JP2007142619A - Image processing apparatus, image adjustment method, embedding strength adjustment method, and program - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To stably restore information embedded to a photo and a picture or the like at all times. <P>SOLUTION: A pattern generating section 14 generates an embedded pattern on the basis of a pattern size from a size entry section 11, a pattern attenuation rate from an attenuation rate entry section 12, and the embedding strength from a strength entry section 13. On the other hand, an image input section 15 stores an image to an image storage section 16. Further, an embedded information coding section 18 codes information from an embedded information entry section 17, a pattern selection section 20 selects an embedded pattern corresponding to the coded information, a pattern superimposing section 21 superimposes the embedded pattern to a position of an image in the image storage section 16 designated by an embedded position control section 19, and an image output section 22 outputs the image after the superimposition. In this case, an image adjustment section 25 adjusts the image on the basis of the gradation characteristic of an output apparatus received by a gradation characteristic input section 23 and a density distribution of an image generated by a density distribution generating section 24. <P>COPYRIGHT: (C)2007,JPO&INPIT

Description

  The present invention relates to an image processing apparatus that embeds information in an image expressed in multiple gradations, and more particularly to an image processing apparatus that embeds information by changing pixel values in the image.

In recent years, it has been widely practiced to add product information with barcodes or QR codes to increase the efficiency of sales and management of products. However, in many cases, a product label originally designed neatly using a photograph or a picture is attached to a package of the product. Therefore, when a barcode or the like is attached separately from the product label, some inconvenience occurs.
First, in spite of the fact that the product label is originally attached, attaching a barcode or the like in addition to this is an extra effort, which leads to an increase in cost. In addition, sticking a barcode or the like on the product label lowers the value of the product label, which may affect sales.

  Under such circumstances, MIG (Micro Gradation) has been studied as a technique for embedding information in a photo or picture such as a product label while keeping the image quality high (for example, Patent Document 1). 2). In Patent Documents 1 and 2, square blocks are divided into four equal parts, and information is recorded by the difference in density between diagonals. In addition, information is embedded at a high density by providing a density gradient such that a peak appears at the center value of the block.

Japanese Unexamined Patent Publication No. 2004-140764 (9th, 10th pages, FIGS. 1 and 2) JP 2004-147253 A (pages 10, 11 and 1, 2)

As described above, in Patent Documents 1 and 2, information is embedded by providing a difference in density between square block regions. Therefore, when restoring the information, it is necessary to be able to recognize this difference in density on the printed paper. However, in the so-called highlight portion and shadow portion of an image, since the gradation characteristics of the output device are not linear, it is normal that the difference between the image signals does not directly become the difference in the density of the output image. Since such gradation characteristics are also different for each output device, in order to stably restore information embedded in photos and pictures, the image density is adjusted in consideration of the gradation characteristics of the output device. Or adjusting the information embedding method.
However, Patent Documents 1 and 2 have a problem in that the embedded information cannot be stably restored because the gradation characteristics of the output device are not taken into consideration.

The present invention has been made to solve the technical problems as described above, and an object thereof is to make it possible to always stably restore information embedded in photos, pictures, and the like. .
Another object of the present invention is to make it possible to restore the information stably even if the image in which the information is embedded is output by an output device having any gradation characteristic.

For this purpose, in the present invention, the embedding strength of the image or information embedded in the image is adjusted according to the gradation characteristics of the output device. In other words, the image processing apparatus of the present invention performs information embedding in an image by changing the pixel value in the image according to the information, and the level of the apparatus that outputs the image in which the information is embedded. An acquisition unit that acquires a tone characteristic, and an adjustment unit that adjusts a pixel value in the image or a degree of change of the pixel value (embedding intensity) based on the gradation characteristic acquired by the acquisition unit.
Here, as the adjustment of the pixel value, by analyzing the gradation characteristics, a gradation range (for example, a highlight portion or a shadow portion) in which the change of the pixel value is difficult to be recognized is obtained, and each pixel in the image is determined. It is conceivable to reduce the dynamic range of the image so that the value is not included in the gradation range.
In addition, as an adjustment of the degree of change of the pixel value, by analyzing the gradation characteristics, a gradation range where the change of the pixel value is difficult to recognize mechanically (for example, a highlight part or a shadow part) is obtained and information is obtained. It is conceivable that the degree of change of the pixel value is increased so that each pixel value in the image in which is embedded is not included in the gradation range.

