JP2010141548A - Image display apparatus - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To delete or invalidate effects on a human body by performing video processing to an image with risk having an adverse effect on the human body. <P>SOLUTION: An image display apparatus includes: a video feature detection part 7 which detects a video feature by frame from prescribed video information included in a received video signal Db and outputs a video feature signal Ps; a video change detection part 9 for output of a control value Cr as a control signal when the video feature signal Ps changes more than a fixed times within a prescribed period of time; and a video signal countermeasure part 6 for analyzing the control value Cr to perform prescribed processing to the video signal Db in accordance with results of analysis. <P>COPYRIGHT: (C)2010,JPO&INPIT

Description

  The present invention relates to an image display device, and more particularly to an image display device such as a television receiver that detects and treats an image that adversely affects a human body.

  While viewing an image display device such as a television receiver, there are often cases in which physical conditions such as seizures, dizziness, and motion sickness occur due to the influence of displayed images. These images that adversely affect the human body and give a strong stress are hereinafter referred to as dangerous images.

  In order to prevent such incidents, the broadcasting station also checks the broadcast wave, but it is difficult to completely prevent it, and video tapes and DVDs that have already been released, or on the Internet that are often seen in recent years Due to the influence of posted videos, the same incidents are unending. In particular, since posted videos are freely expressed by posters and producers and can be easily distributed, it is important to take measures when dangerous videos exist.

  Dangerous images are not limited to broadcast waves and DVDs but may be included in entertainment such as games. Therefore, not only checks on the broadcasting station side and content production side, but also an image display device needs a function for detecting and preventing these.

  For example, there is a video signal processing apparatus disclosed in Patent Document 1 as a conventional technique for realizing the above-described functions. In the video signal processing apparatus described in Patent Document 1, a video signal is divided into small areas each having a predetermined area, and a change in average value of at least one of a luminance signal and a color difference signal is performed in pixels existing in each divided area. Is observed for a predetermined time, and an image in which a change of a predetermined number or more of regions continues for a certain time or more is detected as a dangerous image that adversely affects the human body.

  In addition, by dividing the video signal into multiple regions and observing the amount of change in the DC component of one or more of the luminance signal and hue signal in the pixels present in each divided region, the human body has strong optical stimulation. Japanese Patent Application Laid-Open No. H10-228688 discloses a method of detecting a dangerous image that adversely affects the image and displaying a substitute image with suppressed changes.

Japanese Patent Laid-Open No. 11-275385 JP 2002-252792 A

  In the video signal processing apparatus in Patent Document 1, a change that is greater than or equal to a threshold value in at least one of a luminance signal and a color difference signal is detected. However, when a dangerous video is determined based on a change amount by the threshold, the video is not a dangerous video. Regardless, it may be determined that the video is dangerous. For example, in a video in which the same subject is moved, when the background close to the same pattern changes at high speed, such as panning and tilting, both the luminance signal and the color difference signal change greatly. However, an image including such a scene may be seen not only in a dangerous image but also in a general image.

  Such a problem can also be mentioned in Patent Document 2. In other words, it is conceivable that even when the change amount of the direct current component is observed, it is determined that the image is a dangerous image regardless of whether it is not a dangerous image.

  One of the problems related to such misjudgment is that the analysis of the characteristics of the video signal is not performed and the content of the video is not grasped. That is, the content of the content constituting the video signal is a bright video, a dark video, a video with a red hue, a video with a blue hue, or the like. In the detection of a change in the luminance signal or the color difference signal exceeding the threshold value, it is difficult to determine these video features, and there is a problem that the accuracy of the determination in the dangerous video is lowered.

  The present invention has been made to solve the above-described problems, and an object of the present invention is to provide an image display device that detects dangerous images with high accuracy and performs measures such as deletion or invalidation.

  An image display device according to the present invention includes a video feature detection unit that detects video features for each frame from predetermined video information included in a received video signal, and outputs the video feature signal. And a video signal countermeasure unit that analyzes the control signal and performs a predetermined treatment on the video signal in accordance with the analysis result.

  According to the present invention, in the image display device, the video feature detection unit that detects the video feature for each frame from the predetermined video information included in the received video signal and outputs the video feature signal; A video change detection unit that outputs a control signal when it changes more than a certain number of times in time, and a video signal countermeasure unit that analyzes the control signal and performs a predetermined treatment on the video signal according to the analysis result This makes it possible to detect dangerous images with high accuracy and adaptively considering the characteristics of the video signal, and to take appropriate measures to reduce or invalidate the effects of dangerous images on the human body. Can do.

<A. Embodiment 1>
<A-1. Configuration of Image Display Device>
FIG. 1 is a block diagram showing a configuration of an image display apparatus according to Embodiment 1 of the present invention. As shown in the figure, the image display apparatus according to Embodiment 1 includes an input terminal 1, a receiving unit 2 that receives a signal input to the input terminal 1, and an image process that inputs an output from the receiving unit 2. The apparatus 3 and the display part 10 which displays the output from the image processing apparatus 3 are provided.

  A video signal Da having a predetermined format used in a television, a computer, or the like is input to the input terminal 1.

  The receiving unit 2 receives the video signal Da via the input terminal 1, converts the video signal Da into a format that can be processed by the image processing device 3, and outputs it as a video signal Db. For example, the receiving unit 2 converts the video signal Da into video information of several digital formats such as luminance information Y (or lightness information V), hue information H, and saturation information S, and then outputs the video signal Db. . The receiving unit 2 that performs the above-described operation is configured by an A / D converter or the like when the video signal Da is an analog signal, and in the format when the input video signal Da is a digital signal. Consists of a predetermined demodulator and the like. Here, the luminance information Y and the lightness information V are assumed to be the same value, and are described as being unified with the luminance information Y in the first embodiment.

  The image processing device 3 performs a process on the input video signal Db and outputs it to the display unit 10 as a video signal Dc as video information. Details of the functional unit that performs the treatment will be described later.

  The display unit 10 displays an image based on the input video signal Dc. The display unit 10 is, for example, a liquid crystal display, a DMD (Digital Micromirror Device) display, an EL (ElectroLuminescence) display, a plasma display, a CRT (Cathode-Ray Tube) display, a reflective type, a transmissive type, or a self-luminous device. Any display means can be applied.

<A-1-1. Configuration of Image Processing Device 3>
The configuration of the image processing device 3 in the image display device will be described below.

  The image processing apparatus 3 includes a video signal countermeasure unit 6 and a video feature detection unit 7 that receive the output video signal Db from the reception unit 2, and a video change output to the video signal countermeasure unit 6 via the video feature detection unit 7. And a detector 9. The video signal countermeasure unit 6 includes a countermeasure execution unit 5 to which a signal from the reception unit 2 is input and a countermeasure control unit 4 to which a signal from the video change detection unit 9 is input.

  The video feature detection unit 7 calculates a video feature value Ps for each frame from the video information included in the video signal Db, and outputs it to the video change detection unit 9. The configuration of the video feature detection unit 7 will be further described later.

  The video change detection unit 9 determines that the video signal Db is a dangerous video when detecting a change more than a certain number of times in a short period based on the video feature value Ps, and whether or not there is a risk of the video signal Db The control value Cr as a control signal including information such as the type of influence on the human body is output to the countermeasure control unit 4.

  The countermeasure control 4 calculates a countermeasure instruction value Pr indicating the content of the action performed by the countermeasure execution unit 5 on the video signal Db based on the control value Cr, and outputs the calculated value to the countermeasure execution unit 5.

  On the other hand, the countermeasure execution unit 5 takes action on the video signal Db when the input countermeasure instruction value Pr has contents for instructing countermeasure execution (that is, when the video signal Db is determined to be a dangerous video). To reduce or invalidate the influence of the danger image on the human body, and output the treated signal to the display unit 10 as the image signal Dc.

<A-1-2. Configuration of Video Feature Detection Unit 7>
The configuration of the video feature detection unit 7 in the above-described image processing apparatus 3 will be described below.

  FIG. 2 is a block diagram showing details of an internal configuration example of the video feature detection unit 7 shown in FIG. As shown in FIG. 2, the video feature detection unit 7 in the image display apparatus according to the first embodiment includes a signal distribution unit 70 that receives the video signal Db and a luminance histogram calculation that receives a signal from the signal distribution unit 70. 71, color histogram calculation unit 72, luminance histogram analysis unit 73 that receives the output from luminance histogram calculation unit 71, color histogram analysis unit 74 that receives the output from color histogram calculation unit 72, and luminance histogram analysis unit 73 and a feature determination unit 75 that receives the output from the color histogram analysis unit 74. The configuration in FIG. 2 is an example, and the video feature detection unit 7 is not limited to this configuration.

  In the example illustrated in FIG. 2, the video signal Db obtained from the receiving unit 2 and including the hue information H, the saturation information S, and the luminance information Y is input to the signal distribution unit 70. In the first embodiment, the HSV color space is used as an example of the color space.

  The video feature detection unit 7 in FIG. 2 is an example of implementation, and the video feature detection unit 7 may have any configuration as long as the video feature value Ps can be output based on the video signal Db.

  The signal distributor 70 extracts luminance information Y, hue information H, and saturation information S from the video signal Db for one frame. Of the extracted signals, the luminance information Y is output to the luminance histogram calculation unit 71, and the hue information H and the saturation information S are output to the color histogram calculation unit 72.

  In the example shown in FIG. 2, when the input video signal Db is an interlace signal, the signal distributor 70 converts the video signal for two fields into a video signal for one frame to obtain a new video signal. In this way, in the signal distribution unit 70, preprocessing for performing processing by the luminance histogram calculation unit 71 and the color histogram calculation unit 72 may be performed.

  As another example of pre-processing, when the video signal Db is shown in a color system different from the hue information H, the saturation information S, and the luminance information Y, such as an RGB signal, the hue information H is expressed by a known calculation formula. It is also conceivable to convert into saturation information S and luminance information Y.

  The luminance histogram calculation unit 71 calculates luminance information Hy based on the input luminance information Y and outputs the luminance information Hy to the luminance histogram analysis unit 73.

  The color histogram calculation unit 72 calculates color information Hc based on the input hue information H and saturation information S, and outputs the color information Hc to the color histogram analysis unit 74.

  The feature determination unit 75 determines the feature of the video based on the combination content of the luminance feature value Hyc and the color feature value Hcc output from the luminance histogram analysis unit 73 and the color histogram analysis unit 74, and uses the video feature value Ps as the video feature value Ps. Output to the change detection unit 9.

<A-2. Operation of Image Processing Device 3>
In the image display device described above, the operation of the image processing device 3 will be described below for each component.

<A-2-1. Operation of Video Feature Detection Unit 7 (Luminance Histogram Analysis)>
The operation relating to the luminance histogram in the video feature detection unit 7 provided in the image processing apparatus 3 will be described below.

