0, sSr = 0.5, sVr = 0.5,
iHr = 0, iSr = 0.5, iVr = 0.5

When sRateG <Thre or iRateG <Thre,
sHg = 120, sSg = 0.5, sVg = 0.5,
iHg = 120, iSg = 0.5, iVg = 0.5

When sRateB <Thre or iRateB <Thre,
sHb = 240, sSb = 0.5, sVb = 0.5,
iHb = 240, iSb = 0.5, iVb = 0.5

When sRateC <Thre or iRateC <Thre,
sHc = 180, sSc = 0.5, sVc = 0.5,
iHc = 180, iSc = 0.5, iVc = 0.5

When sRateM <Thre or iRateM <Thre,
sHm = 300, sSm = 0.5, sVm = 0.5,
iHm = 300, iSm = 0.5, iVm = 0.5

When sRateY <Thre or iRateY <Thre,
sHy = 60, sSy = 0.5, sVy = 0.5,
iHy = 60, iSy = 0.5, iVy = 0.5

  In the above-described example, as the S value and the V value, 0.5, which is an intermediate value between possible values (0 to 1), is employed. Moreover, the intermediate value of each area | region was employ | adopted about H value. However, the representative values described above are examples, and the present invention is not limited to the above numerical values.

  By using this value and using the conversion formulas (Formula 2) to (Formula 5) described above for the correction for each pixel, the values are not changed in the S value and the V value. That is, for example, with respect to the R region, when S ≦ iSr, as described above (Formula 2),

    S ′ = S × (sSr ÷ iSr)

In this formula, sSr = 0.5 and iSr = 0.5, so the above formula is

S ′ = S × (0.5 ÷ 0.5) = S (Expression 6)
It becomes. Similarly, when S> iSr, S ′ = S. Similarly, the V value and other regions are not converted.

  Further, in the H value, the point plotted in FIG. 7 is changed to the representative value, so that the conversion amount in that region can be reduced. That is, even when the above-described changing formula (Formula 1) is used, the conversion amount is reduced by changing the representative value.

  Next, a method for determining the threshold value Thre will be described. This value can be determined based on sensory evaluation. In sensory evaluation, it was confirmed that if the area occupied about 6% or more, the area was easily perceived. Therefore, 6% can be adopted as the threshold Thre. However, the present invention is not limited to the threshold Thre of 6%.

  Further, the threshold Thre may be determined so as to extract a region having a relatively large area relative to other regions. For example, if the number of areas to be divided is 6, 1/6, which is the reciprocal thereof, can be set as the threshold value Thre.

  “6”, which is the number of divided areas given as an example of the present invention, is an RGB space (number of vertices: 8) that is one of the color gamuts expressing colors, and is the vertex excluding white and black that are achromatic colors. It is the same as the number “6”. In order for a person to identify a color, the number of color areas is sufficient to be 6, and if it is less than 6, the user may feel that the image has not been converted like a model image. If the data is divided more finely than 6, the conversion accuracy becomes higher. However, there is a high possibility that the person cannot be identified, and the amount of calculation increases as the number of divisions increases. In the case of using a printer, the time until obtaining an image to be corrected as a printing result is delayed, and there is a high possibility that user dissatisfaction will increase, so it is considered that the number of divided areas is preferably 6.

  In the example described above, the threshold value is the same in all the regions, but the threshold value Thre may be changed for each region.

[Method using information of maximum area]
In the above-described method, the threshold Thre is set, and the representative value is changed based on the threshold Thre, that is, the image correction processing is stopped and the conversion amount is reduced. Here, an image correction process using information on the maximum area in the image in order to reflect only a specific color of the model image in the original image will be described below.

  In this case, in S71 in FIG. 9, whether or not the area is the largest in both the original image and the model image can be set as a predetermined condition. In this case, the representative value is reset by the following formula. Here, the ratio of the divided area of the model image that has the largest ratio to the model image is iMaxRate. Further, the ratio of the divided area of the original image that has the largest ratio to the original image is sMaxRate.

