JP2010154484A - Device, method and program for video conversion - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To suitably convert colors of a plurality of subjects contained in a video. <P>SOLUTION: An area division unit 22 divides the video into areas of a plurality of objects, and an RGB conversion parameter generation unit 23 generates histograms of the respective areas to generate RGB conversion parameters for distributing the histograms of the respective areas to a target distribution range. An RGB conversion function generation unit 25 generates color conversion functions by using the RGB conversion parameters. An RGB conversion function composition unit 28 calculates a composition coefficient for synthesizing color conversion function, and synthesizes a color conversion function of a plurality of color conversion functions by using the composition coefficient. A video conversion unit 27 applies the synthesized color conversion function to the video. <P>COPYRIGHT: (C)2010,JPO&INPIT

Description

  The present invention relates to a technique for automatically converting the gradation of an image, and more particularly to a technique for converting the gradation of an input image in a digital image processing apparatus.

  The histogram of the video shows the distribution of light and dark values for each pixel in the video. Contrast stretching is a technique for improving the contrast of an image by widely distributing the light and dark values from a low value to a high value for an image with a skewed light and dark value distribution. Through contrast stretching, an image that is too dark becomes brighter, and an image that is too bright becomes darker to maintain an appropriate brightness value. That is, the overall contrast balance of the video is improved by correcting the luminance value distribution of the video.

  FIG. 17 is a block diagram showing a configuration of a conventional contrast stretching apparatus. As shown in the figure, the conventional contrast stretching apparatus has a distribution calculation unit 42 and a stretching unit 43.

  The distribution calculation unit 42 counts the brightness value from the input video to obtain a histogram value or a histogram function. The target value input unit receives the target minimum value and the target maximum value, and outputs the input values to the stretching unit 43. The stretching unit 43 obtains a light / dark value having a minimum value and a maximum value using the histogram function obtained by the distribution calculation unit 42, and a target value in which the minimum value and the maximum value of the brightness of the input video are input to the target distribution input unit. Transform the histogram to match the lowest and target highest values. In the processing of the stretching unit 43, if the target minimum value is 0 and the target maximum value is 255, the image has brightness values from 0 to 255, and the contrast of the image increases.

  Further, the above-described histogram enlarging process is similarly applied to the R component, the G component, and the B component of the video, so that the contrast can be increased while maintaining the color. Alternatively, it is possible to create a video with an increased contrast with little color bias by performing histogram enlargement processing independently on the R component, the G component, and the B component. As prior art documents related to the present application, there are the following.

Japanese Patent Laid-Open No. 4-257082

  However, in the case of contrast stretching according to the prior art, it was possible to improve the overall contrast, but it was not possible to adjust the colors of multiple subjects included in the video to the desired color . In particular, it has been impossible to adjust the brightness and color tone of an image taken with a plurality of persons as subjects.

  The present invention has been made to solve the above problems, and the problem is that the colors of a plurality of subjects included in an image can be appropriately converted, and in particular, a plurality of persons are photographed as subjects. Another object of the present invention is to provide a video conversion device that can adjust the brightness and color tone of an image as desired.

  According to a first aspect of the present invention, there is provided a video conversion device, a storage unit that stores an input video, a region dividing unit that reads the video, divides it into a plurality of regions and stores the divided video in a storage unit, and a desired color component Histogram creation means for creating a histogram of each region; target range designating means for designating a target distribution range for each histogram; and the video so that each histogram is distributed in the target distribution range. A conversion parameter creating means for creating a conversion parameter for conversion; a color conversion function creating means for creating a color conversion function using the conversion parameter; and a synthesis coefficient for synthesizing the color conversion function; Color conversion function combining means for combining a plurality of the color conversion functions using a combination coefficient, and converting the image by applying the combined color conversion function to the image Image conversion means, the color conversion function creating means creates color conversion functions corresponding to a plurality of face areas, and the color conversion function combining means corresponds to a plurality of face areas. A color conversion function is created by synthesizing the generated color conversion functions.

  In the present invention, the image is divided into a plurality of regions, a conversion parameter is created to distribute the histogram of each region in the target distribution range, a color conversion function is created using the conversion parameter, and the color conversion function A composite coefficient is calculated for combining the image, and a plurality of color conversion functions are combined using the composite coefficient, and the combined color conversion function is applied to the video. Each color conversion function is created, and the color conversion function created by combining the color conversion functions created for multiple face areas is created to properly convert the colors of multiple subjects in the video. In particular, it is possible to adjust the brightness and color tone of an image taken with a plurality of persons as subjects, as desired.

