JP2000013763A - Device and method for processing picture data and device and method for recording - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a device and a method for processing picture data with high detection accuracy of an evaluation value to detect a watermark which is added to the picture data and a device and a method for recording. SOLUTION: A watermark detector 2 is provided with a watermark pattern holding memory 3 to output a pattern of the watermark, a differential calculator 4 to calculate a differential value of pixel values between inputted picture data and neighboring pixels, an evaluation value calculator 5 to calculate the evaluation value based on the pattern of the watermark taken out from the watermark pattern holding memory 3 and the differential value and an evaluation value comparator 6 to detect the watermark based on the evaluation value.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an image data processing for adding information accompanying specific image data (still image or moving image sequence) to the image data and detecting the accompanying information during reproduction. The present invention relates to an apparatus and method, and a recording apparatus and method, and more particularly, to an image data processing apparatus and method for detecting accompanying information added to digital image data at the time of reproduction, and a recording apparatus and method.

[0002]

2. Description of the Related Art There is a technique for adding information accompanying specific image data (a still image or a moving image sequence) to the image data and detecting and using the additional information at the time of reproduction. A typical example of this is the addition of copyright information.

[0003] When an unspecified user can use specific image data, in order for a person who has a copyright to the image to claim that right, the copyright information must be stored in advance in the image data. It needs to be added inside. By adding the copyright information, when the copyright information for which the image data should not be displayed is detected in the processing procedure of the image reproducing apparatus or the reproducing method, the image data is displayed. It is possible to take countermeasures such as the absence.

[0004] The addition or detection of the above-mentioned copyright information is often used at present to prevent unauthorized copying of video tapes. Recently, there are many shops that rent videotapes,
If many users illegally copy and enjoy a videotape borrowed from a store at a low price, damage to the owner of the videotape and the store that rents the videotape is enormous.

[0005] Since image data is recorded on a video tape in an analog manner, image quality may be degraded when copying is performed. Therefore, when copying is repeated a plurality of times, it is very difficult to maintain the originally held image quality.

On the other hand, in digitally recording and reproducing devices and the like which are becoming more and more popular recently, the damage due to unauthorized copying is even greater. In a device or the like that handles image data digitally, image quality is not degraded by copying in principle. Therefore, prevention of unauthorized copying in a device or the like that processes digitally is much more important than in the case of analog.

There are two main methods for adding information accompanying image data to the image data.

The first method is a method of adding image data to an auxiliary part. For example, on a video tape, as shown in FIG. 20, auxiliary information of the image data is recorded at the top of the screen. By using a part of this area, it is possible to add additional information.

The second method is a method of adding the image data to the main part. This is, as shown in FIG. 21, a specific pattern, for example, a watermark (Water Mar).
k) The pattern is added to the whole or a part of the image so that the pattern cannot be visually perceived. As a specific example of this,
There is spread spectrum or the like in which information is added or detected using a key pattern generated using a random number, an M sequence, or the like.

Hereinafter, an example of adding and detecting accompanying information to a main portion of image data when a watermark pattern is used, which has been conventionally performed, will be described.

The watermark is, as shown in FIG.
Assume that each pixel takes one of two symbols, plus and minus. Actually, the watermark pattern is a pattern that randomly takes one of the two symbols, and the shape and size of the area are often arbitrary.

When adding the accompanying information, as shown in FIG. 23, an area having the same size as the area of the watermark pattern is set on the image to be added, and the set area and the watermark are set. The mark patterns are overlapped and illuminated, and the value a is added to the pixel of the plus symbol, and the value b is subtracted to the pixel of the minus symbol. Here, both the values a and b are arbitrary values and are constant throughout the watermark pattern. For example, in this example, as shown in FIG. 23B, the values a = 1 and b = 1
23, that is, assuming that the pixel values of the area to be added are all 100 as shown in FIG.
As shown in FIG. 23 (c), it becomes one of 101 and 99.

When detecting accompanying information, an area having the same size as the area of the watermark pattern is set on an image to be detected. Then, a value obtained by summing all the pixels in this area is used as an evaluation value. Specifically, as shown in (A) and (B) of FIG. 24, the sum of all the pixels is calculated by overlapping the set area and the watermark pattern and illuminating them, and adding up the pixels of the plus symbol. , And subtraction is performed for the pixel of the minus symbol. At this time, it is needless to say that the same pattern as the watermark pattern used when adding the accompanying information is used.

When the accompanying information is added by such a detecting operation, as shown in FIG.
The evaluation value is (4n) ＾ 2 (same as the number of pixels included in the area). When no additional information is added, as shown in FIG. Value is 0
become.

When the area of the watermark pattern is sufficiently large and the watermark pattern is sufficiently random, the evaluation value when the accompanying information is not added is almost zero. Therefore, when the evaluation value exceeds a certain threshold value, it can be determined that additional information has been added. According to the above procedure, it is possible to add binary information (1 bit) indicating whether or not additional information has been added. Here, when it is desired to add more information, 2 ＾ k kinds (k bits) of information are added by a processing method such as dividing the entire image into k regions and performing the above operations. Can be.

Further, a watermark pattern generated using an M-sequence can be used. The M-sequence (longest code sequence) is a sequence of binary symbols of 0 and 1, the statistical distribution of 0 and 1 is constant, the code correlation is 1 at the origin, and the other is -1 / code length. Things. Note that there is also a method of generating a watermark pattern by a method other than using the M sequence.

When image data is recorded and reproduced digitally, the amount of information becomes extremely large as it is, so that the data is generally compressed. As a method for compressing image data, JPEG (Joint Photographic Coding Experts Groupe) or MPEG (Moving Picture Coding; Moving Picture Exp
erts Groupe) has been standardized internationally and has been put to practical use.

In the case of compressing image data by high-efficiency coding, the addition and detection of accompanying information is realized by an encoder 301 configured as shown in FIG. 25 and a decoder 305 configured as shown in FIG. You.

As shown in FIG. 25, the encoder 301 adds the accompanying information f to the image data inputted by the watermark adding unit 302. Then, the encoder 301 inputs the image data to which the additional information f has been added to the encoder 303, performs high-efficiency encoding, and generates an encoded bit sequence.

FIG. 26 shows the decoder 305.
, The bit string input by the decoder 306 is restored as image data. And the encoder 30
5 is the watermark information 231 in the watermark detector 231.
Is detected.

If the image data is not encoded with high efficiency, the encoder 301 is removed from the encoder 301 and
In some cases, the decoder 305 is omitted from the decoder 305, whereby additional information is added to the image data or the additional information added to the image data is detected.

Here, the watermark adding device 302
The watermark adding device 302 having such a configuration is configured as shown in FIG.
If n, the additional information is added to the image data input by the additional information adder 312 using the watermark pattern recorded in the watermark pattern holding memory 311, and the additional information f Is off, the input image data is added to the additional information
12 is output as it is.

The watermark detector 307 is configured as shown in FIG. 28. The watermark detector 307 having such a configuration is used for the watermark detector 307 recorded in the watermark pattern holding memory 315. The evaluation value is calculated by the evaluation value calculator 316 based on the input image data using the pattern. The evaluation value calculated here is subjected to threshold processing by the evaluation value comparator 317, and is output as accompanying information f. Further, the input image data itself is output as it is.
The image converter 318 (shown by a dotted line in the figure) is a part that processes or processes the input image data. This will be described later.

FIG. 29 shows a series of processes performed by the watermark adding unit 302, and FIG. 30 shows a series of processes performed by the watermark detector 307.

In the watermark adding process, the watermark adding unit 302 sets the watermark adding levels a and b in step S301 as shown in FIG.

Subsequently, the watermark adding device 302
In step S302, an area having the same size as the area of the watermark pattern is set on the image to which the additional information is to be added, and each pixel in the area is compared with the watermark pattern.
In 3, the watermark symbol is determined.

Here, the watermark adding device 302
If the watermark symbol of the pixel is positive, the process proceeds to step S304, and the value a is added to the pixel. If the watermark symbol of the pixel is negative, the process proceeds to step S305. Subtract the value b from that pixel.

Then, the watermark adding device 302
In step S306, determination processing is performed as to whether or not processing has been performed on all pixels in the target area. If it is confirmed that processing has not been performed on all pixels,
Returning to step S302, the above-described processing such as the collation is performed again, and the processing is repeated for all the pixels in the target area.

In the watermark detection process, the watermark detector 307 initializes the evaluation value sum and sets the threshold value th in step S311, as shown in FIG.

Subsequently, the watermark detector 307
In step S312, an area having the same size as the area of the watermark pattern is set, and each pixel in the area is compared with the watermark pattern. In step S313, the symbol of the watermark is determined.

Here, the watermark detector 307 is
If the watermark symbol of the pixel is positive, the process proceeds to step S314, and the pixel value x is added to the evaluation value sum. If the watermark symbol of the pixel is negative, the process proceeds to step S315. To subtract the pixel value x from the evaluation value sum.

Then, the watermark detector 307
In step S316, a determination process is performed to determine whether or not processing has been performed for all pixels in the target area. If it is confirmed that processing has not been performed for all pixels,
Returning to step S312, the processing such as the above-described collation is performed again, and the processing is repeated for all the pixels in the target area.

After performing the above-described processing for all pixels,
In step S317, the watermark detector 307 compares the evaluation value sum with the threshold th assuming that the evaluation value sum> the threshold th. Here, if the evaluation value sum> threshold th, the watermark detector 307 proceeds to step S318, considers that the additional information is added to the image data, and turns on the additional information f (the additional information f is present). If not, the process proceeds to step S319, where the associated information f is turned off (the associated information f
Does not exist).

The accompanying information f detected here is used as follows, for example, to prevent unauthorized copying.

Taking the decoder 305 configured as shown in FIG. 26 as an example, the output image data and accompanying information f are passed to an image display unit (not shown). When the accompanying information f is on, the image display unit displays the image as it is. When the accompanying information f is off, for example, the image is not displayed, the main area of the image data is not displayed, Processing or processing such as scrambling (randomly displaying received image data) is performed.
For example, the image converter 318 is a part that processes or processes such image data according to the accompanying information f.

Further, the watermark pattern may be constituted by a pattern having a special property such as an M series. In this case, the associated information is detected using the property.

For example, the code correlation of the M sequence is high at the origin,
Others have the property of becoming almost zero. Utilizing this property when detecting the accompanying information, the evaluation value for each shifted position (phase) is obtained while shifting the watermark pattern, and the evaluation values are compared. In this case, since the evaluation value other than the shift amount 0 can be regarded as the evaluation value when the additional information is not added, the comparison of these values uses the relative evaluation criterion, so that the additional information can be reliably determined. Can be detected. Hereinafter, this detection method is referred to as “shift detection”.

FIGS. 31 and 32 show shift detection.
The accompanying information is detected by the processing shown in FIG. By configuring the watermark detector 321 as shown in FIG. 33, it is possible to detect accompanying information by detecting shift.

Except for the watermark detector, this configuration is completely the same as the case where no shift detection is performed, for example, completely the same as the watermark detector 307 shown in FIG. More specifically, regarding the processing, as compared with the processing of the conventional example shown in FIG. 30, evaluation values for respective shift positions (phases) are obtained while shifting the watermark pattern, and the evaluation values are compared. The only difference is the detection of accompanying information.

As shown in FIG. 33, a watermark detector 321 for detecting a watermark pattern by detecting a shift receives input image data into a plurality of evaluation value calculators 323 ₁ , 323 ₂ , and 323 _3. .

The watermark detector 321, a watermark pattern recorded in the watermark pattern holding memory 322 is shifted by watermark pattern shifted 325 _1, 325 ₂ as necessary.

Then, the watermark detector 321
Each evaluation value is calculated by the evaluation value calculator using the watermark pattern shifted as necessary. The watermark detector 321 performs a threshold process on the evaluation value calculated here by the evaluation value comparator 324 and outputs accompanying information f. The input image data itself is output as it is. An image converter 326 (shown by a dotted line in the figure) may be provided, for the same reason as described above.

The watermark detector 321 having such a structure detects the accompanying information f by a series of processes as shown in FIG.

In step S331, the watermark detector 321 sets the threshold value th.

Then, the watermark detector 321
In steps S322 to S337, each evaluation value sum for the image of the current frame when a watermark pattern having a shift amount of 0, i, j is used.
_I, sum_n, and sum_j. To this end, the watermark detector 321 determines in step S33
The process for calculating the evaluation value in each of the steps 3,335,337 (the process shown in FIG.
This is referred to as “evaluation value calculation processing”. )It is carried out.

In the evaluation value calculation process, as shown in FIG. 32, in step S351, the evaluation value sum is initialized, and then in step S352, the watermark pattern is shifted by the shift amount z. Then, in the processing after step S353, processing similar to steps S313 to S316 described using FIG. 30 is performed.

That is, the watermark detector 321
In step S352, an area having the same size as the area of the watermark pattern is set, and each pixel in the area is compared with the watermark pattern shifted by the shift amount z. In step S353, the watermark is set. Is determined. here,
If the watermark symbol of the pixel is positive, the watermark detector 321 determines in step S3
The process proceeds to 54, where the pixel value x is added to the evaluation value sum. If the watermark symbol of the pixel is negative, the process proceeds to step S355, where the evaluation value sum is calculated.
From the pixel value x. Then, in step S356, the watermark detector 321 performs determination processing as to whether or not processing has been performed for all pixels in the target area. If it is confirmed that processing has not been performed for all pixels, Returning to step S352, the above-described processing such as the collation is performed again, and the processing is repeated for all the pixels in the target area. As described above, the watermark detector 321 calculates by the evaluation value calculation process.

By such an evaluation value calculation process, the watermark detector 321 performs the evaluation value sum at the shift amount 0 in steps S332 and S333.
_N, followed by step S334 and step S334.
At 335, an evaluation value sum_i when a watermark pattern having a shift amount z = i is used is determined. Then, the watermark detector 321 that has obtained the evaluation value sum_i at the shift amount z = i finally has the shift amount z = i determined in steps S336 and S337.
evaluation value su when the watermark pattern of j is used
Find m_j.

Here, when the watermark pattern is shifted, a process as shown in FIG. 34 is performed.
That is, the watermark pattern is shown in FIG.
When the image is scanned as shown in FIG. 34 (B) in the configuration shown in FIG.
As shown in (C) of FIG. 4, the processing is performed while being shifted according to the scanning order of the image. The unit to be shifted at this time is
The shift is not limited to one pixel unit, but may be shifted in an arbitrary region unit. The shift amount is preferably shifted by the same amount before and after the shift amount 0 as in the case of i> 0, j <0, | i | = | j |, but any shift amount may be used.

The reason why the evaluation value is obtained by shifting the watermark pattern is as follows.