  The present invention can also be understood as a method for adjusting an image. In that case, the image adjustment method of the present invention adjusts the image when the information is embedded in the image by changing the pixel value in the image according to the information, and the information is embedded. Determining a gradation range (for example, a portion other than a highlight part or a shadow part) that can mechanically recognize a change in pixel value in the image based on the gradation characteristics of the device that outputs the image; And changing the dynamic range of the image so that the predetermined pixel value is included in the gradation range when the predetermined pixel value is not included in the gradation range.

  Furthermore, the present invention can be understood as a method for adjusting the embedding strength. In that case, the embedding strength adjustment method of the present invention performs embedding of information in an image by changing the pixel value in the image according to the information, and the embedding strength that is the degree of change of the pixel value is set. Based on the gradation characteristics of the device that outputs the image in which the information is embedded, the gradation range in which the change in the pixel value in the image can be recognized mechanically (for example, the highlight portion or the shadow portion) If the value after changing the specified pixel value in the image is not included in the gradation range, the embedding strength is set so that the changed value is included in the gradation range. And changing steps.

  On the other hand, the present invention can also be understood as a program that causes a computer to execute image adjustment processing. In that case, the program of the present invention causes the computer to realize a function of adjusting the image when the information is embedded in the image by changing the pixel value in the image according to the information. Based on the gradation characteristics of the device that outputs the image with the information embedded in the computer, the gradation range in which the change of the pixel value in the image can be recognized mechanically (for example, the part other than the highlight part and the shadow part) ) And a function of changing the dynamic range of the image so that the predetermined pixel value is included in the gradation range when the predetermined pixel value in the image is not included in the gradation range. It is what is realized.

  The present invention can also be understood as a program that causes a computer to execute an embedding strength adjustment process. In that case, the program of the present invention has a function of adjusting the embedding strength which is the degree of change of the pixel value when embedding information in the image by changing the pixel value in the image according to the information. Is realized by a computer, and based on the gradation characteristics of a device that outputs an image in which information is embedded in a computer, a gradation range in which a change in pixel value in the image can be mechanically recognized (for example, If the value after changing the specified pixel value in the image is not included in the gradation range, the value after the change is included in the gradation range. The function to change the embedding strength is included so as to be included.

  According to the present invention, it is possible to always stably restore information embedded in a photograph or picture.

The best mode for carrying out the present invention (hereinafter referred to as “embodiment”) will be described below in detail with reference to the accompanying drawings.
[First Embodiment]
FIG. 1 is a diagram showing a configuration example of an image processing apparatus according to the first embodiment of the present invention.
As illustrated, the image processing apparatus according to the present embodiment includes a size input unit 11, an attenuation rate input unit 12, an intensity input unit 13, a pattern creation unit 14, an image input unit 15, and an image storage unit 16. An embedded information input unit 17, an embedded information encoding unit 18, an embedded position control unit 19, a pattern selection unit 20, a pattern superposition unit 21, an image output unit 22, and a gradation characteristic input unit. 23, a density distribution generation unit 24, and an image adjustment unit 25.

The size input unit 11 inputs a pattern size designated by the user from a not-shown PC (Personal Computer), an operation panel, or the like. The attenuation factor input unit 12 inputs a pattern attenuation factor instructed by the user from a PC or an operation panel (not shown). The strength input unit 13 inputs an embedding strength instructed by the user from a PC or an operation panel (not shown). The pattern size, pattern attenuation rate, and embedding strength will be described later in detail. Moreover, when using the preset value as such information, the structure which does not provide each input part may be sufficient.
The pattern creating unit 14 creates two patterns based on the input pattern size, pattern attenuation rate, and embedding strength. Details of the pattern creating unit 14 will be described later.