When sRateR ≠ iMaxRate or iRateR ≠ sMaxRate,
sHr = 0, sSr = 0.5, sVr = 0.5,
iHr = 0, iSr = 0.5, iVr = 0.5

When sRateG ≠ iMaxRate or iRateG ≠ sMaxRate,
sHg = 120, sSg = 0.5, sVg = 0.5,
iHg = 120, iSg = 0.5, iVg = 0.5

When sRateB ≠ iMaxRate or iRateB ≠ sMaxRate,
sHb = 240, sSb = 0.5, sVb = 0.5,
iHb = 240, iSb = 0.5, iVb = 0.5

When sRateC ≠ iMaxRate or iRateC ≠ sMaxRate,
sHc = 180, sSc = 0.5, sVc = 0.5,
iHc = 180, iSc = 0.5, iVc = 0.5

When sRateM ≠ iMaxRate or iRateM ≠ sMaxRate,
sHm = 300, sSm = 0.5, sVm = 0.5,
iHm = 300, iSm = 0.5, iVm = 0.5

When sRateY ≠ iMaxRate or iRateY ≠ sMaxRate,
sHy = 60, sSy = 0.5, sVy = 0.5,
iHy = 60, iSy = 0.5, iVy = 0.5

  As a result, since only the region having the largest area in both the original image and the model image is to be converted, the conversion is not performed for the S value and the V value that are not the conversion target, and the H value is converted. The amount can be reduced.

  Here, when only the region B is to be corrected, a hue correction table as shown in FIG. 10 is created. In this hue correction table, the H value representative value (iHc = 180, sHc = 180) in the C region adjacent to the B region in the color space and the H value representative value (iHb, sHb) in the B region are linear. In addition, the representative value of the H value (iHm = 300, sHm = 300) in the M region adjacent to the B region in the color space and the representative value of the H value in the B region (iHb, sHb) are connected by a straight line. It will be.

  For this reason, the C region where the H value is 180 <H ≦ 210 and the M region where the H value is 270 <H ≦ 300 are also corrected. The amount of correction increases as the value approaches the B region.

As described above, in the second embodiment of the image correction process, a correction target region can be selected, and even in a region that is not a correction target, H values adjacent in the color space are partially corrected. Therefore, it is possible to prevent a pseudo contour (tone jump) from being generated between the correction target area and the non-correction area.
[Third Embodiment of Image Correction Processing]
In the second embodiment of the image correction process, although the conversion amount can be reduced, the conversion amount of the H value of the region not to be converted cannot be set to zero. This is because, as shown in FIG. 10, linear interpolation is performed with the representative values of the areas that are not to be converted, and therefore, it is affected by the representative values of other areas.

  Therefore, a hue correction table as shown in FIG. 11 can be employed. FIG. 11 is a hue correction table in the case where only the B region is to be converted. In this figure, the number of areas to be converted is one, but a plurality of areas may be targeted for correction.

  In FIG. 11, since the H values other than the B region are H ′ = H, image correction is not performed. The H ′ value in the B region can be obtained by the following equation, where the minimum value in the B region is Hmin and the maximum value in the B region is Hmax.

When H <iH,
H ′ = Hmin + (sHb−Hmin) × (H−Hmin) ÷ (iHb−Hmin)

When H> iH,
H ′ = sHb + (Hmax−sHb) × (H−iHb) ÷ (Hmax−iHb)

  By using this equation, only the region to be converted can be converted.

  As described above, in the third embodiment of the image correction process, since only the H value to be converted can be converted, the effect of image correction can be increased.

[Fourth Embodiment of Image Correction Processing]
In the second embodiment of the image correction process, since a correction curve (conversion formula) is independently used for each region with respect to the S value and the V value, a pseudo contour (tone jump) may be generated. . That is, as shown in FIG. 12, each region has a table indicating the relationship between S and S ′, and no consideration is given to the nature of the table in adjacent regions.

  In the present embodiment, as shown in FIG. 13, gradation jumps can be prevented by smoothing the correction curve in each color region.

Specific processing of this embodiment will be described below. The image correction process for a part of the area B will be described with reference to FIGS. 14 and 15, but the contents of the process are basically the same for the other areas.
The corrected S value (Sb ″) in this embodiment is
-H value (H) of the conversion target area,
-H value representative value (Hbmid) of the area to be converted,
A representative value (Hcmid) of the H value in the adjacent region (in this case, the C region) closer to the hue coordinate position of the H value of the pixel to be converted;
-S value (corresponding to Sb ', Hbmid) of the conversion target area converted by the conversion formula corresponding to the above formula (2) (that is, calculated using the saturation correction table of the B area),
-S value of the adjacent area (which corresponds to Sc ', Hcid) converted by the conversion formula corresponding to the above formula (3) (that is, calculated using the saturation correction table of the C area),
Can be obtained by the following equation.