For example, when a watermark pattern is generated using an M-sequence, the correlation with a watermark pattern obtained by arbitrarily shifting the pattern at a position (phase) other than 0 or a period becomes very low. In other words, if detection is performed using a watermark pattern slightly shifted from the watermark pattern at the time of addition,
The bias component of the evaluation value is almost 0, which is almost the same as the evaluation value when no additional information is added. For example, in FIG. 24, the bias component of the evaluation value (4n) ＾ 2
Becomes almost zero. Therefore, the evaluation value obtained by shifting the watermark pattern can be regarded as substantially equal to the standard evaluation value when no watermark pattern is added. By comparing those evaluation values with the evaluation value when the shift amount is 0, the relative evaluation criterion can be used, so that the accompanying information can be easily detected. By this method, a sufficiently large area such that the evaluation value when the accompanying information is not embedded is almost 0 is obtained.
Even if a watermark pattern (M-sequence is a higher-order sequence) is not used, it is possible to reliably detect incidental information only by using a watermark pattern in a narrow area (M-sequence is a lower-order sequence). I can do it.

The watermark detector 321 has three evaluation values sum_n, sum_i, su
By relatively evaluating m_j, the accompanying information shown in FIG. 31 is detected.

That is, the watermark detector 321
Is the evaluation value s in step S339 shown in FIG.
Average value sum_av of um_i and evaluation value sum_j
e = (sum_i + sum_j) / 2 is obtained. Then, in the subsequent step S339, the watermark detector 321 sets this value sum_ave as a standard evaluation value and sets the actual evaluation value (evaluation value of the shift amount 0) sum_n.
And the absolute value | sum_n-sum_ave | Here, if the difference is larger than the threshold th, the watermark detector 321 proceeds to step S340, deems that the accompanying information has been added at the shift phase r, and turns on the accompanying information f. If not,
Proceeding to step S341, the associated information f is turned off.

For example, FIG. 35 shows an example in which the above three evaluation values are used for relative evaluation. As shown in FIG. 35, when a watermark is added, the evaluation value at the shift amount of −1, 0, 1 is the evaluation value A, su
m_embed, B, and when no watermark is added, similarly, the evaluation value is the evaluation value A, sum_
non, B.

Here, the standard evaluation value sum_ave =
Comparing (A + B) / 2 (indicated by ● in the figure) with the evaluation value of adding / non-adding a watermark at a shift amount of 0, the evaluation value sum_embed (in the figure, circled)
), The difference becomes larger, and when no watermark is added, the difference becomes smaller because it is compared with sum_non (marked in the figure). Therefore, it can be seen that by performing threshold processing on the difference from the standard evaluation value sum_ave, it is possible to extract accompanying information.

The standard evaluation value for the image of the current frame can be obtained by the following processing method.

For example, a filter such as a median filter is applied, and three evaluation values sum_n, sum_i, su
For m_j, a standard evaluation value sum_med for the image of the current frame is obtained. Here, the median filter is a filter that returns the value at the center position after rearranging the input numerical value sequence in ascending or descending order. That is, for example, 71,8, -345,68, -2
When the five numerical values are input, the median filter performs rearrangement as -345, -2, 8, 68, and 71, and returns 8 as a result. The standard evaluation value sum_med thus obtained and the actual evaluation value su
The absolute value of the difference from m_n is obtained. If the difference is larger than the threshold th, it is determined that the accompanying information has been added, and the accompanying information f is turned on. Otherwise, the associated information f is turned off.

In addition, an evaluation value of an arbitrary single phase may be used as it is, or an average value, a maximum value, a minimum value, etc. of all or some of a plurality of evaluation values may be obtained. For example, a standard evaluation value may be obtained by using any processing method. This includes a more complicated processing method such as estimating or extrapolating an evaluation value when the shift amount is 0 from a transition of the evaluation value when the shift is −2 or −1.

[0059]

In the above-described method of adding information accompanying image data to the image data, the following problem occurs at the time of detection.

When detecting information attached to image data, each pixel value is processed according to a specific pattern to which information is added (a watermark pattern in the above description) to calculate an evaluation value. However, the pixel value is generally a positive value, and a positive value that is not zero on average is processed at the time of detection to calculate an evaluation value. Therefore, the influence of each pixel value on the evaluation value is large, and the possibility of erroneous detection increases when the length of the watermark pattern series is short.

That is, for example, in the above-described high-efficiency coding such as MPEG, the luminance signal Y and the color difference signals Cb and Cr are all quantized in the range of 0 to 255. When calculating the evaluation value, each pixel value of 128 is processed on average, and the evaluation value repeats 128 fluctuations on average. For example, when the sequence length is 100 and the number of plus symbols is two more than minus, the evaluation value is 128 × 2 and is shifted by about +256 minutes. As a result, in the case where ± 1 is added to one symbol as in the example described above, only +100 can be added as a whole, but as described above, there is a difference of about +256 minutes in the conventional art. In the method, the detection accuracy is low.

Therefore, the present invention has been made in view of the above-described circumstances, and has an image data processing apparatus and method which has high detection accuracy of an evaluation value for detecting a watermark added to image data. And a recording apparatus and method.

[0063]

In order to solve the above-mentioned problems, an image data processing apparatus according to the present invention has an additional information output means for outputting a pattern of additional information, and a nearby pixel in input image data. A difference value calculating means for calculating a difference value between pixel values between the two, and an evaluation value calculating means for calculating an evaluation value based on a pattern and a difference value of the accompanying information output from the accompanying information output means; An incidental information detecting means for detecting incidental information based on the value.

The image data processing apparatus having the above-described configuration provides an evaluation value calculating unit based on the pattern of the accompanying information output from the accompanying information output unit and the difference value calculated by the difference value calculating unit. Get. Then, the image data processing device detects accompanying information based on the evaluation value by the accompanying information detecting means.

The image data processing device detects accompanying information based on an evaluation value obtained from a difference value between a neighboring pixel having a high correlation and a neighboring pixel.

Further, in order to solve the above-mentioned problem, the image data processing method according to the present invention includes a step of outputting an accompanying information pattern and a step of outputting an accompanying information pattern between neighboring pixels in the input image data. A difference value calculating step of calculating a difference value between pixel values, an evaluation value calculating step of calculating an evaluation value based on a pattern and a difference value of the incidental information output in the incidental information output step, And an incidental information detecting step of detecting incidental information.

According to this image data processing method, an evaluation value is obtained by the evaluation value calculation means based on the pattern of the accompanying information output in the accompanying information output step and the difference value calculated in the difference value calculating step. Then, the image data processing device detects accompanying information based on the evaluation value by the accompanying information detecting means.

In the image data processing method, accompanying information is detected based on an evaluation value obtained from a difference value between neighboring pixels having a high correlation.

Further, in order to solve the above-mentioned problem, the recording apparatus according to the present invention includes a supplementary information output means for outputting a pattern of supplementary information, and a pixel value between neighboring pixels in input image data. Difference value calculating means for calculating a difference value of the evaluation information, evaluation value calculation means for calculating an evaluation value based on the pattern of the accompanying information output from the accompanying information output means and the difference value, and associated information based on the evaluation value. And a recording control unit that controls the recording of the image data input to the recording medium in accordance with the detection result of the incidental information detecting unit.

In the recording apparatus having such a configuration, an evaluation value is obtained by the evaluation value calculation means based on the pattern of the additional information output from the additional information output means and the difference value calculated by the difference value calculation means. . And the recording device,
The accompanying information detecting means detects the accompanying information based on the evaluation value. Further, the recording device records, on the recording medium, the image data input according to the detection result of the accompanying information detecting means by the recording control means.

The recording apparatus detects accompanying information based on an evaluation value obtained from a difference value between a neighboring pixel having a high correlation.

According to the recording method of the present invention, in order to solve the above-described problem, an additional information output step of outputting a pattern of additional information, and a method of outputting a pixel value between neighboring pixels in input image data. A difference value calculation step of calculating a difference value of the evaluation information; an evaluation value calculation step of calculating an evaluation value based on the pattern and the difference value of the additional information output in the additional information output step; and additional information based on the evaluation value. And a recording control step of controlling the recording of the image data input to the recording medium in accordance with the detection result of the incidental information detecting step.

In this recording method, an evaluation value is obtained by the evaluation value calculation means based on the pattern of the additional information output in the additional information output step and the difference value calculated by the difference value calculation means. Then, in the recording method, in the accompanying information detecting step, the accompanying information is detected based on the evaluation value. Further, in the recording method, in the recording control step, the input image data is recorded on the recording medium according to the detection result of the accompanying information detecting means.

In the recording method, incidental information is detected based on an evaluation value obtained from a difference value between neighboring pixels having a high correlation.

Further, in order to solve the above-mentioned problem, the image data processing apparatus according to the present invention comprises: an auxiliary information output unit for outputting a plurality of patterns of auxiliary information having mutually different phases; Calculating an evaluation value based on a difference value calculating means for calculating a difference value of a pixel value between the pixel and a plurality of incidental information patterns having different phases output from the incidental information output means and the differential value. An evaluation value calculation means is provided, and an associated information detection means for detecting the associated information by comparing a plurality of evaluation values obtained by the evaluation value calculation means.

The image data processing apparatus having such a configuration can calculate an evaluation value based on a plurality of patterns of accompanying information having different phases output from the accompanying information output means and the difference value calculated by the difference value calculating means. An evaluation value is obtained by means. Then, the image data processing device detects the accompanying information based on the plurality of evaluation values by the accompanying information detecting means.

Then, the image data processing device detects accompanying information based on an evaluation value obtained from a difference value between neighboring pixels having a high correlation.

Further, in order to solve the above-mentioned problem, the image data processing method according to the present invention further comprises: an additional information output step of outputting a plurality of patterns of the additional information having different phases; An evaluation value is calculated based on a difference value calculation step of calculating a difference value of a pixel value between the pixel and a plurality of associated information patterns having different phases and a difference value output in the associated information output step. The method includes an evaluation value calculating step and an incidental information detecting step of detecting incidental information by comparing a plurality of evaluation values obtained in the evaluation value calculating step.

In this image data processing method, an evaluation value is calculated by an evaluation value calculation step based on a plurality of patterns of auxiliary information output in the additional information output step and having different phases, and the difference value calculated in the difference value calculation step. obtain. Then, the image data processing method includes,
Associated information is detected based on a plurality of evaluation values.

In the image data processing method, accompanying information is detected based on an evaluation value obtained from a difference value between neighboring pixels having a high correlation.

Further, in order to solve the above-mentioned problem, the recording apparatus according to the present invention comprises: an auxiliary information output means for outputting a plurality of patterns of auxiliary information having mutually different phases; A difference value calculating means for calculating a difference value between pixel values between the two, and an evaluation value for calculating an evaluation value based on a pattern and a difference value of a plurality of pieces of accompanying information having different phases output from the accompanying information output means. A calculating means, an incidental information detecting means for detecting incidental information by comparing a plurality of evaluation values obtained by the evaluation value calculating means, and the input to the recording medium according to a detection result of the incidental information detecting means. Recording control means for controlling the recording of the selected image data.

The recording apparatus having the above-described configuration uses the evaluation value calculating means based on the plurality of patterns of the accompanying information having different phases output from the accompanying information output means and the difference value calculated by the difference value calculating means. Obtain an evaluation value. Then, the recording device detects incidental information based on the plurality of evaluation values by the incidental information detecting means. Further, the recording device records, on the recording medium, the image data input according to the detection result of the accompanying information detecting means by the recording control means.

The recording apparatus detects accompanying information based on an evaluation value obtained from a difference value between a neighboring pixel having a high correlation and a neighboring pixel.

According to the recording method of the present invention, in order to solve the above-mentioned problem, an additional information output step of outputting a plurality of patterns of auxiliary information having different phases from each other includes a step of outputting a plurality of adjacent pixels in the input image data. A difference value calculating step of calculating a difference value of a pixel value between the evaluation value and an evaluation value for calculating an evaluation value based on a pattern and a difference value of a plurality of pieces of incidental information having different phases output in the incidental information output step An additional information detecting step of detecting additional information by comparing a plurality of evaluation values obtained in the calculating step and the evaluation value calculating step, and the input to the recording medium according to a detection result of the additional information detecting step. And a recording control step of performing recording control of the selected image data.

According to this recording method, an evaluation value is obtained by an evaluation value calculation step based on a plurality of patterns of auxiliary information having different phases output in the auxiliary information output step and the difference value calculated in the difference value calculation step. Then, the recording method detects incidental information based on the plurality of evaluation values in the incidental information detecting step. Further, in the recording method, the image data input according to the detection result of the incidental information detection step is recorded on the recording medium by the recording control step.

In the recording method, incidental information is detected based on an evaluation value obtained from a difference value between neighboring pixels having a high correlation.

[0087]

Embodiments of the present invention will be described below in detail with reference to the drawings. In this embodiment, an image data processing apparatus and method according to the present invention are applied to a watermark detector that detects image data in which a watermark is embedded as accompanying information.

First, the configuration of the watermark detector according to the first embodiment will be described with reference to FIG. As shown in FIG. 1, a watermark detector 2 according to the first embodiment has a watermark pattern holding memory 3 as an accompanying information output unit for outputting a watermark pattern.
A difference calculator 4 which is a difference value calculating means for calculating a difference value of a pixel value between neighboring pixels in the input image data, and a watermark pattern extracted from the watermark pattern holding memory 3. An evaluation value calculator 5 that is an evaluation value calculation unit that calculates an evaluation value based on the difference value, and an evaluation value comparator 6 that is an incidental information detection unit that detects a watermark based on the evaluation value. Have. Further, the watermark detector 2 includes an image converter 7 for processing an input image based on the result of the watermark collation.

The watermark detector 2 having the above-described configuration can detect a watermark added to image data.

The watermark detector 2 is, for example,
It is provided in a decoder for decoding input image data. By providing the watermark detector 2, the decoder can detect a watermark and perform image processing according to the detection result.

Specifically, the decoder has the same configuration as the encoder 305 as shown in FIG. 26 used in the description of the conventional watermark detector. That is, in this case, the watermark is used. Detector 3
07, the watermark detector 2 of the present embodiment is applied. The process of adding a watermark to image data is performed by an encoder 301 as shown in FIG.

The difference calculator 4 calculates a difference value for each pixel of the input image data. The difference value calculated here is input to the evaluation value calculator 5.

The above-mentioned watermark pattern holding memory 3
Is a storage unit in which a watermark is stored in advance, and the evaluation value calculator 5 calculates an evaluation value using the watermark pattern recorded in the memory 3 for retaining the watermer pattern. The evaluation value calculated here is input to the evaluation value comparator 6.

The evaluation value comparator 6 performs threshold processing on the evaluation value and outputs accompanying information f.

The input image data is normally output as it is, but the image converter 7 has a function of processing or processing the input image data as needed. For example, in the image display unit that displays an image, if the accompanying information f is on, the image is displayed as it is, but if the accompanying information f is off, for example, the image is not displayed. , And processing or processing such as scrambling the image (randomly displaying the received image data). The image converter 7 is a part that processes or processes image data according to the accompanying information f as described above.

The watermark detector 2 having such a configuration performs the detection processing of the accompanying information as shown in FIG.
It is executed by a series of processing.

[0097] The watermark detector 2 performs step S1.
In, the evaluation value sum is initialized and the threshold value th is set.