The image input unit 15 inputs an image to be embedded with information. As an image input method here, a mode in which an image is input from an external device via a communication line, a mode in which an image is input from an application program operating on the own device, a mode in which a file specified by the user is opened and input is considered. It is done. The input image is an image expressed in multiple gradations, and may be an image created by a PC (not shown), or a natural image or CG (Computer Graphics) input by a digital camera or scanner. There may be.
The image storage unit 16 is a memory that stores an input image. In some cases, an image of a pattern to be superimposed on this image is stored.

The embedded information input unit 17 inputs information to be embedded in an image from a PC, an operation panel, an application program, etc. (not shown). Here, various information such as a character string, a number, and image data can be considered as information to be embedded in the image.
The embedded information encoding unit 18 converts the information input by the embedded information input unit 17 into a predetermined encoding format, and creates encoded information that is actually embedded in an image. Note that it may be embedded without encoding.
The embedding position control unit 19 designates the embedding position of the encoded information in the image stored in the image storage unit 16 according to a predetermined embedding format.

The pattern selection unit 20 selects one of the two patterns created by the pattern creation unit 14 based on the coding information created by the embedded information coding unit 18.
The pattern superimposing unit 21 adds, for example, the pattern selected by the pattern selecting unit 20 to the image block existing at the address of the image storage unit 16 designated by the embedding position control unit 19 and superimposes the pattern in the image. Embed in. When the value after addition exceeds the maximum value (for example, 255), the value is set to the maximum value (255), and when the value after addition becomes a negative value, the value is set to 0.
The image output unit 22 outputs an image in which information is embedded to an output device such as a printer.

The gradation characteristic input unit 23 acquires gradation characteristics of an output device (printer) that outputs an image in which information is embedded. Here, the gradation characteristic input unit 23 can be grasped as an acquisition unit from the viewpoint of acquiring gradation characteristics. Details of the gradation characteristic input unit 23 will be described later.
The density distribution generation unit 24 analyzes the image stored in the image storage unit 16 and generates a density distribution. Details of the density distribution generation unit 24 will be described later.
The image adjustment unit 25 stores the image stored in the image storage unit 16 based on the gradation characteristics input from the gradation characteristic input unit 23, the density distribution generated by the density distribution generation unit 24, and the embedding strength. Adjust. Here, the image adjusting unit 25 can be grasped as an adjusting unit from the viewpoint of adjusting an image. The detailed operation will be described later, but for example, the dynamic range of the image is changed.

These functions are realized by cooperation between software and hardware resources. That is, a CPU (not shown) of the image processing apparatus includes a size input unit 11, an attenuation rate input unit 12, an intensity input unit 13, a pattern creation unit 14, an image input unit 15, an embedded information input unit 17, and an embedded information encoding unit. 18, a program that realizes the functions of the embedding position control unit 19, the pattern selection unit 20, the pattern superposition unit 21, the image output unit 22, the gradation characteristic input unit 23, the density distribution generation unit 24, and the image adjustment unit 25. For example, these functions are realized in the image processing apparatus by reading into the main memory from an external storage device such as a hard disk.
The configuration example of the image processing apparatus in the present embodiment has been described above. Next, the main components of this configuration example will be described in more detail.

First, the pattern creation unit 14 will be described in detail. The pattern creation unit 14 creates two patterns based on the values input by the size input unit 11, the attenuation rate input unit 12, and the intensity input unit 13. These two patterns have the following characteristics.
When the pixel values corresponding to the two patterns are added, the value is 0 for all the pixels.
In each pattern, 0 is obtained when all pixel values are added.
Each pattern has discontinuous pixel values called two or more edges that pass through the center and have different directions. The direction of the edge can be, for example, a direction along a vertical line and a horizontal line.
Furthermore,
The absolute value of the pixel value of each pattern is the largest at the center and decreases as the distance from the center increases.
It is good to have the characteristics.