  FIG. 3 shows an example of the luminance information Hy generated by the luminance histogram calculation unit 71. In the example shown in FIG. 3, the luminance histogram Hy regarding the luminance information Y is generated as the luminance information Hy. Hereinafter, information defining the histogram of the luminance information Y in the video signal Db generated by the luminance histogram calculation unit 71 is referred to as a luminance histogram HY.

  In the figure, the horizontal axis indicates the gradation value (class), and the vertical axis indicates the frequency, that is, the number of pixels with respect to the luminance of the video signal Db for one frame. In the following description, the luminance information Y of the video signal Db is composed of, for example, 8-bit data, and the gradation value takes a value from “0” to “255”, and the number of gradations is “ 256 ". The video signal Db is represented by 8 bits in this example, but may be represented by other gradation numbers such as 10 bits and 6 bits.

  The luminance histogram calculation unit 71 according to the first embodiment divides, for example, 256 gradations into 32 areas every 8 gradations, and the 32 areas are used as histogram classes. Then, a value near the center value in each class, in this example, an integer value closest to the center value and larger than that is used as the representative value of the class. For example, in a class composed of gradation values “0” to “7”, the central value is “3.5”, so the representative value of the class is “4”. The numbers on the horizontal axis in FIG. 3 indicate the representative values of each class.

  If the center value of the class is an integer, the center value may be used as the representative value of the class. Further, even when the center value of the class is not an integer but a decimal number as in this example, the center value of the class may be adopted as the representative value of the class. When the center value of a class is a decimal, the amount of calculation can be reduced by adopting an integer near the center value of the class as a representative value of the class as in this example.

  As described above, in the luminance histogram calculation unit 71 according to the first embodiment, an area composed of eight continuous gradation values is set as one class, and therefore each frequency of the histogram shown in FIG. The sum of the minutes signal. For example, the frequency indicated by the numerical value 4 on the horizontal axis corresponds to the sum of signals from gradation value 0 to gradation value 7 included in the luminance information Y for one frame.

  Note that, unlike the histogram of FIG. 3, the histogram may be generated by counting the frequency for each gradation value. That is, each class may be configured with one gradation value. In this case, the representative value of each class is the gradation value itself constituting the class.

  Further, when the number of gradations is divided, the number of divisions may be set to other than 32, and the division number and range of the histogram may be set freely. For example, when the number of gradations is “256”, the gradation values “0” to “32” and “200” to “255” can be in four gradations, and the others can be in 24. Further, the histogram may be divided unevenly so that the gradation value range can be freely set. By changing the number of divisions in this way, it is possible to adjust the calculation amount in the luminance histogram calculation unit 71 and the accuracy of the histogram.

  The luminance histogram analysis unit 73 extracts a representative value of a class in which the cumulative frequency becomes larger than a predetermined threshold value YA for the first time in the histogram generated by the luminance histogram calculation unit 71, and outputs it as the maximum gradation information value Yimax.

  In addition, the luminance histogram analysis unit 73 extracts a representative value of a class in which the cumulative frequency becomes larger than a predetermined threshold YB for the first time in the histogram generated by the luminance histogram calculation unit 71, and outputs it as a minimum gradation information value Yimin.

  In addition, the luminance histogram analysis unit 73 extracts a representative value of the class in which the cumulative frequency becomes larger than a predetermined threshold YC (for example, half of the total number of pixels) for the first time in the histogram generated by the luminance histogram calculation unit 71, and the intermediate luminance Output as gradation Yimid.

  Note that the cumulative frequency used to calculate the maximum gradation information value Yimax, the minimum gradation information value Yimin, and the intermediate luminance gradation Yimid is the cumulative frequency HYB · Any of the cumulative frequencies HYW obtained by accumulating the frequencies from the maximum to the minimum of the class may be used. In the above example, the cumulative frequency HYB is used to calculate the maximum gradation information value Yimax and the intermediate luminance gradation Yimid, and the cumulative frequency HYW is used to calculate the minimum gradation information value Yimin.

  In the histogram shown in FIG. 3, since the representative value of the class in which the cumulative frequency HYW becomes larger than the threshold value YA for the first time is “188”, “188” is the maximum gradation information value Yimax. Thus, unlike the maximum gradation value “204” in the video signal Db for one frame, the maximum gradation information value Yimax is a value according to the maximum gradation value detected using the cumulative frequency HYW and the threshold value YA. is there. Note that the maximum gradation value itself may be used as the maximum gradation information value in order to reduce processing. The same applies to the following minimum gradation information values.

  In the example of FIG. 3, the representative value of the class in which the cumulative frequency HYB becomes larger than the threshold value YB for the first time is “20”, so “20” becomes the minimum gradation information value Yimin. The minimum gradation information value Yimin is not the minimum gradation value in the video signal Db for one frame, but a value according to the minimum gradation value detected using the cumulative frequency HYB and the threshold value YB.

  Since the representative value of the class in which the cumulative frequency HYB becomes larger than the threshold value YC for the first time is “76”, this “76” becomes the intermediate gradation information value Ymid. Normally, this intermediate gradation information value Ymid is a gradation value when it reaches half (50%) of the total number of pixels in the video signal Db for one frame.

  Also, the luminance histogram analysis unit 73 calculates an average luminance information value from the luminance information Y obtained from the video signal Db for one frame, and outputs the average luminance information value as an average luminance value Yave. Specifically, the average luminance value = Σ (Y × nYi) / ΣnYi is calculated with the number of luminance signal gradations as Yi and the number of pixels of the luminance signal gradations as nYi. The average brightness value Yave can be displayed simply, for example, as “high”, “medium”, “low”, etc.

  As described above, the luminance histogram analysis unit 73 calculates four types of feature values, that is, the maximum gradation information value Yimax, the minimum gradation information value Yimin, the intermediate luminance gradation Yimid, and the average luminance value Yiave. Output. In this example, these values are output as the luminance feature value Hyc regarding the luminance information Y, but only a part of the information may be output as the luminance feature value Hyc. Further, if necessary, further feature values can be calculated and output as luminance feature values Hyc.

  Thus, by increasing the number of luminance feature values, the accuracy of feature determination can be improved. Further, by reducing the number, it is possible to reduce the number of processes at the time of feature determination.

  As another example of the luminance feature value Hyc, for example, there is a method of calculating a statistical value such as a standard deviation or variance regarding the luminance histogram Hy.

  The luminance feature value Hyc is desirably displayed in a simple manner such as “high”, “medium”, “low”, and the like, by dividing the luminance feature value Hyc according to a threshold value. By performing simple display in this way, it is possible to reduce the amount of information and the amount of calculation while maintaining the luminance feature.

<A-2-2. Operation of Image Feature Detection Unit 7 (Color Histogram Analysis)>
The operation relating to the color histogram in the video feature detection unit 7 provided in the image processing apparatus 3 will be described below.

  The color histogram calculation unit 72 calculates color information Hc based on the input hue signal H and saturation signal S and outputs the color information Hc to the color histogram analysis unit 74.

  FIG. 4 shows an example of the color information Hc generated by the color histogram calculation unit 72. In the example shown in FIG. 4, a hue histogram HH related to the hue signal H is generated as the color information Hc. Hereinafter, information defining the histogram of the hue information H in the video signal Db generated by the color histogram calculation unit 72 is referred to as a hue histogram HH.

  In the example shown in FIG. 4, when creating the color information Hc, a histogram is created using the hue information H, but a histogram is created using the saturation information S other than the hue information H. It doesn't matter. Also, a histogram may be created by combining hue information H, saturation information S, or other color information such as RGB.

  In the example shown in FIG. 4, the horizontal axis indicates the hue angle, and the vertical axis indicates the frequency, that is, the number of pixels with respect to the hue angle of the video signal Db for one frame. In the following description, the hue information H of the video signal Db takes a value from “0” to “360”, but “0” to “256”, “0” to “1”, etc. It may be expressed using other scales. In this example, 0 degrees represents red, followed by 60 degrees yellow, 120 degrees green, 180 degrees light blue, 240 degrees blue, and 300 degrees purple, and again represents red at 360 degrees.

  In the hue histogram HH generated by the color histogram calculation unit 72 according to the first embodiment, for example, the hue angle of 360 is divided into six regions every 60 degrees, and the six regions are hue angles of the hue histogram. It is said. Then, a value near the central value at each hue angle, in this example, an integer value closest to the central value and larger than that is set as the representative value of the hue angle. For example, in a class composed of hue angles “0” to “60”, the central value is “30”, so the representative value of the hue angle is “30”. The numbers on the horizontal axis in FIG. 4 indicate the representative values of the hue angles.

  If the central value of the hue angle is an integer, the central value may be used as the representative value of the hue angle. Even if the center value of the hue angle is not an integer but a decimal number, the center value of the hue angle may be adopted as a representative value of the hue angle. When the central value of the hue angle is a decimal, the amount of calculation can be reduced by adopting an integer near the central value of the hue angle as a representative value of the hue angle.

  When it is necessary to further reduce the amount of calculation, a simple number may be assigned as a representative value of each hue angle for convenience. That is, in the case of this example, the hue angle of the representative value “30” can be expressed as a representative value “1”, and subsequently expressed as “2”, “3”.

  As described above, in the color histogram calculation unit 72 according to the first embodiment, an area composed of continuous hue angle values is set as one class. Therefore, each frequency of the hue histogram shown in FIG. This is the sum of signals of hue angles up to degrees. For example, the frequency indicated by the numerical value 30 on the horizontal axis corresponds to the sum of signals from a hue angle of 0 degree to a hue angle of 60 degrees included in the luminance signal of the video signal Db for one frame. Hereinafter, the hue of the hue angle with the representative value “i” is referred to as Cbh (i), and the frequency is referred to as the video signal Dbh (i). That is, in the example of FIG. 4, the sum of signals of hue angles from 0 to 60 degrees is represented as a representative value “30”, so the hue of the region is Cbh (30) and the frequency is the video signal Dbh (30). To express.

  Unlike the hue histogram of FIG. 4, the hue histogram may be generated by counting the angle for each hue angle. That is, each hue angle may be constituted by one hue angle. In this case, the representative value of each hue angle is the value of the hue angle that constitutes the hue angle.

  Further, when the hue angle is divided, the number of divisions may be set to other than 6, and the division number and range of the hue histogram may be set freely. For example, the hue angles “0” to “60” and “300” to “360” can be set in increments of 10 degrees, and the others can be set in increments of 30 degrees. Alternatively, the frequency of unnecessary hue angles may be omitted. In this way, by changing the number of divisions and omitting the frequency of unnecessary hue angles, the calculation amount in the color histogram calculation unit 72 and the accuracy of the hue histogram can be adjusted. A method of selecting the number of divisions and the range according to the hue of the feature to be detected can be considered.

  In this example, the frequency of the hue histogram is represented by the number of pixels with respect to the hue angle of the video signal Db for one frame, but may be displayed as the cumulative number of pixels. Further, 10% or the like may be displayed as a ratio of the total number of pixels, not the number of pixels.