Subsequently, in step S2, the watermark detector 2 sets an area having the same size as the area of the watermark pattern, and compares each pixel in the area with the watermark pattern.
3, the difference value x with respect to the pixel X subjected to the comparison
Find d.

Then, in step S4, the watermark detector 2 determines the symbol of the watermark. Here, if the watermark symbol of the pixel is positive, the watermark detector 2 proceeds to step S5, adds the difference value xd to the evaluation value sum, and outputs the watermark symbol of the pixel. Is negative, the process proceeds to step S6, where the evaluation value su
The difference value xd is subtracted from m.

Then, in step S7, the watermark detector 2 determines whether or not processing has been performed on all the pixels in the target area. If it is confirmed that the processing has not been performed on all the pixels, Returns to step S2, performs the above-described processing such as the collation again, and repeats the processing for all the pixels in the target area.

After performing the above-described processing for all the pixels,
In step S8, the watermark detector 2 sets the evaluation value sum> the threshold th to the evaluation value s with respect to the threshold th.
Compare um. Here, if the evaluation value sum> threshold th, the watermark detector 2 proceeds to step S9, considers that the additional information is added to the image data, and turns on the additional information f (the additional information f is present). If not, the process proceeds to step S10, where the associated information f is turned off (the associated information f does not exist). Based on the accompanying information f detected here,
As in the related art, for example, an illegal copy prevention process is performed.

As described above, the watermark detector 2 to which the present invention is applied performs the detection processing of the accompanying information based on the evaluation value, but calculates the evaluation value sum as compared with the processing of the conventional example. The target pixel X itself, the pixel value x
Is used instead of calculating the difference value xd of the pixel X.

Since the watermark detector 2 calculates the evaluation value using the difference value in the above-described configuration, the influence of each value of the image data on the evaluation value can be reduced. Thereby, the watermark detector 2 can increase the detection accuracy of the incidental information, so that the incidental information can be reliably detected.

That is, specifically, as described above,
Conventionally, for each pixel value quantized in the range of 0 to 255, if a difference between the pixel value and a neighboring pixel value is taken, the range of the value itself will be expanded to −255 to 255. However, in general, the correlation between neighboring pixel values is high in an image,
The difference value becomes 0 on average. Therefore, for example, even when the sequence length is 100 and the number of plus symbols is two more than minus, the deviation of the evaluation value is about ± 0. If ± 1 is added for one symbol,
If there is an additional amount of +100 as a whole, it is possible to obtain higher detection accuracy than before.

The following example is given as a method of calculating the difference value xd for the pixel X.

The first calculation method for obtaining the difference value xd includes:
The difference between the pixel X and the pixel located at the same vertical coordinate (hereinafter, the difference is
This is referred to as a lateral difference. ).

That is, for example, by taking a difference from the pixel XL located on the left of the pixel X, the difference value xd = XL
Get -X. Note that the difference value xd = X-XL may be set.

The object for obtaining the difference does not need to be limited to the left side, and a difference from n pixels XLn located on the left side may be used. In this case, the difference value xd = XLn−
X. Alternatively, the difference value xd = X−XLn. Of course, a difference from the pixel located on the right side of the pixel X may be determined.

Next, as a second calculation method, there is a method of calculating a difference between a pixel X and a pixel located at the same horizontal coordinate (hereinafter, referred to as a vertical difference). For example, by taking a difference from the pixel XU located on the upper side of the pixel X, a difference value xd =
XU-X is obtained. Note that the difference value xd may be set to X−XUd.

The object for which the difference is to be obtained does not need to be limited to the upper neighbor, and a difference from the pixel XUn located n pixels above may be used. That is, in this case, the difference value xd
= XUn-X. Or, the difference value xd = X−XUn
Becomes Of course, the difference from the pixel located below pixel X may be determined.

As a third calculation method, there is a method in which a difference is calculated on the assumption that the vertical coordinate or the horizontal coordinate is not the same.

For example, the difference between the coordinate position of the pixel X and the pixel 3 pixels upward and 12 pixels to the right may be calculated.

In addition to the calculation method described above,
There is also a calculation method in consideration of a case where a pixel to be subtracted exists at a position outside the image when the pixel is located at the upper, lower, left, or right end of the image (fourth calculation method). In this case, the difference value xd is set to an arbitrary value. For example, in this case, it is determined that the difference value cannot be calculated, and the difference value xd = 0 may be set. Alternatively, the pixel to be subtracted may be configured by using any of the calculation methods as described above. Furthermore, when the target pixel is located outside the image, a difference value can be obtained by using a method of cycling the image. For example, considering the case where the difference value is obtained using the pixel on the left side, when the coordinates (y, x) of the pixel X are (5, 0), the pixel XL on the left side to be a difference object has coordinates (5, 0) -1), and the pixel XL is located outside the image. Therefore, the number of pixels NH in the horizontal direction of the image is periodically added to the horizontal component of the pixel XL, and coordinates (5,
The pixel located at NH-1) is used. Of course, the pixels to be subtracted may be configured by other methods.

As a fifth calculation method, the difference value xd for the pixel X can be obtained by using the following calculation method.

First, there is a method of obtaining a difference value using both the horizontal difference and the vertical difference described above. For example, when calculating the difference value xd for the pixel X (y, x), the pixels XL (y, x-1), XU (y-1, x), XUL (y
Using the three pixels of (−1, x−1), a difference value xd is obtained as follows.

Xd = (XUL-XU)-(XL-X) An example of a method of obtaining a difference value using a plurality of pixels is not limited to this, and the following calculation method can be employed.

For example, in the case of a horizontal difference, when calculating a difference value xd for the pixel X0, four pixels X0 adjacent to the right are used.
(Y, x), X1 (y, x + 1), X2 (y, x +
2), X3 (y, x + 3) may be used.
In this case, each difference value xd1, xd is calculated by the following equation.
2, xd3.

Xd1 = X0-X1 + X2-X3 xd2 = X0-X1-X2 + X3 xd3 = X0 + X1-X2-X3 Then, a difference value xd to be finally obtained is calculated from these difference values xd1, xd2, xd3. For example, xd
The difference value xd for which it is desired to obtain an average, an intermediate value of 1, xd2, and xd3, a value closest to 0, and the like. Alternatively, a configuration may be adopted in which evaluation values are individually obtained for these values, and these values may be used when comparing the evaluation values.

When obtaining the difference value xd for the pixel X, the pixel X itself may not be used. In this case,
For example, when obtaining the difference value xd for X (y, x), the difference value xd is obtained as follows using the pixels XL (y, x-1) and XR (y, x + 1).

Xd = XL (y, x−1) −XR (y, x + 1) As another example in which the pixel X itself is not used in obtaining the difference value xd, for example, the same watermark symbol as that of the pixel X is used. There is also a method of calculating a difference value xd from a pixel Xsame and a pixel Xdiff of a watermark symbol different from the pixel X as follows.

Xd = Xsame-Xdiff Here, the criterion for selecting the pixels Xsame and Xdiff is, for example, a pixel whose pixel position is closest to the pixel X or a pixel whose value is closest to the pixel X.

As described above, the difference value is calculated by a variety of calculation methods. This is because the correlation between neighboring pixel values is high in an image, and the difference value of pixel X is 0 on average. We are using.

When the pixel position is located at the boundary of an edge or the like, the absolute value of the difference value often becomes large. Unless such a phenomenon is further taken into account in the above-described calculation method, The evaluation value is greatly affected by the difference value.

In order to avoid this, when the absolute value of the difference value exceeds a certain range, a method is adopted in which the difference value is not reflected on the evaluation value. Alternatively, the value may be clipped.

Specifically, the absolute value of the difference value is a predetermined value ra
If | xd |> range in relation to nge, the difference value xd is set to xd = 0. Or, set as follows:

Xd = range (xd ≧ 0) xd = −range (xd <0) Note that the above-described clipping is performed such that when the difference value reaches a certain value, the difference value falls within a predetermined value range. However, this conversion may be performed by function conversion.

It should be noted that any watermark symbol other than plus and minus symbols can be used. Further, as for the types of watermark symbols, not only two types but also three or more types of symbols can be used. For example, plus
Three types of symbols, ie, zero and minus, are prepared, and for a pixel whose symbol is zero when collation with the watermark pattern is performed, the evaluation value sum is not affected (the pixel value is determined by the evaluation value sum). What is the meaning of each symbol?

The area where the watermark pattern is added on the image may have any shape and range.

Further, as long as the matching with the added watermark pattern is achieved, the shape and range of the area for which the evaluation value is to be obtained at the time of detection may be arbitrary. Further, the watermark pattern may be detected by using a wider area over time or space. For example, in a moving image sequence, a temporal reference is used, and not only the temporal position of the current frame but also past and future frames may be used. For example, in a still image having a very large image size, one image is divided into a plurality of image areas in a certain unit and handled. For example, image areas located before and after in the scanning order may be used.

Next, as an embodiment of the present invention, a watermark detector for detecting accompanying information embedded as a watermark in image data by detecting displacement will be described. That is, the watermark detector according to the second embodiment described here obtains the evaluation value using the difference value in accordance with the shift detection.

Here, what happens to the evaluation value when the shift detection is performed using the difference value will be considered.

First, properties regarding the series M used as a watermark pattern are as follows.

For example, when an M sequence is used as M, since plus and minus symbols appear as pseudo-random numbers,
The inner product of the series M and the image P becomes almost 0. Also, taking the inner product of the series and the series of the same phase increases the correlation, and taking the inner product of the series that is not in phase reduces the correlation. It should be noted that the sequence M used as the watermer pattern is not limited to the one described here, as long as it is a pattern having such a special property as well as the M sequence.

The above can be summarized as an equation.

M (y, x) = + a (when the symbol is positive) M (y, x) = − b (when the symbol is negative) {M (y, x) × P (y, x)} {0} M (y1, x1) × M (y2, x2)｝ ≒ α (y
1 = y2 and x1 = x2) {M (y1, x1) × M (y2, x2)} 0 (y
1 ≠ y2 or x1 ≠ x2) Next, the difference between the immediately preceding and the immediately following is considered.

First, when the difference from the immediately preceding pixel is used, for example, the difference value between the pixel of interest X (x, y) and the pixel XL (y, x−1) adjacent to the pixel of interest X (x, y) is calculated as the difference value. Value diff
_L. Each of the pixels X and XL is obtained by adding a watermark pattern M to the image P before adding the watermark pattern. For example, the difference value d
If_L is calculated as follows.

Diff_L = XL (y, x−1) −X (y, x) = {P (y, x−1) + M (y, x−1)} − {P (y, x) + M (y) , X)} = YL + M (y, x-1) -M (y, x) where YL = P (y, x-1) -P (y, x).

Then, the evaluation value sum_L is calculated using the difference value diff_L. Evaluation value su when the shift amount is 0
m_L (0) is obtained as follows by calculating the inner product of the pixel M (y, x) and the difference value diff_L over the image.

Sum_L (0) = {M (y, x) × diff_L} = {M (y, x) × YL} + {M (y, x) × M (y, x−1)} − {M (y, x) × M (y, x)} Here, since the first term of the above equation is an inner product with the image, almost zero
Becomes Since the second term is an inner product with a series that is not in phase, it is almost zero. Since the third term is the inner product of the series having the same phase, it is substantially -α. From these, the following values can be derived.

Sum_L (0) ≒ -α Then, similarly, the evaluation value sum_L (−1) for the shift amount of −1 is similarly obtained. Note that, in the following, the expression is developed by taking as an example a case where the shift amount z affects the x component of the image. The evaluation value sum_L (-1) is obtained as follows.

Sum_L (−1) = {M (y, x−1) × diff_L} = {M (y, x−1) × YL} + {M (y, x−1) × M (y , X−1)} − {M (y, x−1) × M (y, x)} Here, since the first term of the above equation is an inner product with the image, almost 0
Becomes Also, the second term is the inner product of the in-phase series, so
It is almost α. Since the third term is an inner product with a series that is not in phase, it is almost zero. Summarizing the above, the following values can be derived.

Sum_L (-1) ≒ α Further, even in cases other than the shift amounts 0 and -1, all the evaluation values calculated by the above-described method are almost zero. That is, the following values can be derived.

Sum_L (z) ≒ 0 (z ≠ 0 and z ≠ −1) Next, in the case of using the difference from the immediately preceding one, evaluation is performed by the same method as that performed on the difference from the immediately preceding one. Find the value. For example, a difference value between a pixel of interest X (x, y) and a pixel XR (y, x + 1) adjacent to the pixel XR (y, x + 1) is represented by a difference value d.
Let it be if_R. Each of the pixels X and XR is obtained by adding a watermark pattern M to the image P before adding the watermark pattern. For example,
The difference value diff_R is calculated as follows.

Diff_R = X (y, x) −XR (y, x + 1) = {P (y, x) + M (y, x)} − {P (y, x + 1) + M (y, x + 1)} = YR + M (Y, x) -M (y, x + 1) Here, YR = P (y, x) -P (y, x + 1).

The evaluation value sum is calculated using the difference value diff_R.
_R is calculated. Evaluation value sum_R when shift amount is 0
(0) is obtained as follows by calculating the inner product of M (y, x) and diff_R over the image.

Sum_R (0) = {{M (y, x) × diff_R} = {M (y, x) × YR} + {M (y, x) × M (y, x)} − Σ ｛ M (y, x) × M (y, x + 1)｝ Here, the first term in the above equation is an inner product with the image, so that almost 0
Becomes Also, the second term is the inner product of the in-phase series, so
It is almost α. Since the third term is an inner product with a series that is not in phase, it is almost zero. Summarizing the above, the following values can be derived.

Sum_R (0) ≒ α Then, the evaluation value sum_R (1) when the shift amount is 1 is as follows. In the following, the shift amount z
Has an effect on the x component of the image.

Sum_R (1) = {M (y, x + 1) × diff_R} = {M (y, x + 1) × YR} + {M (y, x + 1) × M (y, x)} − Σ ｛ M (y, x + 1) × M (y, x + 1)｝ Here, the first term of the above equation is an inner product with the image, so that almost 0
Becomes Since the second term is an inner product with a series that is not in phase, it is almost zero. Since the third term is the inner product of the series having the same phase, it is substantially -α. To summarize the above,
The following values can be derived.

Sum_R (1) ≒ -α Then, similarly, when the evaluation values other than the shift amounts 0 and 1 are obtained, all of them become almost 0.

Sum_R (z) ≒ 0 (z ≠ 0 and z ≠ 1) The above results are summarized as follows. That is,
The evaluation value sum_L (z) obtained using the immediately preceding difference changes depending on the shift amount z, and can be summarized as follows.

Sum_L (z) ≒ -α (z = 0) sum_L (z) ≒ α (z = -1) sum_L (z) ≒ 0 (z ≠ 0 and z ≠ -1) Here, the evaluation value sum_L ( The relationship between z) and the shift amount z is as shown in FIG.

The evaluation value sum_R (z) obtained by using the succeeding difference changes depending on the shift amount z, and can be summarized as follows.