  In the video conversion apparatus, the color conversion function combining means increases the weight of the combination as the area of the face area increases. In the present invention, the color weight of the face area having a large area is increased.

  In the video conversion apparatus, the color conversion function combining means increases the weight at the time of combining as the distance from the face region to the center of the video is smaller. In the present invention, the color weight of the face region having a small distance to the center of the video is increased.

  In the video conversion apparatus, the color conversion function combining means increases the weight at the time of combination as the color of the face region becomes brighter. In the present invention, the color weight of the bright face area is increased.

  In the video conversion apparatus, the target range designating unit designates the target distribution range based on a model video dragged and dropped onto the input video display area. In the present invention, the input video is converted based on the model video.

  In the video conversion apparatus, the video conversion means changes the conversion intensity according to the location of the pointer used in the drag and drop. In the present invention, when the video is converted based on the model video, the conversion strength is changed according to the location of the pointer.

  In the video conversion apparatus, the video conversion means converts only a peripheral portion of a pointer used in the drag and drop. In the present invention, when the video is converted based on the model video, only the peripheral portion of the pointer is converted.

  In the video conversion apparatus, the video conversion means changes the conversion strength in accordance with a drag time length in the drag and drop. In the present invention, when converting the video based on the model video, the conversion intensity is changed according to the length of the drag time.

  In the video conversion apparatus, the video conversion means uses a face region located closest to a pointer position when the drag-and-drop is performed as a conversion target. In the present invention, when a video is converted based on the model video, the face area located closest to the position of the pointer is set as a conversion target.

  A video conversion method according to a second aspect of the present invention is a video conversion method performed by a video conversion device, the step of storing an input video in a storage means, and the video is read out and divided into a plurality of areas and stored. Means for storing, a step of creating a histogram of each region in a desired color component, a step of designating a target distribution range for each histogram, and each histogram as the target distribution range Creating a conversion parameter for converting the video to be distributed, creating a color conversion function using the conversion parameter, calculating a synthesis coefficient for synthesizing the color conversion function, A step of combining a plurality of the color conversion functions using a combination coefficient, and converting the image by applying the combined color conversion function to the image In the step of creating the color conversion function, a color conversion function is created for each of a plurality of face regions, and in the step of synthesizing the color conversion function, a plurality of face regions are handled. A color conversion function obtained by synthesizing the color conversion functions generated in this way is created.

  According to a third aspect of the present invention, there is provided a video conversion program, a process for storing an input video in a storage unit, a process for reading the video, dividing it into a plurality of areas and storing it in a storage unit, and a desired color component A process for creating a histogram for each region; a process for specifying a target distribution range for each histogram; and a conversion for converting the video so that each histogram is distributed in the target distribution range. A process for creating a parameter, a process for creating a color conversion function using the conversion parameter, a synthesis coefficient for synthesizing the color conversion function, and a plurality of the color conversion functions using the synthesis coefficient In the process of creating the color conversion function by causing the computer to execute the process of combining the image and the process of converting the image by applying the combined color conversion function to the image, In the process of creating color conversion functions corresponding to a number of face areas and synthesizing the color conversion functions, a color conversion function is created by synthesizing color conversion functions created corresponding to a plurality of face areas. It is characterized by making it.

  According to the present invention, it is possible to appropriately convert the colors of a plurality of subjects included in an image, and in particular, it is possible to adjust the brightness and color tone of an image shot using a plurality of persons as subjects. .

1 is a block diagram illustrating an overall configuration of a video conversion apparatus according to a first embodiment. It is a block diagram which shows the structure of the area division part 22 for detecting face area information and black eye area information, and dividing an input image | video into a face area and a black eye area. It is a figure which shows an example of the process at the time of detecting a human face in the area | region division part. It is a figure which shows an example of RGB distribution information. It is a figure which shows an example of the probability density function (histogram function) showing the probability that the color value of the pixel p in a certain color component will be x. It is a figure which shows the cumulative distribution function about the probability density function shown in FIG. It is a figure which shows an example of the control value calculation function for calculating a control value from the accumulation ratio value A. It is a figure which shows what added the information of the control value and the target value to each RGB distribution record of FIG. It is a figure which shows an example of the brightness | luminance histogram of an input image | video. It is a figure which shows the luminance histogram of the image | video after applying a color conversion function to the RGB data of the input image | video used for FIG. FIG. 5 is a diagram showing information obtained by adding R target value, G target value, and B target value information to each RGB distribution record of FIG. 4. It is a figure which shows the example in the case of producing | generating a synthetic | combination function when the RGB conversion function synthetic | combination part 28 detects the face of three people. It is a figure which shows an example of the look-up table for each color conversion of R component, G component, and B component. It is a block diagram which shows the whole structure of the video converter which concerns on 2nd Embodiment. It is a figure which shows an example of the utilization method of a video converter. It is a figure which shows an example of distribution feature information. It is a block diagram which shows the structure of the conventional contrast stretching apparatus.

