JP2642262B2 - Exposure determination method - Google Patents

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an exposure determining method,
More specifically, the present invention relates to an exposure determining method for extracting characteristic image data such as density data of a person's face, which is used when copying a color original image onto a color copying material or a black and white copying material, and determining an exposure amount.

[0002]

2. Description of the Related Art The most noticeable part when viewing a portrait photograph is the face of the person, and the color and density of the face of the person are important for producing a high-quality photograph. Must be printed to the proper color and density.

Conventionally, there is a method of extracting human face data by extracting skin color data (Japanese Patent Laid-Open No. Sho 5
JP-A-2-156624, JP-A-52-156625, JP-A-53-12330, JP-A-53-1
No. 45620, JP-A-53-145621,
See JP-A-53-145622). According to this, a color original image is divided into a large number of photometric points, and each photometric point is decomposed into three colors of R (red), G (green), and B (blue), and photometry is performed. It is determined whether the color of each photometric point is within the skin color range. Then, clusters (groups) of photometric points determined to be in the skin color range are used as face density data.

However, in this method, since the color within the skin color range is assumed to be the density data of the face, portions other than the face having a skin color or a color similar to the skin color, such as the ground, tree trunks and clothes, are also included in the face. It may be extracted as density data, and it may not be possible to extract accurate data.

In addition to the above-mentioned method, there is a method of discriminating a face by the same density information being a circle. In this method, the shape in which the skin color portion of the face is exposed differs depending on the state at the time of photographing. As a result, the face area may not be accurately extracted because the face is not circular or a part of the face is missing.

SUMMARY OF THE INVENTION The present invention has been made to solve the above-described problem. A feature image area such as face data of a person is obtained with high accuracy from a color original image, and the feature image data of the obtained feature image area is obtained. It is an object of the present invention to provide an exposure determining method for determining an exposure to a copy material based on the exposure.

[0007]

According to a first aspect of the present invention, there is provided an exposure determining method for reading information relating to a color original image and dividing the color original image into a plurality of pixels. Each pixel is decomposed into three colors of red light, green light and blue light, and photometry is performed. A histogram of hue values is obtained based on the data obtained by the photometry, and the obtained histogram is divided for each mountain to obtain a color original image. Judging which of the divided mountains each pixel belongs to, dividing the pixels into groups corresponding to the divided mountains, dividing the color original image for each group, and reading the above from the divided area It is characterized in that an area most suitable for the information related to the color original image is selected as a characteristic image area, and an exposure amount to the copy material is determined based on the image data of the characteristic image area.

According to a second aspect of the present invention, in the exposure determining method, information relating to the color original image is read, and the color original image is divided into a large number of pixels, and each pixel is divided into three colors of red light, green light and blue light. Into a light source image, obtain a histogram of hue values or a two-dimensional histogram of hue values and saturation values based on the data obtained by the light measurement, divide the obtained two-dimensional histogram into each mountain, and obtain a color original image. It is determined which of the divided mountains each pixel belongs to, and the pixels are divided into groups corresponding to the divided mountains, and the color original image is divided for each group, and the read image is read from the divided area. An area most suitable for the information related to the color original image is selected as a characteristic image area, and the exposure amount to the copy material is determined based on the image data of the characteristic image area.

According to a third aspect of the present invention, in the exposure amount determining method according to the first or second aspect, the information relating to the color original image is the size information of the main image or the size information for obtaining the size of the main image. It is characterized by being.

According to a fourth aspect of the present invention, in the exposure determining method according to the first or second aspect, the information related to the color original image is area information representing an image area where a main image exists. And

According to a fifth aspect of the present invention, in the exposure amount determining method according to the first or second aspect, the information related to the color original image is information representing a focus position of the focused image in the color original image. It is characterized by being.

According to a sixth aspect of the present invention, in the exposure amount determining method according to the first or second aspect, the information relating to the color original image includes size information representing a size of a main image and an image area where the main image exists. Is characterized in that at least one of the area information indicating is camera information recorded or stored by the photographing apparatus at the time of photographing.