Sum_L (z) ≒ α (z = 0) sum_L (z) ≒ -α (z = 1) sum_L (z) ≒ 0 (z ≠ 0 and z ≠ -1) Here, the evaluation value sum_R ( The relationship between z) and the shift amount z is as shown in FIG.

With these values, the additional amount can be amplified (or emphasized). Next, the amplification (emphasis) of this additional amount will be described.

For example, the evaluation value sum is calculated by the following equation.
Is calculated.

Sum (z) = sum_R (z) −sum_L (z) According to this equation, when the shift amount z = 0, the evaluation value su
m = 2α, and when the shift amount z = −1, 1, the evaluation value sum = −α, and for other shift amounts, the evaluation value sum becomes almost 0. . Here, the relationship between the evaluation value sum and the shift amount z is as shown in FIG.

Therefore, as described above, the evaluation value sum =
Sum_R−sum_L is calculated, and a shift amount z = −1,
The evaluation values in the case of 1 are averaged to obtain a standard evaluation value sum_a
When ve is obtained and compared with an actual evaluation value when the shift amount is 0, the additional amount α is amplified (or emphasized) three times. That is, from sum_ave ≒ -αsum_n ≒ 2α, sum = sum_n-sum_ave = 2α-(− α) = 3α, and the additional amount can be obtained as a triple amplification amount.

As described above, when the shift detection is performed by using the difference value, the additional amount is amplified in this manner, so that it is possible to reliably detect the accompanying information with higher detection accuracy than in the related art.

In the example described above, the effect of amplification (or emphasis) can be obtained only by calculating either the evaluation value sum_L or the evaluation value sum_R. For example, s
Regarding um_L, as shown in FIG. 3A, the difference between the evaluation values when the shift amount is −1 and the shift amount is 0 is 2
α. Therefore, a double amplification (or enhancement) effect can be obtained only by using the evaluation values at the time of these two shift amounts. Of course, such a configuration may be adopted.

Next, the second processing which makes the above-described processing executable
The configuration of the watermark detector according to the embodiment will be described.

As shown in FIG. 4, the watermark detector includes a watermark pattern holding memory 12 as storage means for storing a watermark pattern and a watermark pattern holding memory 12 stored in the watermark pattern holding memory 12. Pattern shifter 13 ₁ , 1 which is a phase setting means for setting a different phase to
3 _2, and the difference calculator 14 _1, 14 _2, which is a difference value calculating means for calculating a difference value between pixel values of the neighboring pixels in the input image data, the watermark pattern shifting unit 13 _1, 13 ₂ Evaluation value calculators 15 ₁ , 1, which are operation means for calculating an evaluation value based on the plurality of watermark patterns having different phases output from the above and the difference value.
5 ₂ , 15 ₃ , 16 ₁ , 16 ₂ , 16 ₃ and the evaluation value calculator 1
5 _1, 15 _2, 15 _3, 16 _1, 16 _2, 16 by comparing a plurality of evaluation values obtained by the _3, and a is an accompanying information detection means for detecting an accompanying information evaluation value comparator 17 ing. In addition, the watermark detector 11 includes an image converter 18 that processes an input image based on the result of the watermark collation. Note that the watermark detector 11 is hereinafter referred to as a “watermark detector of“ Configuration Example 1 ”in the second embodiment.

Next, each component of the watermark detector 11 will be described.

The difference calculators 14 ₁ and 14 ₂ calculate a difference value for each pixel of the input image data. Here calculated in the difference calculator 14 ₁ difference value is input to the evaluation value calculator 15 _1, 15 _2, 15 _3, the difference calculated in the difference calculating unit 14 _2, the evaluation value calculator 16 is input to the _1, 16 _2, 16 _3. The calculation of the difference value in the difference calculator 14 ₁ and the difference calculator 14 _2, may be carried out in a similar manner to each other or in different ways. For example, if the method of calculating the difference value is adopted different methods, the difference between the previous one in the difference calculator 14 _1, the difference between the difference calculator 14 _2, after one to calculate the difference value.

The watermark pattern holding memory 1
Numeral 2 is a storage means for storing a watermark in advance, and the watermark pattern shifter 13 ₁ , 1
3 _2, a watermark pattern that is recorded in the watermark holding memory 12 is shifted as required. Note that the watermark shifters 13 ₁ and 13 ₂ and the watermark holding memory 12 constitute additional information output means.

More specifically, the watermark pattern shifter 13 ₁ shifts the watermark pattern by the shift amount i, and the watermark pattern shifted by the shift amount i is sent to the evaluation value calculators 15 ₁ and 16 ₁ . is input, also shifting the watermark pattern by the watermark pattern shifting unit 13 ₂ is the shift amount j, the watermark pattern shifted by where shift amount j is input to the evaluation value calculator 15 _3, 16 ₃ .

The evaluation value calculators 15 ₁ , 15 ₂ , 15 ₃ ,
16 ₁ , 16 ₂ , and 16 ₃ calculate evaluation values using watermark patterns shifted as necessary. All the evaluation values calculated here are compared with the evaluation value comparator 1
7 is input.

The evaluation value comparator 17 performs a process of amplifying (or emphasizing) the additional amount based on the input evaluation value, performs a threshold process, and outputs the accompanying information f.

A portion for performing the amplification (or emphasis) processing of the additional amount may be provided outside and provided before the evaluation value comparator 17. Further, the input image data itself is output as it is.

The image converter 18 has a function of processing or processing input image data as needed.

The watermark detector 11 having such a configuration executes the detection processing of the accompanying information by a series of processing as shown in FIG. 5 and FIG.

The watermark detector 11 determines in step S
In step 21, the threshold value th is set, and the subsequent step S
At 22, the evaluation value sum_ is calculated using the difference from the immediately preceding one.
Prepare to find L. As a specific example of this preparation, for example, when the evaluation value is calculated by the evaluation value calculation units 15 ₁ , 15 ₂ , and 15 ₃ (the part performing the “difference value evaluation value calculation process” described later), the target pixel X When calculating the difference value xd, a difference value xd (z) described later with reference to FIG.
= X (z-1) -X (z).

Then, in steps S23 to S28, the watermark detector 11 sets the shift amount i,
Each evaluation value sum_L for the image of the current frame when the watermark pattern of 0, j is used
(I), sum_L (0), and sum_L (j) are obtained. For this reason, the watermark detector 11 uses the processing for calculating the evaluation value in each of the steps S24, S26, and S28 (the processing shown in FIG. Calculation process ”).

In the evaluation value calculation process, as shown in FIG. 6, the evaluation value sum is initialized in step S51, and then the watermark pattern is shifted by the shift amount z in step S52. Then, the watermark detector 11 performs the subsequent processing in step S53 and subsequent steps in the same manner as in steps S3 to S7 described with reference to FIG.

That is, the watermark detector 11
In step S52, an area having the same size as the area of the watermark pattern is set, and each pixel in the area is collated with the watermark pattern shifted by the shift amount z. The difference value xd of the pixel X is calculated. Then, in step S54, the watermark detector 11 determines the symbol of the watermark. Here, when the watermark symbol of the pixel is plus, the watermark detector 11 determines in step S
The process proceeds to 55, where the difference value xd is added to the evaluation value sum. If the watermark symbol of the pixel is negative, the process proceeds to step S56, where the difference value xd is subtracted from the evaluation value sum. Then, in step S57, the watermark detector 11 performs a determination process as to whether or not processing has been performed for all pixels in the target area. If it is confirmed that processing has not been performed for all pixels, Returning to step S52, the above-described processing such as the collation is performed again, and the processing is repeated for all the pixels in the target area. As described above, the watermark detector 11 calculates by this evaluation value calculation process.

Accordingly, the watermark detector 11 obtains the evaluation value sum_L (i) at the shift amount i by the difference value evaluation value calculation processing in steps S23 and S24 shown in FIG. Then, in steps S25 and S26, an evaluation value sum_L (0) when a watermark pattern having a shift amount z = 0 is used is obtained. Then, the watermark detector 11 that has obtained the evaluation value sum_L (0) at the shift amount z = 0 finally evaluates when the watermark pattern of the shift amount z = j is used in steps S27 and S28. Find the value sum_L (j).

Then, in the following step S29, the watermark detector 11 makes preparations for obtaining the evaluation value sum_R using the difference from the immediately succeeding one. As a specific example of this preparation, for example, in a case where an evaluation value is calculated by a difference value evaluation value calculation process, when calculating a difference value xd of a target pixel X, a difference value xd (z) = X (z) −X (z +
Setting to use 1) can be mentioned.

As described above, the evaluation value su for the shift amount z = i, 0, j is obtained by the difference value evaluation value processing.
Calculate m_R (z).

That is, the watermark detector 11
In step S30 and step S31, FIG.
The evaluation value sum_R (i) at the shift amount i is obtained by the difference value evaluation value calculation process shown in (1). Subsequently, in step S32 and step S33, the evaluation value when the watermark pattern with the shift amount z = 0 is used sum_
Find R (0). Finally, in steps S34 and S35, the evaluation value sum_R (j) when using the watermark pattern with the shift amount z = j
Ask for. The method of shifting the watermark pattern may be the same as the method described in the conventional example.

The watermark detector 11 performs step S
At 36, the six evaluation values sum_L (i), sum_L (0), and sum_L obtained as described above are obtained.
(J), sum_R (i), sum_R (0), sum
From _R (j), sum used for performing relative evaluation
_I, sum_n, and sum_j are calculated (conversion of the evaluation value is performed). The calculation method performed here will be briefly described. Sum_L and sum_L obtained for the same shift amount
Using the evaluation value of R, sum = sum_R-sum_L
That you are looking for. Such conversion of the evaluation value amplifies (or emphasizes) the additional amount when the accompanying information is detected. Therefore, this process can be considered as a process for amplifying (or enhancing) the additional amount.

Thereafter, the watermark detector 11 determines in step S37 that the evaluation values sum_i, sum_j
From the standard evaluation value sum_ave = (sum_i + s
um_j) / 2, and in a succeeding step S38,
Using this value sum_ave as a standard evaluation value, the absolute value | sum_n-sum_ave | of the difference from the actual evaluation value (evaluation value of shift amount 0) sum_n is obtained. here,
If the difference is greater than the threshold th, the watermark detector 11 proceeds to step S39 and shifts the phase r
Then, it is assumed that the additional information is added, and the additional information f is turned on. Otherwise, the process proceeds to step S40, and the additional information f is turned off.

The watermark detector 11 of the above configuration example 1 has two difference calculators and six evaluation value calculators. However, it is possible to take another form of reducing these numbers (reducing the amount of calculation) while having the same functions and effects. Next, the watermark detector will be described.

Here, the basic concept for reducing the calculation amount will be described first.

The watermark detector 11 of the first configuration example
Then, as described with reference to FIG. 3, the evaluation value sum
_L and sum_R are evaluated to find associated information and detect accompanying information.

On the other hand, the evaluation value sum_L and the evaluation value sum
In relation to _R, as shown in FIG. 7, a change in the evaluation value sum_R with respect to the shift amount z is regarded as equivalent to a change in the evaluation value sum_L with respect to the shift amount z shifted in the positive direction of the shift amount z. be able to.

For this reason, the process of obtaining the evaluation value sum_R is omitted, and instead, a value obtained by shifting the evaluation value sum_L by the shift amount 1 in the shifting direction is used as the evaluation value sum_R. In this way, for example, the amplification (or enhancement) effect similar to that of the watermark detector 11 of the above-described configuration example 1 can be obtained only by calculating the evaluation value sum_L in the case of the four shift amounts −2, −1, 0, and 1. Is obtained.

As described above, the structure that enables the substitution of the evaluation value by shifting the phase of the obtained evaluation value is similar to that of the watermark detector 3 shown in FIG.
It is one. The watermark detector 31 includes a watermark pattern holding memory 32, watermark pattern shifters 33 ₁ , 33 ₂ , 33 ₃ , a difference calculator 34, evaluation value calculators 35 ₁ , 35 ₂ , 35 ₃ , 35 ₄ , It comprises an evaluation value comparator 37 and an image converter 38. This watermark detector 31 is hereinafter referred to as a “watermark detector of“ Configuration Example 2 ”in the second embodiment.

[0187] The components of the watermark detector 31 will be described below.

The difference calculator 34 calculates a difference value for each pixel of the input image data. The difference values calculated here are used as evaluation value calculators 35 ₁ , 35 ₂ , 35
_3, it is input to the 35 _4.

The watermark pattern holding memory 3
Numeral 2 is a storage means for storing the watermark in advance, and the watermark pattern shifters 33 ₁ , 3
3 _2, 33 _3, the watermark patterns stored in the watermark pattern holding memory, shifted if necessary.

[0190] Specifically, shifting the watermark pattern by the watermark pattern shifting unit 33 ₁ is offset amount i, the watermark that is shifted by where shift amount i, is input to the evaluation value calculator 35 _2, also , shifting the watermark pattern by the watermark pattern shifted 33 ₂ shift amount j, the watermark that is shifted by where shift amount j, evaluation value calculator 35 ₄
Is input to the further shifting the watermark pattern by the watermark pattern shifted 33 ₃ shift amount h, water marks offset by where shift amount h is input to the evaluation value calculator 35 _1.

The evaluation value calculators 35 ₁ , 35 ₂ , 35 ₃ ,
35 _4, using the watermark pattern are offset as necessary, calculates the respective evaluation values. All the calculated evaluation values are input to the evaluation value comparator 37.

The evaluation value comparator 37 performs a process of amplifying (or emphasizing) the additional amount based on the input evaluation value, performs threshold processing, and outputs the accompanying information f.

A portion for performing the amplification (or emphasis) processing of the additional amount may be provided outside and provided before the evaluation value comparator 37. Further, the input image data itself is output as it is.

The image converter 38 has a function of processing or processing input image data as needed.

The watermark detector 31 of the second configuration example having the above-described components has the difference calculator and the evaluation value calculator reduced from the watermark detector 11 of the first configuration example. Function and effect can be maintained.

In this embodiment, only the same shift amount (for example, three of i, o, and j) as in the conventional example may be used. However, in order to enhance the effect of amplifying (or enhancing) the additional amount by using the difference value, the watermark detector 31 is used.
Of the evaluation value calculator 35 ₁ and the watermark pattern shifted 33 ₃ (may be more a) provided, the shift amount other than it (for example, h) may be calculated evaluation value with respect.

The watermark detector 31 having such a configuration executes the detection processing of the accompanying information by a series of processing as shown in FIG.

The watermark detector 31 determines in step S
In step 71, a threshold value th is set, and the subsequent step S
At 72, the evaluation value sum_
Prepare to find L. As a specific example of this preparation, for example, in a case where an evaluation value is calculated by a difference value evaluation value calculation process, when calculating the difference value xd of the target pixel X, the difference value xd (z) = X (z−1) ) -X (z).

Then, in steps S73 to S80, the watermark detector 31 sets the shift amount i,
Each evaluation value sum_L for the image of the current frame when the watermark pattern of 0, j is used
(H), sum_L (i), sum_L (0), sum
_L (j). For this purpose, the watermark detector 31 performs the above-described difference value evaluation value calculation processing (processing shown in FIG. 6) for calculating the evaluation value in each of steps S74, 76, 78, and 80. I have.