[First Embodiment]
FIG. 1 is a block diagram showing the overall configuration of the video conversion apparatus according to the first embodiment. As shown in the figure, the video conversion device includes an input device 1, a central processing control device 2, and a storage device 3. The input device 1 includes a video signal input unit 11, a shutter input unit 12, and a target distribution selection unit 13. The central processing control device 2 includes a frame extraction unit 21, a region division unit 22, an RGB conversion parameter creation unit 23, a target An RGB distribution creation unit 24, an RGB conversion function creation unit 25, a conversion LUT (lookup table) creation unit 26, a video conversion unit 27, and an RGB conversion function synthesis unit 28 are included. The storage device 3 stores information output by each unit. In addition to the storage unit for storing, an RGB distribution storage unit 31 and a conversion LUT storage unit 32 are provided.

  The video conversion apparatus may be configured as dedicated hardware, or may be configured using a general-purpose computer so that the processing of each unit is executed by a computer program. The results processed by each unit are stored in the storage unit so as to be readable.

  When the video signal is input, the video signal input unit 11 outputs the video signal to the frame extraction unit 21 and the video conversion unit 27. Here, the video output from the video signal input unit 11 is referred to as an input video.

  The input video handled in the present embodiment is a moving image composed of a plurality of frames, and each frame is a still image composed of a plurality of pixels. When the width of the input video is represented by width and the height is represented by height, each frame is composed of width × height pixels. Each pixel is data representing a color in the RGB color model, and is composed of an x coordinate value, a y coordinate value, an R value, a G value, and a B value in the frame. The x coordinate value is an integer value of 1 or more and width or less. Yes, the y-coordinate value is an integer value between 1 and height, and the R value, G value, and B value are integer values between 0 and 255, respectively.

  The target distribution selection unit 13 outputs the target RGB distribution name selected by the user to the target RGB distribution creation unit 24.

  The target RGB distribution creation unit 24 receives the target RGB distribution name and the RGB distribution information group, creates the target RGB distribution information, and outputs the created target RGB distribution information to the RGB conversion parameter creation unit 23. Note that the RGB distribution information group is input by reading from the RGB distribution storage unit 31.

  When a shutter operation is performed by the user, the shutter input unit 12 outputs a shutter signal that tells the frame extraction unit 21 of the shutter operation.

  The frame extraction unit 21 receives a video signal and a shutter signal and outputs a still image. The still image output from the frame extraction unit 21 is a one-frame still image extracted from the input video.

  The area dividing unit 22 divides the input image into a plurality of object areas.

  The RGB conversion parameter creation unit 23 creates a histogram of each region in the R component, the G component, and the B component, receives the target value output from the target RGB distribution creation unit 24 as an input, and creates an RGB conversion parameter.

  The RGB conversion function creating unit 25 receives the RGB conversion parameters, and the R conversion function and the G conversion function corresponding to each histogram so that the histograms of the R component, the G component, and the B component are in a distribution range that matches the RGB conversion parameters. And B conversion function.

The region dividing unit 22 receives a still image and outputs a region information group. The area information group includes a plurality of area information, and each area information includes an area name R and an area set Region _R. If the x coordinate value of pixel p is xp and the y coordinate value is yp, the region set Region _R is

  It is expressed. The area dividing unit 22 may detect the entire area information, the face area information, and the black eye area information when the subject of the still image is a person. Alternatively, when the subject of the still image is an object, the entire region information, the subject region information, and the background region information may be detected. Hereinafter, an example in which the entire area information, the face area information, and the black eye area information are detected when the subject is a person will be described.

Here, the whole area information is composed of the area name WHOLE and the whole area set Region _WHOLE , the face area set is composed of the area name FACE and the face area set Region _FACE , and the black eye area set is the area name EYE and the black eye area set Region _EYE. It shall be comprised by. The whole region set Region _WHOLE is a set including all pixels included in the input still image.

  FIG. 2 is a block diagram showing a configuration of the area dividing unit 22 for detecting face area information and black eye area information and dividing an input image into a face area and a black eye area. The region dividing unit 22 includes an image scale converting unit 221, a detection target region extracting unit 222, a spatial frequency analyzing unit 223, a face candidate determining unit 224, a skin region extracting unit 226, a black eye region extracting unit 227, Consists of.

