JP2008072172A - Image processor, printer, image processing method, and printing method - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To easily perform image correction processing matching user's preference without requesting the user to have high-level knowledge about image correction. <P>SOLUTION: Image data generated by photographing an object of photography are analyzed to calculate degrees of matching of a plurality of predetermined classifications, for example, a person image degree, a scene image degree, etc. The calculated degrees of matching are corrected by reflecting user's preference. Correction contents previously stored corresponding to the respective classifications are reflected at rates corresponding to the corrected degrees of matching to determine contents of correction to be performed for the image data. Consequently, when an image is corrected, the degree of matching of a classification considered to be important is only varied, so correction matching the user's preference can be performed without requesting the user to have high-level knowledge. <P>COPYRIGHT: (C)2008,JPO&INPIT

Description

  The present invention relates to a technique for printing an image.

Due to advances in computer-related technology, color images are now handled as digitized image data. For example, when an image is captured using a digital camera, the captured image is stored as image data, and can be printed immediately by selecting the image data and supplying it to a printing device when necessary. It has become.

Also, when printing an image from image data in this way, the image data is analyzed and what the image was taken (for example, a person or a landscape) ), And a technique for printing after correcting the image data according to the object to be photographed has been developed (Patent Document 1, etc.). For example, if the image is a photograph of a person, the brightness is slightly increased to correct the overall impression, and the outline is slightly blurred to correct the overall impression. To do. In addition, the image obtained by photographing the landscape is corrected so that the outline is slightly emphasized to give a clear impression. By printing after correcting the image data in this way, a more preferable image can be printed according to the captured image.

JP 2003-281514 A

However, there is a problem that a preferable image is not always obtained even though the image is corrected in accordance with the photographing target. This is because, although the content of correction that should be applied according to the shooting target is strictly different for each user, the correction is actually performed with the content set for everyone. it is conceivable that.

Of course, it is conceivable for each user to modify the correction content according to his / her preference. Absent.

SUMMARY An advantage of some aspects of the invention is that it provides a technique capable of easily outputting an image that has been appropriately corrected according to a user's preference.

In order to solve at least a part of the problems described above, the image processing apparatus of the present invention employs the following configuration. That is,
An image processing apparatus that analyzes image data generated by copying a shooting target, classifies the image data into a plurality of predetermined classes based on the shooting target, and then performs correction according to the class. ,
Correction content storage means for storing correction content to be added to the image data for each category;
A degree-of-match detection means for detecting a degree of match for each classification of the image data by analyzing the image data;
A degree-of-match correction means for correcting the degree of match of each detected category;
The gist of the invention is to provide image data correction means for correcting the image data by reflecting the correction contents stored for each category at a ratio corresponding to the corrected degree of match.

The image processing method of the present invention corresponding to the above image processing apparatus is
An image processing method for analyzing image data generated by copying a shooting target, classifying the image data into a plurality of predetermined classes based on the shooting target, and then performing correction according to the classification ,
A first step of storing correction contents to be added to the image data for each category;
A second step of analyzing the image data to detect a degree of matching of the image data with respect to each category;
A third step of correcting each detected category;
And a fourth step of correcting the image data by reflecting the correction contents stored for each category at a ratio corresponding to the corrected degree of match.

In the image processing apparatus and the image processing method of the present invention, a plurality of categories (persons, landscapes, etc.) based on the object to be photographed are set in advance, and correction contents corresponding to each category are stored. When the image data is received, the degree of match for each category is calculated by analyzing the image data. Next, correction processing to be performed on the image is determined as follows based on the calculated degree of matching for each category and the stored correction content corresponding to each category.
First, in order to reflect the user's preference, the degree of match for each category is modified. Next, the correction content corresponding to each category is reflected according to the corrected degree of matching of each category to determine the correction content. According to the correction content thus determined, the image data is corrected.

In this way, it is possible to correct the image with the correction content according to the user's preference by correcting the degree of matching for each category. Also, when reflecting the user's preferences in the correction details,
Since it is only necessary to correct the degree of match obtained for each category, it is sufficient to capture the user's preference in the form of which category is important. For this reason, even if the user does not have knowledge about advanced image correction processing such as brightness correction, contrast correction, and sharpness correction, it is possible to easily correct to a preferable image.

In addition, a table (matching degree correction table) in which combinations of matching degrees for each category are associated with correction amounts to be added to the matching degrees for each category is stored, and the current image data is referenced with reference to the table. It is also possible to correct the degree of match for each category.

In this way, the amount of correction added to the degree of match for each category can be made different for each combination of degree of match for each category. In general, user preferences differ depending on the content of the image, so it is possible to reflect user preferences more accurately by making corrections correspond to combinations of matching levels for each category. Become. Further, since the correction amount can be referred to simply by reading information from the table, no special calculation process is required, and user preferences can be easily reflected.

In addition, after estimating the user's preferred correction content using the stored match correction table, an image corrected with the estimated correction content is output on a screen or printing paper so that the user can check it. May be. Then, the output value may be confirmed, and the correction value changed so that the user can obtain the desired correction content may be stored in the matching degree correction table together with the matching degree of each category.

In this way, the user can confirm whether or not the estimated correction content actually matches the preference. Furthermore, since the user can set the correction content by changing the correction amount for the degree of match for each category, it is possible to easily correct to a favorite image without knowledge of advanced image correction. Become. In addition, since the information stored in the matching degree correction table increases with such processing, it is possible to estimate the correction contents reflecting the user's preference more appropriately, which is preferable.

In view of the fact that the image processing method of the present invention described above makes it possible to print an image that has been corrected to the user's preference, the present invention can be understood as a printing apparatus as follows. Is also possible. That is, the printing apparatus of the present invention is
Print that analyzes the image data generated by copying the object to be photographed, classifies the image data into a plurality of predetermined classes based on the object to be photographed, and then prints the image with corrections according to the classes A device,
Correction content storage means for storing correction content to be added to the image data for each category;
A degree-of-match detection means for detecting a degree of match for each classification of the image data by analyzing the image data;
A degree-of-match correction means for correcting the degree of match of each detected category;
Image data correction means for correcting the image data by reflecting the correction content stored for each category at a rate corresponding to the corrected degree of match;
And an image printing unit that prints an image based on the corrected image data.

Also, the printing method of the present invention corresponding to the above printing apparatus is
A printing method in which image data generated by copying a shooting target is analyzed, and the image data is classified into a plurality of predetermined classes based on the shooting target, and then printed with corrections according to the classes. There,
(A) storing correction contents to be added to the image data for each category;
Analyzing the image data to detect a degree of match for each classification of the image data (B);
A step (C) of correcting the degree of matching of each detected category;
A step (D) of correcting the image data by reflecting the correction content stored for each category at a ratio corresponding to the corrected degree of matching, and an image based on the corrected image data And a step (E) for printing.

Furthermore, the present invention can be realized using a computer by causing a computer to read a program for realizing the above-described image processing method or printing method and executing a predetermined function. Therefore, the present invention includes the following program or a mode as a recording medium on which the program is recorded. That is, the program of the present invention corresponding to the image processing method described above is
Using a computer, a method for classifying the image data into a plurality of predetermined classes based on the shooting target by analyzing the image data generated by copying the shooting target, and then performing correction according to the classification A program for realizing
A first function storing correction contents to be added to the image data for each of the categories;
A second function of detecting the degree of match for each classification of the image data by analyzing the image data;
A third function for correcting the degree of match of each detected category;
A fourth function for correcting the image data is realized by using a computer by reflecting the correction content stored for each category at a rate corresponding to the corrected degree of match. And

The recording medium of the present invention corresponding to the above program is
By analyzing the image data generated by copying the object to be imaged, the image data is classified into a plurality of predetermined classes based on the object to be imaged, and then a program for performing correction according to the class is read by a computer A recording medium capable of recording,
A first function storing correction contents to be added to the image data for each of the categories;
A second function of detecting the degree of match for each classification of the image data by analyzing the image data;
A third function for correcting the degree of match of each detected category;
A program for realizing, using a computer, a fourth function for correcting the image data by reflecting the correction contents stored for each category at a rate corresponding to the corrected degree of coincidence. It is a summary.

