JP2896311B2 - How to make a color image mask - Google Patents

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a method for producing a mask used for cutting out a desired color portion in a color image.

[0002]

2. Description of the Related Art In a printing plate making process, it is sometimes desired to selectively perform various processes such as color change and sharpness enhancement on a specific color portion of a color image such as a photo original.
For example, there are cases where it is desired to change only the color of the clothes of the model wearing the clothes, or to emphasize the sharpness on the portion excluding the skin of the model. As described above, when the desired processing is performed (or not performed) only on a specific color portion of a color image,
A cutout mask indicating the color portion is created.

FIG. 1 is an explanatory diagram showing an example of a color image and a preferable mask. The color image shown in FIG. 1A is a photograph in which a black hair model is wearing clothes in which a rose flower pattern is printed on a yellow background. Rose flower
It has white and pink petals and green leaves around it. The mask shown in FIG. 1B is a mask showing a yellow portion and a green portion of the clothes.

As a method of creating a mask by analyzing the color of a color image, for example, Japanese Patent Laid-Open No. 1-298
There is one described in Japanese Patent No. 477. According to this method, the colors of a plurality of pixels in a portion (training area) to be a mask region are analyzed to obtain a principal component axis of the color. When the color of each pixel in the color image includes many components other than the principal component axis (that is, when the color is far from the principal component axis), the pixel is excluded from the mask area.

[0005]

However, in the above-described conventional technique, it was difficult to exclude the skin color from the mask area while using yellow as the mask area as shown in FIG. 1 (B). This is because the skin color contains a considerable amount of yellow component, and if yellow is specified as the color of the mask area, the skin color is also recognized as the mask area. Such a problem is a common problem when one of two colors having relatively similar hues is used as a mask region and the other is excluded from the mask region.

The present invention has been made to solve the above-mentioned problem in the prior art, and one of two colors having relatively close hues is used as a mask area.
It is an object of the present invention to provide a mask creating method capable of excluding the other color portion from a mask area.

[0007]

In order to solve the above-mentioned problems, a method according to claim 1 of the present invention comprises:
Specifying a target color of the mask in the color image; specifying a non-target color of the mask in the color image; and obtaining a first color vector of the target color in a predetermined color space Obtaining a second color vector of the non-target color in the predetermined color space; obtaining a third color vector independent of the first and second color vectors; Calculating the first to third coefficients for the first to third color vectors when the color of each pixel is represented by a linear combination of the first to third color vectors; And forming the mask in accordance with the value of the first coefficient in each pixel.

According to the above-described method, the first coefficient is large and the second coefficient is small for a color close to the target color, while the first coefficient is small for the color close to the non-target color. Becomes larger. Therefore, even when the hue of the target color and the non-target color are close to each other, if a mask is created according to the first coefficient, a color part close to the target color is set as a mask area and a color part close to the non-target color is set as a mask area Can be excluded from

According to a second aspect of the present invention, the mask forming step includes a step of forming mask data representing the mask by binarizing the first coefficient with a threshold value.

This makes it possible to easily create binary mask data indicating only the mask area.

According to a third aspect of the present invention, the step of binarizing the first coefficient includes the step of creating a histogram indicating the frequency of occurrence of the first coefficient, and the step of binarizing the first coefficient. Setting a coefficient of 1 as the threshold value.

In this case, the threshold for binarization can be automatically determined according to the histogram.

[0013] In the method according to claim 4, the third color vector is a vector representing white.

In this case, the third color vector can be easily determined.

The method according to claim 5, wherein the step of obtaining the third color vector includes the steps of converting the first and second color vectors into fourth and fifth color vectors in a hue / saturation / lightness space. And the fourth and fifth steps, respectively.
If at least one of the chroma components of the color vector exceeds a predetermined value, a vector representing white in the predetermined color space is selected as the third color vector, and the fourth and fifth color vectors are selected. If at least one of the chroma components is less than the predetermined value, the hue in the hue / saturation / brightness space is determined for the color vector having the larger chroma component among the fourth and fifth color vectors. Generating a sixth color vector rotated by a predetermined angle, and generating the third color vector by converting the sixth color vector into a vector in the predetermined color space.