  Selection of face candidates in the region dividing unit 22 uses Haar-type feature values, and uses an AdaBoost learning method and a method using a cascade structure detector (see, for example, JP-A-2006-293720).

  The detection target region cutout unit 222 cuts out a region having a predetermined size from the scale-converted image. However, the shape of the region handled here may be an arbitrary shape.

  The spatial frequency analysis unit 223 performs spatial frequency filtering on the cut out region. For example, an AdaBoost learning method and a Haar type feature amount detection method having a cascade detector structure may be used.

  The face candidate determination unit 224 determines whether the region can be a face region candidate based on the output value of the spatial frequency analysis unit 223.

The skin area extraction unit 226 receives a face area candidate and outputs a face area set Region _FACE . The face area set Region _FACE is composed of pixels included in face area candidates whose pixel color is skin color. In other words, the Region _FACE has xp as the x coordinate value of pixel p, yp as the y coordinate value, rp as the R value, gp as the G value, and bp as the B value.

  It is expressed. Note that the RGB values handled as skin color are set in advance. For example, in the YUV color model, a method is used in which the Cb value is -40 or more and -20 or less and the Cb value is 15 or more and 35 or less as skin color.

The black eye region extraction unit 227 outputs a black eye region set Region _EYE with the face region candidate as an input. The black eye region set Region _EYE is composed of pixels with low luminance values among the pixels included in the face region candidate. More specifically, among the pixels included in the face area candidate, a 1% pixel group is set as a black eye area set in order of increasing luminance value. FIG. 3 is a diagram illustrating an example of processing when the area dividing unit 22 detects a human face.

One face area set Region _FACE and one black eye area set Region _EYE are created for each face area candidate. Hereinafter, a processing method when there is only one face area candidate will be described.

  The target RGB distribution creation unit 24 receives the target RGB distribution name and the RGB distribution information group and outputs target RGB distribution information. The RGB distribution information group is read from the RGB distribution storage unit 31. The RGB distribution information group includes a plurality of RGB distribution information, and each RGB distribution information has an RGB distribution name and includes a plurality of RGB distribution records. FIG. 4 is a diagram illustrating an example of RGB distribution information. Each RGB distribution record is composed of a record number, a region name, a cumulative ratio value, and a target color. Here, the cumulative ratio value is a decimal value between 0 and 1.

  The color components handled in this embodiment will be described. Luminance (luminance: Y component in the YCbCr color model), Cb (Cb component in the YCbCr color model), Cr (Cr component in the YCbCr color model), black (in the CMYK color model) K component), red (R component in RGB color model), green (G component in RGB color model), blue (B component in RGB color model), hue (H component in HSV color model), saturation (HSV color model) S component) and brightness (V component in the HSV color model), and the minimum value is 0 and the maximum value is 255 in all color components.

  The RGB conversion parameter creation unit 23 receives a still image, a region information group, and target RGB distribution information, and creates and outputs an RGB conversion parameter. The RGB conversion parameter is created by the following procedure.

First, a color value calculation function that returns the color value of the pixel p in the color component Component

And Where g (Component, p, x)

If the pixel p included in the region set Region _R in the pixel set P is extracted, the probability that the color value of the pixel p in the color component Component is x, that is, color (p, Component) = x. Probability density function (histogram function) frequency (P, Region _R , Component, x)

  Is defined.

For example, region information of whole image region information (region name WHOLE, region set Region _WHOLE ), face region information (region name FACE, region set Region _FACE ), and black eye region information (region name EYE, region set Region _EYE ) If the set of pixels representing an image is Py and the luminance color component is Y, the luminance histogram of the entire area is expressed as frequency (Py, Region _WHOLE , Y, x). In addition, the luminance histogram of the face region is represented as frequency (P, Region _FACE , Y, x), and the luminance histogram of the black eye region is represented as frequency (P, Region _EYE , Y, x).

The cumulative distribution function cumulative (P, Region _R , Component, x) derived from the probability density function frequency (P, Region _R , Component, x) representing the histogram of the color component Component is

  It is expressed.

If the probability density function is represented by the curve of FIG. 5, the cumulative distribution function is a curve represented as shown in FIG. Furthermore, the inverse function of the cumulative distribution function with respect to x is

It is expressed. Here, y is a value satisfying the relationship y = cumulative (P, Region _R , Component, x).

Here, the control value calculation function control (P, Region _R , Component, A) is defined as follows using the cumulative distribution function cumulative.

However, here, the set of pixels included in the input still image is P, the region name in the target RGB distribution record is R, the region set corresponding to the region name R created by dividing the still image into regions is Region _R , The color component is Component, and the cumulative ratio value is A.