Furthermore, the program of the present invention corresponding to the printing method described above is
A method of printing image after analyzing image data generated by copying a shooting target and classifying the image data into a plurality of predetermined classes based on the shooting target and then applying correction according to the classification Is a program for realizing using a computer,
A function (A) for storing correction contents to be added to the image data for each category;
A function (B) for detecting the degree of match of the image data with respect to each category by analyzing the image data;
A function (C) for correcting the degree of matching of each detected category;
A function (D) for correcting the image data by reflecting the correction content stored for each category at a rate corresponding to the corrected degree of match;
The gist is to realize a function (E) of printing an image based on the corrected image data using a computer.

The recording medium of the present invention corresponding to the above program is
A program for analyzing image data generated by copying a shooting target, classifying the image data into a plurality of predetermined classes based on the shooting target, and then performing correction according to the class and printing an image Is a computer-readable recording medium,
A function (A) for storing correction contents to be added to the image data for each category;
A function (B) for detecting the degree of match of the image data with respect to each category by analyzing the image data;
A function (C) for correcting the degree of matching of each detected category;
A function (D) for correcting the image data by reflecting the correction content stored for each category at a rate corresponding to the corrected degree of match;
The gist of the invention is that a program for realizing a function (E) of printing an image based on the corrected image data by using a computer is recorded.

If these programs are read into a computer and the above functions are realized, the user can perform appropriate image correction processing that matches his / her preference. Nevertheless, since the user is not required to have advanced image correction processing knowledge, it is possible to easily obtain a print image that matches the preference.

Hereinafter, in order to clarify the contents of the present invention described above, examples will be described in the following order.
A. Summary of Examples:
B. Device configuration:
B-1. overall structure:
B-2. Internal configuration:
B-2-1. Internal configuration of the scanner unit:
B-2-2. Internal configuration of the printer unit:
C. Image printing process:
D. Image correction processing:
E. Variation:

A. Summary of Examples:
Prior to detailed description of the embodiment, an outline of the embodiment will be described with reference to FIG. FIG. 1 is an explanatory diagram showing an overview of a printing apparatus 10 according to the present embodiment. The illustrated printing apparatus 10 is provided with a print head 12 that ejects ink droplets, and an image is formed by ejecting ink droplets and forming ink dots while reciprocating the print head 12 on the print medium P. Is a so-called inkjet printer.

Such ink jet printers have improved print image quality year by year, and can easily print high-quality color images. Also, in order to further improve the print image quality, the image data to be printed is analyzed, and what the image was taken (for example, a photograph of a person or a landscape) Judgment and a technique of printing while applying correction according to an object to be photographed have been introduced.

However, there is a problem that a preferable image is not always obtained even though the image is corrected in accordance with the photographing target. This is because, although the content of correction that should be applied according to the shooting target is strictly different for each user, the correction is actually performed with the content set for everyone. it is conceivable that. To avoid this problem,
The user may set the correction contents individually, but in order to set the appropriate correction contents, knowledge about advanced image correction processing is necessary, and this is not easy in practice.

In view of such a situation, the apparatus 10 of this embodiment shown in FIG. 1 includes a “correction content storage module”, “matching degree calculation module”, “matching degree correction module”, “correction content determination module”, “
Modules “image correction module” and “image printing module” are incorporated. still,
A “module” is a series of processes that are internally performed by the printing apparatus 10 for printing an image, focusing on functions. Therefore, the “module” can be realized as a part of the program, or can be realized by using a logic circuit having a specific function. Furthermore, it is also possible to realize by combining these.

In the illustrated apparatus 10, when image data is received, processing is performed as follows. First, the “matching degree calculation module” calculates the degree of matching for a plurality of categories (such as a person image and a landscape image) by analyzing the received image data. Further, for each category, the corresponding correction content is stored in the “correction content storage module”. For example, the correction content corresponding to the “person image” is set so that a preferable print image corresponding to the image can be obtained, such as increasing brightness and softening.

After the degree of match for each category is calculated, the “match level correction module” then corrects the level of match for each category to reflect the user's preference. The degree of match for each category modified in this way,
Based on the correction content corresponding to each type stored in the “correction content storage module”,
The “correction content determination module” determines the correction content to be actually applied to the image. Various methods can be considered for determining the correction content. For example, the correction content can be determined by adding the correction content corresponding to each class using the corrected degree of matching as a weighting factor. By using the correction content determined in this way, it is possible to perform a correction process reflecting the user's preference.

The image data thus corrected is supplied to the “image printing module”, converted into a signal for driving the print head 12, and an image is printed on the print medium P.

When a certain image is classified into a plurality of categories according to the shooting target, the user's preference can be grasped in the form of emphasizing correction for which category. From this, it is possible to obtain a print image that has been subjected to correction processing reflecting the user's preference by correcting the degree of matching of each category extracted from the image according to the user's preference. Below,
Such a printing apparatus 10 will be described in detail based on an embodiment.

B. Device configuration :
B-1. overall structure :
FIG. 2 is a perspective view showing the external shape of the printing apparatus 10 according to the present embodiment. As shown,
The printing apparatus 10 of this embodiment includes a scanner unit 100, a printer unit 200, and a scanner unit 10
0, an operation panel 300 for setting the operation of the printer unit 200, and the like. The scanner unit 100 has a scanner function of reading a printed image and generating image data, and the printer unit 200 has a printer function of receiving image data and printing an image on a print medium. . Further, if an image (original image) read by the scanner unit 100 is output from the printer unit 200, a copy function can be realized. That is, the printing apparatus 10 of this embodiment is a so-called scanner / printer / copy combined apparatus (hereinafter referred to as an SPC combined apparatus) that can independently realize a scanner function, a printer function, and a copy function.
It has become.

FIG. 3 shows a document table cover 1 provided at the top of the printing apparatus 10 for reading a document image.
It is explanatory drawing which shows a mode that 02 was opened. As shown in the drawing, when the document table cover 102 is opened upward, a transparent document table glass 104 is provided, and various mechanisms to be described later for realizing the scanner function are mounted therein. . When reading a document image, as shown in the figure, the document table cover 102 is opened and the document image is placed on the document table glass 104.
The button on the operation panel 300 is operated after the document table cover 102 is closed. This way
It is possible to immediately convert a document image into image data.

The scanner unit 100 is entirely housed in an integrated case, and the scanner unit 100 and the printer unit 200 are provided with a hinge mechanism 204 (FIG. 4) on the back side of the printing apparatus 10.
Reference). Therefore, by lifting the front side of the scanner unit 100, only the scanner unit 100 can be rotated at the hinge portion.

FIG. 4 is a perspective view illustrating a state in which the front side of the scanner unit 100 is lifted and rotated. As shown in the drawing, in the printing apparatus 10 of this embodiment, the upper surface of the printer unit 200 can be exposed by lifting the front side of the scanner unit 100. Inside the printer unit 200, various mechanisms to be described later for realizing the printer function, a control circuit 260 to be described later for controlling the operation of the entire printing apparatus 10 including the scanner unit 100, and the scanner unit 100 are further described. And a power supply circuit (not shown) for supplying power to the printer unit 200 and the like. Also, as shown in FIG. 4, an opening 202 is provided on the upper surface of the printer unit 200, and replacement of consumables such as ink cartridges, paper jam handling, and other minor repairs are performed. Can be performed easily.

B-2. Internal configuration:
FIG. 5 is an explanatory diagram conceptually showing the internal configuration of the printing apparatus 10 of this embodiment. As described above, the printing apparatus 10 includes the scanner unit 100 and the printer unit 200, and various configurations for realizing the scanner function are mounted in the scanner unit 100. Is equipped with various configurations for realizing the printer function. Hereinafter, the internal configuration of the scanner unit 100 will be described first, and then the internal configuration of the printer unit 200 will be described.

B-2-1. Internal configuration of the scanner unit:
The scanner unit 100 includes a transparent platen glass 104 on which a document image is set, a document platen cover 102 for holding the set document image, a reading carriage 110 for reading the set document image, and a reading carriage 110. The driving belt 120 is configured to move in the reading direction (main scanning direction), the driving motor 122 supplies power to the driving belt 120, the guide shaft 106 that guides the movement of the reading carriage 110, and the like. The operations of the drive motor 122 and the reading carriage 110 are controlled by a control circuit 260 described later.