That is, the watermark detector 31
In steps S73 and S74, the evaluation value su at the shift amount h is obtained by the difference value evaluation value calculation processing.
Find m_L (h). Then, in the subsequent steps S75 and S76, the watermark detector 31 that has obtained the evaluation value sum_L (h) at the shift amount z = h uses the evaluation value sum_L ( i), and in steps S77 and S78, the shift amount z =
Evaluation value su when a watermark pattern of 0 is used
m_L (0) is obtained, and in steps S79 and S80, an evaluation value sum_L (j) when a watermark pattern having a shift amount z = j is used is obtained.

Note that, for example, the evaluation value sum_L (h) using the watermark pattern with the shift amount z = h may not be obtained, but in this case, the effect of amplifying (or enhancing) the additional amount is small. Become. The method of shifting the watermark pattern may be the same as, for example, the method described in the conventional example.

The watermark detector 31 determines in step S
At 81, the four evaluation values sum_L (h), sum_L (i), and sum_L obtained as described above are obtained.
From (0), sum_L (j), sum_i, sum_n, and sum_j used for performing relative evaluation are calculated (evaluation value conversion is performed).

The calculation method performed here will be described in brief. The evaluation value sum_L obtained by shifting the evaluation value sum_L in the positive direction (the right direction in FIG. 7A) of the shift amount is the evaluation value sum_R (FIG. )). That is, as shown in FIG. 8, the evaluation value sum_L (z)
The above evaluation value sum_R, which is an evaluation value indicating a difference after the evaluation value sum_L (z + 1) ((B) in FIG. 10) obtained by shifting the shift amount z in the plus direction with respect to ((A) in FIG. 10). It is calculated assuming that

Specifically, the evaluation value sum_L (z + z) obtained by shifting the evaluation value sum_L (z) by a shift amount 1
1) is regarded as the evaluation value sum_R (z), and the evaluation value sum
(Z) = sum_R (z) −sum_L (z) = sum
_L (z + 1) -sum_L (z) is obtained ((C) in FIG. 10).

The conversion of the evaluation value amplifies (or emphasizes) the additional amount when detecting the accompanying information. Therefore, this process can be considered as a process for amplifying (or enhancing) the additional amount.

Thereafter, the watermark detector 31 determines in step S82 that the evaluation values sum_i, sum_j
From the standard evaluation value sum_ave = (sum_i + s
um_j) / 2, and in a succeeding step S83,
Using this value sum_ave as a standard evaluation value, the absolute value | sum_n-sum_ave | of the difference from the actual evaluation value (evaluation value of shift amount 0) sum_n is obtained. here,
If the difference is larger than the threshold th, the watermark detector 321 proceeds to step S84, and considers that the accompanying information is added at the shift phase r, and the accompanying information f
Is turned on, otherwise, the process proceeds to step S85, and the accompanying information f is turned off.

For example, when the evaluation value sum_L (h) for the shift amount z = h is not obtained, the evaluation value sum
Any value may be substituted for _L (h). Or,
Processing that requires the evaluation value sum_L (h) may be omitted, and a configuration may be adopted in which the influence is taken into account at the time of determination. In either case, the effect of amplifying (or enhancing) the additional amount is reduced.

The watermark detector 31 of the above configuration example 2 has a configuration in which one difference calculator and two evaluation value calculators are reduced compared to the watermark detector 11 of the above configuration example 1. ing. Next, a description will be given of a watermark detector capable of further reducing the amount of calculation.

First, an example of a basic concept for reducing the calculation amount will be described. In the watermark detectors of Configuration Example 1 and Configuration Example 2 described above, when the relative evaluation is performed using the evaluation value obtained for each shift amount, the evaluation value sum is calculated.
(Z) = sum_R (z) -sum_L (z) is used to convert the evaluation value (where z = i, n, j = 3)
Only points, n = 0).

By developing this equation and expressing it with the image P before adding a watermark pattern and the watermark pattern M, the following equation can be derived. Note that, in the following, the formula is developed taking as an example a case where the shift amount z affects the x component of the image.

Sum (z) = sum_R (z) −sum_L (z) = {M (y, x + z) × diff_L (z)} − {M (y, x + z) × diff_L (z)} = {[ M (y, x + z) × {YR (z) + M (y, x + z) −M (y, x + z + 1)}] − {[M (y, x + z) × ｛YL (z) + M (y, x + z−1) −M (y, x + z)}] = M (y, x + z) × {YR (z) −YL (z) −M (y, x + z−1) + 2M (y, x + z) −M (y, x + z + 1) ｝ Here, YL (z) = P (y, x + z−1) −P (y, x + z) YR (z) = P (y, x + z) −P (y, x + z + 1) Therefore, sum (z) = M (y, x + z) × {[｛− P (y, x + z−1) + 2P (y, x + z) −P (y, x + z + 1)} + ｛− M (y, x + z−1 ) + 2M (y, x + z) −M (y, x + z + 1)}] Further, for the pixel of interest, X (z) = P (y, x + z) + M (y, x + z) For the immediately preceding pixel, XL (z-1) = P (y, x + z-1) + M (y, x +
z-1) For the next pixel, XR (z + 1) = P (y, x + z + 1) + M (y, x +
z + 1). Therefore, sum (z) = M (y, x + z) × Σ ｛−XL (z−
1) + 2X (z) −XR (z + 1)｝ From the above relationship, the converted evaluation values used when the watermark detectors of the above-described configuration examples 1 and 2 relatively perform the evaluation are: From the beginning, the difference value x is used as the difference value xd
It can be seen that the evaluation value obtained by using d = −X (z−1) + 2X (z) −X (z + 1) finally matches the evaluation value.

Instead of using the difference before and after and the difference after one, the difference value xd = −X (z−z
1) By using + 2X (z) -X (z + 1), z = i,
Amplifying (or enhancing) effects similar to those of the watermark detectors of the above configuration examples 1 and 2 can be obtained only by obtaining evaluation values for three shift amounts of n and j (where n = 0). become.

As described above, by using the difference value between before and after, from the beginning, not only the reduction in the amount of calculation when obtaining the evaluation value, but also the conversion processing of the evaluation value for amplifying (or enhancing) the additional amount. A configuration that can be omitted is the watermark detector described here.

Note that the watermark detector described here is hereinafter referred to as a “watermark detector of“ Configuration Example 3 ”in the second embodiment.

The configuration of the watermark detector of Configuration Example 3 is substantially the same as that of the watermark detector 11 of Configuration Example 2 shown in FIG.

That is, in the input image data, a difference value for each pixel is calculated in a difference calculator 34, and a plurality of evaluation value calculators 35 ₁ , 35 ₂ , 35 ₃ , 3 are calculated.
Is input to the 5 _4.

The watermark patterns recorded in the watermark pattern holding memory 32 can be replaced with watermark pattern shifters 33 ₁ , 33 ₂ , 33 as necessary.
Staggered by ₃ .

Evaluation value calculators 35 ₁ , 35 ₂ , 35 ₃ , 35 ₄
Then, evaluation values are calculated using watermark patterns shifted as necessary.

[0219] The calculated evaluation value is input to the evaluation value comparator 38, subjected to threshold processing, and the accompanying information f is output. The input image data itself is output as it is.

[0220] Incidentally, (a portion indicated by a dotted line in FIG. 8) the evaluation value calculator 35 ₁ and the watermark pattern shifted 33 ₃ is not essentially necessary, may at all be used them provided .

The watermark detector according to the third configuration example performs the detection process of the accompanying information by a series of processes as shown in FIG.

The watermark detector of Configuration Example 3 sets the threshold value th in step S91, and in the subsequent step S92, uses the difference from the immediately preceding value to evaluate the value s.
Prepare for um. As a specific example of this preparation, for example, in the case where the evaluation value is calculated by the above-described evaluation value calculation processing for a difference value (the processing shown in FIG. 6), when calculating the difference value xd of the target pixel X, the difference value xd (Z) =-X
Setting that uses (z-1) + 2X (z) -X (z + 1) may be performed.

Then, steps S93 to S98 are performed.
, The respective evaluation values sum_i, sum_n, and sum_j for the image of the current frame when the watermark pattern having the shift amounts i, 0, and j are used. Here, in each of the steps S94, 96, and 98, the above-described difference value evaluation value calculation processing for calculating the evaluation value is performed.

That is, the watermark detector obtains the evaluation value sum_i at the shift amount i by the above-described evaluation value calculation processing in steps S93 and S94, and in subsequent steps S95 and S96,
The evaluation value sum_n when using the watermark pattern with the shift amount z = 0 is obtained, and in step 97 and step S98, the evaluation value sum_j when using the watermark pattern with the shift amount z = j is obtained. The method of shifting the watermark pattern may be the same as, for example, the method described in the conventional example.

The watermark detector operates in step S99.
In the above, the above three evaluation values s obtained as described above
From um_i, sum_n, and sum_j, relative evaluation is performed to obtain accompanying information.

Thereafter, in step S100, the watermark detector uses the standard evaluation value sum_ave = (sum_i + su) from the evaluation values sum_i and sum_j.
m_j) / 2, and in a succeeding step S101,
Using this value sum_ave as a standard evaluation value, the absolute value | sum_n-sum_ave | of the difference from the actual evaluation value (evaluation value of shift amount 0) sum_n is obtained. here,
If the difference is greater than the threshold th, the watermark detector proceeds to step S101, and considers that the accompanying information f has been added at the shift phase r and sets the accompanying information f to o.
n, otherwise, the process proceeds to step S102, and the accompanying information f is turned off.

As described above, the watermark detector according to the second embodiment configured as in the first, second, and third configuration examples detects displacement and detects accompanying information. .

In the watermark detector according to the second embodiment, when the watermark pattern used for adding the accompanying information is a pattern having a special property such as an M-sequence, the difference value The additional amount can be amplified by obtaining the evaluation value by using. That is, for example, in an M-sequence, if the inner product of a sequence in phase with the sequence is taken, the correlation becomes high, and if the inner product of a sequence not in phase is taken, the correlation becomes low. By taking the difference, it is possible to provide a phase having a high correlation other than the same phase, and it is possible to amplify (or enhance) the additional amount by using those phases.

Here, with respect to the watermark detector according to the second embodiment configured as in the above-described configuration example 1, configuration example 2, and configuration example 3, the following modifications are possible. ing.

For example, with respect to the watermark detector configured as in Configuration Example 1, Configuration Example 2, and Configuration Example 3,
Difference value xd (z) = X (z−1) −X
(Z), difference value xd (z) = X (z) −X
(Z + 1), a difference value xd (z) = − X (z−
1) Taking the case of using + 2X (z) -X (z + 1) as an example,
And explained.

However, there is no need to be limited to such a difference value, and various methods of calculating the difference value xd for the pixel X can be considered. The method may be the same as the method described variously in the watermark detector 2 configured as shown in FIG. 1, for example. Of course, a configuration may be used in which a difference value between two before and nine after is used instead of a difference value between one before and one after.

The shift amount z (or h, i, 0,
The case where j) affects the x component of the image has been described as an example. However, there is no need to be limited to such a shifting method, and various methods of shifting the watermark pattern can be considered. The method may be, for example, as described with reference to FIG. 34 in the conventional example, a method of shifting in accordance with the scanning order of images, or any other method. The unit of shifting is not limited to one pixel unit, but may be shifted in units of an arbitrary area. The shift amount is i> 0, j <0, | i |
= | J |, it is better to shift the same amount back and forth with the shift amount 0 as the center, but any shift amount is acceptable.

In general, since the correlation between neighboring pixel values is high in an image, the difference value of the pixel X is 0 on average.
However, if the pixel position is on the boundary of the edge,
The absolute value of the difference value often becomes a large value, and the evaluation value is greatly affected by the difference value. In order to avoid this, when the absolute value of the difference value exceeds a certain range, the difference value need not be reflected in the evaluation value. Alternatively, the value may be clipped. As a specific example, when the absolute value of the difference | xd |> range, the difference value xd is set as follows.

Xd = 0 Or set as follows.

Xd = range (xd ≧ 0) xd = −range (xd <0) Further, not only one shift amount before and after, but a plurality of shift amounts are used, and all or some of the shift amounts obtained for them are used. For the evaluation value, a standard evaluation value may be configured using a filter or the like. Conversely, a standard evaluation value may be configured using only one of the shift amounts, for example, using only the previous shift amount.

In addition, iterative processing is performed for the shift amount of decimal precision, and in such a case, the evaluation value may be obtained by interpolating the watermark pattern or the pixel of the target area.

When a standard evaluation value for the image of the current frame is obtained, any processing method may be used. For example, a filter such as a median filter is applied, and three evaluation values sum_n, sum_i, and sum_j
With respect to the standard evaluation value su for the image of the current frame.
m_med may be obtained. Here, the median filter is a filter that returns the value at the center position after rearranging the input numerical value sequence in ascending or descending order.
For example, when five numerical values of 71, 8, -345, 68, and -2 are input, the median filter is set to -34.
Sort them like 5, -2, 8, 68, 71 etc.
Returns 8. The standard evaluation value sum obtained in this way
The absolute value of the difference between _med and the actual evaluation value sum_n is obtained, and if the difference is greater than the threshold th, it is determined that the accompanying information has been added, and the accompanying information f is turned on. Otherwise, the associated information f is turned off.

In addition, an evaluation value of an arbitrary single phase may be used as it is, or an average value, a maximum value, a minimum value, etc., of all or some of a plurality of evaluation values may be obtained and used. The standard evaluation value may be obtained using any processing method. This includes, for example,-
From the transition of the evaluation value when shifted by 2 and −1, the shift amount is 0
A more complicated processing method, such as predicting or extrapolating the evaluation value at the time, is also included.

When comparing with a threshold value using a standard evaluation value and an actual evaluation value, any comparison method other than the above-described comparison method may be used. For example, by using the fact that the bias component B of the evaluation value (corresponding to (4n) / 2 in the example described with reference to FIGS. 22 to 24) is constant, it is determined how much the bias component is held. The comparison may be performed with a bias reliability coefficient c (0 ≦ c ≦ 1) indicating whether or not to be considered. This will be described with a specific example.

In the case where the evaluation value when the shift amount is 0 is larger than the evaluation value when the shift amount i is shifted earlier by B × c, and the shift amount is 0 than the evaluation value when the shift amount is shifted by the shift amount j later When the evaluation value is larger by B × c, it is considered that the accompanying information is added. Alternatively, the shift amount i,
If the evaluation value at the time of the shift amount 0 is larger than the evaluation value at the time of shifting to any one of j by B × c, it is regarded that the accompanying information is added.

As described above, utilizing the fact that the bias component B of the evaluation value is constant, the bias reliability coefficient c (0 ≦
By comparing with c ≦ 1), it is possible to detect accompanying information.