  FIG. 2 is an explanatory diagram of an example of a pattern to be embedded. An example of the pattern having the above-described features is as shown in FIG. Here, FIG. 2 (a) is a basic pattern meaning a bit value “1”, and FIG. 2 (b) is a basic pattern meaning a bit value “0”. The formula shown in c) or (d) is multiplied. As a result, for example, patterns as shown in FIGS. 2E and 2F are generated. In FIGS. 2 (e) and 2 (f), for the sake of illustration, the difference in density is indicated by the difference in hatching.

  Here, the size of the basic pattern is set by the size input unit 11. FIG. 2 shows an example in which the pattern size is 8 × 8. 2C and 2D, “C” is the embedding strength (also simply referred to as “strength”) input by the strength input unit 13, and “α” is input by the attenuation rate input unit 12. Pattern attenuation rate. Furthermore, “x” is a coordinate value in the horizontal direction when the center of the pattern is the origin, and “y” is a coordinate value in the vertical direction when the center of the pattern is also the origin.

The features of these patterns are for facilitating the detection while suppressing the influence on the image quality as much as possible.
However, the pattern used in the present embodiment is not limited to the example shown in FIG. 2, and other functions may be used instead of the equations shown in FIGS. 2 (c) and 2 (d), for example. Further, the exponential function portion in these equations may be omitted, or the patterns shown in FIGS. 2A and 2B may be used as they are without using these equations. Furthermore, in the example shown in FIG. 2, the edge direction is set to the vertical / horizontal direction. However, as long as the edge direction coincides with the edge direction at the time of detecting information, various directions such as 45 degree and 135 degree edges can be used. It can be the edge direction.

Next, the gradation characteristic input unit 23 will be described in detail.
First, as a method of obtaining gradation characteristics, it is conceivable to output gradation patches with an output device, read them with an input device, and measure the gradation characteristics. Further, when the gradation characteristic of the output device is already known, or when the gradation characteristic is regularly acquired by the process controller, the gradation characteristic may be used.

FIG. 3 is an explanatory diagram of an example of gradation characteristics. In the figure, the horizontal axis indicates the image signal transmitted to the output device. The vertical axis represents the density of the image actually printed by the output device based on this image signal. FIG. 3 shows gradation characteristics when attention is paid to one of the color components of the image signal, for example, R of R, G, and B. As can be seen from this figure, the relationship between the image signal and the density is not linear between the vicinity of the image signal “0” and the vicinity of the image signal “255”, and the difference between the image signals corresponds to the difference in density. It is not in a state.
Specifically, the density difference does not reflect the image signal difference in the portion where the density value is larger than “Dh” and the portion where the density value is smaller than “Ds”. When this is viewed from the image signal side, the density difference as the difference between the image signals in the portion where the image signal is larger than “H” (highlight portion) and the portion where the image signal is smaller than “S” (shadow portion). Has not been reproduced.
Therefore, in the present embodiment, processing for narrowing the dynamic range of the image is performed so that the pixel value in the portion where information is embedded does not exist in the highlight portion or the shadow portion.

Therefore, in the present embodiment, the concentration distribution generation unit 24 generates a concentration distribution, which will be described.
FIG. 4 is a diagram showing an example of the density distribution generated by the density distribution generating unit 24. As shown in FIG. This can be obtained using a general histogram function, and the maximum values Rmax, Gmax, Bmax and the minimum values Rmin, Gmin, Bmin can be obtained for each of R, G, B.

Thereafter, the image adjustment unit 25 performs a process of narrowing the dynamic range of the image.
FIG. 5 is a flowchart showing the operation of the image adjustment unit 25 at this time. Note that FIG. 5 shows processing for R among R, G, and B image signals, but similar processing is performed for G and B as well.
First, the image adjustment unit 25 receives the gradation characteristic from the gradation characteristic input unit 23, and obtains the boundary value H of the highlight and the boundary value S of the shadow (Step 101). Here, each boundary value can be obtained by analyzing the gradation characteristics shown in FIG. As an analysis method, any method may be adopted. For example, it is evaluated how the ratio of the image signal and the density changes according to the value of the image signal, and how the change can be regarded as linear. Judgment based on whether or not.