When the drive motor 122 is rotated under the control of the control circuit 260, the movement is transmitted to the reading carriage 110 via the driving belt 120. As a result, the reading carriage 110 is
While being guided by the guide shaft 106, it moves in the reading direction (main scanning direction) according to the rotation angle of the drive motor 122. Further, the drive belt 120 is constantly adjusted to be in a moderately tensioned state by the idler pulley 124. Therefore, if the drive motor 122 is rotated in the reverse direction, the reading carriage 110 is moved in the reverse direction by a distance corresponding to the rotation angle. It is also possible to make it.

Inside the reading carriage 110 are a light source 112, a lens 114, a mirror 116, and a CC.
A D sensor 118 and the like are mounted. Light from the light source 112 is applied to the platen glass 104 and reflected by a document image set on the platen glass 104. This reflected light is guided to the lens 114 by the mirror 116, collected by the lens 114, and detected by the CCD sensor 118. The CCD sensor 118 is configured by a linear sensor in which photodiodes that convert light intensity into an electrical signal are arranged in a row in a direction orthogonal to the moving direction (main scanning direction) of the reading carriage 110. Therefore, by moving the reading carriage 110 in the main scanning direction and irradiating the original image with light from the light source 112 and detecting the reflected light intensity by the CCD 118, an electrical signal corresponding to the original image can be obtained.

The light source 112 is composed of light emitting diodes of three colors of RGB, and can sequentially irradiate light of R color, G color, and B color at a predetermined cycle. C
In CD118, the reflected light of R color, G color, and B color is detected sequentially. In general, the red portion of the image reflects R light, but hardly reflects G or B light, so the R reflected light represents the R component of the image. Similarly, the reflected light of G color represents the G component of the image, and the reflected light of B color represents the B component of the image. Accordingly, if the original image is irradiated while switching light of RGB three colors at a predetermined period and the reflected light intensity is detected by the CCD 118 in synchronization with this, the R component, G component, and B component of the original image can be detected. It is possible to read a color image. Note that since the reading carriage 110 is moved even while the color of light emitted from the light source 112 is switched, the position of the image for detecting each component of RGB corresponds to the movement amount of the reading carriage 110 strictly. The difference is as much as
After reading each component, it can be corrected by image processing.

B-2-2. Internal configuration of the printer unit:
Next, the internal configuration of the printer unit 200 will be described. The printer unit 200 includes a control circuit 260 that controls the overall operation of the printing apparatus 10, a print carriage 240 that prints an image on a print medium, a mechanism that moves the print carriage 240 in the main scanning direction, and printing. A mechanism for feeding media is mounted.

The print carriage 240 includes an ink cartridge 242 that stores K ink, an ink cartridge 243 that stores various inks of C ink, M ink, and Y ink, a print head 241 provided on the bottom surface side, and the like. The print head 241 is provided with an ink discharge head for discharging ink droplets for each ink. When the ink cartridges 242 and 243 are mounted on the print carriage 240, each ink in the cartridge is supplied to the ink discharge heads 244 to 247 of each color through an introduction pipe (not shown).

The mechanism that moves the print carriage 240 in the main scanning direction includes a carriage belt 231 for driving the print carriage 240, a carriage motor 230 that supplies power to the carriage belt 231, and an appropriate tension is constantly applied to the carriage belt 231. Tension pulley 232 for holding the carriage, and carriage guide 233 for guiding the movement of the print carriage 240
And an origin position sensor 234 for detecting the origin position of the print carriage 240. When the carriage motor 230 is rotated under the control of the control circuit 260 described later,
The print carriage 240 can be moved in the main scanning direction by a distance corresponding to the rotation angle. Further, if the carriage motor 230 is rotated in the reverse direction, the print carriage 240 can be moved in the reverse direction.

The mechanism for feeding the print medium includes a platen 236 that supports the print medium from the back side, a paper feed motor 235 that feeds the paper by rotating the platen 236, and the like. By rotating the paper feed motor 235 under the control of the control circuit 260 described later, the print medium can be fed in the sub-scanning direction by a distance corresponding to the rotation angle.

The control circuit 260 has a CPU, a ROM, a RAM, a D / A converter that converts digital data into an analog signal, and a peripheral device interface PIF for exchanging data with peripheral devices. It is composed of The control circuit 260 controls the overall operation of the printing apparatus 10, and controls these operations while exchanging data with the light source 112, the drive motor 122, and the CCD 118 mounted on the scanner unit 100.

The control circuit 260 drives the carriage motor 230 and the paper feed motor 235 to perform main scanning and sub-scanning of the print carriage 240, and the ink ejection head 2 for each color.
Control is also performed to supply ink to 44 to 247 to eject ink droplets. The drive signals supplied to the ink ejection heads 244 to 247 are generated by reading image data from the computer 30, the digital camera 20, the external storage device 32, etc., and performing image processing to be described later. Of course, it is also possible to generate a drive signal by performing image processing on the image data read by the scanner unit 100. In this way, under the control of the control circuit 260, the ink ejection head 2 is moved while the print carriage 240 is being subjected to main scanning and sub scanning.
A color image can be printed by ejecting ink droplets from 44 to 247 to form ink dots of respective colors on the print medium. Of course, the control circuit 260
Instead of performing image processing in the printer, the ink ejection heads 244 to 247 may be driven while performing main scanning and sub-scanning of the print carriage 240 in accordance with this data after receiving the image-processed data from the computer 20. Is possible.

The control circuit 260 is also connected to the operation panel 300 so as to exchange data. By operating various buttons provided on the operation panel 300, detailed operation modes of the scanner function and the printer function are set. It is possible to set. Further, it is possible to set a detailed operation mode from the computer 20 via the peripheral device interface PIF.

FIG. 6 is an explanatory diagram showing a state in which a plurality of nozzles Nz for ejecting ink droplets are formed on the ink ejection heads 244 to 247 for each color. As shown in the figure, four sets of nozzle rows for ejecting ink droplets of each color are formed on the bottom surface of the ink ejection head for each color, and 48 nozzles Nz have a nozzle pitch k in one nozzle row. They are arranged in a staggered pattern at intervals. A drive signal is supplied from the control circuit 260 to each of these nozzles Nz, and each nozzle Nz discharges an ink droplet of each ink according to the drive signal.

As described above, the printer unit 200 of the printing apparatus 10 prints an image by supplying drive signals to the ink discharge nozzles and discharging ink droplets according to the drive signals to form ink dots on the print medium. ing. Control data for driving the ink discharge nozzles is generated by performing predetermined image processing on the image data prior to image printing. Hereinafter, a process of printing an image by performing image processing on the image data to generate control data and forming ink dots based on the obtained control data will be described.

C. Image printing process:
FIG. 7 is a flowchart showing a flow of processing (image printing processing) in which the printer driver executes printing. Such a process is a process executed by the control circuit 260 mounted on the printing apparatus 10 using functions such as a built-in CPU, RAM, and ROM. Hereinafter, a description will be given according to the flowchart shown in FIG.

As shown in FIG. 7, when the image printing process is started, first, image data is read (step S100). Here, it is assumed that the image data is RGB image data expressed by gradation values of R, G, and B colors.

Next, a process for correcting the read image data so as to obtain a preferable print quality (image correction process) is performed (step S102). In a correction process performed in a general printing apparatus, correction is performed so that a more preferable image is obtained according to an object (for example, a person or a landscape) captured in an image. In such correction processing, the content of correction is stored in the printing apparatus in advance, and the user can easily obtain a preferable image without advanced knowledge of image correction. However, on the other hand, it has not always been said that the image obtained in this way always matches the user's preference completely. For example, in the case of an image in which a person is photographed against a landscape, there are users who prefer correction that emphasizes the person, and other users who prefer correction that emphasizes the landscape. In such a case, it is not possible to make corrections according to individual user's preferences using the correction contents stored in advance in the printing apparatus. Therefore, in the image correction process of this embodiment, it is possible to print an image that matches the user's preference by performing a special correction process.

Following the image correction process, a process of converting the resolution of the image data to a resolution (printing resolution) for printing by the printer unit 200 is performed (step S104). When the resolution of the read image data is lower than the print resolution, the image data is converted to a higher resolution by performing interpolation calculation between adjacent pixels and setting new image data. On the other hand, when the resolution of the read image data is higher than the print resolution, the image data is converted to a lower resolution by thinning out the image data at a constant rate from between adjacent pixels. In the resolution conversion process, the read resolution is converted into the print resolution by generating or thinning out the image data at an appropriate ratio with respect to the read image data.