  FIG. 5 is an explanatory diagram showing an example of generation of the color feature value Hcc by the color histogram analysis unit 74. As shown in the figure, the color histogram analysis unit 74 has a threshold value in which each frequency Dbh (i) of the hue histogram HH is smaller than a predetermined hue determination threshold value TDbh2 or a predetermined threshold value larger than the threshold value TDbh2. It is determined whether the value is between the TDbh1 values or larger than the hue determination threshold value TDbh1, and a hue determination information value Dbhc (3) that defines any one of the three classification information values, low, medium, and high. i) is calculated.

  In the example shown in FIG. 5, since Dbh (30) is a value larger than a predetermined threshold value TDbh1, a value indicating “high” is input to Dbhc (30). Since Dbh (90) is a value between the threshold value TDbh2 and the threshold value TDbh1, a value indicating “medium” is input to Dbhc (90). Since Dbh (150), Dbh (210), Dbh (270), and Dbh (330) are smaller than the predetermined hue determination threshold value TDbh2, Dbhc (150), Dbhc (210), Dbhc (270), and Dbhc ( 330) is input a value indicating "low".

  In this example, there are two kinds of predetermined thresholds, and the threshold values are classified into three types of high, medium and low, but may be classified into other than three types. That is, the threshold value may be more or less than two types. More detailed classification is possible by adjusting a large number of threshold values. Further, the processing amount can be reduced by reducing the number of thresholds.

  Further, the threshold value may be changed according to the hue angle region Cbh (i). For example, Dbh (30) is determined based only on a predetermined threshold value TDbh1, and Dbh (90) determines a hue determination information value Dbhc (i) based on a predetermined threshold value TDbh1 and other predetermined threshold values TDbh2 and TDbh3. Techniques can also be taken. As described above, by changing the threshold value according to the hue angle region Cbh (i), it is possible to focus on the hue to be analyzed in detail and reduce the analysis accuracy of the hue that does not require detailed analysis. Obtainable.

  The color histogram analysis unit 74 outputs the hue determination information value Dbhc (i) in the hue angle region Cbh (i) to the feature determination unit 75 as the color feature value Hcc. That is, in the example shown in FIG. 5, Dbhc (30) = “high”, Dbhc (90) = “medium”, Dbhc (150) = Dbhc (210) = Dbhc (270) = Dbhc (330) = “low”. The meaning color feature value Hcc is output to the feature determination unit 75.

  In outputting the color feature value Hcc, by defining one of the hue angle region Cbh (i) and the hue determination information value Dbhc (i), only the hue angle region Cbh (i) or Only the hue determination information value Dbhc (i) may be output.

  For example, a method of outputting a hue angle region Cbh (i) where the hue determination information value Dbhc (i) = “high” is conceivable. Returning to the example of FIG. 5, as the hue angle region Cbh (i) where Dbhc (i) = “high”, the hue angle region Cbh (30) is output to the feature determination unit 75 as the color feature value Hcc.

  As another example, a method for designating a hue angle region in which the hue determination information value Dbhc (30) of the hue angle region Cbh (30) is output can be considered. Returning to the example of FIG. 5, the hue determination information value “high” is output to the feature determination unit 75 as the color feature value Hcc as the hue determination information value of the hue angle region Cbh (30).

  If necessary, it is possible to take a means of outputting only a part of the hue determination information value as the color feature value Hcc and not outputting the remaining hue determination information value. Thus, by limiting the information to be output, the amount of information can be reduced and the amount of calculation can be reduced.

  In this example, the color feature value Hcc is divided into three types of “high”, “medium”, and “low” according to the threshold value, so that the amount of information retaining the color feature is reduced and the information is reduced. The number may be other than three. Further, each frequency Dbh (i) of the hue histogram HH may be output as it is.

<A-2-3. Operation of Feature Judgment Unit 75>
The operation of the feature determination unit 75 in the video feature detection unit 7 provided in the image processing device 3 will be described below.

  The feature determination unit 75 determines the feature of the video based on the combination content of the luminance feature value Hyc and the color feature value Hcc output from the luminance histogram analysis unit 73 and the color histogram analysis unit 74, and uses the video feature value Ps as the video feature value Ps. Output to the change detection unit 9.

  FIG. 6 shows an example in which the video features are classified into seven types for the combinations of the luminance feature value Hyc and the color feature value Hcc input to the feature determination unit 75. In order to simplify the explanation, in this example, the luminance feature value Hyc and the color feature value Hcc are reduced compared to the above example, and the image is obtained using Dbhc (30), Dbhc (90), Dbhc (150), and Yave. Each feature is classified into seven types, and a video feature value Ps (i) is output. In this example, the features are classified into seven types, but any number of features may be classified.

  Further, in this example, classification is made into features relating to hue and luminance, but the classification criteria is not limited to that, and any sort may be used as long as it represents the characteristics of the video signal Db.

  The combination contents of the feature determination by the feature determination unit 75 can be arbitrarily created based on the conventional danger video and human visual characteristic data. In the example of FIG. 6, if Dbhc (30), Dbhc (90), and Dbhc (150) are “low” and Yearve is “high”, the video feature value Ps indicating Ps (1) “light”. Is output to the video change detection unit 9.

  Unlike this example, by increasing the contents of the luminance feature value Hyc and the color feature value Hcc, finer feature classification becomes possible.

  In the above example, since classification into seven types of features is performed, the classification name is referred to as a feature name. In the classification of FIG. 6, the light (Ps (1)) has a feature that many bright images such as white are included. Red (Ps (2)) is an image including a lot of red, yellow (Ps (3)) is an image including a lot of yellow, and green (Ps (4)) is an image including a lot of green. Dark (Ps (5)) has a characteristic that many dark images such as black are included. Colorful (Ps (6)) is an image in which many colors are mixed. Normal is an image that does not have such characteristics.

  As described above, the feature determination unit 75 can determine a feature based on the hue information H, the saturation information S, and the luminance information V obtained from the video signal Db.

  In the video feature detection unit 7 in this example, the input video signal Db is a 1-frame video signal, but a plurality of video signals may be used instead of a 1-frame video signal. For example, as seen in frame interpolation technology, when a new video signal is created using video signals for multiple frames, analysis is performed based on the new video signal created based on multiple frames. It doesn't matter.

<A-2-4. Operation of Video Change Detection Unit 9>
The operation of the video change detection unit 9 provided in the image processing device 3 will be described below.

  The video change detection unit 9 analyzes the video feature value Ps output from the video feature detection unit 7 and determines that the video signal Db is a dangerous video when a change of a certain number of times in a short period is detected, A control value Cr as a control signal including information such as the presence / absence of danger of the video signal Db and the type of influence on the human body is output to the countermeasure control unit 4 of the video signal countermeasure unit 6.

  It is assumed that the video feature value Ps changes Tt times or more within a Tf frame for a change more than a certain number of times in a short period. If a change of Tt times or more is detected within the Tf frame, the control value Cr is output. Tf and Tt are called detection parameters.

  FIG. 7 is an example of a method for determining that the video signal Db is a dangerous video with respect to the video feature value Ps of the video signal Db input to the video change detection unit 9. Description will be made using the feature classifications Ps (1) to Ps (7) used in FIG.

  In the example shown in FIG. 7, the horizontal axis in the figure indicates an analysis frame (that is, the passage of time), and the vertical axis indicates a video feature value Ps (i). That is, the broken line in the figure represents the transition of the video feature value Ps (i).

  As the transition in the short period, for example, when the detection parameter Tf = 10 frames and Tt = 5 times, the transition is detected 6 times between Ps (2) and Ps (3) between 6-12 frames in FIG. When such a transition of the video feature value Ps is detected, it is determined that the video signal Db is a dangerous video. The video change given in this example is a video in which red (Ps (2)) and yellow (Ps (3)) change drastically between several frames.

  FIG. 8 shows another example of a method for determining a dangerous video in the video change detection unit 9. Similarly, when the detection parameter Tf = 10 frames and Tt = 5 times, the transition is detected 8 times between Ps (2) to Ps (5) between 4 to 12 frames in FIG. When the transition of the video feature value Ps is detected, it is determined that the video signal Db is a dangerous video. The video change given in this example is a video whose characteristics change greatly between several frames.

  As described above, transitions in a short period can be used in the case of transitions only between the same video feature values or when transitions other than between the same video feature values are included.

  In this example, the detection parameters Tf and Tt do not need to be constant, and may be adjusted according to changes in the video feature value Ps. Further, depending on the change in the video feature value Ps, it may be determined that the video is not a dangerous video.

  FIG. 9 is an example of detection parameters used to determine that the video signal Db input in the video change detection unit 9 is a dangerous video, and control values to be output. As shown in the figure, for example, when the video feature value changes between Ps (1) and Ps (5), if three or more changes are detected within 5 frames, the control value Cr is Cr (2) is output. Here, Cr (2) is one of several control values Cr and can be output in accordance with a countermeasure in the countermeasure execution unit 5 described later.

  The change as in the above example is a blinking black and white image in which a dark (Ps (5)) characteristic with many dark images and a light (Ps (1)) characteristic with many bright images are frequently repeated. Close image. This is a dangerous video that may be subjected to strong stress when viewed in a dark room, etc., and requires treatment for the video signal Db. A value indicating the treatment content or the like is output according to the control value.

  Another example in FIG. 9 is shown. When the video feature value changes between Ps (6) and Ps (7), the control value Cr is not output even if there is a change in a short period. As described above, depending on the video feature value, it may be determined that the video is not determined to be a dangerous video.

  The video change detection unit 9 can detect a dangerous video by detecting a feature of a video signal and detecting a short-term transition of the feature. In addition, since the detection parameters Tr and Tf and the control value Cr can be changed for each feature, the detection accuracy can be adjusted. For example, it is possible to increase the detection accuracy of dangerous images that require highly accurate detection.

  Further, by outputting the control value Cr in consideration of the characteristics of the video signal, it is possible to effectively perform the treatment performed on the dangerous video reflecting the characteristics.

  Here, the prepared control values Cr may be provided by the number of combinations of Ps (i) or may be the same as the number of video features. Further, only one type of control value Cr may be defined and only the presence / absence of a danger signal may be transmitted.

  Unlike this example, when the transition in a short period is a change over two or more video feature values Ps (i), the respective detection parameters Tf and Tt and the control value Cr may be set.

  By outputting the control value Cr in accordance with the combination of the video feature values Ps (i) as shown in FIG. 9, it is possible to define a change from one specific video feature to another specific video feature. If it is desirable to uniquely determine a specific feature change of the video signal, the control value Cr may be set uniquely.

  By creating the control value Cr in accordance with the feature change of the video signal, it is possible to effectively perform the treatment performed on the dangerous video in the video signal countermeasure unit 6 reflecting the feature.

  The video change detection unit 9 may have any configuration as long as it uses the video feature value Ps of the video signal Db to calculate the control value Cr.