Next, the image adjustment unit 25 receives the density distribution from the density distribution generation unit 24, and obtains the maximum value Rmax and the minimum value Rmin for the color component R (step 102).
The image adjustment unit 25 also acquires the intensity C (step 103). Here, although simply expressed as “intensity C”, as described with reference to FIG. 2, when the intensity differs between the center and the peripheral portion of the pattern, the intensity C is considered as a function of the pixel position. Shall. That is, the image of the pattern selected by the pattern selection unit 20 (including information on the embedding position) is stored in the image storage unit 16 via the pattern superimposing unit 21, so that the image adjustment unit 25 stores the image of this pattern. By acquiring, the intensity according to the position of the pixel can be grasped.

Thereafter, the image adjustment unit 25 performs the following processing for each pixel in the image to be embedded.
That is, first, paying attention to a certain pixel, the pixel value R of the R component is acquired (step 104). Then, whether the pixel value R is included in the highlight portion and the pixel is at a position where the intensity C is subtracted (in FIG. 5, “highlight (−)”), the pixel value R is included in the shadow portion. Then, it is determined whether the pixel is at a position where the intensity C is added (in FIG. 5, “shadow (+)”) or none of them (step 105). When the pixel value R is included in the highlight portion, the dynamic range of the image needs to be narrowed in principle, but the pixel of interest is the upper left or lower right region of FIG. 2A and the upper right portion of FIG. Alternatively, if it is in the lower left region, the pixel value (RC) after subtracting the intensity C may not be included in the highlight portion, so it is determined whether or not it is “highlight (−)”. . Similarly, when the pixel value R is included in the shadow portion, it is necessary to narrow the dynamic range of the image in principle, but the pixel of interest is the upper right or lower left region of FIG. 2A, FIG. ) In the upper left or lower right region, the pixel value (R + C) after adding the intensity C may not be included in the shadow part, so it is determined whether or not it is “shadow (+)”. .

As a result, if it is determined that none of them is applicable, no processing is performed and the process proceeds to determination of whether there is another pixel (step 108).
On the other hand, if it is determined that it is “highlight (−)”, it is determined whether or not the value (RC) after the change of the pixel value is lower than the highlight boundary value H (step 106). In this case, it is assumed that there is a difference in density by embedding information with intensity C, and the process proceeds to determination of whether there is another pixel (step 108). As described above, since the intensity C is a function of the pixel position, the intensity C corresponding to the pixel position is also subtracted here.
If it is determined that the value is “shadow (+)”, it is determined whether the value (R + C) after the change of the pixel value exceeds the shadow boundary value S (step 107). Assuming that there is a difference in density by embedding information in C, the process proceeds to determination of whether there is another pixel (step 108). In this case as well, since the intensity C is a function of the pixel position, the intensity C corresponding to the pixel position is added.

On the other hand, for any pixel value, if the determination in step 106 is “No”, or if the determination in step 107 is “No”, the density is determined by embedding information with intensity C. Since there is no difference, the image adjustment unit 25 changes the dynamic range of the image (step 109). Specifically, when there is no difference in density in the highlight portion, the dynamic range is changed so that the maximum value Rmax of the pixel value R is converted to the highlight boundary value H, and the difference in density is detected in the shadow portion. If not, the dynamic range is changed so that the minimum value Rmin of the pixel value R is converted into the shadow boundary value S. Note that the change of the dynamic range here may be performed for the entire image input from the image input unit 15, or may be performed only for a portion of the image in which information is embedded.
Then, the image adjustment unit 25 repeats the processing in steps 104 to 107 until there are no more pixels, and when there are no more pixels (“No” in step 108), the processing ends.

  In the above operation example, it is determined in step 106 whether the highlight portion is removed when the intensity C is subtracted, and in step 107, it is determined whether the shadow portion is removed when the intensity C is added. I did it. However, these determination steps are not provided, and if there is a pixel value included in the highlight part or shadow part in the part to be embedded in the image, the dynamic range is changed and the pixel value is changed to the highlight part or shadow part. It may be excluded.