Subsequently, the control circuit 260 of the printing apparatus 10 performs color conversion processing on the image data (step S106). Here, the color conversion process is a process of converting image data expressed in R, G, and B colors into image data expressed by gradation values of C, M, Y, and K colors. The color conversion process is performed by referring to a three-dimensional numerical table called a color conversion table (LUT).

FIG. 8 is an explanatory diagram conceptually showing a color conversion table (LUT) referred to for color conversion processing. Now, it is assumed that gradation values of RGB colors can take values from 0 to 255. Further, as shown in FIG. 8, when considering a color space in which gradation values of R, G, and B are taken on three orthogonal axes, all RGB image data have a side length of 255 with the origin at the apex. Can be associated with points inside the cube (color solid). From a different perspective, this can be thought of as follows. That is, if a color solid is subdivided into a grid perpendicular to the RGB axes and a plurality of grid points are generated in the color space, each grid point can be considered to represent RGB image data. Therefore, if a combination of C, M, Y, and K gradation values is stored in advance in each grid point, the RGB image data can be converted into each color by reading the gradation value stored in the grid point. It is possible to convert the image data (CMYK image data) represented by the gradation value.

For example, if the R component of the image data is RA, the G component is GA, and the B component is BA,
This image data is associated with point A in the color space (see FIG. 8). Therefore, a cube dV containing point A is detected from small cubes that subdivide the color solid into a lattice shape, and the gradation values of the CMYK colors stored in the lattice points of the cube dV are read out. Then, if the interpolation calculation is performed from the gradation values of these grid points, the gradation value at the point A can be obtained. As described above, the color conversion table LUT is a three-dimensional number in which a combination of gradation values of CMYK colors (CMYK image data) is stored at each grid point indicated by a combination of gradation values of RGB colors. It can be considered as a table, and by referring to the color conversion table, RGB image data can be quickly converted into CMYK image data.

When the color conversion process is completed as described above, the control circuit 260 starts the halftone process (step S108 in FIG. 7). Halftone processing is the following processing. The CMYK image data obtained by the color conversion process is image data expressed in the range of gradation value 0 to gradation value 255 for each color of C, M, Y, and K. In contrast, the printer unit 200
Since an image is printed by forming dots, it is necessary to convert CMYK image data expressed by 256 gradations into image data (dot data) expressed by the presence or absence of dot formation. Halftone processing is processing for converting image data of CMYK colors into dot data in this way.

As a method for performing the halftone process, various methods such as an error diffusion method and a dither method can be applied. The error diffusion method is to determine whether or not dots are formed for a certain pixel, so that the error in gradation expression that occurs in that pixel is diffused to the surrounding pixels and the error diffused from the surroundings is eliminated. This is a method of determining the presence or absence of dot formation for each pixel. Also, the dither method uses a threshold value and CM that are randomly set in the dither matrix.
Comparing the image data of each color of YK for each pixel, it is determined that a dot is formed for a pixel having a larger image data, and conversely, a dot is not formed for a pixel having a larger threshold value. This is a technique for obtaining dot data for each pixel. As a halftone method,
Either the error diffusion method or the dither method can be used, but the printing apparatus 10 of this embodiment performs the halftone process using the dither method.

FIG. 9 is an explanatory diagram illustrating an enlarged part of the dither matrix. In the illustrated matrix, threshold values that are uniformly selected from the range of gradation values 0 to 255 are randomly stored in a total of 4096 pixels, 64 pixels in the vertical and horizontal directions. Here, the gradation value of the threshold is 0 to
In the present embodiment, the selection from the range of 255 corresponds to the fact that the image data of each color of CMYK is 1-byte data and the gradation value can take a value from 0 to 255. Note that the size of the dither matrix is not limited to 64 pixels in the vertical and horizontal directions as illustrated in FIG. 9, and can be set to various sizes including those having different numbers of vertical and horizontal pixels. It is.

FIG. 10 is an explanatory diagram conceptually showing a state in which the presence / absence of dot formation is determined for each pixel while referring to the dither matrix. This determination is made for each color of CMYK, but in the following, in order to avoid complicated explanation, image data of each color of CMYK is simply referred to as image data without being distinguished.

When determining the presence or absence of dot formation, first, the gradation value of the image data for the pixel of interest (the pixel of interest) as the object of determination is compared with the threshold value stored at the corresponding position in the dither matrix. . The thin broken arrow shown in the figure schematically represents that the image data of the pixel of interest is compared with the threshold value stored at the corresponding position in the dither matrix. If the image data of the pixel of interest is larger than the threshold value of the dither matrix, it is determined that a dot is formed for that pixel. On the contrary, when the threshold value of the dither matrix is larger, it is determined that no dot is formed in the pixel.
In the example shown in FIG. 10, the image data of the pixel at the upper left corner of the image is “97”, and the threshold value stored at the position corresponding to this pixel on the dither matrix is “1”. Accordingly, for the pixel at the upper left corner, the image data is larger than the threshold value of the dither matrix, and therefore it is determined that a dot is formed on this pixel. An arrow indicated by a solid line in FIG. 10 schematically represents a state in which it is determined that a dot is to be formed in this pixel and the determination result is written in the memory.

On the other hand, for the pixel on the right side of this pixel, the image data is “97”, and the threshold value of the dither matrix is “177”. Since the threshold value is larger, it is determined that no dot is formed for this pixel. Thus, by comparing the image data with the threshold value set in the dither matrix, it is possible to determine whether or not dots are formed for each pixel. In the halftone process (step S108 in FIG. 7), by applying the above-described dither method to the image data of each color of C, M, Y, and K, the dot data is determined for each pixel to determine dot data. Process to generate.

As shown in FIG. 7, in the image printing process, when halftone processing is performed to generate dot data for each color of CMYK, interlace processing is started (step S1).
10). The interlace process is a process in which the print head 241 rearranges the dot data in the order in which dots are formed and supplies them to the ink discharge heads 244 to 247 for each color.
That is, as shown in FIG. 6, the nozzles Nz provided in the ink discharge heads 244 to 247 are provided with an interval of the nozzle pitch k in the sub-scanning direction. When droplets are ejected, dots are formed at intervals of the nozzle pitch k in the sub-scanning direction. Therefore, in order to form dots in all the pixels, the relative position between the print carriage 240 and the print medium is moved in the sub-scanning direction, and new dots are formed in the pixels between the dots separated by the nozzle pitch k. Necessary. As described above, when an image is actually printed, dots are not formed in order from the upper pixel on the image. Furthermore, for pixels in the same row in the main scanning direction, instead of forming dots in a single main scan, the dots are divided into a plurality of main scans in response to image quality requirements. In this main scanning, dots are also widely formed on the pixels at the skipped positions.

For this reason, prior to actually starting dot formation, the dot data obtained for each color of C, M, Y, and K is rearranged in the order in which the ink ejection heads 244 to 247 form dots. Is required. Such a process is a process called interlace.

As shown in FIG. 7, when the interlacing process is completed, a process for actually forming dots on the print medium (dot forming process) is started according to the dot data rearranged by the interlace process (step S112). That is, while the carriage motor 230 is driven to cause the print carriage 240 to perform main scanning, the rearranged dot data is supplied to the ink ejection heads 244 to 247. As a result, the ink discharge head 244
From 247 to 247, ink droplets are ejected according to the dot data, and dots are appropriately formed in each pixel.

When one main scan is completed, the paper feed motor 235 is driven to feed the print medium in the sub-scanning direction, and then the carriage motor 230 is driven again to print the print carriage 2.
40. The ink discharge head 244 converts the dot data rearranged in the order of 40 to the main scanning.
To 247 to form dots. By repeating these operations,
On the print medium, dots of each color of C, M, Y, and K are formed with an appropriate distribution according to the gradation value of the image data, and as a result, the image is printed.

In the image printing process described above, the image is printed after correcting the image data so that a preferable print image can be obtained. However, since user preferences vary, it is difficult to make corrections that match all user preferences. That said, it is not realistic because individual users need advanced knowledge to set the correction scheme according to their preferences. Therefore, in the image printing process of the present embodiment, the following image correction process is performed, so that each user can easily perform a correction that matches his / her preference.