[0013]

According to the first aspect of the present invention, a color original image is divided into a large number of pixels, and each pixel is separated into three colors of red light, green light and blue light, and photometry is performed. In addition, information related to the color original image is read. As information related to this color original image,
The size information indicating the size of the main image described in claim 3, the area information indicating the image area where the main image exists according to claim 4, and the combination of the focused image described in claim 5 in the color original image. At least one of the information indicating the focal position, the size information indicating the size of the main image described in claim 6, and the area information indicating the image area where the main image exists is camera information recorded or stored by the imaging device at the time of shooting. . Next, a histogram of hue values is obtained based on the data obtained by photometry. The obtained histogram is divided into peaks at a valley or a foot of a peak of the histogram. Thus, the hue value range of each mountain is determined. Next, it is determined which hue value range the hue value of each pixel belongs to, so that it is determined which of the crests each pixel belongs to. Cluster). Subsequently, the color original image is divided into regions corresponding to the divided groups. At this time, pixels included in the same group may be divided into different regions, but pixels included in different groups are not included in the same region. As a result, the color original image is divided into regions each including a pixel having a hue value within the hue value range divided by the histogram. Therefore, one area on the color original image includes pixels whose hue value is within a predetermined range, and most suitable for information related to the color original image read from the area representing the feature of this image. An area is selected as a feature image area. The image data of the selected characteristic image area is extracted as characteristic image data.

Here, if there is a change in the kind of film or light source, a change with time, a difference in film development, etc., the color of the color original image changes uniformly over the entire screen. Also, since the group formed by each pixel of the image is preserved only by changing the position on the histogram, the divided region of the original color image does not change even if the color changes. Therefore, according to the present invention, density data of a person's face can be extracted even when the color or color range of a color original image changes due to a change in a film type or a light source type, a change over time, a film development difference, or the like.

When the size information is used as the information related to the color image, an area to be extracted can be selected according to the size of the main image, and the data of the selected area is the data of the main image. It can be extracted as feature image data. When the above-described area information is used, an area to be extracted can be selected based on an image area where the main image exists, and data of this area can be extracted as characteristic image data of the main image. Also,
Because the presence of the main image is high at the in-focus position of the color original image, by using the information indicating the in-focus position, the extraction region of the main image can be easily specified, and the feature image of the main image can be specified. Data can be extracted in a short time. Further, in the camera information, at least one of size information of the main image, size information for obtaining the size of the main image, and area information indicating an image area where the main image exists, is recorded or stored by the imaging device at the time of shooting. By using this information, it is possible to specify an image size, a shooting magnification, and a region when the main image is shot. For this reason, the feature image data of the main image can be easily extracted.

If the exposure amount is determined based on the characteristic image data extracted as described above and a print is created, the characteristic image portion can be printed with an appropriate density or density and color.

By using at least one of the three color data of red, green, and blue in the characteristic image portion, it is possible to determine an exposure amount for printing to an appropriate density. Further, by using the data of the three colors, it is possible to determine an exposure amount for printing an appropriate density and color.

If the hue of the characteristic image, which is the characteristic part of the image, is the same or similar to the hue of another part, the original color image is divided based on the histogram of only the hue values. Sometimes cannot be distinguished.
Therefore, according to the second aspect of the present invention, a saturation value is further introduced in addition to the hue value, a two-dimensional histogram of the hue value and the saturation value is obtained, and the two-dimensional histogram is divided for each mountain and the same as above. As described above, a region that best matches the information related to the color original image read from the divided region is selected as a feature image region. Image data of the selected characteristic image area is extracted as characteristic image data, and an exposure amount is determined based on the extracted characteristic image data.

As described above, by using the hue value and the saturation value, the feature image data can be extracted even if the feature image and the part having the same or similar hue are mixed.

Since the most noticeable part when viewing a portrait is the face of a person, it is determined whether or not the divided area of the color original image is the face of the person, and the face is determined to be the face of the person. It is preferable to extract the data of the area as feature image data. In this case, feature image data, that is, data of a person's face can be extracted based on a two-dimensional histogram of hue values, but data of a person's face is extracted based on a two-dimensional histogram of hue values and saturation values. You can also. The hue of a person's face is similar to the skin color portion of the ground, trees, etc., but in most cases the saturation is different. Therefore, the data of the person's face is calculated based on a two-dimensional histogram of hue values and saturation values. By extracting the data, the face data of the person can be extracted from the image in which the face, the ground, the tree, and the like are mixed.

The data to be extracted as the characteristic image data may be other than the data of the face of a person.

[0022]

Embodiments of the present invention will be described below in detail with reference to the drawings. In this embodiment, the present invention is applied to an auto printer.

As shown in FIG. 1, the automatic printer according to the present embodiment includes a transport roller 12 for transporting a color negative film 10. A magnetic head 50 is disposed upstream of the transport roller 12 in the transport direction of the color negative film 10. The magnetic head 50 is arranged at a position where the information at the time of photographing recorded on the color negative film 10 can be read. The magnetic head 50 is a magnetic head 50
Is connected to the face extraction circuit 36 via an amplifier 52 that amplifies the output of the face extraction circuit and an analog-digital (A / D) converter 54.