This makes it possible to easily determine a third color vector independent of the first and second color vectors. In addition, since the first to third color vectors each represent an actual color, the first to third color vectors correspond to the color of each pixel.
Is an index that actually represents the component of the target color.

According to a sixth aspect of the present invention, the first to third color vectors are unit vectors.

In this case, the first to third color vectors are vectors representing only the hues, so that a mask can be created according to the hues of each color image.

[0019]

FIG. 2 is a block diagram showing the configuration of a mask making system for making a cutout mask by applying an embodiment of the present invention. This mask creation system is based on the CPU 2
0, an original image memory 22 for storing a color original image,
A vector value memory 24 for storing components of a color vector,
This is a computer system including a matrix memory 26 for storing components of a matrix described later, a multi-tone mask memory for storing multi-tone mask data, and a binary mask memory 30 for storing binary mask data. The system further includes a keyboard 32 and a mouse 34 as input means or designation means, a reading scanner 36 as image input means, and a color CRT 3 as display means.
8 and a hard disk device 40 as external storage means.

The CPU 20 includes a matrix operation unit 50,
It has a function as a multi-tone mask calculation unit 52 and a binarization calculation unit 54. These components are realized by the CPU 20 executing a software program stored in a RAM (not shown). Note that these functions will be further described later.

FIG. 3 is a flowchart showing the overall procedure for creating a cutout mask in the embodiment. Step S
In step 1, the image data of the color original is read by the reading scanner 36 and stored in the original image memory 22. This color original is, for example, a color photograph as shown in FIG. The original image memory 22 is a frame memory, and the image stored in the original image memory 22 is a color CRT.
38 is displayed.

In steps S2 and S3, the user specifies a target color and a non-target color on the color image displayed on the color CRT 38, respectively. For example, yellow as the background color of the clothes in FIG. 1A is designated as the target color, and the skin color of the model is designated as the non-target color. The color is specified by using a pointing device such as a mouse 34 to specify a point on the color image displayed on the color CRT 38. Alternatively, a target color and a non-target color may be respectively specified by a process of specifying a plurality of points of an approximate color and calculating the average color.

FIG. 4 is an explanatory diagram showing the positions of target colors and non-target colors on the Munsell hue circle. The yellow color specified as the target color and the flesh color specified as the non-target color are close to each other on the hue circle. According to the present invention, even when the hues of two colors are close to each other, it is possible to set one color as a target color of the mask and the other color as a non-target color of the mask. In the following, unless otherwise specified, the case where yellow and flesh color are designated as target colors and non-target colors will not be specified, and will be generally described.

In step S4, the matrix operation unit 50
(FIG. 2) calculates the color vector of the target color and the color vector of the non-target color, and performs a process of obtaining a matrix (matrix) described later.

FIG. 5 is a flowchart showing a detailed procedure of step S4. In step S11, a first color vector is obtained by normalizing the color vector of the target color. FIG. 6 is a graph showing the first and second color vectors. Each of the RGB components of the target color Csub is represented by (R1, G
1, B1), the vector representing the target color Csub is represented as Vsub (R1, G1, B1). FIG.
For simplicity of illustration, the G axis in the RGB space is omitted.
In step S11, the matrix operation unit 50 determines that the unit vector V1 (r1, g1,
b1), and the components (r1, g1, b1) are stored in the vector value memory 24. Here, the unit vector is a vector having a length of one. Similarly, in step S12, the color vector Vnsub (R2, G2, B2
) Is determined, and a unit vector V2 (r2, g2, b2)
The component is stored in the vector value memory 24.