D. Image correction processing:
As preparation for explaining the image correction processing performed in the image printing processing of the present embodiment,
The image correction that is generally performed will be briefly described. In general, the content of correction to be applied to an image is usually different depending on the object in the image. For example, in the case of an image of a landscape, a vivid and clear image is preferred, so that a process for slightly reducing the brightness is performed in order to increase the contrast and sharpness while mitigating the influence of this. On the other hand, in the case of an image in which a person is photographed, a bright and soft impression image is preferred. Therefore, correction for increasing the brightness and decreasing the sharpness is performed. As described above, the content of the correction applied to the image differs depending on the subject to be photographed. Nevertheless, correction items (that is, brightness, contrast, sharpness, etc.) are usually the same regardless of the subject. Therefore, by defining a correction vector whose components are the basic correction elements of brightness, contrast, and sharpness, the correction contents can be handled together.

FIG. 11 shows a state where a correction vector is defined using three correction coefficients of brightness, contrast, and sharpness as components. Further, by using such a correction vector, it is possible to express the correction content according to the object to be photographed by the correction vector.
FIG. 12 illustrates a correction vector (person correction vector) for an image obtained by photographing a person and a correction vector (landscape correction vector) for an image obtained by photographing a landscape. As described above, a processing method of correcting a picture based on a correction vector set according to a shooting target to obtain a preferable image according to the shooting target has been used in recent image printing apparatuses. I came. In the image correction processing of this embodiment, by further developing such image correction, it is possible to print a more preferable image while flexibly responding to differences in user preferences.

FIG. 13 is a flowchart showing the flow of image correction processing of this embodiment. As shown in this flowchart, in the image correction process, first, a process of calculating a “person image degree” is performed (step S200). Here, the “person image degree” is a numerical value of how much a person is reflected in the image. For example, the ratio of the area of the portion where the person is captured to the entire image is represented by the person image. Can be used as a degree. In order to calculate such a person image degree, for example, a skin-colored part is searched from the image data, an area is obtained by assuming that the person is reflected in the part, and the ratio of the area to the entire image Can be taken as the degree of person image.

Alternatively, in addition to a method of using a simple area ratio as a person image degree, a portion in which a person is reflected is detected by the following method, taking into consideration the certainty (accuracy) at the time of detection. The person image degree can also be calculated. That is, first, the contour portion of the object is extracted from the image data. When extracting the contour, remove the noise using a two-dimensional filter such as a median filter, or enhance the contrast and edges, and then binarize. Extract as Next, the extracted contours that are apparently not human faces are excluded. For example, an object having a large proportion of straight lines in the extracted contour is highly likely to be a so-called artifact. In this way, objects that can be clearly judged not to be human faces are excluded, and the remaining objects are extracted from the contour shape such as “eyes”, “mouth”, “nasal muscles”, and other suspicious objects. Go. Of course, since it cannot be determined that the extracted object is surely “eyes”, “mouth”, or “nose muscle”, the probability is numerically expressed as accuracy. Next, the extracted object is evaluated as follows. If the extracted objects are really “eyes”, “mouth”, “nose muscles”, etc., they should be in a predetermined positional relationship with each other. For example, when an object that seems to be “mouth” is extracted, an object that seems to be “eyes” or “nasal muscles” (or an object that can be clearly determined to be “eyes” or “nasal muscles”) exists above For example, it can be determined that the extracted object is a “mouth”. Similarly, regarding an object that seems to be an “eye”, if it is really an “eye”, an object that seems to be an “eye” in the same direction is likely to exist in the vicinity. In this way, "eye", "mouth" from the contour
By extracting an object that seems to be “nasal muscles” and the like, and considering the mutual positional relationship among the extracted objects, “eyes”, “mouth”, “nasal muscles” and the like can be specified. When facial components such as “eyes”, “mouth”, and “nose muscles” are detected, the contour portion of the face including them is detected. In addition, the “face-likeness” in consideration of the positional relationship of “eyes”, “mouth”, “nose muscles”, etc. is numerically expressed as the accuracy. In this way, after detecting the portion of the image in which the human face is reflected, the area of the detected face portion is calculated. Furthermore, the weighting coefficient is determined based on the accuracy when the face components such as “ear”, “mouth”, and “nose muscle” are detected, and the accuracy when the face is detected. Finally, the face image area previously calculated is multiplied by this weighting coefficient, and the obtained numerical value is used as the person image degree. In this way, the person image degree can be calculated as a numerical value including the probability of person detection.

Although the person image degree can be obtained by these various methods, in this embodiment, the person image degree is calculated in a state normalized to a value from 0 to 100. That is,
It is assumed that an image for which it is determined that a person is not captured at all is calculated as a person image degree of 0, and an image that is determined to include only a person for the entire image is calculated as a person image level of 100.

After calculating the person image degree as described above, next, a process of calculating how much landscape is reflected in the image (landscape image degree) is performed (step S202). Various methods have been proposed for this calculation method, but can be simply performed as follows. That is,
In the image data, if the sky blue part continues for a certain amount or more, the part can be estimated as sky. Similarly, if the green part continues for a certain amount or more, the part is a mountain or trees. Can be estimated as a part of the image. Therefore, by calculating the ratio of these portions to the entire image, the landscape image degree can be obtained. It is assumed that the landscape image level is also normalized to a value from 0 to 100, like the person image level.

In this way, if the person image degree and the landscape image degree are obtained, the correction vector (
The correction vector corresponding to the image is obtained by adding the correction vector for the landscape image (see FIG. 12A) and the correction vector for the landscape image (see FIG. 12B) by the ratio of the person image level and the landscape image level. It is possible. However, in the image correction processing of the present embodiment, the correction vector is not obtained in this way, but by referring to the user correction information LUT in which information related to user preferences is stored (step S204), the following is performed. Thus, a correction vector reflecting the user's preference is calculated. The user correction information LUT is stored in the ROM of the control circuit 260 in the form of a lookup table.

FIG. 14 is an explanatory diagram illustrating user modification information LUT. User modification information LUT
Stores the person image degree and landscape image degree, and the corresponding person degree correction value and landscape degree correction value for images printed by the user in the past. Here, the person image degree and the landscape image degree are values calculated by the method described above. Further, the person degree correction value and the landscape degree correction value are values obtained by correcting the calculated person image degree and landscape image degree so that the user has a favorite image. In this way, the user correction information LUT stores user preferences in the form of a combination of a person image level and a landscape image level and a correction value corresponding to the combination of the person image level and the landscape image level.

The user's preferences can be expressed in this format for the following reasons. For example, in the case of an image of a person against a landscape, if the person is only small,
In some cases, people ignore and prefer corrections that emphasize landscapes. In addition, if the person and the landscape are half-way, there is a case where a correction that emphasizes the person is preferred over the landscape. In this way, the user's preference appears in which part of the image is important. Then, if the point of which part of the image is important is regarded as the person degree or the landscape degree, the user's preference can be expressed as a correction value for the person image degree and the landscape image degree calculated from the image. In addition, as shown in the example above, the user's preference is to focus on the landscape when the landscape is more than the person, and focus on the person if the landscape and the person are about halfway. The ratio varies depending on the ratio of the person and the landscape, that is, the combination of the person image degree and the landscape image degree of the image. In other words,
The user's preference actually depends on the combination of the person image degree and the landscape image degree of the image. Therefore, the correction value, which is a value representing the user preference, is the person image degree and the landscape image degree at that time. Must be remembered along with the combination. For this reason, the user correction information LUT stores a correction value and a combination of a person image level and a landscape image level in an associated form.

As described above, the user correction information LUT stores the person image degree and landscape image degree of images printed by the user in the past, and information corrected by the user according to his / her preference. Therefore, if the user has printed an image having the same person image degree and landscape image degree as the current image in the past, the user correction information at that time can be used as it is to match the user's preference. However, the user does not always print images having the same person image level and landscape image level in the past. Therefore, in such a case, it is considered to select and use the optimum information from the stored user correction information.

FIG. 15 is an explanatory diagram showing a method for selecting user modification information to be referred to from the user modification information LUT. The horizontal axis of the graph is the person image degree, and the vertical axis is the landscape image degree. A in the figure
The point represented by is the current image, the person image degree is a, and the landscape image degree is b. On the other hand, points indicated by numerals “1” to “4” in the figure are images stored in the user correction information LUT (see FIG. 14). As described above, the user's preference depends on the combination of the person image level and the landscape image level (that is, the position on the plane of the graph in FIG. 15) that is the content shown in the image. Therefore, if a point closest to the current image (A in the figure) is selected and the information is referred to, the current image can be corrected closer to the user's preference. In the example of FIG. 15, the closest “1” is selected. Once the user modification information to be referenced is decided,
This is read from the user correction information LUT. Next, based on the read information, the person image level and the landscape image level of the image to be printed are corrected as follows.