A light source 14, a color correction filter 16 such as a light control filter, and a diffusion box 18 are provided below the color negative film 10 transported by the transport rollers 12.
Are arranged in order.

On the other hand, above the color negative film 10, a distribution prism 20 for distributing light transmitted through the color negative film 10 in two directions is arranged. On one optical path distributed by the distribution prism 20, a projection optical system 22, a black shutter 23, and color paper (printing paper) 24 are sequentially arranged, and on the other optical path, a projection optical system 26 and a CCD image sensor. 28 are arranged in order.

The CCD image sensor 28 divides an entire screen (one frame) of the color negative film 10 into a large number of pixels (for example, 256 × 256 pixels) and divides each pixel into R pixels.
Photometry is performed by separating the color into three colors (red), G (green), and B (blue). The CCD image sensor 28 is connected to a 3 × 3 matrix circuit 34 for correcting the sensitivity of the CCD image sensor via an amplifier 30 for amplifying the output of the CCD image sensor and an analog-digital (A / D) converter 32.

The 3 × 3 matrix circuit 34 is connected to an appropriate exposure amount calculation circuit 40 via a face extraction circuit 36 composed of a microcomputer in which a program for a routine described below is stored. It is connected to an appropriate exposure amount calculation circuit 40 via an average density calculation circuit 38 for calculating an average density. Then, the appropriate exposure amount calculation circuit 40 includes a driver 42 for driving the color correction filter.
Is connected to the color correction filter 16 via the.

The color negative film 10 magnetically records camera information as information relating to a color original image. The camera information includes main image size information and main image existence area information. The main image size information includes a main image size S or a shooting magnification m. Note that the main image size S or the imaging magnification m is a standard length (or width, for example,
S0, focal length f of the photographing lens, distance L from the photographing lens to the subject,
Based on the distance F to the imaging point, the following equation (1)
Alternatively, it can be obtained by (2). This main image size information is obtained by recording the main image size S on the camera side and recording it, and also obtaining the photographing magnification m on the camera side,
The main image size S may be obtained on the auto printer side by recording the obtained value. Furthermore, the above values may be recorded, and the main image size S may be calculated and calculated on the auto printer side.

S = S0 · f / (L−f) −−−− (1) m = f / (F−f) −−−− (2) As the above main image, the present embodiment is subtle. Use the face of a person who needs color reproduction. It should be noted that the main image is not limited to a person, and may be an image area in which appropriate color reproduction is desired.

Further, the main image existence area information, that is, the area where the face of the person exists in the present embodiment, is specified based on, for example, the focus point information in the multipoint distance measuring apparatus or the area information of the image area including the same. be able to. Therefore, the camera may record the main image existence area obtained from the focus point position or the area information of the image area including the focus point position, and read this information to identify the main image existence position and the area. The location and area of the main image may be calculated on the printer side.

Although the camera information is magnetically recorded on the color negative film 10, any information can be recorded as long as the information can be recorded, and the camera information may be optically recorded by a bar code, an optical mark, or the like. Reading of the information when this information is optically recorded is performed by disposing a detector such as a photoelectric sensor instead of the magnetic head. A signal is output from the detector in accordance with the information, and the information can be read based on the signal. Further, the information may be stored in a storage medium such as an LSI card or an IC card without being recorded on the color negative film 10.

Next, the operation of this embodiment will be described. The color negative film 10 after the development processing is set at a predetermined position of the auto printer. When the printing process is started, an image frame to be printed on the color negative film 10 is transported to the printing position. During this transfer, the magnetic head 50
Reads information recorded on the color negative film 10,
A signal corresponding to the read information is output. The output signal is amplified by an amplifier 52, converted into a digital signal by an A / D converter 54, and input to a face extraction circuit 36.

When the image frame reaches the printing position, the printing process is started. The light emitted from the light source 14 is transmitted to the color correction filter 16, the diffusion box 18, and the color negative film 1.
0, is distributed by the distribution prism 20, and is received by the CCD image sensor 28 via the projection optical system 26. At this time, the black shirt 23 is closed.

The light received by the CCD image sensor 2
8 divides the entire screen into a large number of pixels and divides each pixel into R,
The light is separated into three colors of G and B, and the light is measured, and a light measurement data signal is output. After the photometric data signal is amplified by the amplifier 30, the A / D
The signal is converted into a digital signal by the converter 32, the sensitivity of the image sensor is corrected by the 3 × 3 matrix circuit 34, and is input to the face extraction circuit 36 and the average density calculation circuit 38. The average density calculation circuit 38 calculates the average density of one entire screen.