The first and second color vectors V1 and V2 thus obtained constitute two of the three vectors constituting the basis for expressing colors in the RGB space. As the third color vector V3 for forming the basis, a unit vector independent of the first and second color vectors V1 and V2 is selected. That is, the third color vector is the first color vector.
Is a unit vector that cannot be expressed by a linear combination of the second color vector V1 and the second color vector V2. For example, the third color vector V3
Is selected as the unit vector VWH representing white.
The component of the white unit vector VWH is (1 / {3,1 / √)
3,1 / √3).

FIG. 7 shows the first to third color vectors V
FIG. 3 is an explanatory diagram illustrating a relationship between 1, V2, and V3 and an RGB space. In this embodiment, as shown in the following Expression 1, three linearly independent color vectors V1, V2, and V3 are used as bases, and an arbitrary color E (Re, Ge, Be) in an RGB space is used.
Is represented by a linear combination (linear combination) of three color vectors V1, V2, and V3.

[0028]

(Equation 1)

As will be described later, mask data representing a mask is created based on the coefficient k1 for the first color vector V1 (ie, the color vector for the target color). By the way, when one of the first and second color vectors V1 and V2 coincides with the third color vector V3, the three color vectors are not linearly independent.
An arbitrary color cannot be represented by the three vectors V1 to V3. Also, the first and second color vectors V1, V
Even when one of the two is sufficiently close to the third color vector V3, the coefficient k1 for the first color vector V1 may become excessively large or small. Therefore, in step S13 of FIG.
It is checked whether one of the color vectors V1 and V2 is sufficiently close to the white unit vector VWH (1 / √3, 1 / √3, 1 / √3). If they are sufficiently close, in step S14, a vector other than the white unit vector VWH is set as the third color vector V3.

First, in step S13, the first and second color vectors V1 and V2 are converted into an HSV coordinate system (hue / saturation / lightness coordinate system) according to the following equation (2).

[0031]

(Equation 2)

In equation (2), the operators "max" and "m
"in" indicates an operation that takes the maximum value and the minimum value of the values in parentheses, respectively. According to Equation 2, the first color vector V1
(R1, g1, b1) and the second color vector V2 (r2,
g2, b2), the hue value H, lightness value V, and saturation value S are obtained.

FIG. 8 is an explanatory diagram showing the HSV space.
As can be seen from FIG. 8, the white unit vector VWH is
Exists on the coordinate axis. In other words, the white unit vector VWH is a vector having no saturation S and no hue H.
The HSV space is a cylindrical coordinate system (zrθ coordinate system), in which lightness V corresponds to vertical coordinate z, saturation S corresponds to diameter r, and hue H corresponds to angle θ.

A color vector having a small saturation value S is close to a white unit vector VWH (1 / √3, 1 / √3, 1 / √3). Accordingly, the first and second color vectors V1, V
If at least one of the saturation values S is equal to or less than a predetermined value, it can be determined that the color vector is sufficiently close to the white unit vector VWH. As the predetermined value, for example, each component is 8-bit data, that is, 0 to 255
10 (0A in hexadecimal)
h) The degree is appropriate.

Instead of the above method, when the ratio S / V between the saturation value S and the lightness value V is equal to or less than a predetermined value, it is determined that the color vector is sufficiently close to the white unit vector VWH. You may make it.

If at least one of the first and second color vectors V1 and V2 is sufficiently close to the white unit vector VWH, the white unit vector V3 is set as the third color vector V3 in step S14. Vectors other than VWH are determined. FIG. 9 is an explanatory diagram showing a method of setting a vector other than the white unit vector VWH as the third color vector V3. First, the first and second color vectors V
A color vector that is farther from the white unit vector is selected from 1, V2. In the example of FIG. 9, the first color vector V1 having a relatively large saturation value S is selected. Then, 90 is subtracted from the hue value H of the selected color vector V1. That is, the color vector V2 is rotated clockwise by 90 ° in the HSV space. The vector (H-90, S, V) obtained in this way is inversely transformed into an RGB coordinate system, and the RGB components are normalized, whereby a third color vector V3 as a unit vector is obtained. FIG. 9 illustrates the third color vector V3 obtained by such an operation. Note that the rotation angle can be set to any angle other than 90 °.