  When the control value Cr is being output, a video feature change different from the control value Cr (Bf) detected so far is observed, and when a new control value Cr (Af) is calculated, Cr (Bf), Cr ( Any of Af) may be output. Further, another control value Cr (Ba) indicating that both Cr (Bf) and Cr (Af) are output may be newly output.

  In the case of a configuration that outputs Cr (Af), it is possible to detect a change in the dangerous video each time and take a countermeasure corresponding to the type of the dangerous video. On the other hand, when Cr (Ba) is configured to be output, it can be seen that the danger video has a characteristic that the type of danger changes frequently. Therefore, measures such as taking general measures effective for the danger video in general can be considered. It is done.

  In this example, when it is determined that the video signal Db is a dangerous video, the control value Cr is output to the video signal countermeasure unit 6. However, even if the video signal Db is not a dangerous video, the control value Cr It may be configured to output Cr. In this case, the control value Cr may output information that means that no correspondence with the video signal Db is necessary, information that means that the change of the video signal Db is not dangerous, or the like.

  Unlike this example, the detection parameters Tf and Tt and the control value Cr may all be set to the same value. However, in this case, detection according to the feature cannot be performed, and the effect of the treatment is reduced.

  Regarding the several frames until the video change detection unit 9 detects the dangerous video, since the detection is not completed, the dangerous video is output as it is. However, if the dangerous video is continuously viewed, it has a strong influence on the human body. Therefore, the influence on the human body is small in a short time required for detection. In order to shorten the time until detection, the detection parameters Tf and Tt may be set small. Although the detection time can be shortened, the detection accuracy is somewhat lowered.

  The output of the control value Cr by the video change detection unit 9 is continued until the change of the video feature value Ps is completed. Note that after the change of the video feature value Ps is finished, the output of the control value Cr may be stopped depending on other conditions such as the elapse of a fixed time or the end of the video content.

  However, as described above, when the output of the control value Cr is stopped under a condition other than the end of the change in Ps, the video signal that is not a dangerous video is also treated, and the content of the content is It can be damaged. On the other hand, there is a possibility that a similar dangerous video is included again in the same content, and when a dangerous video is detected again, several frames until the dangerous video is detected become unnecessary, so that an effect can be expected.

<A-2-5. Operation of video signal countermeasure unit 6>
The operation of the video signal countermeasure unit 6 provided in the image processing apparatus 3 will be described below.

  The countermeasure control section 4 provided in the video signal countermeasure section 6 selects the countermeasure instruction value Pr for the video signal Db corresponding to the control value Cr as the control signal and outputs it to the countermeasure execution section 5. The measure instruction value Pr can be freely adjusted based on the characteristics of the danger video.

  The instruction by the countermeasure instruction value Pr output from the countermeasure control unit 4 to the countermeasure execution unit 5 is, for example, a method of reducing the number of frames of the video to reduce the degree of change, or a method of calling attention to the viewer by text or voice. A method of replacing with another video or still image, a method of reducing values such as luminance and saturation, and the like are conceivable.

  The instruction based on the countermeasure instruction value Pr is preferably created in consideration of the control value Cr as a control signal calculated from the video feature. For example, in the case of a video in which a black and white image blinks, a method of reducing the number of frames and the degree of change can be considered. On the other hand, in the case of a video where bright colors such as yellow and light blue blink, a method of reducing the degree of change by reducing the number of frames after reducing the saturation of the video signal is conceivable. .

  An example of the countermeasure instruction value Pr output by the countermeasure control unit 4 will be described using the example of FIG. In the example of FIG. 9, the control value Cr as the control signal is output from the video change detection unit 9 as four types of values 1 to 4. If the control value Cr as a four-value control signal is expressed in the form of Cr (i) as Cr (1), Cr (2), Cr (3), Cr (4), respectively, Cr (i) i) The countermeasure instruction value Pr corresponding to each is derived by the countermeasure control unit 4.

  Here, Pr (i) corresponding to Cr (i) may be the same or different from each other. When all are the same, for example, Cr (i) (i = 1, 2, 3, 4) = Pr (1), and when different, for example, Cr (i) = Pr ( i) It is configured as (i = 1, 2, 3, 4).

  In this example, the countermeasure instruction value Pr is output when it is determined that the video signal Db is a dangerous picture and countermeasures are required. However, when the video signal Db is not a dangerous picture, the countermeasure instruction value is output. A configuration for outputting Pr may also be used. In this case, the countermeasure instruction value Pr may be output as information indicating that no countermeasure regarding the video signal Db is required, information indicating that a change in the video signal Db is not dangerous, or the like.

  In the example in FIG. 9, when a change of a certain number Tt or more of red (Ps (2)) and green (Ps (4)) is detected in a short period Tf, the control value Cr (4) as a control signal is Is output. Pr (4) is derived as the countermeasure instruction value Pr corresponding to the control value Cr (4) as the control signal.

  Since Pr (4) is a change in red and green in a short period of time, it is a dangerous video that may be subjected to strong stress when viewed in a dark room or the like, and treatment for the video signal Db is necessary. Therefore, as an example of processing, a method of holding video information of an arbitrary frame in the dangerous video and displaying the held video as a still image for a certain period of time is used.

  The countermeasure execution unit 5 provided in the video signal countermeasure unit 6 performs image processing based on the countermeasure instruction value Pr output from the countermeasure control value 4 to reduce or invalidate the influence of the dangerous image on the human body. .

  There may be a frame in which image processing is not performed on the dangerous video. As an example, there may be a case where the number of frames is reduced, and a frame that does not display is generated. On the other hand, instead of a frame that is not displayed, a method of continuing to display as a still image can be considered.

<A-3. Effect>
According to the first embodiment of the present invention, in the image display device, a video feature detection unit that detects video features for each frame from predetermined video information included in the received video signal Db and outputs a video feature signal Ps. 7 and when the video feature signal Ps changes more than a predetermined number of times within a predetermined time, the video change detection unit 9 that outputs a control value Cr as a control signal, and the control value Cr are analyzed and according to the analysis result By providing the video signal countermeasure unit 6 that performs a predetermined treatment on the video signal Db, it is possible to detect a dangerous video, and to reduce the influence of the dangerous video on the human body by taking appropriate measures for this. Alternatively, treatment such as invalidation can be performed.

  According to the first embodiment of the present invention, in the image display device, the predetermined treatment is a treatment that suppresses a factor that adversely affects the human body included in the video signal Db, thereby detecting a dangerous video. By taking appropriate measures for this, it is possible to take measures such as reducing or invalidating the influence of the danger image on the human body.

Further, according to the first embodiment of the present invention, in the image display device, the predetermined video information includes any one of the luminance information V, the hue information H, and the saturation information S. It is possible to detect video features with high accuracy by acquiring features of changes and color changes, and combining such information, and the accuracy of detection of dangerous video can be improved.
it can.

  According to the first embodiment of the present invention, in the video change detecting unit 9 of the image display device, the video feature value Ps as the video feature signal is determined separately from a predetermined specific video feature. When a change to a specific video feature occurs, a control value Cr as a control signal is output, so that the treatment according to the change feature can be defined in advance in consideration of the feature of the video signal Db. It is possible to make the treatment performed on the dangerous image in the signal countermeasure unit 6 effective by reflecting the feature. Since a specific trajectory of the image change can be determined, it is possible to identify a particularly high-risk image or the like in a specific feature change as compared with a previously analyzed dangerous image.

  According to the first embodiment of the present invention, the video feature detection unit 7 of the image display device detects video features from the video signal Db for a plurality of frames instead of the video signal Db for one frame. Thus, it is possible to determine a dangerous video even for a video generated from a plurality of frames such as double speed driving.

  Further, according to the first embodiment of the present invention, the video signal countermeasure unit 6 of the image display device performs different predetermined treatments according to different analysis results of the control value Cr as the control signal. As a result, by changing the treatment for the video signal, the corresponding treatment can be executed depending on the feature, and a more effective treatment suitable for the danger of the dangerous video is possible.

  In addition, the image display device according to the first embodiment is not limited to the video display device and may be used in other fields related to video as a technique for detecting a dangerous video from the video signal Db. For example, a video recording device such as a video recorder such as a hard disk or a DVD may be used as another field.

  In addition, when these applications are performed in the video recording device, unlike the case of viewing in real time, by analyzing in advance, the number of frames required until the detection of dangerous video is unnecessary, and a safer video can be obtained. Can be provided. When the detection is performed in advance, the treatment for the dangerous image can be performed in advance as well.

  On the other hand, in order to perform the same process as the present embodiment using the techniques described in Patent Document 2 and Patent Document 3 described above, it is necessary to hold multimedia data whose content type is known in advance. . For this reason, classification cannot be performed for first-time programs.

  In the techniques described in Patent Document 2 and Patent Document 3 described above, dangerous images are uniformly detected using only threshold values in a luminance signal, a hue signal, and a color difference signal. For this reason, it is not possible to obtain the characteristics of the dangerous video, and it is not possible to perform treatments according to the characteristics. Moreover, the detection accuracy is inferior and detailed detection cannot be performed.

  In the image display device according to the first embodiment, the dangerous video is detected using the HSV color space as an example. For example, the RGB color space, the CMY color space, the HLS color space, the YCbCr color space, the Lab color system, L Any other color space or color system such as * a * b * color system, L * u * v * color system, etc. can be applied.

  The video feature detection method according to the first embodiment can also be used in the second and third embodiments to be described later.

<B. Second Embodiment>
<B-1. Configuration of Image Display Device>
FIG. 10 is a block diagram showing a configuration of an image display apparatus according to Embodiment 2 of the present invention. The image display device according to the second embodiment includes the image processing device 13 instead of the image processing device 3 in the image processing device according to the first embodiment described above. Other constituent elements are the same as those shown in the first embodiment, and thus description thereof is omitted.

<B-1-1. Configuration of Image Processing Device 13>
The configuration of the image processing device 13 in the image display device will be described below.

  The image processing apparatus 13 according to the second embodiment includes a video signal countermeasure unit 6 to which an output video signal Db from the receiving unit 2 is input, a region division video feature detection unit 17 as a video feature detection unit, and a region division video. An area division video change detection unit 19 is provided as a video change detection unit that outputs to the video signal countermeasure unit 6 via the feature detection unit 17. The video signal countermeasure unit 6 includes a countermeasure execution unit 5 to which a signal from the reception unit 2 is input and a countermeasure control unit 4 to which a signal from the region division video change detection unit 19 is input.

  The area division video feature detection section 17 as the video feature detection section divides each frame of video information into one or more areas based on the video information included in the video signal Db, and divides the area into areas. The area division video feature value Pa as the feature signal is calculated and output to the area division video change detection unit 19 as the video change detection unit.

  At this time, the division number of the video signal Db is n, and the divided video signal is represented as a video signal Dba (n). As n increases, the amount of calculation required for processing is required, but more detailed features can be detected.