The face extraction circuit 36 estimates the part of the face (main image) of a person in one screen based on the camera information recorded on the color negative film 10 and the photometric data of the image, as described below. , The R of the part estimated to be the face,
Outputs G and B colorimetric data. Exposure calculation circuit 40
Calculates the exposure using the three-color photometric data output from the face extraction circuit 36 and the average density calculated by the average density calculation circuit 38, and outputs the color correction filter 1 via the driver 42.
6 and the black shutter 23 is opened and closed to perform printing.

When the average density obtained by the average density calculation circuit 38 is used, an exposure correction amount for the average density can be obtained. When the exposure correction amount is not determined, the average density calculation circuit 38 is not necessarily required, and the face extraction circuit 3 is not required.
The exposure amount may be obtained from the three-color photometric data output from the unit 6.

FIG. 2 shows a face extraction routine by the face extraction circuit 36. In step 100, noise removal, that is, smoothing of the three-color photometric data input is performed. In the next step 102, the R, G, and B colorimetric data are converted into H (hue value) and L by the following equations (3) to (5).
(Lightness value) and S (saturation value).

L = (R + G + B) / 3 (3) S = 1-min (r ′, g ′, b ′) (4) H = H ′ / 2Pi (4) 5) However, R, G, and B are standardized such that the minimum value is 0 and the maximum value is 1 as shown in the three-dimensional color coordinates of FIG.
Colorimetric data, min () is the minimum value in parentheses, r ′, g ′, b ′ are r ′ = R / L, g ′ = G / L,
b ′ = B / L. H ′ is given by the following equation (6), and Pi (i is one of R, G, and B) is P
It is.

[0039]

(Equation 1) However,

[0040]

(Equation 2) In step 104, as shown in FIG. 4A, a two-dimensional histogram of the hue value and the saturation value is obtained by using a coordinate system including the orthogonal hue value axis, saturation value axis, and pixel number axis. In the next step 106, as described later, the obtained two-dimensional histogram is divided into mountains, that is, clustering of the two-dimensional histogram is performed. In the next step 108, a large number of pixels are clustered based on the peaks of the clustered two-dimensional histogram, the screen is divided based on the clustering, and a region that is a candidate for a human face is extracted from the divided region. .
In the next step 110, a face area is estimated based on the area extracted as a face candidate and the camera information, which will be described in detail later, and R, G, and B three-color photometric data of the area estimated as the face is output. I do. Then, it is determined in step 112 whether or not printing of all frames has been completed. When it is determined that printing has been completed, this routine is terminated.

Next, the details of steps 106 to 110 will be described. FIG. 5 shows details of step 106. In step 120, an area to be evaluated is cut out from the two-dimensional histogram of the hue value and the saturation value.
In FIG. 4, one frame is set as an evaluation area for simplifying the explanation. In step 122, it is determined whether or not there is an evaluation area. When the evaluation area cannot be cut out in step 120, that is, when the evaluation of all the areas is completed, there is no evaluation area, so this routine ends. If there is an evaluation region, the X and Y axes for creating a histogram for mountain cutting are determined in step 124. In other words, the evaluation area is rotated around an axis parallel to the pixel number axis, and when a mountain of the histogram is viewed from the side, a multimodal property is prioritized and a position where the mountain is the sharpest is obtained. Determine X and Y axes. If the processing time needs to be shortened, the accuracy is slightly reduced, but an axis with the maximum variance of the histogram may be used as the X and Y axes. In the example of FIG. 4 (1), when the four mountains numbered 1 to 4 are viewed from the side, multi-modality is prioritized, and the positions where the mountains are sharpest are positions where the three mountains can be seen. Therefore, the X axis is defined in a direction orthogonal to the viewing direction, and the Y axis is defined in a direction orthogonal to the X axis.

In the next step 126, a one-dimensional histogram is created by projecting the two-dimensional histogram on the X and Y axes. In the example of FIG. 4A, when viewed from a direction orthogonal to the X axis, the peaks denoted by reference numerals 1 and 2 appear to overlap each other. Three peaks, that is, peaks 1 and 2, and peaks 4 appear, and when viewed from a direction orthogonal to the Y axis, the peaks 1 to 4 appear to be overlapped, so that one dimension about the Y axis is obtained. One peak appears in the histogram. In the next step 128, the histogram is converted into an evaluation function H (a) by the following equation (7), and peaks are cut out from the histogram on the X axis based on this evaluation function.

[0043]

(Equation 3) Here, f (a) is the number of pixels when the value (feature value) in the X-axis direction is a, and x is the displacement from the feature value a.

That is, the average value T of the evaluation function H (a) is obtained, and the range (the existence range of the valleys and the skirts) of the average value T of the evaluation function H (a) is obtained. Next, the minimum position of the histogram within this range is defined as a valley or a skirt of the histogram. Then, a histogram is cut out at the determined valley or foot.