By applying this control value calculation function to the cumulative ratio value A, as shown in FIG.

  Thus, the control value C corresponding to the cumulative ratio value A is calculated.

Further, using the control value sequence {C _k } _{k = 1,2, ..., n} (where C1 ≦ C2 ≦ ... ≦ Cn) and the target value sequence {T _k } _{k = 1,2, ..., n} , The color conversion function convert ({C _k } _{k = 1,2, ..., n} , {T _k } _{k = 1,2, ..., n} , x) that converts the color value x

It is defined as

  Here, for example, a luminance histogram of a still image is distributed as shown in FIG. 9, and control values {C1, C2, C3, C4} and target values {T1, T2, T3, T4} are determined as shown in the figure. Assuming that the luminance value is converted by applying the color conversion function convert ({C1, C2, C3, C4), {T1, T2, T3, T4}, x), the histogram is as shown in FIG. become. As shown in the figure, the color conversion function converts the histogram so that the control value matches the target value.

  Here, as shown in FIG. 11, the R value of the target color is set as the R target value, the G value as the G target value, and the B value as the B target value for each target RGB distribution record.

Further, assuming that a set of pixels of a still image is P, an area name of a certain target RGB distribution record Record is AREA, and an accumulation ratio value is A, an R control value C _R is calculated using a control value calculation function control.

R control value sequence {C _{R, k} } _{k = 1, 2,..., N} (where C _{R, 1} ≦ C _{R, 2} ≦ ... ≦) by calculating control values for all target RGB distribution records. C _{R, n} ) can be calculated.

Similarly, G control value C _G of Record is

And the G control value sequence {C _{G, k} } _{k = 1, 2,..., N} can be calculated.

Also, the B control value C _B of Record is

And B control value sequence {C _{B, k} } _{k = 1, 2,..., N} can be calculated.

  The RGB conversion function creation unit 25 receives RGB conversion parameters and outputs an R conversion function, a G conversion function, and a B conversion function.

Here, the R control value sequence {C _{R, k} } _{k = 1, 2,..., N} (where C _{R, 1} ≦ C _{R, 2} ≦... C _{R, n} ) and the R target value sequence {T _{R , k} } _{k = 1,2, ..., n} , an R conversion function convert _R (x) that converts R values using

And G control value sequence {C _{G, k} } _{k = 1, 2,..., N} and G target value sequence {T _{G, k} } _{k = 1, 2,.} G conversion function convert _G (x)

B value is converted using the B control value sequence {C _{B, k} } _{k = 1, 2,..., N} and the B target value sequence {T _{B, k} } _{k = 1, 2} ,. Convert function convert _B (x)

It is defined as

The RGB conversion function creation unit 25 outputs the R conversion function convert _R (x), the G conversion function convert _G (x), and the B conversion function convert _B (x).

  The above processing is a procedure for creating an RGB conversion function when there is only one face area candidate in the area dividing unit 22, but when there are N face area candidates (N is an integer of 2 or more), RGB conversion is performed. The function synthesis unit 28 synthesizes each of the N R conversion functions, the G conversion function, and the B conversion function, combines the R conversion function (hereinafter referred to as R conversion synthesis function), and the combined G conversion function (hereinafter referred to as G conversion). Composite function) and B conversion function after synthesis (hereinafter referred to as B conversion composite function) are generated and output.

  FIG. 12 is a diagram illustrating an example in which a synthesis function is created when three faces are detected by the RGB conversion function synthesis unit 28.

First, with 0 ≦ n <N, a synthesis coefficient calculation function synth (n) corresponding to the nth face region candidate is defined. For example, to make the weights uniform for all subjects

And Alternatively, if the weight is increased as the face size increases, the area of the nth face region candidate is set to faceSize (n)

And Here, C is a constant.

Conversely, the child's face can be emphasized by increasing the weight of the smaller face. In that case, for example

And Here, the constant C uses, for example, the maximum value of faceSize (n).

In addition, when increasing the weight of the face near the center of the video, a constant C is used with the Euclidean distance from the center coordinate of the video to the detected center coordinate of the face as faceDistance (n).

And

Alternatively, the color information of the detected face area can be used. For example, the average value of the RGB values of the pixels in the face area is calculated, and the luminance value is used as a skinLuminance (n) by using a constant C.

By doing so, it is possible to increase the weight of light skin color, to decrease the weight of men, and to increase the weight of women.

Although a plurality of definitions for the synthesis coefficient calculation function have been described above, a plurality of effects can be realized by combining and multiplying each. For example

Then, the weight of the central woman can be increased. C and D are constants.