FIG. 16 is an explanatory diagram showing a method of correcting the person image level and the landscape image level based on the read user correction information. As shown in FIG. 16, the person image degree is corrected by adding the person degree correction value of the user correction information to the person image degree of the image to be printed at a constant ratio k. Here, the reason why the correction value read from the LUT is added with a certain ratio is as follows. In other words, as described above, the read user correction information is for an image having a person image level and a landscape image level closest to the current image,
It is not appropriate to use this correction value as it is because it is not exactly the same. Therefore, the correction value is adjusted by adding the ratio k.

FIG. 17 is an explanatory diagram illustrating a method for calculating the ratio k in consideration of the correction value read from the LUT. In this figure, S is the distance on the plane of the landscape image degree and the person image degree as shown in FIG. For example, if the ratio k is calculated by the method illustrated in FIG. 17A, the ratio k is small when the distance S is large, and the ratio k is large when the distance S is small. Therefore, when the difference between the current image and the past image is large, the past information is not so much affected. When the difference is small, the past information can be emphasized. . Further, the ratio k can be calculated by a method as shown in FIG. That is, when the distance S between the current image and the past image is a certain value or more, the ratio k is set to “0”. . In this way, if the current image and the past image are more than a certain distance apart, the past information is not used at all, and if it is less than a certain amount, the current image is considered the same as the past image. The same correction as the past image can be made. Using the ratio k calculated by such a method, the corrected person image degree (displayed as X in the figure) and the corrected landscape image degree (displayed as Y in the figure) are calculated according to the mathematical formula shown in FIG. Next, a correction vector is determined using the obtained corrected person image degree and corrected landscape image degree (step S206).

FIG. 18 is an explanatory diagram showing a method for determining a correction vector corresponding to an image. In the figure, X and Y are the corrected person image degree and the corrected landscape image degree calculated previously (see FIG. 16).
. As shown here, a correction vector for a person (see FIG. 12 (a)) and a correction vector for a landscape (see FIG. 12 (b)) are multiplied by a weighting factor and added together. A correction vector is determined. Since the weighting coefficient to be multiplied is a person image degree and a landscape image degree corrected using information when the user has printed in the past, the obtained correction vector reflects the user's preference. In this way, it is possible to calculate the correction vector reflecting the user's preference by correcting the person image degree and the landscape image degree using the information of the user correction information LUT and synthesizing the correction vector at the corrected ratio. become.

By using the correction vector obtained in this way, it is possible to perform a correction that matches the user's preference. Therefore, the correction is actually performed and the correction result is confirmed (step S2).
08). In this case, it is assumed that three correction coefficients “lightness correction coefficient”, “contrast correction coefficient”, and “sharpness correction coefficient” are set in the correction vector (see FIG. 11).
The correction processing is performed in order according to the respective correction coefficients. The reason why the correction vector is called a “provisional” correction vector in step S208 shown in the flowchart of FIG. 13 will be described later.

FIG. 19 is a conversion formula for converting image data expressed in RGB display into YCrCb display in order to perform brightness correction processing. In order to perform the brightness correction process, first, after the image data is converted from RGB display to YCrCb display according to this equation, the calculated brightness Y value is corrected according to the brightness correction coefficient. In order to correct the Y value, a lightness correction coefficient is simply multiplied by the Y value. After correcting Y in this way, the image data subjected to the brightness correction process can be obtained by performing inverse conversion from YCrCb display to RGB display according to the conversion formula of FIG. Next, a contrast correction process is performed on the image on which the brightness correction process has been performed. There are various methods for the contrast correction processing, but it can be easily corrected using a tone curve.

FIG. 20 is an explanatory view exemplifying contrast correction processing using a tone curve. The horizontal axis of the graph is an input value (R, G, or B value), and the vertical axis is an output value. The tone curve indicated by the solid line is the one before correction, and the output value matches the input value. The tone curve indicated by the broken line is for performing contrast correction processing, and has a larger slope than the tone curve indicated by the solid line. When the input value is converted according to such a tone curve, the change of the output value (after correction) becomes larger than the change of the input value (before correction), and the image is corrected to a more vivid impression. By setting the inclination of the tone curve corresponding to the contrast correction coefficient, it is possible to obtain image data that has been subjected to correction processing according to the contrast correction coefficient.

Following the contrast correction processing, sharpness correction processing is performed. This correction extracts parts where the color tone changes abruptly, such as contours and shadows of the subject, so-called edges, and emphasizes them (when the sharpness correction factor is positive) or makes them inconspicuous (sharpness correction) Correction when the coefficient is negative. The correction that makes the edge inconspicuous can be performed by applying a two-dimensional filter such as a Gaussian filter and performing so-called blur correction.

FIG. 21 is an explanatory diagram illustrating a Gaussian filter having a size of three pixels in the vertical and horizontal directions. As shown in the figure, the Gaussian filter has a weighting factor that is set to a smaller value as the distance from the center increases. When such a two-dimensional filter is applied to image data, the image looks natural. Can be blurred. In addition, the degree of blur can be adjusted by appropriately setting the weighting coefficient of the Gaussian filter. For example, the Gaussian filter shown in FIG. 21B has a larger peripheral weight than the Gaussian filter shown in FIG. By appropriately setting the weighting coefficient according to the sharpness correction coefficient, blur correction corresponding to the sharpness correction coefficient can be performed.

On the other hand, when it is desired to emphasize an edge, the following method is used. That is, a process is performed in which a difference between an image obtained using a two-dimensional filter such as a Gaussian filter and the original image is taken and added to the original image at a constant ratio k. This is a so-called unsharpness mask. Here, by setting the ratio k added to the original image to a value proportional to the sharpness correction coefficient, edge enhancement correction corresponding to the sharpness correction amount can be performed.

In this way, after performing three correction processes of “brightness correction process”, “contrast correction process”, and “sharpness correction process” according to the (provisional) correction vector obtained from the user correction information LUT, the image obtained in this embodiment is used. Are displayed on a screen provided on the operation panel 300 of the printing apparatus 10.

FIG. 22 is an explanatory diagram showing a state in which an image corrected according to the provisional correction vector is displayed on the screen. In this way, the user can check the corrected image on the screen of the operation panel 300. If the displayed image is a favorite image, the user operates the operation panel 300 and issues an instruction to print the image as it is. On the other hand, if the displayed image does not match the user's preference, as shown in FIG. 22, two amounts of “personality” and “scenery” are manipulated to obtain a favorite image. The final correction content is determined as follows. That is, since the correction vector obtained from the person image degree, landscape image degree, and user correction information LUT of the image is based on the contents of correction performed by the user in the past, Although they coincide with each other, they are merely correction vectors calculated by estimation, so that a corrected image is displayed on the screen just in case and the final correction vector is determined by the user. The correction vector obtained from the user correction information LUT is called a “provisional” correction vector, as described above, that the correction vector is tentatively determined to display the correction image on the screen. It's just a matter of things.

When the user confirms the display on the operation panel 300 and operates the “person degree” or “landscape degree” (see FIG. 22), the printing apparatus of the present embodiment recalculates the correction vector according to the following procedure, The corrected image is displayed on the screen of the operation panel 300 again. First, according to the equation shown in FIG.
Recalculate X (corrected person image degree) and Y (corrected landscape image degree). In this calculation, FIG.
As shown in FIG. 3, the amount manipulated by the user is added to the corrected person image degree and the corrected landscape image degree when the provisional correction vector is obtained (see FIG. 18). When the corrected person image degree and the corrected landscape image degree are recalculated in this way, a correction vector is calculated by the mathematical formula shown in FIG. Once the correction vector is obtained, “brightness correction processing” and “sharpness correction processing” are performed accordingly.
“Contrast correction processing” is performed, and the obtained image is displayed on the screen of the operation panel 300 (
(See FIG. 22). In this way, the corrected image reflecting the “personality” and “scenery” operated by the user is displayed, so that the user can confirm on the screen that a desired image has been obtained. If the image is not a favorite image, the “personality” and “scenery” operations may be repeated until the image becomes a favorite image. When it is confirmed that the desired image is obtained, the user issues a print instruction from the operation panel 300. When a print instruction is received from the user in this way, the correction vector at that time is determined as the “final correction vector”.