The cut-out of the mountain will be described with reference to FIG. 6. When the evaluation function H (a) is obtained from the histogram represented by the solid line SI, the result is as shown by the broken line in the figure. The range in which the evaluation function H (a) is equal to or less than the average value T for the negative part is a range in which the feature amounts are v0 to v1 and v2 to v3. The position where the frequency of the histogram within this range is the minimum is the range v
Av0 = v0 for 0 to v1, av1 for the range v2 to v3
Av0 is obtained as a skirt, and av2 is obtained as a valley. A histogram is cut out at this position.

In step 130, the peak of the histogram on the Y axis is cut out in the same manner as the peak of the histogram on the X axis. Next step 132
Then, a region where the peaks of the one-dimensional histogram on the X-axis and the Y-axis cut out as described above are overlapped on the two-dimensional histogram is obtained, and the peak is cut out from the two-dimensional histogram on the hue value and the saturation value. Region E in FIG. 4 (1)
Reference numeral 1 denotes an example of a mountain cut out as described above.

In the next step 134, it is determined whether or not the mountain cut out from the two-dimensional histogram is a single peak. If not, steps 124 to 134 are performed until the mountain cut out from the two-dimensional histogram becomes a single peak. repeat. The area E2 in FIG. 4 (3) shows an example of a single-peak mountain cut out as described above.

In the next step 136, a process (labeling) for attaching a label to identify the cut-out single-peak mountain is performed. In step 138, the labeled mountain is masked, and the process returns to step 120. Then, the above steps are repeated to divide the entire area of the two-dimensional histogram for the hue value and the saturation value into a single peak.

FIG. 7 shows the details of step 108 in FIG. 2. In step 140, the X-axis range XR (FIG. 4 (3)) and Y The axial range YR (FIG. 4 (3)) is obtained for each single peak, and it is determined whether the hue value and the saturation value of each pixel of the original image belong to these ranges, and the pixel clustering is performed. At the same time, pixels belonging to the range surrounded by the ranges XR and YR are collected, and the original image is divided so that the collected pixels form one region on the original image. Numbering is performed on the divided areas.

FIG. 4 (2) shows an example in which the original image is divided, and the pixels in the respective areas denoted by reference numerals 1 to 4 are shown in FIG.
Correspond to the pixels included in the single peaks denoted by reference numerals 1 to 4. In FIG. 4 (1), pixels belonging to the same single-peak mountain are divided into different regions in FIG. 4 (2). This is because in FIG. Although the pixel has a saturation value range, the region is divided in FIG. 4B.

In the next step 142, the small area is removed by judging the area of the divided area, and the numbering is performed again. In the next step 144, a large area is obtained by performing a contraction process of deleting all the boundary pixels of the region and removing it by one skin, and a dilation process of expanding the boundary pixels in the direction of the background pixel and increasing the thickness of one skin in contrast to the contraction process. Are separated from the large area. In the next step 146, a small area is removed and renumbering is performed in the same manner as in step 142, and in step 148, the same contraction and expansion processing as described above is performed to separate the weakly coupled areas. At 150, removal and renumbering of the minute area are performed in the same manner as described above.

FIG. 8 shows the details of step 110. In step 162, the camera information recorded on the color negative film 10 corresponding to the original image is fetched. The camera information includes main image size information or main image existence area information as described above, and in this embodiment, the size information of the main image (face) is used. For this reason,
Using the value for specifying the face size, that is, the length of the face, the focal length of the photographing lens, and the like, the face size is calculated according to the above equation (1). As the size of the face, the major axis, minor axis, average value of major axis and minor axis, peripheral length, and the like can be used. In the case of the size of a person, the size of the face is estimated from that.

After calculating the face size, step 163
In step 108, one of the regions extracted in the routine of FIG. 7 is sequentially selected as a region of interest, the horizontal fillet diameter and the vertical fillet diameter of the region of interest are calculated, and the image size of the region of interest is reduced. Derive. The image size of the attention area may be obtained from the maximum length and the maximum vertical length of the attention area.

In step 164, the image size of the derived area of interest is compared with the face size calculated based on the above equation (1).

In step 166, it is determined whether or not the comparison has been completed for all the extracted regions. If the comparison has not been completed, the comparison of the image sizes is repeated. When the comparison of all image sizes is completed, in step 168, the area having the highest matching degree is estimated as the face image area, and the R, G, and B photometric data of the estimated area is output to the appropriate exposure amount calculation circuit 40. At this time, a range for comparing image sizes may be set using the main image existence area information. By doing so, the processing time for comparing image sizes can be reduced.