The third color vector V3 obtained by the above procedure is independent of the first and second color vectors V1 and V2, so that the three color vectors V1 to V3 can be used as a basis. In other words, any color in the RGB color space is represented by the three color vectors V1
ＶV3. The third color vector V3 is a vector indicating a color that actually exists because the third color vector V3 is obtained by rotating the hue of the first or second color vector. Since all three color vectors V1 to V3 are vectors indicating actual colors, the coefficient k1 for each color vector
The value of ~ k3 will have a realistic meaning representing the mixture ratio of the three colors.

As the third color vector, a vector independent of the first and second color vectors V1 and V2 may be selected, so that the third color vector is set by various methods other than those described above. Can be. For example, the outer product V1 × V2 of the first and second color vectors V1 and V2 is converted to the third color vector V3.
It is also possible to use as. However, this cross product V
In some cases, 1 × V2 does not represent a real color. In this case, the values of the coefficients k1 to k3 for each color vector have no practical meaning. Therefore, as described above, the first
And by rotating the hue of the second color vector
It is preferable to obtain the color vector of

When the third color vector V3 is determined in this way, in step S15 (FIG. 5), a 3 × 3 matrix M composed of components of three color vectors V1 to V3 is used.
(See Equation 1) is created and stored in the matrix memory 26.

The coefficient K (k1, k2, k3) for an arbitrary color E (Re, Ge, Be) is given by the following equation (3).

[0041]

(Equation 3)

Therefore, if the inverse matrix M ^-1 of the matrix M is determined, the coefficient K (k1, k2, k) can be obtained by multiplying the inverse matrix M ^-1 by an arbitrary color E (Re, Ge, Be).
3) can be obtained. Therefore, in step S16, the matrix calculation unit 50 calculates the inverse matrix M ⁻¹ ,
It is stored in the matrix memory 26.

When the processing in step S4 in FIG. 3 is completed, a multi-tone mask is created in step S5. FIG. 10 is a flowchart showing a procedure for creating a multi-tone mask. In step S21, the multi-tone mask calculation unit 52 reads out the pixel value E (Re, Ge, Be) of each pixel of the color image in the original image memory 22, substitutes it into the right side of Expression 3 and assigns its coefficient K (k1 , K2, k3).
In step S22, the obtained coefficient K (k1, k2, k
The coefficient k1 of the first color vector V1 is extracted from 3) and stored in the multi-tone mask memory 28 in step S23.

The first coefficient k1 indicates the intensity of the first color vector V1 in the color of each pixel. In other words,
The value of the first coefficient k1 increases as the color of each pixel includes more components of the first color vector V1. Therefore, the bitmap data representing the first coefficient k1 for all the pixels in the color image can be used as a multi-tone mask indicating a color region similar to the target color.

When the value of the first coefficient k1 is negative, the value of the coefficient k1 may be replaced with 0 since the pixel has a color opposite to the color to be clipped.

Further, the first coefficient k1 of each pixel is set to the first coefficient k1a (= R1 / r1 = G1 / g1) for the target color.
= B1 / b1) divided by kk (= k1 / k)
It is also possible to use 1a) as a multi-tone mask. At this time, if the value of kk is 1 or more, it may be replaced with 1, and a negative value may be replaced with 0. By doing so, the value of the bitmap data representing the multi-tone mask can be contained in the range of 0 to 1, so that 2
Setting of the threshold value in the binarization process is facilitated.

Alternatively, three coefficients k for each pixel
The values of 1, k2, and k3 may be normalized according to the following Expression 4, and the bitmap data of the normalized coefficient ku1 may be used as a multi-tone mask.

[0048]

(Equation 4)

It should be noted that a negative value of 0 is also set for the coefficient ku1.
Is preferable. The coefficient ku1 obtained in this way can also be set within the range of 0 to 1, so that
Setting of the threshold value in the binarization process is facilitated.