In this way, by operating the “person degree” and the “landscape degree”, the user can determine a correction vector that gives a favorite image. In addition, since the method of operating “personality” and “scenery” is adopted, even if the user does not have advanced image correction knowledge such as brightness, contrast, sharpness, etc., the correction contents are determined. As a result, the user can easily reflect his / her preference.

In this way, when a correction that matches the user's preference is determined, information about the current image is additionally stored in the user correction information LUT for use in subsequent image printing (step S212). As described above, the information to be stored includes the person image degree and landscape image degree calculated for the image, and values corrected for the person image degree and the landscape image degree (see FIG. 14). In step S208, if the user issues an instruction to print the corrected image based on the temporary correction vector without operating “personality” and “landscape degree”, information is stored in the user correction information LUT. No additional storage is performed (step S210: no)
). This is because in this case, the user's preference can be accurately reflected by the information already stored in the user correction information LUT (the provisional correction vector calculated based on the user correction information LUT is used as the final correction as it is. Therefore, it is not necessary to add new information to the user correction information LUT.

On the other hand, if the user has made corrections (step S210: yes), new information regarding the user's preferences has been obtained, so by storing the information in the user correction information LUT, the next image printing can be performed. In this case, it becomes possible to more accurately reflect user preferences. As described above, if additional storage is performed only when the user makes corrections, the user correction information LUT increases each time printing is performed, and the ROM and CP of the control circuit 260 are increased.
It is preferable because information on user preferences can be appropriately accumulated while avoiding a situation in which U is burdened.

On the other hand, if the ROM or CPU processing capacity of the control circuit 260 has sufficient capacity, the user correction information LU is printed each time printing is performed regardless of whether the user has made corrections.
A method of additionally storing information in T may be adopted. In this case, there are the following advantages over the method of additionally storing only when the user makes corrections. That is, in the method of additionally storing only when the user makes corrections, new information is stored in the user correction information LU.
Since it was added to T, there may be a case where a favorite image cannot be obtained after the addition even if an image that suits the preference was obtained before that. In this regard, with the method of adding information every time printing is performed, correction information when a preferable image is obtained is stored in the user correction information LUT, and therefore, it is possible to obtain a preferable image using the information. Furthermore, a method is adopted in which additional information is stored each time printing is performed until a certain amount of information is accumulated in the user correction information LUT, and additional information is stored as necessary after the certain amount of information is accumulated. May be.

After the information is additionally stored in the user correction information LUT by such a method, the image data is corrected according to the final correction vector (step S214), and the image correction process shown in FIG. 13 is ended.

As described above, in the image correction processing of the present embodiment, the target imaged in the image is digitized and “
It is calculated as “person image degree” and “landscape image degree”. As for user preferences,
A combination of “person image degree” and “landscape image degree” and a correction value for the combination are stored.
In this way, since the “person image degree” and “landscape image degree” obtained by quantifying the “object captured in the image” are determined based on the correction processing, the correction processing is determined based on the standard. Correction can be performed, and the preference can be reflected in the form of which part of the image is important, so that the user can easily obtain a preferable image without knowledge of advanced image correction processing. It becomes possible to correct.

E. Modified example:
In the image printing process described above, two values of the person image degree and the landscape image degree are calculated from the image to be printed, and correction is performed according to the user's preference by correcting these two values. . However, the value extracted from the image is not limited to the person image degree or the landscape image degree. For example, the “night scene image degree” indicating whether or not the night scene is reflected is extracted and the user's preference is extracted. It is also possible to make corrections. Furthermore, it is possible to correct the image by extracting more values from the image. Hereinafter, a description will be given of an image correction process according to a modified example in which three values of “person image degree”, “landscape image degree”, and “night scene image degree” are extracted to perform correction reflecting user's preference.

In the image correction process described above, two values of “person image degree” and “landscape image degree” are extracted from the image, and the user's preference is expressed as a correction value for these values. In view of extracting three values of “image quality”, “landscape image quality” and “night scene image quality”, the user's preference is expressed as a correction value for these three values. Therefore, in the image correction process of the modification, the user correction information LUT that stores user preferences is in the form of a three-dimensional lookup table.

FIG. 24 is an explanatory view exemplifying a user modification information LUT of a modification using three values of “person image degree”, “landscape image degree”, and “night scene image degree”. As shown in FIG. 24, the user correction information LUT of the modified example stores a combination of three values of “person image degree”, “landscape image degree”, and “night scene image degree”, and these correction values. It is a three-dimensional lookup table. In the image correction processing of the modification, after extracting “person image degree”, “landscape image degree”, and “night scene image degree” from the image to be printed, the user's preference is obtained by referring to such user correction information LUT. The correction value according to is determined.

FIG. 25 is an explanatory diagram showing a state in which information for correcting an image is selected with reference to the user correction information LUT of the modification. In the figure, the “person image degree”, “landscape image degree”, and “night scene image degree” extracted from the images are taken on three orthogonal axes, so that the “person image degree” “
“Landscape image degree” and “Night scene image degree” are expressed by coordinate points. The point A shown in the figure is the current image, whereas the points indicated by the numbers “1” to “4” in the figure are images stored in the user correction information LUT. . If the current image (point A) matches one of the coordinate points stored in the user correction information LUT, the correction amount corresponding to the coordinate point is used to meet the user's preference. Correction can be performed. But,
This is rare, and usually the user's preference is selected by selecting the coordinate point closest to the coordinate point of the image to be printed this time from the coordinate points stored in the user correction information LUT. Correction close to is performed. FIG. 25 shows a case where the closest coordinate point “3” is selected. The image information thus selected is referred to as user correction information LU.
By reading from T, the “corrected person image degree”, “corrected landscape image degree”, and “corrected night view image degree” for the image to be printed are calculated.

FIG. 26 is an explanatory diagram showing a method of calculating “corrected person image degree”, “corrected landscape image degree”, and “corrected night view image degree” based on information read from the user correction information LUT of the modification.
The “corrected person image”, “corrected landscape image”, and “corrected night view image” of the image to be printed are
It can be calculated by the same concept as in the image correction process described above. That is, the “person image degree”, “landscape image degree”, and “night scene image degree” extracted from the image to be printed are added to the “person degree correction value”, “landscape degree correction value”, and “night scene degree” read from the user correction information LUT. What is necessary is just to consider "correction value" by the fixed ratio k. Further, the certain ratio k can be calculated by the method illustrated in FIG. In this way, "corrected person image degree""corrected landscape image degree"
If the “corrected night view image degree” is obtained, the correction vector can be calculated in the same manner as the image printing process described above.

FIG. 27 is an explanatory diagram showing a method for calculating a correction vector in the image correction processing according to the modification. The corrected person image degree (denoted as X in the figure), the corrected landscape image degree (denoted as Y in the figure), and the corrected night view image degree (denoted as Z in the figure) calculated by the method described above are read out from the user correction information LUT. Since the value is corrected according to the information, the value reflects the user's preference. By using this value as a weighting factor, the correction vector for reflecting the user's preference can be calculated by adding the correction vector for person, correction vector for landscape, and correction vector for night view. In this way, even when three values of “person image degree”, “landscape image degree”, and “night scene image degree” are used, the combination of these three values and their correction values are used as the user correction information LU.
By storing in T, it is possible to obtain “corrected person image degree”, “corrected landscape image degree”, and “corrected night view image degree”, and by using these values, a correction vector reflecting the user's preference is calculated. It becomes possible to do. When the correction vector is obtained in this way, the image is actually corrected according to the correction vector, and the user confirms this on the operation panel 300 and performs the process of determining the final correction content.

FIG. 28 is an explanatory diagram showing a state in which a corrected image is displayed on the operation panel 300 in the modified example. The user checks the image displayed on the operation panel 300, and if the image does not match the preference, the “personality”, “scenery”, “nightscape” is the same as the image correction process described above (see FIG. 22). By adjusting the three values, the correction contents can be changed so that a desired image is obtained. When the user adjusts the “personality”, “scenery”, and “nightscape”, the weighting coefficient is corrected according to the formula shown in FIG. 29, and the correction vector is calculated again (see FIG. 27).
A corrected image is displayed. In this way, the user can confirm the final correction content while confirming the correction image on the screen of the operation panel 300. Based on the correction content thus determined, correction processing that matches the user's preference is performed.