The proper exposure amount calculation circuit 40 includes a face extraction circuit 3
6, the R, G, and B photometric data of the face area extracted as described above and the screen average density D _i (i = R, G, or B) of one frame calculated by the average density calculation circuit 38 ) and using the calculated the proper exposure amount E _i according to the following equation, and outputs to the driver 42. The driver 42 controls the light adjustment filter 16 calculates an exposure control value from the appropriate exposure amount E _i.

L _og E _i = LM _i · CS _i · (DN _i -D _i ) + PB _i + LB _i + MB _i + NB _i + K ₁ + K ₂ (8) where each symbol represents the following.

LM: Magnification slope coefficient, which is set in advance according to the enlargement magnification determined by the type of the color negative film and the print size.

CS: There are color slope coefficients prepared for each type of color negative film for underexposure and overexposure, and it is determined whether the average density of the frame to be printed is under or over the standard negative density value. Then, either under exposure or over exposure is selected.

DN: standard negative density value D: average density value of print frame

PB: Correction balance value for standard color paper, determined according to type of color paper LB: Correction lens balance value for standard printing lens, determined according to type of printing lens MB: a correction value (master balance value) for a change in print light source or a change in paper development performance NB: a negative balance (color balance) value determined by the characteristics of a color negative film.

K ₂ : color correction amount K ₁ : density correction amount represented by the following equation

[0063]

(Equation 4) Here, K _a, K _b are constants, FD is the face region average density.

[0064] Further, as the correction value determined density correction amount K ₁ in equation (8) by the film detecting device may represent a color correction amount K ₂ using the face region average density as follows.

[0065]

(Equation 5) Here, K _c is a constant.

[0066] Furthermore, the density correction amount K ₁ in equation (8), the correction amount determined by the color correction amount K ₂ film test device, the average density D _i of the face area of the print frame in formula (8) may be obtained exposure amount is replaced average density FD _i.

As described above, in this embodiment, the face image area is determined by comparing the image size of the attention area with the size of the face obtained from the camera information. An appropriate face area can be estimated in a short time without estimating the area. In addition, since the presence and possibility of extraction of the face can be obtained from the camera information, it is possible to eliminate unnecessary extraction time and errors spent in an area where the presence of the face is low.

It should be noted that, for each of the candidate regions extracted in step 108, the shape and color information of the region of interest and the shape and color information of the neighboring region located around the region of interest determine whether the region of interest is a face. May be determined. For example,
Whether an area having the same hue value and saturation value or a similar hue value and saturation value as the attention area and an image size within a predetermined range of the image area of the attention area is extracted around the attention area. By making the determination, the range to be determined can be the range in which the body of the person exists. Since the body of a person is usually left-right axis symmetric and non-target in the vertical direction and continuous to the face, there is an area that is continuous with the attention area, and whether the area is left-right axis-target and vertical non-target By making the determination, it can be determined whether or not an area corresponding to the body of the person exists. Here, the head is adjacent to the face and forms a substantially circular shape when integrated with the face. Since the head usually has a hat, hair, and the like, the hue or saturation is different from the face. Therefore, for a region adjacent to the region of interest, the ratio between the perimeter of this region and the boundary length of the portion adjacent to the region of interest is 30% or more, or the circularity when the region adjacent to the region of interest is integrated. The saturation value or the brightness value difference between the hue value of the region of interest and the hue value of the region adjacent to the region of interest is large, or the saturation value or brightness value of the region adjacent to the region of interest Is smaller than the attention area, it is possible to determine whether or not the head is present.

Further, it may be determined whether or not an area where the image size matches in a certain range is a face. For example, adults, infants,
The area of the face and the range of the face are dispersed depending on the variation in height and the direction of the face. For this reason, several standard face images,
A plurality of standard body images and a plurality of standard head images are stored in advance, and the attention area can be compared with these standard images to determine whether the image is a face. .

Next, a second embodiment of the present invention will be described. In the present embodiment, a photometric area is determined based on a focus point obtained from read camera information, the photometric area is measured, and face extraction processing is performed. As shown in FIG. 10, a focus point 90 obtained from the read information
Is defined as a photometric area 92 which is the periphery of.

FIG. 9 shows a face extraction routine by the face extraction circuit 36. In step 170, camera information is read. This camera information can use main image existence area information in addition to the main image size information. For example, in this embodiment, the focus point in the multi-point distance measuring device or the existence area information of the face including the focus point is used.
It should be noted that the number of focus points may be one or more. In step 172, the photometric area 92 is set based on the camera information. The setting of the photometric area 92 uses the information of the focus point, and a predetermined area around the focus point 90 is set as the photometric area 92. In step 174, noise removal (smoothing) of the three-color photometric data in the photometric area 92 is performed.
I do. In the next step 176, the above (3) to (5)
The R, G, and B three-color photometric data are represented by H (hue value),
It is converted into L (brightness value) and S (saturation value).