When the multi-tone mask is created in this way, in step S6 of FIG. 3, an instruction is given to select whether to output the multi-tone mask as it is or to create and output a binary mask. If the instruction is No, a multi-tone mask is output in step S7.

An application of the multi-tone mask is, for example, a watermark synthesizing process. In this case, the intensity of the target color can be used as a synthesizing ratio. In addition, by referring to the gradation value of the multi-tone mask, it is possible to weight or weaken the image processing performed on the cutout target portion. For example, when performing a contour emphasis process on a target portion of an image, a strong contour emphasis can be applied to a portion having a high tone value of the mask, and a weak contour emphasis can be applied to a portion having a low tone value.

If the instruction in step S6 is Yes, in step S8, the binarization operation section 54 binarizes the multi-tone mask to create a binary mask. In step S9, the binary mask is generated. Is output. As a method of setting a threshold value used for binarization, the following various methods can be considered.

FIG. 11 is a flowchart showing a procedure for creating a binary mask while manually inputting a threshold value. When the user inputs a threshold value through the interactive processing (step S31), the binarization calculation unit 54 binarizes the multi-tone mask using the threshold value to create a binary mask (step S32). ). The user has access to color C
Observe the binarized mask displayed on the RT 38 and determine whether or not the mask is satisfactory (steps S33 and S3).
4). Note that when displaying the binary mask, FIG.
It is preferable to display a color image and a binary mask side by side as in 1 (B). If the binary mask is not satisfactory, the process returns to step S31, inputs a new threshold value, and executes the binarization process again. On the other hand, if the binary mask is satisfactory, the binarization process ends.
If a binary mask is created according to the procedure of FIG. 11, there is an advantage that a mask desired by a user can be easily created.

It is also possible to automatically set the threshold for binarization based on the distribution of the multi-tone mask. FIG.
Is a histogram of multi-tone mask data. FIG.
Is the multi-tone mask value of the target color. In a normal color image, the number of pixels having a color close to the target color to be clipped is usually quite large, and therefore, a peak of the histogram appears near the mask value of the target color.
Further, since the background portion of the image has a dark color, a peak also appears in a portion where the mask value is small. In such a case, as shown in FIG. 12, the appearance frequency shows the minimum value at a value x smaller than the mask value Kst of the target color. Therefore, it is smaller than the mask value Kst for the target color, and
If a mask value x whose appearance frequency indicates a minimum value is obtained and used as a threshold value for binarization, a binary mask representing a color portion close to the target color can be created.

As shown in FIG. 13, when the maximum value of the multi-tone mask value is set to a predetermined value Kmax, and all values above Kmax are replaced by Kmax, the mask value with which the appearance frequency becomes the minimum value is obtained. x can be determined more easily. When the multi-tone mask value is represented by 8-bit data, a value of about 128 is appropriate as the value Kmax.

As a method for obtaining the threshold value for binarization,
Based on the histogram of the multi-tone mask values, it can be determined using a so-called non-hierarchical clustering method (also called a rearrangement method or k-mean method). If a cluster in the histogram is obtained by this method and the lower limit value of the cluster of the target color is used as a threshold value, a binary mask indicating a color portion similar to the target color can be obtained.

FIG. 14 is a graph showing a color region cut out by the binary mask. The color in the region (Ra + Rb) is a color in which the value of the coefficient k1 of the first color vector V1 is equal to or greater than Ta. The color in the region Rb is a color in which the value of the coefficient k1 of the first color vector V1 is equal to or larger than Tb. Therefore, if the binarization threshold is set to Ta, the region (R
It is possible to create a binary mask indicating the color portion in (a + Rb). At this time, the region R adjacent to the left side of the region Ra
The color in c is excluded from the mask area because the component of the target color is small. Note that the threshold value for binarization is T
If it is set to b, a binary mask indicating the color portion in the region Rb can be created.