[Second Embodiment]
FIG. 6 is a diagram illustrating a configuration example of an image processing apparatus according to the second embodiment of the present invention.
As illustrated, the image processing apparatus according to the present embodiment includes a size input unit 11, an attenuation rate input unit 12, an intensity input unit 13, a pattern creation unit 14, an image input unit 15, and an image storage unit 16. An embedded information input unit 17, an embedded information encoding unit 18, an embedded position control unit 19, a pattern selection unit 20, a pattern superposition unit 21, an image output unit 22, and a gradation characteristic input unit. 23 and an intensity adjusting unit 26.
Among these, the size input unit 11, the attenuation rate input unit 12, the intensity input unit 13, the pattern creation unit 14, the image input unit 15, the image storage unit 16, the embedded information input unit 17, the embedded information encoding unit 18, Since the insertion position control unit 19, the pattern selection unit 20, the pattern superimposing unit 21, and the image output unit 22 are the same as those described in the first embodiment, detailed description thereof is omitted.

The gradation characteristic input unit 23 acquires gradation characteristics of an output device (printer) that outputs an image in which information is embedded.
The intensity adjustment unit 26 adjusts the embedding strength input by the intensity input unit 13 based on the gradation characteristics input from the gradation characteristic input unit 23. Here, the strength adjusting unit 26 can be grasped as an adjusting unit from the viewpoint of adjusting the embedding strength. The detailed operation will be described later. For example, the embedding strength is maximized as much as possible.
In this embodiment, since the dynamic range of the image is not changed, the density distribution generation unit 24 is not provided.

These functions are realized by cooperation between software and hardware resources. That is, a CPU (not shown) of the image processing apparatus includes a size input unit 11, an attenuation rate input unit 12, an intensity input unit 13, a pattern creation unit 14, an image input unit 15, an embedded information input unit 17, and an embedded information encoding unit. 18, programs for realizing the functions of the embedding position control unit 19, the pattern selection unit 20, the pattern superposition unit 21, the image output unit 22, the gradation characteristic input unit 23, and the intensity adjustment unit 26 are stored in an external storage such as a hard disk, for example. These functions are realized in the image processing apparatus by reading into the main memory from the apparatus.
The configuration example of the image processing apparatus in the present embodiment has been described above. Next, further explanation will be given on the main components in this configuration example.

First, also in the present embodiment, the pattern creating unit 14 creates two patterns based on values input by the size input unit 11, the attenuation rate input unit 12, and the intensity input unit 13. These two patterns have the characteristics described in the first embodiment, and for example, the patterns shown in FIG. 2 are exemplified.
Further, the gradation characteristic input unit 23 measures the gradation characteristic of the output device, and also acquires the gradation characteristic as shown in FIG. 3 in the present embodiment. Here, since the density difference as the difference of the image signal cannot be reproduced in the portion where the image signal is larger than “H” (highlight portion) and the portion where the image signal is smaller than “S” (shadow portion), this embodiment is performed. In this mode, processing for increasing the embedding strength is performed so that the pixel value after embedding information does not exist in the highlight portion or the shadow portion.

FIG. 7 is a flowchart showing the operation of the intensity adjusting unit 26 at this time. FIG. 7 shows processing for R among R, G, and B image signals, but similar processing is performed for G and B as well.
First, the intensity adjustment unit 26 receives the gradation characteristic from the gradation characteristic input unit 23, and obtains a highlight boundary value H and a shadow boundary value S (step 201). Here, each boundary value can be obtained by analyzing the gradation characteristics shown in FIG. As an analysis method, any method may be adopted. For example, it is evaluated how the ratio of the image signal and the density changes according to the value of the image signal, and how the change can be regarded as linear. Judgment based on whether or not.

  Next, the strength adjusting unit 26 acquires the strength C (step 202). Here, although simply expressed as “intensity C”, as described with reference to FIG. 2, when the intensity differs between the center and the peripheral portion of the pattern, the intensity C is considered as a function of the pixel position. Shall. That is, the image of the pattern selected by the pattern selection unit 20 (including information on the embedding position) is stored in the image storage unit 16 via the pattern superimposing unit 21, so that the image adjustment unit 25 stores the image of this pattern. By acquiring, the intensity according to the position of the pixel can be grasped.