In step 176, a two-dimensional histogram of the hue value and the saturation value is obtained by using a coordinate system composed of the hue value axis, the saturation value axis, and the pixel number axis which are orthogonal to each other. Divided two-dimensional histogram by mountain (clustering of two-dimensional histogram)
I do. In the next step 180, clustering of a large number of pixels is performed based on the peaks of the clustered two-dimensional histogram, and in step 182, the screen is divided based on the clustering, and the divided areas are candidates for a person's face. Extract the region. Next Step 1
At 84, the image size of the region extracted in the same manner as in the first embodiment is compared with the size of the face obtained from the camera information, and the region with the highest degree of coincidence is estimated as the region of the face. R, G, and B colorimetric data of the selected area are output. Then, in step 186, it is determined whether or not the printing of all the frames has been completed. When it is determined that the printing has been completed, this routine is terminated.

It is preferable that the size setting of the photometric area 92 be changed according to the photographing magnification of the photographing device (camera). That is, since the size of the face changes depending on the photographing magnification, the size of the photometric area determined in advance by the photographing magnification may be set. The derivation of the focus point 90 and the photometric area 92 can be easily performed by recording such information using a camera equipped with a multi-point ranging autofocus (AF) device and using this information. .

Here, when the size of the face is small, it is preferable that the photometric point size be reduced together with the change (reduction) of the photometric area. For example, by reducing the size of one pixel for photometry by the projection optical system, even if the size of the face is small, the number of pixels can be set to an appropriate number for photometry of an image. According to this method, even a small person can accurately extract a face image area. Further, there is an effect that the extraction processing time does not change depending on the face size.

If the size of the face is estimated to be equal to or smaller than a predetermined value which is relatively small relative to the entire area of the image frame, the area extraction is stopped, and information on the entire screen, that is, the average density calculation is performed. It is preferable to determine the exposure amount from the average density obtained by the circuit 38. By doing so, it is possible to prevent color reproducibility from deteriorating due to determining the exposure amount from a small amount of image information. On the other hand, if the face size is equal to or larger than a certain value, it is preferable to perform face extraction processing by increasing the number of pixels to be measured at one time by combining four photometric points, for example. By doing so, the calculation time of the photometric data in the area where the face image exists can be shortened, and the processing can be shortened.

In this embodiment, since the attention area is specified from the focus point and the surrounding area to determine whether or not the face is a face,
An appropriate face region can be specified, and the accuracy of determining the region where the face exists is improved. Furthermore, since the face of a person mainly exists around the focus point, the presence or the possibility of extraction of the face can be easily obtained from the camera information or the like recorded at the time of shooting, so that the face area is specified without error. In addition to this, the face can be specified without spending unnecessary extraction time in an area where the presence of the face is low. Note that, in order to determine the face area, after the entire color original image is measured, the calculation processing range for face extraction may be determined based on the focus point.

FIG. 11 shows a modification in which the present invention is applied to an exposure amount determining apparatus separate from a printer or a printer processor. In FIG. 11, parts corresponding to those in FIG. 1 are denoted by the same reference numerals, and description thereof is omitted. Although the average density calculation circuit 38 is not always necessary, an integrated transmission density detection circuit for detecting LATD of the entire screen may be used instead.

FIG. 12 shows a configuration in which the face extraction circuit of FIG. 11 is composed of a plurality of face extraction circuits 36 ₁ , 36 ₂ ... 36n, and the exposure amount is calculated by parallel processing. Face extraction circuit 36
_1, 36 ₂ ··· 36n reads an image according to the time chart of FIG. 13, calculates the exposure amount, and outputs the result. In FIG. 13, t ₁ is the image reading time of one frame, t
₂ one frame of an exposure amount calculating time, t ₃ is the one frame of an exposure amount computation result transfer time is t ₂ >> t _1, t _3. The face extraction circuit 36 ₁ reads an image of one frame at time t ₁ ,
It calculates the exposure amount in ₂ hours, and transfers the calculation result t ₃ hours. At the same time when the image reading of one frame by the face extraction circuit 36 ₁ is completed, the film is fed by one frame and the face extraction circuit 36
₂ starts reading a single frame image, and the face extraction circuit 3
6 ₁ of the image reading of the exposure operation and the face extraction circuit 36 ₂ is performed in parallel, and so the face extraction circuit 36 _3, 36 ₄
.. 36n are processed in parallel.