Here, the R conversion function, G conversion function, and B conversion function corresponding to the nth face region candidate are respectively

And the sum S of the composite coefficients is

R conversion synthesis function convertSynth _R (x), G conversion synthesis function convertSynth _G (x), B conversion synthesis function convertSynth _B (x)

Output as.

  The conversion LUT creation unit 26 receives the R conversion synthesis function, the G conversion synthesis function, and the B conversion synthesis function, and outputs an R conversion LUT, a G conversion LUT, and a B conversion LUT. Specifically, an LUT as shown in FIG. 13 corresponding to values obtained by applying the R conversion function, the G conversion function, and the B conversion function to all R values, G values, and B values that can be taken as values, respectively. It is created and stored in the conversion LUT storage unit 32.

  The video conversion unit 27 receives the input video and the color conversion LUT and outputs a converted video. Specifically, with reference to the color conversion LUT for each pixel of each frame of the input video, the R value, the G value, and the B value are converted to create a converted frame, and the generated converted frame is sequentially output to finally A typical converted video.

(Example)
Here, with reference to FIG. 12, a process for creating a synthesis function when the RGB conversion function synthesis unit 28 detects three faces will be described.

The area dividing unit 22 detects the areas of the faces of three people from the input image. The RGB conversion function creation unit 25 creates an R conversion function convert _R (x), a G conversion function convert _G (x), and a B conversion function convert _B (x) for each person. The RGB conversion function synthesis unit 28 calculates a synthesis coefficient. RGB conversion function composition unit 28 uses the synthesis coefficient, combines the R transformation function the convert _R (x), obtained after combining R transformation function the convert _R a (x). RGB conversion function composition unit 28 uses the synthesis coefficient, combines the G transformation function the convert _G (x), obtained G transformation function the convert _G after combining the (x). The RGB conversion function synthesis unit 28 synthesizes each B conversion function convert _B (x) using the synthesis coefficient, and obtains a B conversion function convert _B (x) after synthesis.

  As described above, according to the first embodiment, the colors of a plurality of subjects included in a video can be appropriately converted and adjusted to a desired color. In particular, it is possible to adjust the brightness and color of an image taken with a plurality of persons as subjects as desired.

  Next, a second embodiment of the present invention will be described. Note that the basic configuration and operation are the same as those in the first embodiment, and here, differences will be mainly described.

[Second Embodiment]
FIG. 14 is a block diagram illustrating an overall configuration of a video conversion apparatus according to the second embodiment. As shown in the figure, the video conversion device includes an input device 1, a central processing control device 2, and a storage device 3. The input device 1 includes a video signal input unit 11, a model video input unit 14, and a target distribution selection unit 13. The central processing control device 2 includes a frame extraction unit 21, a region division unit 22, an RGB conversion parameter creation unit 23, The storage device 3 includes a target RGB distribution creation unit 24, an RGB conversion function creation unit 25, a conversion LUT (lookup table) creation unit 26, a video conversion unit 27, and an RGB conversion function synthesis unit 28. In addition to the storage unit for storing the data, the distribution feature storage unit 33 and the conversion LUT storage unit 32 are provided.

  FIG. 15 is a diagram illustrating an example of a method of using the video conversion apparatus.

  As shown in the figure, the video conversion apparatus obtains a target color for video conversion based on the model video dragged and dropped by the user, and converts the input video using the target color.

  The model video input unit 14 receives a model video dragged and dropped by a user using, for example, a mouse (input device) in a display area of the input video (for example, a part of a display screen in a liquid crystal display device), and creates a target RGB distribution To the unit 24. The dragged and dropped model video is displayed on a part of the display screen in the liquid crystal display device, for example. The model video may be a still image or a video. When the user performs a drag and drop operation on the model video, the model video input unit 14 outputs a shutter signal to the frame extraction unit 21.

  The target RGB distribution creation unit 24 receives the model video and the distribution feature information group, creates target RGB distribution information, and the created target RGB distribution information is output to the RGB conversion parameter creation unit 23. .

Also in the second embodiment, one face area set Region _FACE and one black eye area set Region _EYE are created for each face area candidate. If there are multiple face area candidates, for example, the face area candidate closest to the position of the pointer when the mouse or other button is released (drag) during the drag and drop operation is selected as the conversion target. To do.

  The target RGB distribution creation unit 24 receives the model video and the distribution feature information group and outputs target RGB distribution information. The distribution feature information group is read from the distribution feature storage unit 33.

  FIG. 16 is a diagram illustrating an example of distribution feature information.