Sb ″ = {(H−Hcmid) × Sb ′ + (Hbmid−H) × Sc ′} /
{(Hbmid−Hcmid)} (Expression 7)

Further, the corrected V value (Vb ″) in the present embodiment is
-H value (H) of the conversion target area,
-H value representative value (Hbmid) of the area to be converted,
A representative value (Hcmid) of the H value in the adjacent region (in this case, the C region) closer to the hue coordinate position of the H value of the pixel to be converted;
-V value (corresponding to Vb ', Hbmid) of the conversion target area converted by the conversion formula corresponding to the above formula (4) (that is, calculated using the brightness correction table of the B area),
-S value of the adjacent area (that corresponds to Vc ', Hcid) converted by the conversion formula corresponding to the above formula (5) (that is, calculated using the brightness correction table of the C area),
Can be obtained by the following equation.

Vb ″ = {(H−Hcmid) × Vb ′ + (Hbmid−H) × Vc ′} /
{(Hbmid−Hcmid)} (Equation 8)

The above-described processing is performed on part of the B region (H value range: 210 <H ≦ 240) and part of the C region (H value range 180 <H ≦ 210) shown in FIG. Thus, the saturation value (S ″) and the lightness value (V ″) of the output are calculated by weighting calculation according to the hue value (H) of the input.
Thus, the correction effect between the hues can be smoothed.

  Further, the present invention can be realized by appropriately combining the above-described image correction processes. That is, it is possible to make the image correction stand out in H, and to prevent gradation skipping in S and V.

[Display Mode Change Processing (First Embodiment)]
As described above, in the present invention, image correction processing can be performed only on a partial region of the original image. In this case, it is desirable to be able to grasp which part of the original image has been subjected to the image correction processing. As an example, as shown in FIG. 17, the boundary line 20 can be displayed on the display screen at the boundary between the image-corrected region and the region where the image correction is not performed.

Next, an example of a process for displaying the boundary line 20 will be described. For example, the boundary line 20 can be generated by changing a predetermined pixel of the display image to another color using a 3 × 3 mask as shown in FIG. Specifically, 8 neighborhoods of the target pixel are set as reference pixels,
(1) A pixel of interest is a pixel to be image corrected (2) A pixel that satisfies both of the two conditions that at least one of the reference pixels is not an image correction target is converted into another color to obtain a boundary Line 20 can be generated. In the example described above, since the line width of the boundary line 20 is one pixel, the line width of the boundary line 20 may be increased according to the size of the display image. In this case, expansion processing may be performed on the boundary line 20.

The color of the boundary line can be set as appropriate. For example, the user may select the border color in advance or may be set in advance in the image processing apparatus 1. Alternatively, R ′, G ′, and B ′ generated by converting the pixel value corresponding to the boundary line into an RGB value and converting the RGB value may be used. Here, when R, G, and B are expressed with 256 gradations,
R '= 255-R
G '= 255-G
B '= 255-B
It is good.

  Further, as shown in FIG. 20, the image corrected area may be surrounded by a frame line 21.

[Display Mode Change Processing (Second Embodiment)]
As a display form of the display image, a region where image correction is not performed may be processed to be displayed in gray scale (achromatic color). Here, as a method for correcting the achromatic image, the following processing can be considered.

[How to use the average value]
When the display image is in the RGB format, the pixels (R, B, G) in the region where the image correction is not performed are
R ′ = (R + G + B) / 3
G ′ = (R + G + B) / 3
B ′ = (R + G + B) / 3
Thus, a grayscale pixel value can be calculated.

[Method of using luminance component Y]
When the display image is in the RGB format, the luminance value Y is set to the pixels (R, G, B) in the region where the image correction is not performed.
Y = 0.29891 × R + 0.58661 × G + 0.11448 × B
As a result of conversion as R ′ = G ′ = B ′ = Y, a grayscale pixel value can be calculated. The Y value derivation formula is merely an example, and the Y value may be calculated using another formula.