The time Tp required to process m × n frames in parallel is Tp = m (t ₁ + t ₂ + t ₃ ) + (n−1) t ₁ . On the other hand, the processing time Ts when the parallel processing is not performed
Is Ts = mn (t ₁ + t ₂ + t ₃ ). Therefore,

[0080]

(Equation 6) Double the speed is possible.

The parallel processing device can be applied to the printer shown in FIG. According to the present invention, in addition to the determination of the exposure of the photographic printing apparatus, the determination of the exposure of the digital color printer, the determination of the copying conditions of the copying machine, the determination of the exposure of the camera, the determination of the display conditions of the CRT screen, and the creation of a hard copy from the magnetic image data It can also be applied to the determination of the amount of light at the time.

The present invention also requires, for example, a high-quality one that does not require a high-speed operation for instructing the position of a main image area on a monitor on which an image is displayed by a pointing device such as a light pen or a mouse. Alternatively, the main image can be extracted by using the above-described camera information or the like instead of the pointing device.

[0083]

As described above, according to the present invention, the main image can be extracted based on the information related to the color original image, so that the operation time required for extracting the main image can be reduced and the main image can be extracted. It is possible to obtain the effect that the photometric point size when photometrically measuring the color original image can be made appropriate according to the region, and the color reproducibility of the obtained image can be improved.

Further, since the area where the main image exists can be specified based on the information related to the color original image, the effect of improving the accuracy of determining the main image is obtained.

Further, since the existence and the possibility of extraction of the main image can be obtained from the information related to the color original image, it is possible to reduce the unnecessary extraction time spent in the area where the existence of the main image area is low, The effect of eliminating image extraction can be obtained.

[Brief description of the drawings]

FIG. 1 is a schematic view showing a printer according to an embodiment of the present invention.

FIG. 2 is a flowchart showing a face extraction routine of a face extraction circuit.

FIG. 3 is a diagram showing color coordinates.

FIG. 4A is a diagram illustrating a two-dimensional histogram of hue values and saturation values. (2) is a diagram showing a state in which the original image is divided. (3) is a diagram showing a state where a single peak is cut out from a two-dimensional histogram.

FIG. 5 is a flowchart showing details of step 106 in FIG. 2;

FIG. 6 is a diagram showing a histogram and an evaluation function.

FIG. 7 is a flowchart showing details of step 108 in FIG. 2;

FIG. 8 is a flowchart showing details of step 110 in FIG. 2;

FIG. 9 is a flowchart showing a face extraction routine of a face extraction circuit in a second embodiment.

FIG. 10 is a diagram showing a photometric area around a focus point of an image frame.

FIG. 11 is a schematic diagram of an exposure calculation device to which the present invention is applied.

FIG. 12 is a schematic diagram of an exposure calculation device that performs parallel processing by a plurality of face extraction circuits.

FIG. 13 is a diagram showing a time chart of parallel processing.

[Explanation of symbols]

 28 CCD image sensor 30 Amplifier 36 Face extraction circuit 50 Magnetic head

Claims (6)

(57) [Claims] 1. A method of reading information relating to a color original image, dividing the color original image into a large number of pixels, decomposing each pixel into three colors of red light, green light and blue light and performing photometry. A histogram of hue values is obtained based on the obtained data, and the obtained histogram is divided into hills. And divides the color original image for each group, and selects, from the divided areas, an area most suitable for the information related to the read color original image as a characteristic image area, An exposure amount determining method for determining an exposure amount to a copy material based on the image data of the image. 2. A method of reading information relating to a color original image, dividing the color original image into a large number of pixels, decomposing each pixel into three colors of red light, green light and blue light, and performing photometry. A histogram of hue values or a two-dimensional histogram of hue values and saturation values is obtained based on the obtained data, and the obtained two-dimensional histogram is divided into hills. The pixels are divided into groups corresponding to the divided mountains by judging whether they belong to each other, and the color original image is divided for each group, and the most suitable information relating to the read color original image is read from the divided area. An exposure amount determining method for determining an exposure amount for a copy material based on image data of the characteristic image region. 3. The exposure determining method according to claim 1, wherein the information related to the color original image is size information of a main image or size information for obtaining a size of the main image. 4. The exposure determining method according to claim 1, wherein the information related to the color original image is area information indicating an image area where a main image exists. 5. The exposure determining method according to claim 1, wherein the information related to the color original image is information indicating a focus position of the focused image in the color original image. 6. A camera in which at least one of size information indicating a size of a main image and area information indicating an image area where the main image exists is recorded or stored by an imaging device at the time of shooting. 3. The exposure amount determining method according to claim 1, which is information.