  The region division video change detection unit 19 as a video change detection unit changes the region division video feature value Pa more than a certain number of times in a short period based on the region division video feature value Pa as a region division feature signal for each region. Is detected, the control value Crn for each area is calculated, and when the control value Crn for each area exceeds a certain threshold, the video signal Db is determined to be a dangerous video, and the risk of the video signal Db is determined. A control value Cr as a control signal including information such as presence / absence and the type of influence on the human body is output to the countermeasure control unit 4.

  The countermeasure control 4 calculates a countermeasure instruction value Pr indicating the content of the action performed by the countermeasure execution unit 5 on the video signal Db based on the control value Cr, and outputs the calculated value to the countermeasure execution unit 5.

  On the other hand, the countermeasure execution unit 5 takes action on the video signal Db when the input countermeasure instruction value Pr has contents for instructing countermeasure execution (that is, when the video signal Db is determined to be a dangerous video). To reduce or invalidate the influence of the danger image on the human body, and output the treated signal to the display unit 10 as the image signal Dc.

<B-1-2. Configuration of Region Divided Video Feature Detection Unit 17>
The configuration of the area-divided video feature detection unit 17 as the video feature detection unit in the image processing apparatus 13 described above will be described below.

  FIG. 11 is a block diagram showing details of an example of the internal configuration of the area-divided video feature detection unit 17 shown in FIG. As shown in FIG. 11, the area division video feature detection unit 17 in the image display apparatus according to the second embodiment includes an area division unit 178 and a video feature detection unit 179 to which a signal from the area division unit 178 is input. It has.

  The area division video feature detection unit 17 of FIG. 11 is an example of implementation, and the area division video feature detection unit 17 may be any configuration that can output the area division video feature value Pa based on the video signal Db. It may be anything.

  The video feature detection unit 179 receives from the histogram calculation region determination unit 170 to which the signal from the region division unit 178 is input, the histogram calculation unit 171 to which the output from the histogram calculation region determination unit 170 is input, and the histogram calculation unit 171. The histogram analysis unit 173 that inputs the output of the image and the feature determination unit 175 that inputs the output from the histogram analysis unit 173 are included. The configuration in FIG. 11 is an example, and the video feature detection unit 17 is not limited to this configuration.

  In the example illustrated in FIG. 11, the video signal Db obtained from the receiving unit 2 and including the hue information H, the saturation information S, and the lightness information V is input to the region dividing unit 178. In the second embodiment, the HSV color space is used as an example of the color space.

  In the example shown in FIG. 11, when the input video signal Db is an interlace signal, the region dividing unit 178 converts the video signal for two fields into a video signal for one frame to obtain a new video signal. As described above, the region dividing unit 178 may perform preprocessing for performing processing by the histogram calculation region determining unit 170.

  As another example of pre-processing, when the video signal Db is shown in a color system different from the hue information H, the saturation information S, and the lightness information V, such as an RGB signal, the hue information H is expressed by a known calculation formula. It is also conceivable to convert to saturation information S and lightness information V.

  The region dividing unit 178 divides the video signal Db for one frame into n regions defined in advance, and outputs the video signal in the divided region to the histogram calculation region determining unit 170 as the video signal Dba. Thereafter, the processing on the divided video signal Dba is performed on each video signal Dba (n).

  The video feature detection unit 179 in the second embodiment receives the divided video signal Dba instead of the video signal Db in the video feature detection unit 7 in the first embodiment, and represents the characteristics of the video signal Db. The same function is achieved although it is different in that a segmented video feature value Pa representing the feature of the video signal Dba is output instead of outputting the video feature value Ps. However, the second embodiment uses an example different from the first embodiment. Therefore, the configuration of the video feature detection unit 179 described in the second embodiment can be used also in the first embodiment, and the configuration of the first embodiment is used in the second embodiment. You can also

<B-2. Operation of Image Processing Device 13>
The video signal countermeasure unit 6 according to the second embodiment is the same as that of the first embodiment, and performs the same operation as the operation described in the first embodiment.

  Hereinafter, the operations of the area division video feature detection unit 17 and the area division video change detection unit 19 will be described.

<B-2-1. Operation of Region Divided Video Feature Detection Unit 17>
The operation of the area division video feature detection unit 17 in the image processing apparatus 13 will be described below.

  The area division video feature detection unit 17 includes an area division unit 178 and a video feature detection unit 179.

  FIG. 12 is an example of region division of the video signal Db performed in the region dividing unit 178. In the example of FIG. 12, the video signal Db is divided into nine areas in area, and the histogram calculation provided in the video feature detection unit 179 uses the video signal Dba (1) to the video signal Dba (9) as the video signal Dba. This is output to the area determination unit 170.

  In this example, the video signal Db is divided unevenly, but it may be divided equally. Further, the division number n of the video signal Db may be any number. The determination of the division number n and the division area is adjusted according to conditions such as the size of the input signal and the area of the black band included in the video.

  The histogram calculation region determination unit 170 provided in the video feature detection unit 179 further obtains lightness information V, hue information H, and saturation information S from the input video signal Dba divided into regions for one frame. Extract. Then, using the extracted hue information H, saturation information S, and lightness information V, the color space is divided into a plurality of color areas Dban, and the color area information value Dban related to the range of the divided color areas is divided. Along with the video signal Dba in the area, it is output to the histogram calculation unit 171 provided in the video feature detection unit 179.

  Examples of the output color area information value Dban include hue information H, saturation information S, lightness information V and the like indicating each area.

  FIG. 13 shows an overall view of the color space. FIG. 14 shows an example in which the number of divided color spaces is m, and the video signal Dba (n) is divided into a plurality of divided regions Dban (n, m).

  FIG. 14 shows an example in which the color space of FIG. 13 is divided using hue information H, saturation information S, and lightness information V, and is divided into nine regions of divided regions Dban (n, 1) to Dban (n, 9). It is divided. In this example, the saturation information S is divided into an area where r1 or less and an area where r1 or more is greater. The brightness information V is divided by the lengths r3, r4, and r5 with respect to the region that is equal to or less than r1, and Dban (n, 1) to Dban (n, 3) are created. The hue information H is divided by 60 degrees with respect to the area that is equal to or greater than r1, and divided areas Dban (n, 4) to Dban (n, 9) are created.

  Since the saturation information S is a small value, the divided area Dban (n, 1) is a black and white video area without vivid colors. Therefore, the divided area Dban (n, 1) is close to white, and the divided area Dban (n, 3) is close to black.

  The divided area Dban (n, 4) represents a hue angle from 0 degree to 60 degrees, and the hue changes from red to yellow, and the divided area Dban (n, 5) represents a hue angle from 60 degrees to 120 degrees, and yellow to green The hue that changes to, the divided area Dban (n, 6) represents a hue angle of 120 degrees to 180 degrees, and the hue that changes from green to light blue, the divided area Dban (n, 7) has a hue angle of 180 degrees to 240 degrees. Represents a hue that changes from light blue to blue, and the divided area Dban (n, 8) represents a hue angle of 240 degrees to 300 degrees, and a hue that changes from blue to purple, and the divided area Dban (n, 9) represents a hue. It represents an angle from 300 degrees to 360 degrees, and represents a hue that changes from purple to red.

  In the example illustrated in FIG. 14, the image is divided into nine regions of divided regions Dban (n, 1) to Dban (n, 9), but may be more or less than the example illustrated in FIG. 14. Further, in the division, some information of the hue information H, the saturation information S, and the lightness information V may be omitted. Although accuracy is reduced, high-speed computation is possible.

  In the division of the color space, the hue information H, the saturation information S, and the lightness information V may be divided so as to be uniform or may be divided so as to be non-uniform. That is, when the area is divided, the division number m and the range may be freely set.

  A histogram calculation unit 171 provided in the video feature detection unit 179 calculates each feature information Ha in the input color area information value Dban based on the video signal Dba, and a histogram provided in the video feature detection unit 179. The data is output to the analysis unit 173.

  FIG. 15 shows an example of the feature information Ha generated by the histogram calculation unit 171. In the example shown in FIG. 15, the number of pixels for the divided area Dban (n, m) of the video signal Dba for one frame is calculated as the feature information Ha, and the histogram is generated. . Hereinafter, information defining the histogram of each color region Dban (n, m) in the video signal Dba generated by the histogram calculation unit 171 is referred to as a color histogram HA.

  In the example shown in FIG. 15, the horizontal axis in the figure indicates the divided area Dban (n, m), and the vertical axis indicates the frequency, that is, the number of pixels for the divided area Dban (n, m) of the video signal Dba for one frame. Is shown. Hereinafter, the number of pixels for the divided region Dban (n, m) is represented as Dbad (n, m).

  In this example, the frequency of the hue histogram is represented by the number of pixels with respect to the divided area Dban (n, m) of the video signal Dba for one frame, but may be displayed as the cumulative number of pixels. Further, 10% or the like may be displayed as a ratio of the total number of pixels, not the number of pixels.

  FIG. 16 is an explanatory diagram illustrating an example of generation of the feature value Hac by the histogram analysis unit 173. As shown in the figure, the histogram analysis unit 173 has a threshold value in which each frequency Dbad (n, m) of the color histogram HA is smaller than a predetermined determination threshold value TDbh2, or a predetermined threshold value larger than the threshold value TDbh2. It is determined whether the value is between the TDbh1 values or larger than the determination threshold value TDbh1, and a determination information value Dbac (n, which defines any one of three classification information values, low, medium, and high m) is calculated.

In the example shown in FIG. 16, since Dbad (n, 1) and Dbad (n, 9) are larger than a predetermined threshold value TDbh1, a value indicating “high” is input. Further, since Dbad (n, 2) and Dbad (n, 8) are values between the threshold value TDbh2 and the threshold value TDbh1 value, a value indicating “medium” is input. Since Dbad (n, 3) to Dbad (n, 7) are smaller than a predetermined determination threshold value TDbh2, a value indicating “low” is input. In this example, there are two types of predetermined threshold values. Although classified into three types of low, it may be classified into other than three types. That is, the threshold value may be more or less than two types. More detailed classification is possible by adjusting a large number of threshold values. Further, the processing amount can be reduced by reducing the number of thresholds.

  Further, the threshold value may be changed depending on the divided area Dban (n, m). For example, Dban (n, 1) is determined only by a predetermined threshold value TDbh1, and Dban (n, 2) is determined by a predetermined threshold value TDbh1 and another predetermined threshold value TDbh2, TDbh3. The method of obtaining m) can also be taken. As described above, by changing the threshold value according to the divided area Dban (n, m), the area to be analyzed in detail is focused on, and the analysis accuracy of the area that does not require detailed analysis is reduced. Can be obtained.

  The histogram analysis unit 173 outputs the determination information value Dbac (n, m) in the divided region Dban (n, m) to the feature determination unit 175 provided in the video feature detection unit 179 as the color feature value Hac.

  That is, in the example shown in FIG. 16, Dbac (n, 1) = Dbac (n, 9) = “high”, Dbac (n, 2) = Dbac (n, 8) = “medium”, Dbac (n, 3) = Dbac (n, 4) = Dbac (n, 5) = Dbac (n, 6) = Dbac (n, 7) = The color feature value Hac meaning “low” is output to the feature determination unit 175.