  The distribution feature information is composed of a plurality of distribution feature records, and each distribution feature record is composed of a record number, a region name, and a cumulative ratio value. Here, the cumulative ratio value is a decimal value between 0 and 1.

  As shown in FIG. 4, the target RGB distribution information is composed of a plurality of RGB distribution records, as in the first embodiment. Each RGB distribution record is composed of a record number, a region name, a cumulative ratio value, and a target color. Here, the cumulative ratio value is a decimal value between 0 and 1.

  Here, a procedure for creating target RGB distribution information when the model video is a still image will be described.

A set of model image pixel M, the area name of a certain distribution characteristic record AREA, the cumulative percentage value is A, the area of AREA detected from the model image as mRegion _AREA, target color _{(T R, T G, T} B )

Ask for.

  The target RGB distribution information is created using the model image and the distribution feature information by the above procedure.

   FIG. 4 is an example of target RGB distribution information created from the distribution feature information of FIG.

  The target RGB distribution information is created from the model video by the above procedure. When the model video is a moving image, the target RGB distribution information is created by the same procedure using a still image cut out from the video.

  Next, a color conversion procedure for bringing the input video closer to the shade of the model image will be described.

A control value for a certain color component is calculated corresponding to each distribution record using the control value calculation function control. For example, if the area name included in a certain RGB distribution record is AREA, the cumulative ratio value is A, the set of pixels of the still image is P, and the area of AREA detected from the still image is Region _AREA , the control value in the R component is Using the control value calculation function control

Is calculated by Further, for each RGB distribution record, a target value T can be set by calculating a target color value for a certain color component. An example in which the control value and the target value are calculated corresponding to each RGB distribution record is as shown in FIG. 8 as in the first embodiment.

  Others are the same as in the first embodiment, and finally a converted video is output.

  Note that the video conversion unit 27 may adjust the strength of color conversion by the color conversion LUT.

  For example, the color conversion LUT may be created by the above procedure while the model video is being dragged to the display area of the input video, and the color conversion may be performed only at the peripheral portion of the dragged pointer in the video conversion unit 27.

Specifically, first, R, G, B the respective LUT LUT _r, LUT _g, the LUT _b, color conversion adjustment function convertControl depending on the conversion strength intensity (r, g, b, intensity) the

And

Next, assuming that the coordinates of the drag pointer on the display area of the input video are (px, py), the color conversion intensity calculation function convertWeight is set using radii r1 and r2 (r1 <r2).

The conversion intensity at each pixel of the input video is calculated. Here, using the color conversion adjustment function convertControl (r, g, b, intensity), the RGB value (r, g, b) of the pixel at the coordinates (x, y) is calculated.

Thus, the color conversion is performed by increasing the intensity of color conversion in the region closer to the pointer.

Alternatively, when the conversion intensity is adjusted according to the length of the dragging time, the color conversion intensity calculation function convertWeight is set using the constant T _MAX with the drag time t.

And convert by convertControl (r, g, b, convertWeight (t)).

  It is also possible to adjust the conversion strengths of brightness and color according to the coordinate position being dragged.

When adjusting the conversion strength of brightness according to the x coordinate value and adjusting the conversion strength of the hue according to the y coordinate value, respectively, from the coordinates (x, y) of the drag pointer

Let us define a conversion strength calculation function for brightness and hue. Here, luminance calculation function RGBtoY (r, g, b) is used from RGB (r, g, b) of a certain pixel.

To calculate the luminance L before conversion and the luminance L ′ after LUT conversion, and calculate the luminance L ″ after color conversion adjustment.

Calculated by The color before conversion (color _R , color _G , color _B ) and the color after LUT conversion (color ' _R , color' _G , color ' _B )

The color after the color conversion function (color " _R , color" _G , color " _B )

Calculated by Using the brightness value and hue after color conversion adjustment calculated above

To calculate the RGB value after the color conversion adjustment.

  As described above, according to the second embodiment, the color of a subject can be appropriately converted based on a model video selected by a general computer operation called drag and drop. Further, since the target color is calculated from the model video using Formula 26, it is not necessary to store the target color in advance as in the first embodiment, which is highly convenient.