The watermark symbol may be any symbol other than plus and minus. In addition, any two or more types of symbols may be used instead of the two types. For example, three types of symbols, plus, zero, and minus, are prepared, and a pixel whose symbol is zero when matching with a watermark pattern does not affect the evaluation value sum (the pixel value May not be added to or subtracted from the evaluation value sum).

The area where the watermark pattern is added on the image may have any shape and range. Furthermore, the shape and range of the area for which the evaluation value is to be obtained at the time of detection may be arbitrarily set as long as the matching with the added watermark pattern is achieved. Then, the watermark pattern uses a wider area that extends over time or space,
Addition or detection may be performed. For example, in a moving image sequence, a temporal reference is used, and not only the temporal position of the current frame but also past and future frames may be used. For example, in a still image having a very large image size, one image is divided into a plurality of image areas in a certain unit and handled. For example, image areas located before and after in the scanning order may be used.

The above is the description of the watermark detector according to the second embodiment. Next, a watermark detector according to a third embodiment will be described.

The watermark detector according to the third embodiment uses a standard evaluation value and an actual evaluation value to determine a threshold value when relatively evaluating an evaluation value and detecting accompanying information. When the comparison is performed, the phase of the plurality of shift amounts is referred to and the phases are comprehensively determined. In this way, by devising a method of calculating the difference value, the comparison can be performed for a plurality of phases, and the reliability of detection can be increased.

Here, a method of obtaining a difference value using a plurality of pixels from among several methods of calculating the difference value xd for the pixel X described in the first embodiment will be described as an example.

For example, in the case of a horizontal difference, when calculating the difference value xd for the pixel X0, four pixels X0 adjacent to the right are used.
(Y, x), X1 (y, x + 1), X2 (y, x +
2), X3 (y, x + 3) may be used.
From this, the difference values xd1, xd2, xd3 are obtained as follows.
Ask for.

Xd1 = X0-X1 + X2-X3 xd2 = X0-X1-X2 + X3 xd3 = X0 + X1-X2-X3 where X0, X1, X2 and X3 are all relative to the image P before the watermark pattern is added. And a watermark pattern M is added. That is,
The value is as shown below.

X0 = P (y, x) + M (y, x) X1 = P (y, x + 1) + M (y, x + 1) X2 = P (y, x + 2) + M (y, x + 2) X3 = P (y , X + 3) + M (y, x + 3) Here, the evaluation value sum_1 is calculated using the difference value xd1. The evaluation value sum_1 (0) when the shift amount is 0 is obtained by calculating the inner product of M (y, x) and the difference value xd1 over the image. That is, it can be represented by the following equation. sum_1 (0) = {M (y, x) × xd1} = Σ
{M (y, x) × Y1} + {M (y, x) × M (y,
x)｝ − {M (y, x) × M (y, x + 1)} + Σ
{M (y, x) × M (y, x + 2)} − {M (y,
x) × M (y, x + 3)｝ where Y1 = P (y, x) −P (y, x + 1) + P
(Y, x + 2) -P (y, x + 3).

Here, + {M (y, x) × M (y, x)} in the second term of the above expression sum — 1 (0) is substantially the same as α because it is an inner product of in-phase series. Term is almost 0
Becomes Therefore, sum_1 (0) ≒ α. Similarly, the evaluation value in the case of the shift amounts 1, 2, 3 is sum_1 (1) ≒ -αsum_1 (2) ≒ αsum_1 (3) ≒ -α. Similarly, when the evaluation values other than the shift amounts of 0, 1, 2, and 3 are obtained, all of them become almost zero. That is, sum_1 (z) ≒ 0 (z ≠ 0 and z ≠ 1 and z ≠
2 and z ≠ 3).

The evaluation value sum_1 in the case of the difference value xd1 thus derived is as shown in FIG. 12A in relation to the shift amount z.

Next, the evaluation value sum is calculated using the difference value xd2.
_2 is calculated. Evaluation value sum_2 when shift amount is 0
(0) is obtained by calculating the inner product of M (y, x) and the difference value xd2 over the image. That is, it can be represented by the following equation.

Sum_2 (0) = {M (y, x) × x
d2} = {M (y, x) × Y2} + {M (y, x)
× M (y, x)｝ − Σ ｛M (y, x) × M (y, x +
1) {− {M (y, x) × M (y, x + 2)} +}
{M (y, x) × M (y, x + 3)} where Y2 = P (y, x) -P (y, x + 1) -P
(Y, x + 2) + P (y, x + 3).

Here, + {M (y, x) × M (y, x)} of the second term of the above expression sum_2 (0) is substantially an α because it is an inner product of a series having the same phase. Term is almost 0
Becomes Therefore, sum_2 (0) ≒ α. Similarly, the evaluation value in the case of the shift amounts 1, 2, and 3 is sum_2 (1) ≒ -αsum_2 (2) ≒ -αsum_2 (3) ≒ α. Similarly, when the evaluation values other than the shift amounts of 0, 1, 2, and 3 are obtained, all of them become almost zero. That is, sum_2 (z) ≒ 0 (z ≠ 0 and z ≠ 1 and z ≠
2 and z ≠ 3).

The evaluation value sum_2 in the case of the difference value xd2 derived in this way is as shown in FIG. 12B in relation to the shift amount z.

Next, the evaluation value sum is calculated using the difference value xd3.
_3 is calculated. Evaluation value sum_3 when shift amount is 0
(0) is obtained by calculating the inner product of M (y, x) and the difference value xd3 over the image. That is, it can be represented by the following equation.

Sum — 3 (0) = Σ ｛M (y, x) × x
d3} = {M (y, x) × Y3} + {M (y,
x) × M (y, x)｝ + Σ ｛M (y, x) × M (y, x
+1)｝ − {M (y, x) × M (y, x + 2)} − Σ
{M (y, x) × M (y, x + 3)} where Y3 = P (y, x) + P (y, x + 1) -P
(Y, x + 2) -P (y, x + 3).

Here, + {M (y, x) × M (y, x)} of the second term of the above expression sum — 3 (0) is substantially the same as α because it is an inner product of a series having the same phase. Term is almost 0
Becomes Therefore, sum_3 (0) ≒ α. Similarly, the evaluation value in the case of the shift amounts 1, 2, 3 is sum_3 (1) {αsum_3 (2)} − αsum_3 (3) ≒ −α. Similarly, when the evaluation values other than the shift amounts of 0, 1, 2, and 3 are obtained, all of them become almost zero. That is, sum_3 (z) ≒ 0 (z ≠ 0 and z ≠ 1 and z ≠
2 and z ≠ 3).

The evaluation value sum_3 in the case of the difference value xd3 derived in this way is as shown in FIG. 12C in relation to the shift amount z.

As described above, the evaluation value sum_
1, sum_2, and sum_3 were obtained. For example, the following evaluation values sum_p0, sum_p1, sum_p
By performing the conversion to 2, sum_p3, the additional amount amplification effect described in the second embodiment can be obtained with a plurality of shifted phases. That is, by sum_p0 = sum_1 + sum_2 + sum_3, a peak value can be obtained at a shifted phase 0 as shown in FIG. In addition, by sum_p1 = −sum_1−sum_2 + sum_3, a peak value can be obtained in the shift phase 1 as shown in FIG. Further, by sum_p2 = sum_1-sum_2-sum_3, a peak value can be obtained in the shifted phase 2 as shown in FIG. Then, by sum_p3 = −sum_1 + sum_2−sum_3, a peak value can be obtained at the shift phase 3 as shown in FIG.

Therefore, for example, sum_p0 (0), su
m_p1 (1), sum_p2 (2), sum_p3
When the peak value is reached in all of (3), it can be determined that the accompanying information has been added. With this configuration, the determination of presence / absence of the accompanying information, which can basically target only one phase of the shift amount (shift amount 0), can be performed for a plurality of phases. Can be raised.

Next, the configuration of a watermark detector according to a third embodiment which enables this processing will be described with reference to FIG.

The watermark detector according to the third embodiment includes a watermark pattern holding memory 52, a watermark pattern shifter 53, a difference calculator 54 ₁ ,
· · ·, 54 _n, the evaluation value calculator 55 _1, ···, 55 _m,
An evaluation value comparator 57 and an image converter 58 are provided. In this embodiment, since the configuration of the evaluation value comparator is characteristic,
Other parts will be described conceptually.

In the watermark detector 51 configured as described above, the difference value for each pixel is calculated by _n difference calculators 54 ₁ ,..., 54 _n of the input image data. You. Then, the calculated difference value is calculated by using a plurality of m evaluation value calculators 55 ₁ ,.
Input to 5 _m . Note that each difference calculator 54 ₁ ,.
The method of calculating the difference value by 54 _n may use the same method as each other or a different method.

The watermark pattern recorded in the watermark pattern holding memory 52 is shifted by the watermark pattern shifter 53 as needed.

Each of the evaluation value calculators 55 ₁ ,..., 55 _m calculates an evaluation value by using a watermark pattern shifted as necessary. The calculated evaluation value is input to the evaluation value comparator 57, and after a process of amplifying (or emphasizing) the additional amount is performed, a threshold process is performed, and the accompanying information f is output.

A portion for performing the amplification (or emphasis) processing of the additional amount may be provided outside and provided before the evaluation value comparator 57. Further, the input image data itself is output as it is.

The image converter 58 is not indispensable, but may be placed, and the image converter 58 processes the image data.

The above-described evaluation value comparator 57 is a feature of the watermark detector 51 according to the third embodiment, and is specifically configured as shown in FIG. FIG. 16 shows a configuration example of a conventional evaluation value comparator in order to clarify the characteristics. For example, in the conventional watermark detector 321, as shown in FIG. 33 described above, the evaluation values calculated by the evaluation value calculators 323 ₁ , 323 ₂ , and 323 ₃ are input to the evaluation value comparator 324. . Correspondingly, the conventional evaluation value comparator 324 shows a case where three evaluation values are input as shown in FIG. 16, for example.

The correspondence between the shift amounts (and the evaluation values) shown in FIGS. 16 and 33 is as shown in Table 1. In addition, in order to prevent the figure from becoming complicated, the “shift amount z
What should be described as “evaluation value in case of 1” is abbreviated as “shift amount z1”.

[0271]

[Table 1]

The conventional evaluation value comparator 324 calculates the addition values of the adders 401 and 1/1 from the evaluation values of the shift amounts z1 and z2, for example.
The average value derived by the squarer 402 is regarded as a standard evaluation value, and a difference is calculated by the subtracter 403 from this value and the evaluation value when the shift amount is 0. Then, the absolute value of the difference is taken by the absolute value converter 404, and the value is compared with the threshold value by the comparator 405. When the value is larger than the threshold, the conventional evaluation value comparator 324 evaluates that the accompanying information is added, and turns on the accompanying information f. Otherwise, the accompanying information f
Is turned off.

Evaluation value comparator 57 in the present embodiment
Are the adders 71 ₁ , 71 ₂ , 71 as shown in FIG.
_3, 71 _4, 1/2 multipliers 72 _1, 72 _2, 72 _3, 72 _4,
Subtractors 73 ₁ , 73 ₂ , 73 ₃ , 73 ₄ , absolute value converter 7
4 _1, 74 _2, 74 _3, 74 _4, comparators 75 _1, 75 _2, 75
₃ , 75 ₄ , and a total judgment unit 76.

The construction of the evaluation value comparator 57 is as follows.
As can be seen from the comparison with the conventional evaluation value comparator 324 shown in FIG.
It is characterized in that a total judgment unit 76 for judging these evaluation results comprehensively is provided. The configuration of the evaluation value comparator 57 is an example when the difference values (difference values xd1, xd2, xd3) described earlier in the description of the third embodiment are used, that is, the evaluation of the accompanying information. Any difference value or configuration may be used as long as two or more steps can be taken.

The evaluation values calculated by the evaluation value calculators 55 ₁ ,..., 55 _m shown in FIG. 14 are input to the evaluation value comparator 57. When calculating these evaluation values, difference values are used. For example, the difference values (difference values xd1, xd2, x
When d3) is used, the relationship between the evaluation value and the shift amount is shown in FIG.
As shown in FIG. The correspondence between the shift amounts shown in FIGS. 13 and 15 is as shown in Table 2.

[0276]

[Table 2]

The processing performed by the evaluation value comparator 57 in the case of evaluation values z1, z2, z3 will be described.
Evaluation value comparator 57, regarded as a standard evaluation values an average value derived by the adder 71 ₁ and 1/2 multiplier 72 ₁ from the evaluation value z1, z2 input, shift amount and the value 0
The difference is calculated by the subtractor 731 from the evaluation value in the case of ( ₁₎ . Then, the absolute value of this difference is converted to an absolute value converter 74 _1.
Taken in are compared in the comparator 75 ₁ and its value with a threshold value. Then, when the value is larger than the threshold value, the evaluation value comparator 57 evaluates that the accompanying information is added, and turns on the accompanying information f. If not, the associated information f is turned off.

Similarly, evaluation values z4 to z12
Is calculated in each corresponding part to detect the presence or absence of accompanying information.

[0279] Finally, the evaluation value comparator 57 comprehensively judges the accompanying information detected in each stage by the overall judgment unit 76. The determination criterion may be any criterion, for example, if the accompanying information f of all stages is on
Only when is the final incidental information f is determined to be on, otherwise, the final incidental information f is turned off.
Is determined. Alternatively, the judgment criterion is that if the incidental information f of any stage is on, the final incidental information f is turned on.
Otherwise (if the associated information f of all stages is o
ff), the final accompanying information f is determined to be off. Of course, other methods may be used.

In the present embodiment, the case of a difference value using four pixels adjacent to the right has been described. However, if it is possible to take two or more stages for evaluating the accompanying information, Other than this difference value may be used. The pixels used for calculating the difference value need not be continuous, and may be configured to use, for example, a difference value between two pixels before and nine pixels after.

There are various ways of shifting the watermark pattern. The method is described in, for example, FIG.
As shown in FIG. 4, a method of shifting in accordance with the scanning order of the image may be used, or another method may be used. The unit of shifting is not limited to one pixel unit, but may be shifted in units of an arbitrary area. It is better to shift the shift amount by the same amount before and after the shift amount 0, such as i> 0, j <0, | i | = | j |, but any shift amount may be used.

Generally, since the correlation between neighboring pixel values in an image is high, the difference value of pixel X is 0 on average.
become. However, when the pixel position is at an edge boundary or the like, the absolute value of the difference value is often large, and the evaluation value is greatly affected by the difference value. In order to avoid this, when the absolute value of the difference value exceeds a certain range, the difference value need not be reflected in the evaluation value. Alternatively, the value may be clipped.

Specifically, when the absolute value of the difference value is a predetermined value ra
If | xd |> range in relation to nge, the evaluation value xd is set to the evaluation value xd = 0. Or
Set as follows.

Xd = range (xd ≧ 0) xd = −range (xd <0) It is to be noted that not only one shift amount before and after each but also a plurality of shift amounts are used, and all or some of the shift amounts obtained for these are used. For the evaluation value, a standard evaluation value may be configured using a filter or the like. Conversely, a standard evaluation value may be configured using only one of the shift amounts, for example, using only the previous shift amount.