  In outputting the color feature value Hac, only one of the divided regions Dban (n, m) is defined by defining one of the divided region Dban (n, m) and the determination information value Dbac (n, m). Alternatively, only the determination information value Dbac (n, m) may be output.

  For example, a method of outputting the divided region Dban (n, m) where the determination information value Dbac (n, m) = “high” is conceivable. Returning to the example of FIG. 16, the divided regions Dban (n, 1) and Dban (n, 9) have the color feature value Hac as the divided region Dban (n, m) where Dbac (n, m) = “high”. Is output to the feature determination unit 175.

  As another example, a method of designating a divided area in which the determination information value Dbac (n, 1) of the divided area Dban (n, 1) is output can be considered. Returning to the example of FIG. 16, the determination information value “high” is output to the feature determination unit 175 as the color feature value Hac as the determination information value of the divided region Dban (n, 1).

  If necessary, it is also possible to take a means of outputting only a part of the determination information value as the color feature value Hac and not outputting the remaining determination information value. Thus, by limiting the information to be output, the amount of information can be reduced and the amount of calculation can be reduced.

  In this example, the color feature value Hac is divided into three types of “high”, “medium”, and “low” according to the threshold value, so that the amount of information retaining the color feature is reduced and the information is reduced. The number may be other than three. Further, each frequency Dbad (n, m) of the color histogram HA may be output as it is.

  The feature determination unit 175 determines the feature of the video based on the combination content of the color feature value Hac output from the histogram analysis unit 173, and outputs it to the region division video change detection unit 19 as the region division video feature value Pa.

  FIG. 17 shows an example in which video features are classified into seven types with respect to combinations of color feature values Hac input to the feature determination unit 175. In order to simplify the explanation, in this example, the color feature value Hac is reduced from the above example, and Dbac (n, 1), Dbac (n, 3), Dbac (n, 4), Dbac (n, 5). , Dbac (n, 6) is used to classify into 7 types for each video feature, and output a region-divided video feature value Pa (n, i). In this example, the features are classified into seven types, but any number of features may be classified.

  In this example, the features are classified into features relating to hue and luminance. However, the classification criteria are not limited thereto, and any feature may be used as long as it represents the features of the video signal Dba.

  The combination content of the feature determination by the feature determination unit 175 can be arbitrarily created based on a conventional danger video or human visual characteristic data. In the example of FIG. 17, Dbac (n, 1), Dbac (n, 3), Dbac (n, 4), and Dbac (n, 5) are “low” and Dbac (n, 6) is “high”. If so, the area division video feature value Pa instructing Pa (n, 4) “green” is output to the area division video change detection unit 19. Unlike this example, by increasing the content of the feature value Hac, finer feature classification becomes possible. It is a video that does not have such characteristics.

  As described above, the feature determination unit 175 can determine a feature based on the hue information H, the saturation information S, and the luminance information V obtained from the video signal. Since the feature determination is performed for each of the video signals Dba (n) in the divided regions, the features in each divided region Dban (n, m) can be obtained.

  In the region-divided video feature detection unit 17 in this example, the input video signal Db is a one-frame video signal, but a plurality of video signals may be used instead of a one-frame video signal. For example, as seen in frame interpolation technology, when a new video signal is created using video signals for multiple frames, analysis is performed based on the new video signal created based on multiple frames. It doesn't matter.

<B-2-2. Operation of Region Divided Video Change Detection Unit 19>
The operation of the area-divided video change detection unit 19 as the video change detection unit provided in the image processing device 13 will be described below.

  The area division image change detection unit 19 analyzes the area division image feature value Pa output from the area division image feature detection unit 17, and detects a change in a certain number of times in a short period or more when a change is detected in a certain area or more. The signal Db is determined to be a dangerous image, and a control value Cr as a control signal including information such as the presence / absence of the danger of the video signal Db and the type of influence on the human body is given to the countermeasure control unit 4 of the video signal countermeasure unit 6. Output.

  It is assumed that the region division video feature value Pa changes Tt times or more within a Tf frame for a change more than a certain number of times in a short period. Further, the change over a certain region in a short period is set to Ta or more. Within the Tf frame, if there are Ta or more areas where a change of Tt times or more is detected, the control value Cr is output. In the second embodiment, Tf, Tt, and Ta are detection parameters.

  In each video signal Dba (n), a control value Crn (n) as a control signal is calculated when the region-divided video feature value Pa changes Tt times or more within a Tf frame. When the video signal Dba (n) for which the control value Crn (x) as an arbitrary control signal is calculated is Ta or more, the video signal countermeasure unit uses the control value Crn (x) as the control signal as the control value Cr. 6 to the countermeasure control unit 4.

  When there are a plurality of video signals Dba (n) for calculating control values Crn (x) as Ta or more control signals, a method of taking a region occupying a larger area or a method of taking a region having a larger number Etc. are considered.

  In this example, the detection parameters Tf, Tt, and Ta do not have to be constant, and may be adjusted according to changes in the region-divided video feature value Pa. Further, depending on the change of the area division image feature value Pa, it may be determined that the image is not a dangerous image. However, in this example, since the control value Cr as the output control signal is uniquely determined for the video signal Db, the control value Crn (n as the control signal representing the video change in each video signal Dba (n). ) Should be determined at the same time.

  The operation example of the video change detection unit 9 in the first embodiment is shown in the examples shown in FIGS. 7, 8, and 9. Similarly, the region division video change detection unit 19 in the second embodiment is also shown in FIG. , 8 and 9 can be used. However, instead of the video feature value Ps, the area division video feature value Pa is input, and Crn is input instead of the control value Cr.

  Therefore, regarding the transition in a short period, it is possible to use both in the case of transition only between the same video feature values and in the case where transition other than between the same video feature values is included. In addition, depending on the video feature value, it may be determined that the video is not determined as a dangerous video.

  The operation of the region-divided video change detection unit 19 will be described with reference to an example (see FIG. 18) using the divided video signals Dba (1) to Dba (9) shown in FIG.

  As shown in FIG. 18, control values Crn (n) (n = 1, 2,..., 9) as control signals in the video signal Dba (1) to the video signal Dba (9) are respectively Crn (a). , Crn (b), Crn (c), and Crn (d). When the detection parameter Ta = 4, Crn (n) having four or more regions is only Crn (a), and Crn (a) is output as the control value Cr.

  In the example of FIG. 18, when the detection parameter Ta = 3, there are two types of Crn (n) having three or more regions, Crn (a) and Crn (b). Since Crn (a) is 4 and Crn (b) is 3, Crn (a) satisfying a larger number may be output as a control value Cr, or Crn (b ) May be output as the control value Cr.

  Note that the detection parameter Ta in this example is defined as the number of regions that satisfy the condition, but as described in part in this example, it can also be defined as the area of the region that satisfies the condition.

  The area-divided video change detection unit 19 can detect a dangerous video by detecting a feature of a video signal and detecting a transition of the feature in a short period. In addition, since the detection parameters Tr, Tf, Ta and the control value Cr (control value Crn) can be changed for each feature, the detection accuracy can be adjusted. For example, it is possible to increase the detection accuracy of dangerous images that require highly accurate detection.

  Further, by outputting the control value Cr in consideration of the characteristics of the video signal, it is possible to effectively perform the treatment performed on the dangerous video reflecting the characteristics.

  Here, the prepared control value Cr (control value Crn) may be provided by the number of combinations of Pa (i), or may be the same as the number of video features. Further, only one type of control value Cr (control value Crn) may be defined and only the presence / absence of a danger signal may be transmitted.

  Also, unlike the present example, each detection parameter Tf, Tt, Ta and control value Crn are set even when the transition in a short period is a change over two or more types of region-divided video feature values Pa (n, i). It doesn't matter.

  By outputting the control value Cr (control value Crn) in accordance with the combination of the region-divided video feature values Pa (n, i), a change from one specific video feature to another specific video feature is defined. be able to. When it is desirable to uniquely determine a specific feature change of the video signal, the control value Cr (control value Crn) may be set uniquely.

  By creating the control value Cr in accordance with the feature change of the video signal, it is possible to effectively perform the treatment performed on the dangerous video in the video signal countermeasure unit 6 reflecting the feature.

  Further, since the control value Cr is determined based on the change Crn (n) of the region-divided video feature value Pa (n, i) determined for each region, for example, there is a region where the change in the video feature is small. In such a case, an effect of improving the detection accuracy of dangerous images can be expected.

  In this example, the control value Cr is calculated by integrating the control value Crn with a threshold value when calculating the control value Cr with respect to the change in the region-divided video feature value Pa. Any configuration may be used as long as the control value Cr is calculated using the region-divided video feature value Pa of the video signal Dba in the divided region. For example, a configuration in which the video feature value Ps in all frames is calculated based on the region-divided video feature value Pa, and the control value Cr is calculated based on the video feature value Ps is conceivable.

  When the control value Cr is being output, a video feature change different from the control value Cr (Bf) detected so far is observed, and when a new control value Cr (Af) is calculated, Cr (Bf), Cr ( Any of Af) may be output. Further, another control value Cr (Ba) indicating that both Cr (Bf) and Cr (Af) are output may be newly output.

  In the case of a configuration that outputs Cr (Af), it is possible to detect a change in the dangerous video each time and take a countermeasure corresponding to the type of the dangerous video. On the other hand, when Cr (Ba) is configured to be output, it can be seen that the danger video has a characteristic that the type of danger changes frequently. Therefore, measures such as taking general measures effective for the danger video in general can be considered. It is done.

  In this example, when it is determined that the video signal Db is a dangerous video, the control value Cr is output to the video signal countermeasure unit 6. However, even if the video signal Db is not a dangerous video, the control value Cr It may be configured to output Cr. In this case, the control value Cr may output information that means that no correspondence with the video signal Db is necessary, information that means that the change of the video signal Db is not dangerous, or the like.

  Unlike this example, the detection parameters Tf, Tt, Ta and the control value Cr may all be set to the same value. However, in this case, detection according to the feature cannot be performed, and the effect of the treatment is reduced.

  Regarding the several frames until the region-divided video change detection unit 19 detects the dangerous video, since the detection has not been completed, the dangerous video is output as it is. Since there is a tendency to exert a strong influence, there is little influence on the human body in a short time required for detection. In order to shorten the time until detection, the detection parameters Tf, Tt, and Ta may be set small. Although the detection time can be shortened, the detection accuracy is somewhat lowered.

  The output of the control value Cr by the area division video change detection unit 19 is continued until the change of the area division video feature value Pa is completed. Note that the output of the control value Cr may be stopped depending on other conditions such as the elapse of a fixed time or the end of the video content after the change of the region-divided video feature value Pa is completed.