Thereafter, the intensity adjustment unit 26 performs the following processing for each pixel in the image to be embedded.
That is, first, paying attention to a certain pixel, the pixel value R of the R component is acquired (step 203). Then, whether the pixel value R is included in the highlight portion and the pixel is in a position where the intensity C is subtracted (in FIG. 7, “highlight (−)”), the pixel value R is included in the shadow portion. Whether the pixel is at a position where the intensity C is added (denoted as “shadow (+)” in FIG. 7) or not is determined (step 204). When the pixel value R is included in the highlight portion, it is necessary to increase the intensity C in principle, but the pixel of interest is the upper left or lower right region of FIG. 2A, the upper right or the lower portion of FIG. If it is in the lower left region, the pixel value (R−C) after subtracting the intensity C may not be included in the highlight portion, so it is determined whether it is “highlight (−)”. Similarly, when the pixel value R is included in the shadow portion, it is necessary to increase the intensity C in principle, but the pixel of interest is the upper right or lower left region of FIG. 2A, FIG. 2B. In the upper left or lower right region, the pixel value (R + C) after the addition of the intensity C may not be included in the shadow part, so it is determined whether or not it is “shadow (+)”.

As a result, if it is determined that none of them is applicable, no processing is performed and the process proceeds to determination of whether there is another pixel (step 209).
On the other hand, if it is determined that it is “highlight (−)”, it is determined whether the value (RC) after the change of the pixel value is lower than the highlight boundary value H (step 205), and not lower. In this case, the intensity C is increased so that there is a difference in density between the pixel value after the addition of the intensity C and the pixel value after the subtraction of the intensity C. Here, as an example, the intensity C is changed to an arbitrary value equal to or greater than (R−H) (step 206). On the other hand, if the value is lower, it is determined that there is a difference in density by embedding information with intensity C, and the process proceeds to determination of whether there is another pixel (step 209). As described above, since the intensity C is a function of the pixel position, the intensity C corresponding to the pixel position is also subtracted here.

If it is determined that the value is “shadow (+)”, it is determined whether the value (R + C) after the change of the pixel value exceeds the shadow boundary value S (step 207). The intensity C is increased so that there is a difference in density between the pixel value after addition of C and the pixel value after subtraction of intensity C. Here, as an example, the strength C is changed to an arbitrary value equal to or greater than (S−R) (step 208). On the other hand, if it exceeds, it is determined that there is a difference in density by embedding information with intensity C, and the process proceeds to determination of whether there is another pixel (step 209). In this case as well, since the intensity C is a function of the pixel position, the intensity C corresponding to the pixel position is added.
Then, the intensity adjustment unit 26 repeats the processing in steps 203 to 208 until there are no more pixels, and ends when there are no more pixels (“No” in step 209).

  In the above operation example, the intensity C is set for each pixel. However, a common intensity C may be set for at least a portion where information is embedded in the image input from the image input unit 15.

  As described above, in this embodiment, the dynamic range of the image is narrowed or the information embedding strength is increased in accordance with the gradation characteristics of the output device. Thereby, when embedding information in an image is performed by changing a pixel value in the image, it is possible to stably restore the embedded information.

1 is a block diagram illustrating a configuration example of an image processing device according to a first embodiment of the present invention. It is the figure which showed an example of the embedding pattern used in the 1st and 2nd embodiment of this invention. It is the figure which showed an example of the gradation characteristic acquired in the 1st and 2nd embodiment of this invention. It is the figure which showed an example of the density distribution acquired in the 1st Embodiment of this invention. 3 is a flowchart illustrating an operation of an image adjustment unit in the image processing apparatus according to the first embodiment of the present invention. It is the block diagram which showed the structural example of the image processing apparatus in the 2nd Embodiment of this invention. It is the flowchart which showed operation | movement of the intensity | strength adjustment part in the image processing apparatus of the 2nd Embodiment of this invention.