In the modification described above, in addition to “person image degree” and “landscape image degree”, “night scene image degree”
By extracting, it is possible to correct the user's preference more appropriately and correct it to a preferable image. For example, even if the values of “Portrait Image Level” and “Landscape Image Level” are the same,
Depending on whether or not the image is a night view, the user's preference such as whether to emphasize a person or a landscape may differ. Alternatively, for an image showing a night view, an image different from a person or landscape may be preferred. Even in such a case, by extracting “night scene image degree” in addition to “person image degree” and “landscape image degree”, it becomes possible to reflect the user's preference in the user correction information LUT. It is possible to correct the image appropriately according to the user's preference.

Of course, this effect is not limited to the case where the “night view image degree” is extracted.
For example, “plant image degree” or “underwater image degree” may be extracted instead of “night scene image degree”. Furthermore, in addition to “person image degree”, “landscape image degree”, and “night scene image degree”, it is also possible to extract “plant image degree”, “underwater image degree”, and the like. Even if the value to be extracted increases, it is possible to cope with the problem by simply increasing the dimension of the user correction information LUT, and the processing for correcting the image is not significantly complicated.

Although the printing apparatus of the present embodiment has been described above, the present invention is not limited to all the above-described embodiments, and can be implemented in various modes without departing from the scope of the present invention.

It is explanatory drawing which showed the outline | summary of the printing apparatus of a present Example. It is a perspective view which shows the external appearance shape of the printing apparatus of a present Example. FIG. 6 is an explanatory diagram showing a state in which a document table cover provided on the upper part of the printing apparatus is opened to read a document image. It is the perspective view which showed a mode that the front side of the scanner part was lifted and rotated. It is explanatory drawing which showed notionally the internal structure of the printing apparatus of a present Example. It is explanatory drawing which showed a mode that the several nozzle which discharges an ink drop to the ink discharge head of each color was formed. 4 is a flowchart illustrating a flow of processing (image printing processing) in which a printer driver executes printing. It is explanatory drawing which showed notionally the color conversion table referred for a color conversion process. It is explanatory drawing which expanded and illustrated a part of dither matrix. It is explanatory drawing which showed notionally the mode that the presence or absence of dot formation was judged for every pixel, referring a dither matrix. It is explanatory drawing which showed the correction vector used by the image correction process of a present Example. It is explanatory drawing which illustrated the correction vector for persons, and the correction vector for scenery. It is a flowchart which shows the flow of the image correction process of a present Example. It is explanatory drawing which illustrated user correction information LUT. It is explanatory drawing which showed the method of selecting the user correction information referred from user correction information LUT. It is explanatory drawing which showed the method of correcting a person image degree and a landscape image degree based on the read user correction information. It is explanatory drawing which illustrated the calculation method of the ratio k which considers the correction value read from user correction information LUT. It is explanatory drawing which showed the method of determining a correction vector. This is a conversion formula for converting image data expressed in RGB display into YCrCb display in order to perform brightness correction processing. It is explanatory drawing which illustrated the contrast correction process by a tone curve. It is explanatory drawing which illustrated the Gaussian filter which has a magnitude | size for vertical and horizontal 3 pixels. It is explanatory drawing which showed a mode that the image correct | amended according to the provisional correction vector was displayed on the screen. It is explanatory drawing which showed the method of changing "corrected person image degree" and "corrected landscape image degree" according to the value which the user correct | amended. It is explanatory drawing which illustrated user modification information LUT of the modification using three values of "person image degree", "landscape image degree", and "night view image degree". It is explanatory drawing which shows a mode that the information for correct | amending an image is selected with reference to the user correction information LUT of a modification. It is explanatory drawing which showed the method of calculating "corrected person image degree", "corrected landscape image degree", and "corrected night view image degree" based on the information read from the user correction information LUT of a modification. It is explanatory drawing which showed the method of calculating a correction vector in the image correction process of a modification. In a modification, it is explanatory drawing which showed a mode that the correction image by a temporary correction vector was displayed on the screen. FIG. 11 is an explanatory diagram showing a method of changing “corrected person image degree”, “corrected landscape image degree”, and “corrected night view image degree” according to values corrected by a user in a modified example.

Explanation of symbols

DESCRIPTION OF SYMBOLS 10 ... Printing apparatus, 12 ... Ink discharge head, 100 ... Scanner part,
200: Printer unit, 240: Print carriage, 241: Print head,
242 ... Ink cartridge, 243 ... Ink cartridge,
260 ... control circuit, 300 ... operation panel

Claims (8)

An image processing apparatus that analyzes image data generated by copying a shooting target, classifies the image data into a plurality of predetermined classes based on the shooting target, and then performs correction according to the class. ,
Correction content storage means for storing correction content to be added to the image data for each category;
A degree-of-match detection means for detecting a degree of match for each classification of the image data by analyzing the image data;
A degree-of-match correction means for correcting the degree of match of each detected category;
An image processing apparatus comprising: image data correction means for correcting the image data by reflecting the correction content stored for each category at a rate corresponding to the corrected degree of match. The image processing apparatus according to claim 1,
A degree-of-matching correction table storage means for storing a degree-of-matching correction table in which a set of matching levels for each category is associated with a correction amount to be added to each degree of matching;
The degree-of-match correction means is an image processing apparatus that, after determining the correction amount by referring to the degree-of-match correction table based on the degree of match for each classification of the image data, corrects the degree of match for each classification. . The image processing apparatus according to claim 2,
Corrected image output means for outputting an image based on the corrected image data;
A correction amount changing means for changing the correction amount added to the degree of match for each category based on the output image;
An image comprising: a degree-of-match correction table reflecting means for detecting the degree of matching for each category detected from the image data and the amount of correction after the change to each degree of matching, and reflecting the detected amount in the degree-of-matching correction table Processing equipment. Print that analyzes the image data generated by copying the object to be photographed, classifies the image data into a plurality of predetermined classes based on the object to be photographed, and then prints the image with corrections according to the classes A device,
Correction content storage means for storing correction content to be added to the image data for each category;
A degree-of-match detection means for detecting a degree of match for each classification of the image data by analyzing the image data;
A degree-of-match correction means for correcting the degree of match of each detected category;
Image data correction means for correcting the image data by reflecting the correction content stored for each category at a rate corresponding to the corrected degree of match;
An image printing unit that prints an image based on the corrected image data. An image processing method for analyzing image data generated by copying a shooting target, classifying the image data into a plurality of predetermined classes based on the shooting target, and then performing correction according to the classification ,
A first step of storing correction contents to be added to the image data for each category;
A second step of analyzing the image data to detect a degree of matching of the image data with respect to each category;
A third step of correcting the degree of matching of each detected category;
And a fourth step of correcting the image data by reflecting the correction content stored for each category at a rate corresponding to the corrected degree of match. Print that analyzes the image data generated by copying the object to be photographed, classifies the image data into a plurality of predetermined classes based on the object to be photographed, and then prints the image with corrections according to the classes A method,
(A) storing correction contents to be added to the image data for each category;
Analyzing the image data to detect a degree of match for each classification of the image data (B);
A step (C) of correcting the degree of matching of each detected category;
A step (D) of correcting the image data by reflecting the correction content stored for each category in a proportion corresponding to the corrected degree of match;
And a step (E) of printing an image based on the corrected image data. Using a computer, a method for classifying the image data into a plurality of predetermined classes based on the shooting target by analyzing the image data generated by copying the shooting target, and then performing correction according to the classification A program for realizing
A first function storing correction contents to be added to the image data for each of the categories;
A second function of detecting the degree of match for each classification of the image data by analyzing the image data;
A third function for correcting the degree of match of each detected category;
A program for realizing, using a computer, a fourth function for correcting the image data by reflecting the correction content stored for each category at a rate corresponding to the corrected degree of match. A method of printing image after analyzing image data generated by copying a shooting target and classifying the image data into a plurality of predetermined classes based on the shooting target and then applying correction according to the classification Is a program for realizing using a computer,
A function (A) for storing correction contents to be added to the image data for each category;
A function (B) for detecting the degree of match of the image data with respect to each category by analyzing the image data;
A function (C) for correcting the degree of matching of each detected category;
A function (D) for correcting the image data by reflecting the correction content stored for each category at a rate corresponding to the corrected degree of match;
A program for realizing, using a computer, a function (E) for printing an image based on the corrected image data.

Images