  Further, the gradation of the region converted to an achromatic color may be lowered. That is, what was expressed with 256 gradations may be expressed with 128 gradations. Further, a region where image correction is not performed may be converted to an achromatic color while the boundary line 20 is displayed.

[Display Image Generation Processing (Second Embodiment)]
In the processing shown in FIG. 4, image correction processing is performed on the display image, and when there is a print instruction from the user, the image correction processing is performed on the original image. However, another aspect of the present invention is as follows. It is also possible to generate and display a display image by performing image correction processing on the original image, and converting the resolution of the original image that has been corrected.

  FIG. 20 shows a flowchart of the process. The basic process is the same as the process shown in FIG. 4 except that a display image is generated from the corrected original image in S87. In the process shown in FIG. 20, since the original image correction process is performed before the display image generation, the display image is displayed as compared with the image correction process performed on the reduced image in FIG. However, the processing time from the printing instruction to the completion of printing can be shortened.

  Further, it goes without saying that the representative value resetting process and the display mode changing process may be added to the process shown in FIG. In the process of FIG. 4, a feature amount extracted from the display image may be used instead of the second feature amount as the feature amount for correcting the display image.

[Other aspects of basic processing]
FIG. 21 shows a flowchart of another embodiment of the present invention. In this embodiment, it is determined whether the model image is installed in the image reading unit of the scanner 2 (S102). If the model image is installed (S102: YES), the installed model image is used. To perform image correction processing. On the other hand, if the model image is not set (S102: NO), the original image is printed as it is. Accordingly, it is possible to automatically determine whether or not to perform image correction and perform processing.

The process of determining whether the model image is installed in S102 can be realized by pre-scanning. At this time, it is not necessary to perform high-definition scanning in the pre-scan.

  Further, it goes without saying that the representative value resetting process and the display mode changing process may be added to the process shown in FIG. In the processing of FIG. 4, a feature amount extracted from the display image may be used instead of the second feature amount as the feature amount for correcting the display image.

  According to the present invention, since the correction contents can be grasped at the pre-printing stage, an efficient image correction process can be realized. Further, by performing image correction so as to have the characteristics of the image input from the scanner, it is possible to perform the image correction operation intuitively and intuitively.

  Furthermore, according to the image correction processing of the present invention, for example, when it is desired to convert sky blue to vivid sea blue with respect to the original image in which the building and the sky are reflected as the original image, You can convert the blue color of the original image into vivid sea blue by scanning the photo with the scanner.

  Also, if you want to brighten the skin color in an image showing a human face, you can convert the skin color of the original image to a light skin color by reading a picture of the palm that has moved to a bright skin color with a scanner. .

  Since the user does not need to input parameters or the like, he / she does not need any specialized knowledge and can perform desired image correction only by reading an image serving as a model for image correction. Furthermore, since it is possible to automatically select a region for performing image correction, it is possible to stop or reduce conversion of a region that is difficult to perceive and convert only a region that is easily perceived.

  In addition, this invention is not limited to the said embodiment, Of course, various improvement and deformation | transformation are possible within the range which does not deviate from the summary of this invention. For example, instead of reading a model image from a scanner, the image can be read as a model image from a storage medium. Further, instead of reading the original image from the storage medium, the original image can be read from the scanner. For example, a multifunction machine equipped with a scanner and a printer is described as an embodiment as an image processing apparatus. However, the present invention is not limited to this. For example, an information processing apparatus such as a personal computer performs image correction, and the information processing apparatus. The printer may be configured to perform printing processing.

  The present invention can also be realized as an image processing method for executing the above-described processing. Further, the present invention can be realized as a program for causing the computer to execute the image processing method and a recording medium on which the program is recorded.

  Further, the above-described flowchart is merely an example, and the process may be realized by another flowchart as long as it can obtain a result equivalent to the above-described process.