DESCRIPTION OF SYMBOLS 1 ... Input device 2 ... Central processing control device 3 ... Memory | storage device 11 ... Video signal input part 12 ... Shutter input part 13 ... Target distribution selection part 14 ... Model video input part 21 ... Frame extraction part 22 ... Area division part 23 ... RGB Conversion parameter creation unit 24 ... Target RGB distribution creation unit 25 ... RGB conversion function creation unit 26 ... Conversion LUT creation unit 27 ... Video conversion unit 28 ... RGB conversion function synthesis unit 31 ... RGB distribution storage unit 32 ... Conversion LUT storage unit 33 ... Distribution feature storage unit 221 ... Image scale conversion unit 222 ... Detection target region extraction unit 223 ... Spatial frequency analysis unit 224 ... Face candidate determination unit 226 ... Skin region extraction unit 227 ... Black eye region extraction unit

Claims (19)

Storage means for storing the input video;
Area dividing means for reading out the video, dividing it into a plurality of areas and storing it in a storage means;
A histogram creating means for creating a histogram of each region in a desired color component;
Target range specifying means for specifying a target distribution range for each histogram;
Conversion parameter creating means for creating a conversion parameter for converting the video so that each histogram is distributed in the target distribution range;
Color conversion function creating means for creating a color conversion function using the conversion parameter;
A color conversion function synthesis means for calculating a synthesis coefficient for synthesizing the color conversion function and synthesizing a plurality of the color conversion functions using the synthesis coefficient;
Image conversion means for converting the image by applying the composite color conversion function to the image; and
The color conversion function creating means includes:
Create color conversion functions for each face area,
The color conversion function synthesis means includes:
A video conversion device that creates a color conversion function by combining color conversion functions created corresponding to a plurality of face regions. The color conversion function synthesis means includes:
2. The video conversion apparatus according to claim 1, wherein the weight of the composition is increased as the area of the face area is larger. The color conversion function synthesis means includes:
2. The video conversion apparatus according to claim 1, wherein the weight at the time of composition is increased as the distance from the face region to the center of the video is smaller. The color conversion function synthesis means includes:
2. The video conversion apparatus according to claim 1, wherein the weight of the composition is increased as the color of the face area becomes brighter. The target range specifying means includes
5. The video conversion device according to claim 1, wherein the target distribution range is specified based on a model video dragged and dropped onto the display area of the input video. The video conversion means includes
The video conversion apparatus according to claim 5, wherein the conversion strength is changed according to a location of the pointer used in the drag and drop. The video conversion means includes
The video conversion apparatus according to claim 5, wherein only a peripheral portion of the pointer used in the drag and drop is converted. The video conversion means includes
The video conversion apparatus according to claim 5, wherein the conversion strength is changed according to a drag time length in the drag and drop. The video conversion means includes
6. The video conversion apparatus according to claim 5, wherein a face area located closest to a position of a pointer at the time of the drag-and-drop is set as a conversion target. A video conversion method performed by a video conversion device,
Storing the input video in a storage means;
Reading the video, dividing it into a plurality of areas and storing it in a storage means;
Creating a histogram of each region in a desired color component;
Designating a target distribution range for each of the histograms;
Creating a conversion parameter for converting the video so that each histogram is distributed in the target distribution range;
Creating a color conversion function using the conversion parameters;
Calculating a synthesis coefficient for synthesizing the color conversion function, and using the synthesis coefficient to synthesize a plurality of the color conversion functions;
Applying the combined color conversion function to the video and converting the video;
In the step of creating the color conversion function,
Create color conversion functions for each face area,
In the step of synthesizing the color conversion function,
A video conversion method characterized by creating a color conversion function by combining color conversion functions created corresponding to a plurality of face regions. In the step of synthesizing the color conversion function,
11. The video conversion method according to claim 10, wherein the weight at the time of composition is increased as the area of the face region is larger. In the step of synthesizing the color conversion function,
11. The video conversion method according to claim 10, wherein the weight at the time of composition is increased as the distance from the face region to the center of the video is smaller. In the step of synthesizing the color conversion function,
11. The video conversion method according to claim 10, wherein the weight in the composition is increased as the color of the face region is brighter. In the step of specifying the target distribution range,
The video conversion method according to any one of claims 10 to 13, wherein the target distribution range is specified based on a model video dragged and dropped onto the display area of the input video. In the step of converting the video,
The video conversion method according to claim 14, wherein the conversion intensity is changed according to a location of a pointer used in the drag and drop. In the step of converting the video,
The video conversion method according to claim 14, wherein only a peripheral portion of the pointer used in the drag and drop is converted. In the step of converting the video,
The video conversion method according to claim 14, wherein the conversion intensity is changed according to a drag time length in the drag and drop. In the step of converting the video,
The video conversion method according to claim 14, wherein the face area located closest to the position of the pointer at the time of the drag-and-drop drop is a conversion target.   10. A video conversion program that causes a computer as the video conversion device according to claim 1 to execute processing performed by the video conversion device.

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