JP2923401B2 - 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,
In particular, the present invention relates to an exposure determining method for extracting density data of a person's face and determining an exposure based on the extracted density data when a color original image is copied onto a color copying material or a black and white copying material.

[0002]

2. Description of the Related Art The most noticeable part when viewing a photograph of a person is the face of the person, and the color of the face of the person is important for creating a high-quality photograph or image. Must be printed or displayed in the proper color.

Conventionally, when an image including a person is printed or displayed by a photo processing device such as a printer, a printing device, and an image display device, density data of the face is extracted and the face is extracted based on the extracted density data. The exposure amount is determined so that the density of the face is reproduced as an appropriate density as the target density, and the color of the face is properly printed or displayed.

However, in this method, since the reflectance of a person's face is assumed to be single, if the reflectance of a person's face varies due to individual differences such as tanning and fairness or race, the person's face is reflected. However, there is a problem that it is not possible to perform correction for printing or displaying the face of the subject in an appropriate color.

[0005] For example, as shown in FIG. 15, the spectral reflectance characteristics of skin of six races from white race to black race (Z1: white-blond, Z2: white-brunette, Z
3: Japanese, Z4: Hindu, Z5: Mulato, Z6: the negro)
The racial difference between the white race and the black race can be as much as 7 to 8 times. Therefore, the reflectivity of the face greatly differs between races. For this reason, for example, if the exposure amount is determined so that the face density becomes the target density as described above using an Asian face as a standard subject, the face density becomes white in a subject such as a black race whose face reflectance is low. The exposure amount is determined as follows. As a result, there is a problem that the obtained image is reproduced as an image having a low density as a whole.

SUMMARY OF THE INVENTION The present invention has been made to solve the above problems, and is intended to reproduce a color original image at an appropriate density based on data extracted as a human face from a color original image such as a negative film. It is another object of the present invention to provide an exposure determining method for determining an exposure.

[0007]

According to a 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. Photometry, based on the data obtained by photometry, to determine a hue or a color region having the same or similar hue or hue and saturation on the color original image, and determine whether the obtained color region is a human face region. The density of an area determined to be an area of a person's face is determined, and correction is performed based on the density of the area for a color original image in which the reflectance of the face of a person who is a subject corresponding to the determined density is a predetermined value or more. To determine the amount of exposure to the copy material, and perform correction based on the density of the area for a color original image in which the reflectance of the face of the person corresponding to the obtained density is less than a predetermined value. And determine the amount of exposure to the copy material.

A second aspect of the present invention is the exposure amount determining method according to the first aspect of the present invention, wherein the reflectance of a face of a person who is a subject corresponding to the obtained density is a predetermined value or more. Is characterized in that correction is performed so that the average density of the area becomes the reference density and the exposure amount to the copy material is determined.

A third aspect of the present invention is the exposure determining method according to the first aspect of the present invention, wherein the determined density of the subject is
Upper limit value corresponding to less than a predetermined value of face reflectance and predetermined
Color original image within the specified range between
If the reflectance of the face of the person being the subject is
The image based on the density of the area
The method is characterized in that the amount of exposure to the copy material is determined by performing the correction.

[0010] A fourth aspect of the present invention, there is provided an exposure amount determining method of the invention of claim 3, the color original image determined density is included in the predetermined range, excluding the area of the face of the person thereof a histogram of the density of the color area, to estimate whether the flash exposure based on the obtained histogram, flash exposure
Only when it is estimated to be other than light, the color original image
In the color original image where the reflectance of the person's face is
As another feature, the amount of exposure to the copy material is determined by performing correction based on the density of the region .

[0011]

According to the present invention, a color original image is divided into a large number of pixels, each pixel is separated into three colors of red light, green light and blue light, and photometry is performed. Is used to find a hue or a color region having the same or similar hue and saturation. Next, it is determined whether or not the obtained color area is an area of a person's face. The face area can be determined from the similar color area based on a hue histogram or a two-dimensional histogram of hue and saturation. Subsequently, the density of an area determined to be a human face area is obtained.
From the obtained density, it can be estimated whether or not the reflectance of the face of the corresponding person is equal to or more than a predetermined value. That is, as the reflectance of the face of the person as the subject decreases, the density decreases on the color negative film, and increases on the reversal film. When the reflectance of the face of the person who is the subject is low, if the exposure amount of the color original image is corrected based on the density of the face area, underexposure or overexposure occurs in other areas, and proper exposure can be performed. Can not. According to the present invention, for a color original image in which the reflectance of the face of a person as a subject is equal to or greater than a predetermined value, correction based on the density of the area is performed to determine the exposure amount to the copy material. This correction can be performed so that the average density of the face area becomes the reference density. Further, for a color original image in which the reflectance of the face of the person as the subject is less than a predetermined value, the exposure amount to the copy material is determined without performing correction based on the density of the area. As described above, since the correction based on the density of the face region is performed only on the color original image in which the reflectance of the face of the person who is the subject is equal to or more than the predetermined value, for example, the face of the person who is the subject due to race or sunburn When the reflectance of the image is significantly low, the optimum exposure amount can be determined without being corrected by the face.