FIG. 15 is an explanatory diagram showing the effect of the mask created by the embodiment. Many circles in FIG. 15 indicate the color distribution in the color image. This color image includes a first set Ob1 of pixels of a color close to the target color Csub and a second set Ob2 of pixels of a color close to the non-target color Cnsub. The first set Ob1 has a color of a portion (so-called highlight area) where light rays are reflected and shined during photographing. For example, in the color original shown in FIG. 1A, a shining portion of yellow clothing corresponds to the highlight area. According to the above-described embodiment, by setting the threshold value to Ta in the figure, a binary mask including the first set Ob1 including the highlight region and excluding the second set Ob2 is obtained. be able to. Since both the highlight region in the first set Ob1 and the second set Ob2 have a large B component, the conventional method using the color vector in the RGB space uses the highlight region and the second set Ob2.
Cannot be separated from the set Ob2. On the other hand, in the method according to this embodiment, the highlight area close to the target color can be easily separated from the second set Ob2.

In the color image shown in FIG.
If the color yellow of the cloth is specified as the target color Csub and the skin color of the model is specified as the non-target color Cnsub, the mask shown in FIG. 1B showing the yellow part of the cloth can be obtained.
As can be seen from the Munsell hue circle shown in FIG.
Green is a hue on the opposite side of the non-target color from the target color. Therefore, the target color Csub is designated as yellow, and the non-target color Csub
If nsub is specified as a flesh color, a green leaf portion is also included in the mask area. That is, as shown in FIG. 1B, a binary mask having the yellow and green portions as mask regions can be obtained.

As described above, in this embodiment, the target color C
By specifying the sub and the non-target color Cnsub, a mask including a color portion close to the target color Csub and not including a color close to the non-target color Cnsub can be easily obtained.

The present invention is not limited to the above-described embodiment, but can be embodied in various modes without departing from the gist thereof. For example, the following modifications are possible.

(1) In the above embodiment, RG is used as the color space.
Although the B coordinate system is used, other color spaces such as a CIE-XYZ coordinate system, a YMC coordinate system, and a YUV coordinate system may be used.

(2) The first coefficient k1 or ku1 obtained by the above equation 3 or 4 is used as it is as the multi-tone mask data, and the value of the binary mask is set for the pixel where the multi-tone mask data is positive. May be set to 1, and the value of the binary mask may be set to 0 for a negative pixel. That is, 0 may be used as the threshold. In particular, when creating a binary mask for changing the color of a color image, a good mask can be obtained by such a method.

(3) The first to third color vectors need not be unit vectors. However, if the first to third color vectors are unit vectors, each color vector is a vector representing only the hue. Therefore, if a mask is created according to the first coefficient as described above, it is possible to determine the mask area according to the hue of each pixel of the color image.

[0065]

As described above, according to the first aspect of the present invention, even when the target color and the non-target color have similar hues, a color portion close to the target color is used as a mask area, and Can be excluded from the mask area.

According to the second aspect of the present invention, it is possible to easily create binary mask data indicating only a mask area.

According to the third aspect of the present invention, the binarization threshold can be automatically determined according to the histogram.

According to the fourth aspect of the invention, the third color vector can be easily determined.

According to the invention described in claim 5, the third color vector independent of the first and second color vectors can be easily determined. In addition, since the first to third color vectors each represent an actual color, the first coefficient for the color of each pixel can be used as an index that actually represents the component of the target color.

According to the sixth aspect of the present invention, since the first to third color vectors are vectors representing only the hues, a mask can be created according to the hues of each color image.

[Brief description of the drawings]

FIG. 1 is an explanatory view showing a color photographic document and its mask.

FIG. 2 is a block diagram showing a configuration of a mask creating system that creates a cutout mask by applying an embodiment of the present invention.

FIG. 3 is a flowchart showing an overall procedure for creating a cutout mask in the embodiment.

FIG. 4 is an explanatory diagram showing positions of a target color (yellow) and a non-target color (skin color) on a Munsell hue circle.