It is the figure which showed the external appearance of the image processing apparatus. It is the figure which showed the internal structure of the image processing apparatus. It is the figure which showed the user's operation | movement and the flow of a process of an image processing apparatus. It is a flowchart of the basic processing in 1st Embodiment of this invention. It is a flowchart of a 1st feature-value extraction process. It is a flowchart of the 2nd feature-value extraction process. It is the figure which showed the hue correction table. It is a flowchart of the basic process in another embodiment of this invention. It is a flowchart of a representative value reset process. It is the figure which showed the hue correction table. It is the figure which showed the hue correction table. It is the figure which showed the saturation correction table. It is the figure which showed the change of the curve of saturation correction | amendment. It is the figure which showed the saturation correction table in B area | region and C area | region. It is the figure which showed the corrected S value in B area | region and C area | region. It is the figure which showed that a part of B area | region and C area | region became conversion object. It is the figure which showed the image for a display by which the boundary line was drawn. It is the figure which showed the 3x3 mask used in order to draw a boundary line. It is the figure which showed the image for a display by which the frame line was drawn. It is a flowchart of the basic process in another embodiment of this invention. It is a flowchart of the basic process in another embodiment of this invention.

DESCRIPTION OF SYMBOLS 1 Image processing apparatus 2 Scanner 3 Memory slot 4 Operation panel 5 Ejection port 6 Display means 10 Printer

Claims (11)