  However, as described above, when the output of the control value Cr is stopped under a condition other than the end of the change in Pa, the treatment is performed even on the video signal that is not a dangerous video, and the content of the content is It can be damaged. On the other hand, there is a possibility that a similar dangerous video is included again in the same content, and when a dangerous video is detected again, several frames until the dangerous video is detected become unnecessary, so that an effect can be expected.

<B-3. Effect>
According to the second embodiment of the present invention, in the image display device, the region division video feature detection unit 17 as the video feature detection unit divides the video signal into a plurality of regions, and from the video information of the divided regions. Video feature is detected, and a segmentation feature signal Pa is output for each segmented region. The segmentation video change detection unit 19 as a video change detection unit receives a segmentation video feature value Pa as a segmentation feature signal for a predetermined time. In the case of a certain number of changes, a control value Crn as a control signal is output for each area division video feature value Pa as an area division feature signal, and the video signal countermeasure unit 6 controls the control value for each of the divided areas. By analyzing Crn, dangerous video can be detected by detecting changes in video features in a short period of time based on video features obtained from video signals for one frame. . In addition, by obtaining the characteristics of the danger video, it is possible to perform a treatment in accordance with the characteristics of the danger video. Here, since the video information is acquired from each of the divided areas, not only the characteristics of the entire video signal but also the characteristics of each area can be obtained. Therefore, more detailed features can be obtained compared to analysis without dividing the region, and high-accuracy and adaptive detection of dangerous images in consideration of the features of the video signal is possible. In addition, the detection accuracy of a dangerous image that does not change only in a part of the area is improved.

  The image display apparatus according to the second embodiment is not limited to the video display apparatus and can be used in other fields related to video as a technique for detecting a dangerous video from a video signal. For example, a video recording device such as a video recorder such as a hard disk or a DVD may be used as another field.

  In addition, when these applications are performed in the video recording device, unlike the case of viewing in real time, by analyzing in advance, the number of frames required until the detection of dangerous video is unnecessary, and a safer video can be obtained. Can be provided. When the detection is performed in advance, the treatment for the dangerous image can be performed in advance as well.

  On the other hand, in order to perform the same process as the present embodiment using the techniques described in Patent Document 2 and Patent Document 3 described above, it is necessary to hold multimedia data whose content type is known in advance. . For this reason, classification cannot be performed for first-time programs.

  In the techniques described in Patent Document 2 and Patent Document 3 described above, dangerous images are uniformly detected using only threshold values in a luminance signal, a hue signal, and a color difference signal. For this reason, it is not possible to obtain the characteristics of the dangerous video, and it is not possible to perform treatments according to the characteristics. Moreover, the detection accuracy is inferior and detailed detection cannot be performed.

  In the image display device according to the second embodiment, the dangerous video is detected using the HSV color space as an example. For example, the RGB color space, the CMY color space, the HLS color space, the YCbCr color space, the Lab color system, L Any other color space or color system such as * a * b * color system, L * u * v * color system, etc. can be applied.

<C. Embodiment 3>
<C-1. Configuration of Image Display Device>
FIG. 19 is a block diagram showing a configuration of an image display apparatus according to Embodiment 3 of the present invention. The image display device according to the third embodiment includes an image processing device 23 instead of the image processing device 13 in the image processing device according to the second embodiment described above. Other constituent elements are the same as those shown in the first embodiment, and thus description thereof is omitted.

<C-1-1. Configuration of Image Processing Device 23>
The configuration of the image treatment device 23 in the image display device will be described below.

  The image processing apparatus 23 according to the third embodiment is connected to the video signal countermeasure unit 16 and the region division video feature detection unit 17 that receive the output video signal Db from the reception unit 2 and the region division video feature detection unit 17. And an area division video change detection unit 29 that outputs to the video signal countermeasure unit 16. The video signal countermeasure unit 16 includes a countermeasure execution unit 15 to which a signal from the receiving unit 2 is input, and a countermeasure control unit 14 to which a signal from the region division video change detection unit 29 is input.

  The area division video feature detection unit 17 divides video information for each frame into one or more areas based on the video information included in the video signal Db, and calculates an area division video feature value Pa for each area. Then, it outputs to the area division | segmentation video change detection part 29. FIG. The area-divided video feature detection unit 17 according to the third embodiment is the same as that of the second embodiment and performs the same operation as that described in the second embodiment. To do.

  The area division video change detection unit 29 detects the change of the area division video feature value Pa over a certain number of times in a short period based on the area division video feature value Pa for each area. When the control value Crn for each region exceeds a certain threshold value, the video signal Db is determined to be a dangerous image, and the presence or absence of the video signal Db, the type of influence on the human body, etc. The control value Cra as a control signal including the information in is output to the countermeasure control unit 14.

  The countermeasure control 14 calculates a countermeasure instruction value Pra indicating the content of the treatment performed by the countermeasure execution unit 25 for the video signal Db based on the control value Cra, and outputs it to the countermeasure execution unit 5.

  On the other hand, when the input countermeasure instruction value Pr is a content for instructing countermeasure execution (that is, when it is determined that the video signal Db is a dangerous video), the countermeasure execution unit 15 applies the countermeasure instruction value Pr to the video signal Db. The treatment is performed for each area, the influence of the danger video on the human body is reduced or invalidated, and the signal after the treatment is output to the display unit 10 as the video signal Dc.

<C-2. Operation of Image Processing Device 3>
In the image display device described above, the operation of the image processing device 23 will be described below for each component.

<C-2-1. Operation of Region Divided Video Change Detection Unit 29>
The operation of the area-divided video change detection unit 29 as the video change detection unit in the above-described image processing device 23 will be described below.

  In the third embodiment, similarly to the second embodiment, the region division video feature value Pa changes Tt times or more within a Tf frame after a certain number of changes in a short period. In addition, when the number of areas in which the change of Tt times or more has been detected within the Tf frame is Ta or more, the area division video change detection unit 29 as the video change detection unit has a control value Cra (n) for each area. Is output.

  In the divided video signal Dba (n), a control value Cra (n) as a control signal is calculated when the region-divided video feature value Pa of the video signal divided within the Tf frame changes Tt times or more. . When the video signal Dba (n) for which the control value Cra (y) as one or more arbitrary control signals is calculated is Ta or more, the control value Cra (n) as the control signal is used as the control value Cra. It outputs to the countermeasure control part 14 of the video signal countermeasure part 16. In this example, Cra (y) does not have to be one type of control signal, and can be determined by a plurality of control signals.

  In this example, the detection parameters Tf, Tt, and Ta do not have to be constant, and may be adjusted according to changes in the region-divided video feature value Pa. Further, depending on the change of the area division image feature value Pa, it may be determined that the image is not a dangerous image. However, in order to synchronize with the image quality adjustment performed by the video signal countermeasure unit 16, it is desirable to simultaneously determine the control value Cra (n) as a control signal representing a video change in each video signal Dba (n). When synchronization is not taken, measures are taken for the video at different timings for each of the divided area video signals Dba (n), but it is also possible to take measures against the dangerous video in this way.

  The operation example of the video change detection unit 9 in the first embodiment is shown in the examples shown in FIGS. 7, 8, and 9, but the region division video change detection unit 29 as the video change detection unit in the third embodiment. Similarly, the examples shown in FIGS. 7, 8, and 9 can be used. However, instead of the video feature value Ps, the region division video feature value Pa is input, and Cra is input instead of the control value Cr.

  Therefore, regarding the transition in a short period, it is possible to use both in the case of transition only between the same video feature values and in the case where transition other than between the same video feature values is included. In addition, depending on the video feature value, it may be determined that the video is not determined as a dangerous video.

  The operation of the region-divided video change detection unit 29 will be further described using an example using the divided video signal Dba (1) to Dba (9) shown in FIG.

  As shown in FIG. 20, control values Cra (n) (n = 1, 2,..., 9) as control signals in the video signal Dba (1) to the video signal Dba (9) are Cra (a). , Cra (b), Cra (nop). Here, Cra (nop) is information meaning that the change of the video signal Dba (n) is not dangerous, and Cra (y), which contains a danger signal in the area and needs to be detected, is defined as Cra (a), Let Cra (b).

  As shown in FIG. 21, when the detection parameter Ta = 6, it occupies 7 regions including Cra (a) and Cra (b), so that the control value Cra is Cra (1) = Cra (2 ) = Cra (3) = Cra (a), Cra (5) = Cra (6) = Cra (8) = Cra (9) = Cra (b), Cra (4) = Cra (7) = Cra (nop) ) Is output.

  In this example, when the detection parameter Ta = 8, information indicating that the control value Cra is not output without being recognized as a danger signal, or that the control value Cra does not need to correspond to the video signal Db, or video Information indicating that the change of the signal Db is not dangerous is output. In this example, Cra (nop) is output.

  Although the detection parameter Ta in this example is defined as the number of regions that satisfy the condition, it can also be defined as the area of the region that satisfies the condition as described in the second embodiment.

  The region-divided video change detection unit 29 can detect the dangerous video by detecting the feature of the video signal and detecting the transition of the feature in a short period. In addition, since the detection parameters Tr, Tf, Ta and the control value Cra can be changed for each feature, the detection accuracy can be adjusted. For example, it is possible to increase the detection accuracy of dangerous images that require highly accurate detection.

  Further, by outputting the control value control value Cra considering the characteristics of the video signal, it is possible to effectively perform the treatment performed on the dangerous video reflecting the characteristics.

  Here, the prepared control value control value Cra may be provided by the number of combinations of Pa (i), or may be the same number as the number of video features. Further, only one type of control value Cra may be defined and only the presence / absence of a danger signal may be transmitted.

  Also, unlike the present example, each detection parameter Tf, Tt, Ta and control value Cra is set even when the transition in a short period is a change over two or more types of region-divided video feature values Pa (n, i). It doesn't matter.

  By outputting the control value Cra according to the combination of the region-divided video feature values Pa (n, i), it is possible to define a change from one specific video feature to another specific video feature. When it is desirable to uniquely determine a specific feature change of the video signal, the control value Cra may be set uniquely.

  By creating the control value Cra according to the feature change of the video signal, it is possible to effectively perform the treatment performed on the dangerous video in the video signal countermeasure unit 16 reflecting the feature.

  Further, since the control value Cra is determined based on the change Cra (n) of the region-divided video feature value Pa (n, i) determined for each region, for example, there is a region where the change in the video feature is small. In such a case, an effect of improving the detection accuracy of dangerous images can be expected.

  In addition, since the dangerous video can be treated with respect to the divided video signal Dba, it is possible to more effectively cope with the characteristics of the dangerous video for each area.

  The area division video change detection unit 29 uses any configuration as long as it calculates the control value Cra for each divided video signal using the area division video feature value Pa of the video signal Dba in the divided area. It doesn't matter.

  While the control value Cra is being output, when a video feature change different from the control value Cra (Bf) detected so far is seen and a new control value Cra (Af) is calculated, Cra (Bf), Cra ( Any of Af) may be output. Also, another control value Cra (Ba) indicating that both Cra (Bf) and Cra (Af) have been output may be newly output.