FIG. 5 is a flowchart showing a detailed procedure of step S4.

FIG. 6 is a graph showing first and second color vectors V1 and V2.

FIG. 7 shows first to third color vectors V1, V2, and V3.
FIG. 4 is an explanatory diagram showing the relationship between the RGB space.

FIG. 8 is an explanatory diagram showing an HSV space.

FIG. 9 shows a vector other than the white unit vector VWH as a third vector.
FIG. 5 is an explanatory diagram showing a method of setting a color vector V3.

FIG. 10 is a flowchart showing a procedure for creating a multi-tone mask.

FIG. 11 is a flowchart showing a procedure for creating a binary mask.

FIG. 12 is a histogram of multi-tone mask data.

FIG. 13 is a histogram of multi-tone mask data.

FIG. 14 is a graph showing a color region cut out by a binary mask.

FIG. 15 is an explanatory diagram showing the effect of the mask created by the example.

[Explanation of symbols]

 DESCRIPTION OF SYMBOLS 20 ... CPU 22 ... Original image memory 24 ... Vector value memory 26 ... Matrix memory 28 ... Multi-tone mask memory 32 ... Keyboard 34 ... Mouse 36 ... Reading scanner 38 ... Color CRT 40 ... Hard disk drive 50 ... Matrix computing unit 52 ... Many Tone mask calculation unit Cnsub: Non-target color Csub: Target color

────────────────────────────────────────────────── ─── Continuation of the front page (56) References JP-A-4-61558 (JP, A) JP-A-8-153201 (JP, A) JP-A-5-197804 (JP, A) JP-A-8-183 7106 (JP, A) JP-A-8-96114 (JP, A) JP-A-8-115430 (JP, A) JP-A 8-115431 (JP, A) JP-A 8-272942 (JP, A) Tominaga, G., "Color Classification of Color Images and Its Applications," Journal of the Japan Society of Color Science, 1991, Vol. 15, No. 1, p. 55-56 (58) Field surveyed (Int. Cl. ⁶ , DB name) G06T 7/00

Claims (6)

(57) [Claims] 1. A method of creating a mask indicating a desired color portion in a color image, comprising: specifying a target color of the mask in the color image; and excluding a target of the mask in the color image. A step of specifying a color; a step of obtaining a first color vector of the target color in a predetermined color space; a step of obtaining a second color vector of the non-target color in the predetermined color space; Obtaining a third color vector independent of and the second color vector; and calculating the color of each pixel in the color image from the first to third colors.
Obtaining the first to third coefficients for the first to third color vectors when represented by a linear combination of the color vectors of the color image, and according to the value of the first coefficient at each pixel in the color image. Forming the mask by using a color image. 2. The method according to claim 1, wherein the mask forming step includes: binarizing the first coefficient with a threshold value;
A method for creating a mask for a color image, comprising creating mask data representing the mask. 3. The color image mask creating method according to claim 2, wherein the step of binarizing the first coefficient includes the step of creating a histogram indicating an appearance frequency of the first coefficient; Setting the first coefficient at the minimum value of the histogram as the threshold value. 4. The method according to claim 1, wherein the third color vector is a vector representing white. 5. The method for producing a color image mask according to claim 1, wherein the step of obtaining the third color vector comprises: converting the first and second color vectors into hue / hue. Converting each of the fourth and fifth color vectors into a fourth and fifth color vector in a saturation / brightness space; and if at least one of the saturation components of the fourth and fifth color vectors exceeds a predetermined value, the predetermined A vector representing white in a color space is selected as the third color vector. If at least one of the fourth and fifth color vectors has a saturation component less than the predetermined value, the fourth color vector is selected.
And a sixth color vector obtained by rotating the hue by a predetermined angle in the hue / saturation / brightness space for a color vector having a larger saturation component among the fifth color vector and the sixth color vector. Generating the third color vector by converting to a vector in the predetermined color space. 6. The method for producing a color image mask according to claim 1, wherein said first to third color vectors are unit vectors.