Also, iterative processing is performed for the shift amount of decimal precision, and in such a case, the evaluation value may be obtained by interpolating the watermark pattern or the pixels of the target area.

When a standard evaluation value for the image of the current frame is obtained, any processing method may be used. For example, a filter such as a median filter may be applied to obtain a standard evaluation value sum_med for the image of the current frame with respect to the evaluation values in the case of, for example, three shift amounts z1, z2, and z3. The absolute value of the difference between the standard evaluation value sum_med thus obtained and the actual evaluation value (e.g., the evaluation value in the case of the shift amount z3) is obtained, and when the difference is larger than the threshold th, It is assumed that the accompanying information is added, and the accompanying information f is turned on. Otherwise, the associated information f is turned off.

In addition, an evaluation value of an arbitrary single phase may be used as it is, or an average value, a maximum value, a minimum value, etc., of all or some of a plurality of evaluation values may be obtained and used. The standard evaluation value may be obtained using any processing method. This includes, for example,-
From the transition of the evaluation value when shifted by 2 and −1, the shift amount is 0
A more complicated processing method, such as predicting or extrapolating the evaluation value at the time, is also included.

When comparing the threshold value using the standard evaluation value and the actual evaluation value, any comparison method other than the comparison method described above may be used. For example, by using the fact that the bias component B of the evaluation value (corresponding to (4n) / 2 in the example described with reference to FIGS. 22 to 24) is constant, it is determined how much the bias component is held. The comparison may be performed with a bias reliability coefficient c (0 ≦ c ≦ 1) indicating whether or not to be considered. This will be described with a specific example.

In the case where the evaluation value when the shift amount is 0 is larger than the evaluation value when the shift amount i is shifted before, and the shift amount is larger than the evaluation value when the shift amount is shifted by j after the shift amount j, When the evaluation value is larger by B × c, it is considered that the accompanying information is added. Alternatively, the shift amount i,
If the evaluation value at the time of the shift amount 0 is larger than the evaluation value at the time of shifting to any one of j by B × c, it is regarded that the accompanying information is added.

As described above, using the fact that the bias component B of the evaluation value is constant, the bias reliability coefficient c (0 ≦ 0) indicating how much the bias component is considered to be held.
By comparing with c ≦ 1), it is possible to detect accompanying information.

Further, any symbol other than plus and minus may be used as the watermark symbol. In addition, any two or more types of symbols may be used instead of the two types. For example, three types of symbols, plus, zero, and minus, are prepared, and a pixel whose symbol is zero when matching with a watermark pattern does not affect the evaluation value sum (the pixel value May not be added to or subtracted from the evaluation value sum).

Furthermore, the area where the watermark pattern is added on the image may have any shape and range. Further, as long as the matching with the added watermark pattern is achieved, the shape and range of the area for which the evaluation value is obtained at the time of detection may be arbitrary. Then, the watermark pattern uses a wider area that extends over time or space,
Addition or detection may be performed. For example, in a moving image sequence, a temporal reference is used, and not only the temporal position of the current frame but also past and future frames may be used. For example, in a still image having a very large image size, one image is divided into a plurality of image areas in a certain unit and handled. For example, image areas located before and after in the scanning order may be used.

When the difference value is compared with the watermark pattern in the first embodiment, the watermark pattern itself may be used as the difference value.

For example, when a watermark is detected by the processing shown in FIG. 2, the symbol of the watermark pattern is switched (the pattern is inverted).
The evaluation value sum may be calculated only for the pixel. Further, for example, some processing may be performed when a watermark is added by the processing as shown in FIG. 30 described above.

In the first embodiment, etc., the evaluation value s
When comparing um with the threshold th, the threshold th may reflect the proportion of pixels in which the watermark pattern is inverted.

That is, for example, when the ratio of pixels in which the pattern is inverted is 50% of the whole, a value of th × 50/100 may be used as the threshold th. Alternatively, the evaluation value sum may be multiplied by 100/50 and then compared with the threshold value th.

In the description of the first embodiment of the present invention, the clipping process has been described as a process for not reflecting the difference value on the evaluation value when the difference value exceeds a certain range. Further, an example of clipping will be described with reference to FIGS. Note that the difference value after conversion by clipping is a difference value xd ′
Is shown.

The first example of the clipping has been described in the first embodiment. As shown in FIG. 17, the absolute value | xd |
When (a ≧ 0), the converted difference value xd ′ is converted as follows.

Xd ′ = xd (| xd | ≦ a) xd ′ = 0 (| xd |> a) As shown in FIG. 18, the second example of clipping is converted as follows. .

Xd ′ = xd (| xd | ≦ a) xd ′ = a (| xd |> a, xd ≧ 0) xd ′ = − a (| xd |> a, xd ≧ 0) In the third example, as shown in FIG. 19, the square root of the calculated difference value xd is calculated and converted as follows. Here, the function sqrt (B)
Indicates that the square root of the value B is taken.

Xd ′ = sqrt (xd) (xd ≧ 0) xd ′ = − sqrt (−xd) (xd <0) In addition, the following example can also be given.
For example, as shown below, the fourth root of the difference value xd is taken.

Xd ′ = sqrt (sqrt (xd)) (xd ≧ 0) xd ′ = − sqrt (sqrt (−xd)) (xd <0) Further, as shown below, the difference value is calculated by a polygonal function. x
Convert d.

Xd ′ = − 8 (xd <−16) xd ′ = (xd + 8) / 4−6 (−16 ≦ xd <−8) xd ′ = (xd + 4) / 2−4 (−8 ≦ xd ≦ − 4) xd ′ = xd (| xd | ≦ 4) xd ′ = (xd−4) / 2 + 4 (4 <xd ≦ 8) xd ′ = (xd−8) / 4 + 6 (8 <xd ≦ 16) xd ′ = 8 (16 <xd) Although the above is an example of clipping, the present invention is not limited to this example, and any other conversion may be performed.

In the watermark detector shown as the embodiment of the present invention, the watermark for calculating the difference value has been described as being held in the watermark pattern holding memory in advance. It is not limited to. For example, an additional information generator that generates a watermark pattern from a watermark pattern by a read signal or the like can be provided as additional information output means. For example, when applied to the embodiment of the present invention, an M-sequence generator is used.

[0305] The watermark added to the image as additional information can be added to the image such that a difference is obtained in the time direction of the image in advance.

Further, the above-described first to third embodiments can be configured by applying the recording apparatus and method according to the present invention. That is, in this case, the recording apparatus includes a recording processing unit that records the image data for which the accompanying information has been detected by the watermark detector on a recording medium, and records the image data on the recording medium. Then, for example, in this case, the recording device performs the image recording on the recording medium in accordance with the detection result of the accompanying information detected by the evaluation value comparator included in the watermark detector described in the first to third embodiments. A recording control unit for recording data is provided. Here, the recording control means has, for example, the function of an image converter provided in the watermark detector of the first to third embodiments. That is, for example, when the accompanying information is detected, , The main area of the image data is not displayed, or the image is subjected to processing or processing such as scrambling.

[0307]

According to the present invention, there is provided an image data processing apparatus comprising: a supplementary information output unit for outputting a pattern of supplementary information; and a difference for calculating a difference value of a pixel value between neighboring pixels in input image data. Value calculating means, evaluation value calculating means for calculating an evaluation value based on the pattern and difference value of the accompanying information output from the accompanying information output means, and accompanying information detection for detecting the accompanying information based on the evaluation value Means, an evaluation value can be obtained by the evaluation value calculating means based on the pattern of the accompanying information output from the accompanying information output means and the difference value calculated by the difference value calculating means. The detecting means can detect the accompanying information based on the evaluation value.

Here, the image data processing device detects the accompanying information based on the evaluation value obtained from the difference value between the neighboring pixel having a high correlation and the image data processing device. Can reduce the influence on the evaluation value, so that higher detection accuracy can be obtained than in the past, and the accompanying information can be reliably detected.

In the image data processing method according to the present invention, an additional information output step of outputting a pattern of additional information, and a difference of calculating a pixel value difference between neighboring pixels in the input image data are provided. A value calculating step, an evaluation value calculating step of calculating an evaluation value based on the pattern and the difference value of the accompanying information output in the accompanying information output step,
An additional information detecting step of detecting additional information based on the evaluation value, whereby an evaluation is performed based on the pattern of the additional information output in the additional information output step and the difference value calculated in the difference value calculating step. An evaluation value can be obtained by the value calculation step, and the accompanying information can be detected based on the evaluation value by the accompanying information detection step.

Here, in the image data processing method, the accompanying information is detected based on the evaluation value obtained from the difference value between a neighboring pixel having a high correlation and the individual values of the image data. Can reduce the influence on the evaluation value, so that higher detection accuracy can be obtained than in the past, and the accompanying information can be reliably detected.

[0311] The recording apparatus according to the present invention further comprises: a supplementary information output unit that outputs a pattern of the supplementary information; and a difference value calculation unit that calculates a difference value of a pixel value between neighboring pixels in the input image data. Means, an evaluation value calculating means for calculating an evaluation value based on the pattern and difference value of the accompanying information output from the accompanying information output means, and an accompanying information detecting means for detecting the accompanying information based on the evaluation value. A recording control unit that controls recording of image data input to a recording medium in accordance with a detection result of the incidental information detecting unit, thereby calculating a difference value pattern and an incidental information pattern output from the incidental information output unit. The evaluation value can be obtained by the evaluation value calculating means based on the difference value calculated by the means.
Then, the recording apparatus can perform recording control of the input image data on the recording medium by the recording control unit according to the detection result of the incidental information detected by the incidental information detection unit based on the evaluation value. .

Here, the recording apparatus detects the accompanying information based on the evaluation value obtained from the difference value between a neighboring pixel having a high correlation and thereby, the individual values of the image data are evaluated. Value can be reduced,
Higher detection accuracy than before can be obtained, and the accompanying information can be reliably detected.

[0313] The recording method according to the present invention includes a step of outputting a pattern of accompanying information, and a step of calculating a difference value of a pixel value between neighboring pixels in the input image data. A step, an evaluation value calculating step of calculating an evaluation value based on the pattern and difference value of the accompanying information output in the accompanying information output step, and an accompanying information detecting step of detecting the accompanying information based on the evaluation value. A recording control step of performing recording control of image data input to a recording medium in accordance with a detection result of the incidental information detecting step, whereby a pattern of the incidental information output in the incidental information output step and a difference value An evaluation value can be obtained in the evaluation value calculation step based on the difference value calculated in the calculation step. Then, in the recording method, according to the detection result of the incidental information detected in the incidental information detecting step based on the evaluation value, the recording control step can control the recording of the input image data on the recording medium. .

Here, in the recording method, detection of incidental information is performed based on an evaluation value obtained from a difference value between a neighboring pixel having a high correlation and an individual value of image data is evaluated. Value can be reduced,
Higher detection accuracy than before can be obtained, and the accompanying information can be reliably detected.

Further, the image data processing apparatus according to the present invention comprises: an auxiliary information output means for outputting a plurality of patterns of auxiliary information having different phases; and a pixel value between adjacent pixels in the input image data. Difference value calculation means for calculating a difference value; evaluation value calculation means for calculating an evaluation value based on a pattern of a plurality of pieces of accompanying information having different phases output from the accompanying information output means; and evaluation value calculation. Means for detecting incidental information by comparing a plurality of evaluation values obtained by the means, and a pattern of a plurality of incidental information having different phases output from the incidental information output means, The evaluation value can be obtained by the evaluation value calculating means based on the difference value calculated by the value calculating means, and the accompanying information can be obtained by the accompanying information detecting means based on the plurality of evaluation values. It can be out.

Here, the image data processing device detects the accompanying information based on the evaluation value obtained from the difference value between the neighboring pixel having a high correlation and the individual data of the image data. Can reduce the influence on the evaluation value, so that higher detection accuracy can be obtained than in the past, and the accompanying information can be reliably detected.

Further, when the additional information is added using a pattern having a special property such as an M-sequence, the additional information is amplified using the difference value, whereby the additional information can be reliably detected. it can.

Further, according to the image data processing method of the present invention, there is provided an accompanying information output step of outputting a plurality of patterns of accompanying information having different phases, and a method of outputting a pixel value between neighboring pixels in input image data. A difference value calculation step of calculating a difference value, an evaluation value calculation step of calculating an evaluation value based on a pattern of a plurality of pieces of accompanying information having different phases output in the accompanying information output step, and an evaluation value calculation By comparing a plurality of evaluation values obtained in the process, an accompanying information detecting step of detecting accompanying information is performed. Based on the difference value calculated in the value calculation step, an evaluation value can be obtained in the evaluation value calculation step, and in the accompanying information detection step, based on the plurality of evaluation values, It is possible to detect the incidental information.

Here, in the image data processing method, detection of incidental information is performed based on an evaluation value obtained from a difference value between a neighboring pixel having a high correlation and, thereby, individual values of the image data are obtained. Can reduce the influence on the evaluation value, so that higher detection accuracy can be obtained than in the past, and the accompanying information can be reliably detected.

Further, when the additional information is added using a pattern having a special property such as an M-sequence, the additional information is detected by using the difference value, so that the additional information can be amplified to reliably detect the additional information. it can.

Further, the recording apparatus according to the present invention comprises: a supplementary information output means for outputting a plurality of patterns of the supplementary information having different phases; and a difference value of a pixel value between neighboring pixels in the input image data. Value calculation means for calculating an evaluation value, based on a pattern and a difference value of a plurality of pieces of incidental information having different phases output from the incidental information output means, and an evaluation value calculating means. By comparing a plurality of obtained evaluation values, an accompanying information detecting means for detecting accompanying information, and controlling the recording of the input image data on the recording medium in accordance with a detection result of the accompanying information detecting means. With the recording control unit, the evaluation is performed based on the plurality of patterns of the accompanying information having different phases output from the accompanying information output unit and the difference value calculated by the difference value calculating unit. By calculation means, it is possible to obtain a plurality of evaluation values. The recording device controls the recording of the input image data on the recording medium by the recording control unit in accordance with the detection result of the incidental information detected by the incidental information detection unit based on the plurality of evaluation values. Can be.

Here, the recording apparatus detects the accompanying information based on the evaluation value obtained from the difference value between a neighboring pixel having a high correlation and thereby the individual values of the image data are evaluated. Value can be reduced,
Higher detection accuracy than before can be obtained, and the accompanying information can be reliably detected.

Further, when the additional information is added by using a pattern having a special property such as an M-sequence, the additional information is detected by using the difference value, so that the additional information can be amplified to reliably detect the additional information. it can.

Further, according to the recording method of the present invention, there is provided an additional information output step of outputting a plurality of patterns of auxiliary information having different phases, and a difference value of a pixel value between neighboring pixels in input image data. A difference value calculating step of calculating a plurality of accompanying information patterns having different phases output in the accompanying information output step and a difference value, and an evaluation value calculating step of calculating an evaluation value. By comparing the plurality of obtained evaluation values, an incidental information detection step of detecting incidental information and recording control of the input image data on the recording medium according to a detection result of the incidental information detection step are performed. By having a recording control step,
A plurality of evaluation values can be obtained by the evaluation value calculation step based on the plurality of patterns of the auxiliary information having different phases output in the incidental information output step and the difference values calculated in the difference value calculation step. Then, the recording method controls recording of the input image data on the recording medium by the recording control means in accordance with a detection result of the incidental information detected in the incidental information detecting step based on the plurality of evaluation values. Can be.