  When configured to output Cra (Af), it is possible to detect a change in the dangerous video each time and take a countermeasure according to the type of the dangerous video. On the other hand, in the case of a configuration that outputs Cra (Ba), since it can be seen that the danger video has a characteristic that the type of danger changes frequently, a countermeasure such as taking general measures effective for the danger video in general can be considered. It is done.

  In this example, when it is determined that the video signal Dba is a dangerous video, the control value Cra is output to the video signal countermeasure unit 16, and also when it is determined that the video signal Dba is not a dangerous video, the control value Cra (Cra (nop )) Is output, but when the video signal Dba is not a dangerous video, the control value Cra may not be output.

  Unlike this example, the detection parameters Tf, Tt, Ta and the control value Cra may all be set to the same value. However, in this case, detection according to the feature cannot be performed, and the effect of the treatment is reduced.

  With respect to several frames until the region-divided video change detection unit 29 detects the dangerous video, since the detection is not completed, the dangerous video is output as it is. Since there is a tendency to exert a strong influence, there is little influence on the human body in a short time required for detection. In order to shorten the time until detection, the detection parameters Tf, Tt, and Ta may be set small. Although the detection time can be shortened, the detection accuracy is somewhat lowered.

  The output of the control value Cra by the area division video change detection unit 29 is continued until the change of the area division video feature value Pa is completed. Note that the output of the control value Cra may be stopped depending on other conditions such as the elapse of a fixed time or the end of the video content after the change of the region-divided video feature value Pa is completed.

  However, as described above, when the output of the control value Cra is stopped under conditions other than the end of the change in Pa, the treatment is performed even on the video signal that is not a dangerous video, and the content of the content is It can be damaged. On the other hand, there is a possibility that a similar dangerous video is included again in the same content, and when a dangerous video is detected again, several frames until the dangerous video is detected become unnecessary, so that an effect can be expected.

<C-2-2. Operation of video signal countermeasure unit 16>
The operation of the video signal countermeasure unit 16 in the image processing device 23 will be described below.

  The countermeasure control unit 14 provided in the video signal countermeasure unit 16 selects the countermeasure instruction value Pra for the video signal Dba corresponding to the control value Cra as the control signal for each divided area of the video signal, and the video signal countermeasure unit 16 is output to the countermeasure execution unit 15 provided in 16. The measure instruction value Pra can be freely adjusted based on the characteristics of the danger video.

  The instruction by the countermeasure instruction value Pra output from the countermeasure control unit 14 to the countermeasure execution unit 15 is, for example, a method of reducing the number of frames of the video and reducing the degree of change, or a method of calling attention to the viewer by text or voice. A method of replacing with another video or still image, a method of reducing values such as luminance and saturation, and the like are conceivable.

  The countermeasure execution unit 15 performs image processing for each area of the video signal divided based on the countermeasure instruction value Pra output from the countermeasure control value 14, and reduces or invalidates the influence of the dangerous image on the human body. The countermeasure execution unit 15 processes the entire image on the basis of the control value Cra for each divided area output by the countermeasure execution unit 14, and deletes or invalidates the influence of the danger video on the human body. There may be.

  The instruction based on the countermeasure instruction value Pr is preferably created in consideration of the control value Cr as a control signal calculated from the video feature. For example, in the case of a video in which a black and white image blinks, a method of reducing the number of frames and the degree of change can be considered. On the other hand, in the case of a video where bright colors such as yellow and light blue blink, a method of reducing the degree of change by reducing the number of frames after reducing the saturation of the video signal is conceivable. .

  Also, taking advantage of the strength of image processing for each divided video signal, replacing only a partial area of the video signal with another video or still image, reducing the value of luminance saturation, etc. Can be used.

  Here, Pra (i) corresponding to Cra (i) may be all the same or different.

  As described in the first and second embodiments, the countermeasure instruction value Pra may be output when the video signal Dba is not a dangerous video. In this case, the countermeasure instruction value Pr may be output as information indicating that no countermeasure regarding the video signal Db is required, information indicating that a change in the video signal Db is not dangerous, or the like. A configuration in which the countermeasure instruction value Pra is not output when the video signal Dba is not a dangerous video is also possible.

  In the image processing for the dangerous video, there may be a frame or a region where the image processing is not performed. As an example, there may be a case where the number of frames is reduced, and a frame that does not display is generated. On the other hand, instead of a frame that is not displayed, a method of continuing to display as a still image can be considered.

<C-3. Effect>
According to the third embodiment of the present invention, in the image display device, the video signal countermeasure unit 16 performs predetermined processing on the video signal according to the analysis result of the control value Cra as the control signal for each divided area. By performing the above, it is possible to grasp the characteristics of each divided area, change the treatment to be performed for each area of the video signal, and perform more flexible treatment such as processing only a specific area Can do. In addition, when a dangerous video having a plurality of features is included, processing suitable for each can be performed for each region.

  The image display apparatus according to the third embodiment is not limited to the video display apparatus and can be used in other fields related to video as a technique for detecting a dangerous video from a video signal. For example, a video recording device such as a video recorder such as a hard disk or a DVD may be used as another field.

  In addition, when these applications are performed in the video recording device, unlike the case of viewing in real time, by analyzing in advance, the number of frames required until the detection of dangerous video is unnecessary, and a safer video can be obtained. Can be provided. When the detection is performed in advance, the treatment for the dangerous image can be performed in advance as well.

  On the other hand, in order to perform the same process as the present embodiment using the techniques described in Patent Document 2 and Patent Document 3 described above, it is necessary to hold multimedia data whose content type is known in advance. . For this reason, classification cannot be performed for first-time programs.

  In the techniques described in Patent Document 2 and Patent Document 3 described above, dangerous images are uniformly detected using only threshold values in a luminance signal, a hue signal, and a color difference signal. For this reason, it is not possible to obtain the characteristics of the dangerous video, and it is not possible to perform treatments according to the characteristics. Moreover, the detection accuracy is inferior and detailed detection cannot be performed.

  In the image display apparatus according to the third embodiment, the dangerous video is detected using the HSV color space as an example. For example, the RGB color space, the CMY color space, the HLS color space, the YCbCr color space, the Lab color system, L Any other color space or color system such as * a * b * color system, L * u * v * color system, etc. can be applied.

It is a block diagram which shows the structure of the image display apparatus which concerns on Embodiment 1 of this invention. It is a block diagram which shows the structure of the image | video feature detection part which concerns on Embodiment 1 of this invention. It is a figure which shows the histogram produced | generated by the brightness | luminance histogram calculation part which concerns on Embodiment 1 of this invention. It is a figure which shows the hue histogram produced | generated by the color histogram calculation part which concerns on Embodiment 1 of this invention. It is a figure which shows the hue histogram and threshold value condition which are produced | generated by the color histogram calculation part which concerns on Embodiment 1 of this invention. It is a figure for demonstrating operation | movement of the feature determination part which concerns on Embodiment 1 of this invention. It is a figure for demonstrating operation | movement of the image | video change detection part which concerns on Embodiment 1 of this invention. It is a figure for demonstrating operation | movement of the image | video change detection part which concerns on Embodiment 1 of this invention. It is a figure which shows an example of the calculation method of the control value output by the image | video change detection part which concerns on Embodiment 1 of this invention. It is a block diagram which shows the structure of the image display apparatus which concerns on Embodiment 2 of this invention. It is a block diagram which shows the structure of the area division | segmentation image | video feature detection part which concerns on Embodiment 2 of this invention. It is a figure which shows an example of the video signal divided | segmented by the area division part which concerns on Embodiment 2 of this invention. It is a figure which shows the example of 1 division of the HSV color space divided | segmented by the histogram calculation area | region determination part which concerns on Embodiment 2 of this invention. It is a figure which shows the example of 1 division of the HSV color space divided | segmented by the histogram calculation area | region determination part which concerns on Embodiment 2 of this invention. It is a figure which shows the color histogram produced | generated by the histogram calculation part which concerns on Embodiment 2 of this invention. It is a figure which shows the color histogram produced | generated by the histogram calculation part which concerns on Embodiment 2 of this invention, and threshold value conditions. It is a figure for demonstrating operation | movement of the feature determination part which concerns on Embodiment 2 of this invention. It is a figure for demonstrating operation | movement of the area division | segmentation video change detection part which concerns on Embodiment 2 of this invention. It is a block diagram which shows the structure of the image | video feature detection part which concerns on Embodiment 3 of this invention. It is a figure for demonstrating operation | movement of the area division | segmentation video change detection part which concerns on Embodiment 3 of this invention. It is a figure for demonstrating operation | movement of the area division | segmentation video change detection part which concerns on Embodiment 3 of this invention.

Explanation of symbols

  DESCRIPTION OF SYMBOLS 1 Input terminal, 2 Receiving part, 3, 13, 23 Image processing apparatus, 4,14 Countermeasure control part, 5,15 Countermeasure execution part, 6,16 Video signal countermeasure part, 7,179 Video feature detection part, 9 Video change Detection unit, 10 display unit, 17 region division video feature detection unit, 19, 29 region division video change detection unit, 70 signal distribution unit, 71 luminance histogram calculation unit, 72 color histogram calculation unit, 73 luminance histogram analysis unit, 74 colors Histogram analysis unit, 75, 175 Feature determination unit, 170 Histogram calculation area determination unit, 171 Histogram calculation unit, 173 Histogram analysis unit, 178 Region division unit.

Claims (8)

A video feature detection unit that detects video features for each frame from predetermined video information included in the received video signal, and outputs a video feature signal;
When the video feature signal has changed a predetermined number of times within a predetermined time, a video change detection unit that outputs a control signal;
A video signal countermeasure unit that analyzes the control signal and performs a predetermined treatment on the video signal according to the analysis result;
An image display device comprising: The predetermined treatment is a treatment for suppressing a factor that adversely affects the human body included in the video signal.
The image display device according to claim 1. The predetermined video information includes any one of luminance information, hue information, and saturation information.
The image display device according to claim 1. The video feature detection unit divides the video signal into a plurality of regions, detects video features from video information of the divided regions, outputs a region division feature signal for each of the divided regions,
The video change detection unit outputs a control signal for each region division feature signal when the region division feature signal has changed a predetermined number of times within a predetermined time,
The video signal countermeasure unit analyzes the control signal for each of the divided areas.
The image display apparatus in any one of Claims 1-3. The video signal countermeasure unit performs a predetermined treatment on the video signal according to the analysis result of the control signal for each of the divided areas.
The image display device according to claim 4. The video change detection unit outputs the control signal when the video feature signal changes from a predetermined specific video feature to another predetermined specific video feature.
The image display apparatus in any one of Claims 1-5. The video feature detection unit detects video features from the video signal for a plurality of frames instead of the video signal for the one frame;
The image display device according to claim 1. The video signal countermeasure unit applies different predetermined treatments as the predetermined treatments according to different analysis results of the control signals.
The image display device according to claim 1.

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