In an image processing apparatus comprising a first image input means, a second image input means, a creation means, a feature amount extraction means, an image correction means, a display means, and a print control means,
The first image input means inputs a first image,
The second image input means inputs a second image,
The creating means creates the second image as a second display image,
The feature amount extraction unit extracts a first feature amount from the first image, and extracts a second feature amount from the second image or the second display image,
The image correcting means corrects the second display image and the second image based on the first feature amount and the second feature amount,
The display means displays the second image for display corrected for the image,
The print control unit executes a process for printing the second image image-corrected by the image correction unit based on the display result of the display unit ;
The image correction means performs image correction on a predetermined area of the second display image,
The display means displays the image for which the image has been corrected, an image in which a boundary line is drawn at the boundary between the image-corrected region and the region where the image has not been corrected;
The color of the boundary line is determined based on color information of the image corrected region.
An image processing apparatus. In an image processing apparatus comprising a first image input means, a second image input means, a creation means, a feature amount extraction means, an image correction means, and a display means,
The first image input means inputs a first image,
The second image input means inputs a second image,
The creating means creates the second image as a second display image,
The feature amount extraction unit extracts a first feature amount from the first image, and extracts a second feature amount from the second image or the second display image,
The image correction means corrects the second display image based on the first feature amount and the second feature amount;
The display means displays the second image for display corrected for the image,
The image correction means corrects the second image based on the display result of the display means , performs image correction on a predetermined area of the second display image,
The display means displays the image for which the image has been corrected, an image in which a boundary line is drawn at the boundary between the image-corrected region and the region where the image has not been corrected;
The color of the boundary line is determined based on color information of the image corrected region.
An image processing apparatus.   In an image processing apparatus comprising a first image input means, a second image input means, a creation means, a feature amount extraction means, an image correction means, a display means, and a print control means,
  The first image input means inputs a first image,
  The second image input means inputs a second image,
  The creating means creates the second image as a second display image,
  The feature amount extraction unit extracts a first feature amount from the first image, and extracts a second feature amount from the second image or the second display image,
  The image correcting means corrects the second display image and the second image based on the first feature amount and the second feature amount,
  The display means displays the second image for display corrected for the image,
  The print control unit executes a process for printing the second image image-corrected by the image correction unit based on the display result of the display unit;
  The image correction means performs image correction on a predetermined area of the second display image,
  The display means displays the image-corrected display image by converting the non-image-corrected area to an achromatic color and displaying the gradation of the area converted to the achromatic color smaller than other areas.
An image processing apparatus.   In an image processing apparatus comprising a first image input means, a second image input means, a creation means, a feature amount extraction means, an image correction means, and a display means,
  The first image input means inputs a first image,
  The second image input means inputs a second image,
  The creating means creates the second image as a second display image,
  The feature amount extraction unit extracts a first feature amount from the first image, and extracts a second feature amount from the second image or the second display image,
  The image correction means corrects the second display image based on the first feature amount and the second feature amount;
  The display means displays the second image for display corrected for the image,
  The image correction means corrects the second image based on the display result of the display means, performs image correction on a predetermined area of the second display image,
  The display means displays the image-corrected display image by converting the non-image-corrected area to an achromatic color and displaying the gradation of the area converted to the achromatic color smaller than other areas.
An image processing apparatus. Correction data creating means for creating correction data based on the first feature quantity and the second feature quantity;
The image conversion means performs image correction of the second display image and the second image based on the correction data.
The image processing apparatus according to claim 1 , wherein the image processing apparatus is an image processing apparatus. The feature amount extraction unit extracts a feature amount related to a hue from the first image,
The feature amount extraction means includes:
Extracting a feature quantity related to hue from the second image or the second display image;
Dividing each of the first image, the second image, or the second display image into a plurality of regions based on the feature value relating to the hue;
For each of the divided areas, extract features other than hue,
The correction data creating means includes
For each of the divided areas of the first image and the second image or the second display image, a representative value of the feature value related to the hue is extracted, and hue correction data is created based on the representative value. And
For each of the divided areas of the first image and the second image or the second display image, a representative value of a feature value related to other than the hue is extracted,
The image correcting means includes
Correcting a feature amount related to a hue for each pixel of the second image and the second display image based on the hue correction data;
Correcting a feature amount related to other than the hue for each pixel of the second image and the second display image based on a representative value for each region;
The image processing apparatus according to claim 5 . The feature amount related to the hue is calculated based on the H value in the HSV space.
The image processing apparatus according to claim 6 . On the computer,
A first image input step for inputting a first image;
A second image input step for inputting a second image;
A creation step of creating a second image as a second display image;
A first feature amount extracting step of extracting a first feature amount from the first image;
A second feature amount extracting step of extracting a second feature amount from the second image or the second display image;
A first image correction step of correcting the second display image and the second image based on the first feature amount and the second feature amount;
A first display step of displaying the image-corrected second display image;
A print control step for executing a process for printing the second image after the image correction based on the display result of the first display step;
A second image correction step for performing image correction on a predetermined region of the second display image;
A second display step of displaying the image-corrected display image in an image in which a boundary line is drawn at a boundary between the image-corrected region and a region that has not been image-corrected;
A line color determining step for determining a color of the boundary line based on color information of the image-corrected region;
An image processing program for executing   On the computer,
  A first image input step for inputting a first image;
  A second image input step for inputting a second image;
  A creation step of creating a second image as a second display image;
  A first feature amount extracting step of extracting a first feature amount from the first image;
  A second feature amount extracting step of extracting a second feature amount from the second image or the second display image;
  A first image correction step of correcting the second display image based on the first feature amount and the second feature amount;
  A first display step of displaying the image-corrected second display image;
  A second image correction step of correcting the second image based on the display result of the first display step, and performing image correction on a predetermined region of the second display image;
  A second display step of displaying the image-corrected display image as an image in which a boundary line is drawn at a boundary between the image-corrected region and a region that has not been image-corrected;
  A line color determining step for determining a color of the boundary line based on color information of the image-corrected region;
An image processing program for executing On the computer,
A first image input step for inputting a first image;
A second image input step for inputting a second image;
A creation step of creating a second image as a second display image;
A first feature amount extracting step of extracting a first feature amount from the first image;
A second feature amount extracting step of extracting a second feature amount from the second image or the second display image;
A first image correction step of correcting the second display image and the second image based on the first feature amount and the second feature amount;
A first display step of displaying the image-corrected second display image;
A print control step for executing a process for printing the second image after the image correction based on the display result of the first display step;
A second image correction step for performing image correction on a predetermined region of the second display image;
A second display step of displaying the image-corrected display image by converting the region that has not been image-corrected into an achromatic color and displaying the gradation of the region that has been converted to the achromatic color smaller than other regions;
An image processing program for executing   On the computer,
  A first image input step for inputting a first image;
  A second image input step for inputting a second image;
  A creation step of creating a second image as a second display image;
  A first feature amount extracting step of extracting a first feature amount from the first image;
  A second feature amount extracting step of extracting a second feature amount from the second image or the second display image;
  A first image correction step of correcting the second display image based on the first feature amount and the second feature amount;
  A first display step of displaying the image-corrected second display image;
  A second image correction step of correcting the second image based on the display result of the first display step, and performing image correction on a predetermined region of the second display image;
  A second display step of displaying the image-corrected display image by converting the area not image-corrected into an achromatic color and displaying the gradation of the area converted into the achromatic color smaller than other areas;
An image processing program for executing