Here, in the recording method, detection of incidental information is performed based on an evaluation value obtained from a difference value between a neighboring pixel having a high correlation and an individual value of image data is evaluated. Value can be reduced,
Higher detection accuracy than before can be obtained, and the accompanying information can be reliably detected.

Further, when the additional information is added using a pattern having a special property such as an M-sequence, the additional information is amplified by detecting using the difference value, so that the additional information can be reliably detected. it can.

[Brief description of the drawings]

FIG. 1 is a block circuit diagram showing a configuration of a watermark detector according to a first embodiment to which the present invention is applied.

FIG. 2 is a flowchart showing a series of processes for detecting accompanying information by the watermark detector according to the first embodiment.

FIG. 3 is a characteristic diagram showing a relationship between an evaluation value obtained based on shift detection and a shift amount.

FIG. 4 is a block circuit diagram illustrating a configuration of a watermark detector according to a second embodiment to which the present invention is applied, which is a configuration example 1;

FIG. 5 is a flowchart showing a series of processes for detecting accompanying information by the watermark detector of the configuration example 1;

FIG. 6 is a flowchart illustrating a series of processing for calculating an evaluation value for a difference value performed by the watermark detector according to the second embodiment to calculate an evaluation value based on a difference value.

FIG. 7 is a characteristic diagram showing a relationship between an evaluation value and a shift amount when an additional amount is amplified.

FIG. 8 is a block circuit diagram illustrating a configuration of a watermark detector according to a second embodiment to which the present invention is applied, which is a configuration example 2 and a configuration example 3;

FIG. 9 is a flowchart showing a series of processes for detecting accompanying information by the watermark detector of the configuration example 2;

FIG. 10 is a characteristic diagram illustrating a relationship between an evaluation value and a shift amount when an additional amount is amplified.

FIG. 11 is a flowchart showing a series of processes for detecting accompanying information by the watermark detector of Configuration Example 3;

FIG. 12 is a characteristic diagram illustrating a relationship between an evaluation value and a shift amount in the case of difference values xd1, xd2, and xd3.

FIG. 13 is a characteristic diagram showing a relationship between an evaluation value and a shift amount derived from a relational expression between the evaluation value and the shift amount in the case of the difference values xd1, xd2, and xd3.

FIG. 14 is a diagram illustrating a configuration of a watermark detector according to a third embodiment to which the present invention is applied.

FIG. 15 is a block circuit diagram illustrating a configuration of an evaluation value comparator included in the watermark detector according to the third embodiment.

FIG. 16 is a block circuit diagram showing a configuration of a conventional watermark detector shown for explaining a configuration of an evaluation value comparator provided in the watermark detector of the third embodiment.

FIG. 17 is a diagram illustrating an example of a conversion function for the conversion operation of the difference value.

FIG. 18 is a diagram illustrating another example of the conversion function for the conversion operation of the difference value.

FIG. 19 is a diagram illustrating another example of a conversion function for the conversion operation of the difference value.

FIG. 20 is a diagram showing positions of auxiliary information on an image on a video tape.

FIG. 21 is a diagram illustrating an example in which a specific pattern is embedded in an image.

FIG. 22 is a diagram illustrating an example of a watermark pattern.

FIG. 23 is a diagram illustrating an operation of adding a watermark to an image.

FIG. 24 is a diagram showing addition and detection of accompanying information using a watermark.

FIG. 25 is a block circuit diagram showing a configuration of an encoder.

FIG. 26 is a block circuit diagram showing a configuration of a decoder.

FIG. 27 is a block circuit diagram showing a configuration of a watermark adding device.

FIG. 28 is a block circuit diagram showing a configuration of a conventional watermark detector.

FIG. 29 is a flowchart showing a series of processes for adding a watermark to an image by the watermark adding device.

FIG. 30 is a flowchart showing a series of processes for detecting accompanying information by a conventional watermark detector.

FIG. 31 is a flowchart showing a series of processes for detecting accompanying information based on displacement detection by a conventional watermark detector.

FIG. 32 is a flowchart showing a series of processes of a difference value calculation process for calculating a difference value in shift detection by a conventional watermark detector.

FIG. 33 is a flowchart showing a configuration of a conventional watermark detector that performs shift detection.

FIG. 34 is a diagram illustrating an example of shifting a watermark pattern.

FIG. 35 is a diagram illustrating an example of extraction of accompanying information by shift detection.

[Explanation of symbols]

2 watermark detector, 3 watermark pattern holding memory, 4 difference calculator, 5 evaluation value calculator, 6
Evaluation value comparator, 11 Watermark detector, 12
Watermark pattern holding memory, 13 _1, 13 ₂ watermark pattern shifting unit, 14 _1, 14 ₂ difference calculator, 15 _1, 15 _2, 15 _3, 16 _1, 16 _2, 16 ₃ evaluation value calculator 17 Rating Value comparator

Continued on the front page (51) Int.Cl. ⁷ Identification symbol FI Theme coat II (reference) H04N 1/40 F term (reference) 5B057 CB06 CB18 CE08 CG07 DA20 DC36 5C063 AB03 AB05 CA23 CA40 DA13 DA20 5C076 AA14 5C077 LL14 MP04 NP02 PP80 RR02

Claims (36)

[Claims] 1. An image data processing apparatus for processing image data in which incidental information is embedded, comprising: an incidental information output unit that outputs a pattern of the incidental information; Difference value calculating means for calculating a difference value between pixel values; evaluation value calculating means for calculating an evaluation value based on the pattern of the accompanying information output from the accompanying information output means and the difference value; An image data processing device, comprising: an incidental information detecting means for detecting the incidental information based on a value. 2. The method according to claim 1, wherein the associated information is a watermark whose pattern is binary data, and wherein the evaluation value calculating means adds or subtracts the difference value according to a value of the pattern of the watermark. The image data processing device according to claim 1, wherein the value is calculated. 3. The image data processing device according to claim 1, wherein said difference value calculating means calculates said difference value from a pixel value between a plurality of neighboring pixels. 4. An image data processing method for processing image data in which ancillary information is embedded, wherein an ancillary information output step of outputting a pattern of the ancillary information; A difference value calculating step of calculating a difference value between pixel values; an evaluation value calculating step of calculating an evaluation value based on the pattern of the accompanying information output in the accompanying information output step and the difference value; And an incidental information detecting step of detecting the incidental information based on a value. 5. The evaluation method according to claim 5, wherein the associated information is a watermark whose pattern is binary data. In the evaluation value calculating step, the difference value is added or subtracted according to the value of the watermark pattern. 5. The image data processing method according to claim 4, wherein a value is calculated. 6. The image data processing method according to claim 4, wherein in the difference value calculating step, the difference value is calculated from pixel values between a plurality of neighboring pixels. 7. A recording apparatus for recording image data in which incidental information is embedded on a recording medium, comprising: an incidental information output unit that outputs a pattern of the incidental information; and a neighboring pixel in the input image data. Difference value calculating means for calculating a difference value between the pixel values of the above, evaluation value calculating means for calculating an evaluation value based on the pattern of the accompanying information output from the accompanying information output means and the difference value, An incidental information detecting unit that detects the incidental information based on the evaluation value; and a recording control unit that performs recording control of the input image data on the recording medium according to a detection result of the incidental information detecting unit. A recording device, comprising: 8. The associated information is a watermark whose pattern is composed of binary data, and the evaluation value calculating means adds or subtracts the difference value according to the value of the pattern of the watermark to perform the evaluation. The recording apparatus according to claim 7, wherein the value is calculated. 9. The recording apparatus according to claim 7, wherein said difference value calculating means calculates said difference value from a pixel value between a plurality of neighboring pixels. 10. A recording method for recording image data in which incidental information is embedded on a recording medium, comprising: a step of outputting a pattern of the incidental information; A difference value calculating step of calculating a difference value between the pixel values of the above; an evaluation value calculating step of calculating an evaluation value based on the pattern of the accompanying information output in the accompanying information output step and the difference value; An incidental information detecting step of detecting the incidental information based on the evaluation value; and a recording control step of controlling recording of the input image data on the recording medium according to a detection result of the incidental information detecting step. A recording method comprising: 11. The associated information is a watermark whose pattern is binary data. In the evaluation value calculation step, the difference value is added or subtracted in accordance with the value of the watermark pattern, and the evaluation value is calculated. The recording method according to claim 10, wherein a value is calculated. 12. The recording method according to claim 10, wherein in the difference value calculating step, the difference value is calculated from pixel values between a plurality of neighboring pixels. 13. An image data processing apparatus for processing image data in which incidental information is embedded, an incidental information output means for outputting a plurality of patterns of the incidental information having different phases from each other; A difference value calculating means for calculating a difference value of a pixel value between the pixel and a plurality of incidental information patterns having different phases output from the incidental information output means, and an evaluation value based on the differential value. An image data processing apparatus comprising: an evaluation value calculating means for calculating; and an associated information detecting means for detecting the associated information by comparing a plurality of evaluation values obtained by the evaluation value calculating means. 14. The incidental information output means sets the pattern of the incidental information to first to third phases, and the evaluation value calculation means sets a first phase corresponding to the first to third phases. 14. The image data processing apparatus according to claim 13, wherein the first to third evaluation values are calculated, and a standard evaluation value serving as a reference is set as a corresponding value from the first to third evaluation values. 15. The incidental information output means includes a storage means for storing the incidental information, and a phase setting means for setting a pattern of the incidental information stored in the storage means to a different phase. 14. The image data processing device according to claim 13, wherein: 16. The image data processing apparatus according to claim 13, further comprising comprehensive determination means for comprehensively determining a plurality of detection results obtained by said incidental information detection means. 17. The method according to claim 17, wherein the associated information is a watermark whose pattern is binary data, and wherein the evaluation value calculating means adds or subtracts the difference value according to the value of the pattern of the watermark to perform the evaluation. 14. The image data processing device according to claim 13, wherein a value is calculated. 18. The image data processing apparatus according to claim 13, wherein said difference value calculating means calculates said difference value from a pixel value between a plurality of neighboring pixels. 19. An image data processing method for processing image data in which incidental information is embedded, wherein: an incidental information output step of outputting a plurality of patterns of the incidental information having different phases from each other; A difference value calculation step of calculating a difference value of a pixel value between the pixel and the pixel, based on the pattern of a plurality of incidental information having different phases output in the incidental information output step and the differential value,
Image data, comprising: an evaluation value calculating step of calculating an evaluation value; and an associated information detecting step of detecting the associated information by comparing a plurality of evaluation values obtained in the evaluation value calculating step. Processing method. 20. A step of outputting the accompanying information in the accompanying information output step, wherein the pattern of the accompanying information is set to first to third phases, and in the evaluation value calculating step, a first phase corresponding to the first to third phases is set. 20. The image data processing method according to claim 19, wherein the first to third evaluation values are calculated, and a standard evaluation value serving as a reference is set as a corresponding value from the first to third evaluation values. 21. The image data processing method according to claim 19, wherein, in said incidental information output step, patterns of the incidental information stored in the storage means are set to different phases. 22. The image data processing method according to claim 19, further comprising a comprehensive determination step of comprehensively determining a plurality of detection results obtained in said incidental information detection step. 23. The associated information is a watermark in which a pattern is composed of binary data. In the evaluation value calculation step, the evaluation value is calculated by adding or subtracting the difference value according to the value of the pattern of the watermark. 20. The image data processing method according to claim 19, wherein a value is calculated. 24. The image data processing method according to claim 19, wherein in the difference value calculating step, the difference value is calculated from a pixel value between a plurality of neighboring pixels. 25. A recording apparatus for recording image data in which incidental information is embedded on a recording medium, comprising: an incidental information output means for outputting a plurality of patterns of the incidental information having mutually different phases; A difference value calculating means for calculating a difference value of a pixel value between adjacent pixels, and an evaluation value based on a pattern of a plurality of incidental information having different phases output from the incidental information output means and the differential value. Evaluation value calculation means for calculating the evaluation value calculation means; a plurality of evaluation values obtained by the evaluation value calculation means; and an incidental information detection means for detecting the incidental information; A recording control means for controlling recording of the input image data on the recording medium. 26. The incidental information output means sets the pattern of the incidental information to first to third phases, and the evaluation value calculating means sets a first phase corresponding to the first to third phases. 26. The recording apparatus according to claim 25, wherein the first to third evaluation values are calculated, and a standard evaluation value serving as a reference is set as a corresponding value from the first to third evaluation values. 27. The incidental information output means includes a storage means for storing the incidental information and a phase setting means for setting a pattern of the incidental information stored in the storage means to a different phase. 26. The recording device according to claim 25, wherein: 28. The recording apparatus according to claim 25, further comprising comprehensive judgment means for comprehensively judging a plurality of detection results obtained by said incidental information detection means. 29. The ancillary information is a watermark in which a pattern is composed of binary data, and the evaluation value calculating means adds or subtracts the difference value according to the value of the watermark pattern to perform the evaluation. 26. The recording apparatus according to claim 25, wherein the value is calculated. 30. The recording apparatus according to claim 25, wherein said difference value calculation means calculates said difference value from a pixel value between a plurality of neighboring pixels. 31. A recording method for recording image data in which incidental information is embedded on a recording medium, comprising: outputting a plurality of patterns of the incidental information having different phases from each other; A difference value calculating step of calculating a difference value of a pixel value between the neighboring pixels, and a pattern of a plurality of accompanying information having different phases output in the accompanying information output step and the difference value,
An evaluation value calculating step of calculating an evaluation value; an incidental information detecting step of detecting the incidental information by comparing a plurality of evaluation values obtained in the evaluation value calculating step; and a detection result of the incidental information detecting step A recording control step of performing recording control of the input image data on the recording medium in accordance with the following. 32. In the accompanying information output step, a pattern of the accompanying information is set to first to third phases, and in the evaluation value calculating step, a first phase corresponding to the first to third phases is set. 32. The recording method according to claim 31, wherein the first to third evaluation values are calculated, and a standard evaluation value as a reference is set as a corresponding value from the first to third evaluation values. 33. The recording method according to claim 31, wherein in the accompanying information output step, the patterns of the accompanying information stored in the storage means are set to different phases. 34. The recording method according to claim 31, further comprising a comprehensive determination step of comprehensively determining a plurality of detection results obtained in said incidental information detection step. 35. The associated information is a watermark whose pattern is binary data. In the evaluation value calculating step, the evaluation value is calculated by adding or subtracting the difference value according to the value of the pattern of the watermark. The recording method according to claim 31, wherein a value is calculated. 36. The recording method according to claim 31, wherein in the difference value calculating step, the difference value is calculated from a pixel value between a plurality of neighboring pixels.