Explanation of symbols

DESCRIPTION OF SYMBOLS 11 ... Size input part, 12 ... Attenuation rate input part, 13 ... Intensity input part, 14 ... Pattern creation part, 15 ... Image input part, 16 ... Image storage part, 17 ... Embedded information input part, 18 ... Embedded information Encoding unit, 19 ... Embedded position control unit, 20 ... Pattern selection unit, 21 ... Pattern superposition unit, 22 ... Image output unit, 23 ... Tone characteristic input unit, 24 ... Density distribution generation unit, 25 ... Image adjustment unit , 26 ... Strength adjusting section

Claims (10)

An image processing apparatus for embedding information in an image by changing a pixel value in the image according to the information,
Acquisition means for acquiring a gradation characteristic of a device that outputs the image in which the information is embedded;
An image processing apparatus comprising: an adjustment unit that adjusts a pixel value in the image or a degree of change of the pixel value based on the gradation characteristic acquired by the acquisition unit.   The adjusting means analyzes the gradation characteristics to obtain a gradation range in which the change of the pixel value is difficult to recognize mechanically, so that each pixel value in the image is not included in the gradation range. The image processing apparatus according to claim 1, wherein the dynamic range of the image is narrowed.   The adjusting means analyzes the gradation characteristics to obtain a gradation range in which the change of the pixel value is difficult to recognize mechanically, and each pixel value in the image in which the information is embedded is represented by the gradation range. The image processing apparatus according to claim 1, wherein the dynamic range of the image is narrowed so as not to be included in the image.   The adjusting unit analyzes the gradation characteristics to obtain a gradation range in which it is difficult to mechanically recognize the change in the pixel value, and each pixel value in the image in which the information is embedded corresponds to the gradation range. The image processing apparatus according to claim 1, wherein the degree of change of the pixel value is increased so as not to be included in the image. An image adjustment method for adjusting an image when embedding information in the image by changing a pixel value in the image according to the information,
Obtaining a gradation range capable of mechanically recognizing a change in a pixel value in the image based on gradation characteristics of a device that outputs the image in which the information is embedded;
Changing the dynamic range of the image so that the predetermined pixel value is included in the gradation range when the predetermined pixel value in the image is not included in the gradation range. A characteristic image adjustment method.   6. The image adjustment method according to claim 5, wherein, in the step of changing, the dynamic range of the image is not changed when the value after the change of the predetermined pixel value is included in the gradation range. . In embedding information in an image by changing the pixel value in the image according to the information, an embedding strength adjustment method for adjusting the embedding strength, which is the degree of change of the pixel value,
Obtaining a gradation range capable of mechanically recognizing a change in a pixel value in the image based on gradation characteristics of a device that outputs the image in which the information is embedded;
A step of changing the embedding strength so that the changed value is included in the gradation range when the changed value of the predetermined pixel value in the image is not included in the gradation range; A method for adjusting embedding strength, comprising: A program for causing a computer to realize a function of adjusting the image when embedding information in the image by changing a pixel value in the image according to the information,
In the computer,
A function for obtaining a gradation range capable of mechanically recognizing a change in a pixel value in the image based on a gradation characteristic of a device that outputs the image in which the information is embedded;
A program for realizing a function of changing a dynamic range of an image so that the predetermined pixel value is included in the gradation range when the predetermined pixel value in the image is not included in the gradation range. .   9. The program according to claim 8, wherein the changing function does not change the dynamic range of the image when the value after the change of the predetermined pixel value is included in the gradation range. A program for causing a computer to implement a function of adjusting the embedding strength, which is the degree of change of the pixel value, when embedding information in the image by changing the pixel value in the image according to the information. ,
In the computer,
A function for obtaining a gradation range capable of mechanically recognizing a change in a pixel value in the image based on a gradation characteristic of a device that outputs the image in which the information is embedded;
A function of changing the embedding strength so that a value after the change of a predetermined pixel value in the image is not included in the gradation range so that the value after the change is included in the gradation range; Program to be realized.

Images