Here, even if the reflectance of the face of the person who is the subject is a color original image having a predetermined value or more, it may be included irrespective of the actual reflectance of the face of the person depending on the photographing conditions. For example, when the reflectivity of an actual person's face is standard and the subject is weakly backlit or underexposed overall, the density of the person's face area on the negative film is low as in the case of low face reflectivity. Become. Therefore, as described in claim 3,
The determined density is not the predetermined value of the reflectance of the face of the person who is the subject.
A predetermined value between the upper limit and the lower limit that correspond to full
Person who is the subject for the color original image included in the range
An original color image whose reflectance of the face of the object is equal to or greater than a predetermined value
And the amount of exposure to the copy material is determined by performing correction based on the density of the area . Note that the calculated concentration exceeds the upper limit.
If the value is lower than the lower limit,
Determine the amount of exposure to the copy material without making corrections
You. This makes it possible to prevent correction when the reflectivity of the face of the person being the subject is low, and when the reflectivity of the actual person's face is standard and is weakly backlit or underexposed overall. Can be corrected.

Further, when a face having a low reflectance of an actual person's face is photographed by flash exposure, the predetermined range for the correction includes the face density. Generally, the density distribution of a color original image photographed by strobe exposure is roughly classified into a portion irradiated with light and a portion not irradiated. Therefore,
As described in claim 4, with respect to the obtained concentration color original image included in the predetermined range, a histogram of the density of the color region other than the region of the face of the person thereof, based on the obtained histogram to estimate whether or not the flash exposure, stroke
The color original image is received only when
A color original whose reflectance of the face of the person who is the subject is greater than or equal to a predetermined value
Correction based on the density of the area as an image
Determining the amount of exposure to the copy material Te. This makes it possible to determine the optimal exposure amount without performing correction based on the density of the face when the face of the actual person having low reflectance of the face is photographed by flash exposure.

[0014]

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 that transports a color negative film 10. A light source 1 is provided below the color negative film 10 transported by the transport rollers 12.
4. A color correction filter 16 such as a dimming filter and a diffusion box 18 are sequentially arranged. Above the negative film 10, the light transmitted through the negative film 10 is
A distribution prism 20 for distributing in the direction 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. This CCD image sensor 28
The entire screen (one frame) of the negative film 10 is divided into a large number of pixels (for example, 256 × 256 pixels), and each pixel is
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 storing a program of a routine described below, and calculates the average density of the entire screen. It is connected to an appropriate exposure calculation circuit 40 via an average density calculation circuit 38 for calculating. The appropriate exposure amount calculation circuit 40 is connected to the color correction filter 16 via a driver 42 for driving a color correction filter. The proper exposure amount calculating circuit 40 is constituted by a microcomputer storing a program of a routine (FIG. 9) described below.

Next, the operation of this embodiment will be described. Light source 14
Are transmitted through the color correction filter 16, the diffusion box 18, and the color negative film 10, are distributed by the distribution prism 20, and are received by the CCD image sensor 28 via the projection optical system 26. At this time, the black shirt 23 is closed. By receiving the light, the CCD image sensor 28 divides the entire screen into a large number of pixels, decomposes each pixel into three colors of R, G, and B, performs photometry, and outputs a photometric data signal. The photometric data signal is amplified by an amplifier 30 and then converted into a digital signal by an A / D converter 32. The sensitivity of the image sensor is corrected by a 3 × 3 matrix circuit 34, and a face extraction circuit 36 and an average density calculation circuit 38 Is input to This average density calculation circuit 3
In step 8, the average density of one entire screen is calculated. The face extraction circuit 36 estimates the portion of the face of the person in one screen as described below, and outputs R, G, and B colorimetric data of the portion estimated as the face. The 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 16 via the driver 42. Is controlled, and the black shutter 23 is opened and closed to perform printing. When the average density calculated by the average density calculation circuit 38 is used, an exposure correction amount for the average density can be calculated. If the exposure correction amount is not determined, the exposure amount may be determined directly from the three-color photometric data output from the face extraction circuit 36 without necessarily requiring the average density calculation circuit 38.

FIG. 2 shows a face extraction routine by the face extraction circuit 36. In step 100, noise removal, that is, smoothing of the input three-color photometric data is performed. In the next step 102, the R, G, and B colorimetric data are converted to H (hue value) and L by the following equations (1) to (3).
(Lightness value) and S (saturation value).

L = (R + G + B) / 3 (1) S = 1-min (r ′, g ′, b ′) (2) H = H ′ / 2Pi (.) 3) 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 (4), and Pi (i is one of R, G, and B) is P
It is.

[0018]

(Equation 1)

However,

[0020]

(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 a hue value axis, a saturation value axis, and a pixel number axis which are orthogonal to each other. Then, in the next step 106, as described later, the obtained two-dimensional histogram is divided for each mountain, that is, clustering of the two-dimensional histogram is performed. In the next step 108, the clustered 2
A large number of pixels are clustered based on the peaks of the 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 from the area extracted as a face candidate, and R, G, B three-color photometric data of the area estimated as the face is output. 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 the peaks of the histogram are viewed from the side, multimodality is prioritized, and a position where the peak is the sharpest is obtained. Determine X and Y axes. If the processing time needs to be shortened, the accuracy may be slightly deteriorated, but the X and Y axes may use the axis that maximizes the variance of the histogram. 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 position where the mountain is the sharpest is the position where the three mountains can be seen. 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 (5), and peaks are cut out from the histogram on the X axis based on the evaluation function.

[0024]

(Equation 3)

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

Referring to FIG. 6, the above-mentioned cutting of the mountain will be described. When the evaluation function H (a) is obtained from the histogram represented by the solid line SI, it becomes 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, processing (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 of the single-peak mountain divided in the above-described manner. 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 of the respective regions denoted by reference numerals 1 to 4 are included in the single-peaked mountain denoted by reference numerals 1 to 4 in FIG. Corresponding to the pixel. 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 determining 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, the 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 from each other. In step 150, the small area is removed and renumbered in the same manner as described above.

FIG. 8 shows the details of step 110. In step 162, one of the areas extracted in step 108, that is, the routine extracted in the routine of FIG. 7, is selected as the attention area, and the horizontal fillet diameter of the attention area is selected. In addition to normalizing the size of the attention area by performing scaling processing of the attention area so that the vertical fillet diameter becomes a predetermined value,
The density value or the luminance value is normalized according to the following equation (6).

[0034]

(Equation 4)

Where dmax: maximum density value (or luminance value) in the area dmin: minimum density value (or luminance value) in the area ds: full scale density value (or luminance value) of the image sensor d: density value before standardization (Or luminance value) dr: density value after standardization (or luminance value) In step 164, a plurality of (ten in this embodiment) standard face images stored in advance (a face image viewed from the front, The correlation coefficient r of the attention area with respect to the face image (left / right), downward face image, upward face image, etc.
This correlation coefficient is used as a feature value. Even if this standard face image is data of only the face outline,
The data may be data obtained by adding data of the internal structure of the face (eye, nose, mouth, etc.) to the data of the contour of the face.

[0036]

(Equation 5)

However,

[0038]

(Equation 6)

Where T is the length of the horizontal and vertical fillet diameters of the image (here, the lengths of the fillet diameters are the same), f
(X, y) represents a region of interest, and g (x, y) represents a standard face image.

Then, in step 166, it is determined whether or not the region of interest is a person's face by linear discriminant analysis using the above feature amount as a variable, and the R, G, B photometric data of the region determined to be a face is determined. Is output to the appropriate exposure amount calculation circuit 40. In step 168, it is determined whether or not the determination as to whether or not the face is a face has been completed for all the extracted areas. If not, steps 162 to 168 are repeated.

In step 166, the R, G, and B photometric data of the area determined not to be a face is also output to the appropriate exposure amount calculation circuit 40. In this case, in order to clarify the R, G, and B photometric data of the area determined to be a face, a set is set when the area is determined to be a face,
When it is determined that the area is not a face, a reset face flag is output at the same time.

In the above description, the correlation coefficient is used as the feature value used to determine whether or not the face is a person. However, the invariant derived from the normalized central moment around the center of gravity described below, An autocorrelation function or a geometric invariant may be used.

The central moment μ _pq about the (p + q) th order center of gravity of the image f (x, y) is

[0044]

(Equation 7)

However,

[0046]

(Equation 8)

Then, the normalized central moment about the center of gravity is as follows.

[0048]

(Equation 9)

Here, y = (p + q + 2) / 2 p + q = 2, 3,... From the above, the following seven invariants ψ _{i are} obtained from the normalized central moments around the second and third centroids. _, (I
= 1, 2,..., 7) are derived.

[0050]

(Equation 10)

The autocorrelation function _Rf is expressed as follows.

[0052]

[Equation 11]

The geometric invariant feature is represented by the following equation.

[0054]

(Equation 12)

Here, when the reflectance of the face of the subject is smaller than the reference reflectance, the density of the face on the negative film becomes smaller. When the reflectance of the subject's face is significantly low, if the subject is photographed by backlight, the exposure will be significantly insufficient, and even if the backlight is corrected, the background will fly further without reproducing the appropriate density. Therefore, there is no need for correction based on face density. In the case of proper exposure, overexposure, and underexposure, there is no need for density correction based on face density. In the case of strobe exposure, since the face rarely flies, there is no problem even if the correction based on the face density is not performed.

Therefore, when the reflectance of the subject's face is significantly small, there is no need to correct the density of the face area, and when it is necessary to correct an image photographed by backlight,
It is only necessary to judge whether this image is an image captured by backlight or the reflectance of the subject's face is small, and not to perform the correction based on the face density only when the reflectance of the subject's face is small.

FIG. 9 shows an appropriate exposure amount calculation routine by the appropriate exposure amount calculation circuit 40 for determining the presence / absence of the correction based on the face density described above.
Then, the set values Dnm and dag used in this routine are read. The set value Dnm indicates the density value of the target face density on the negative film, and the set value dag indicates the density value of the backlight correction judgment density which is a reference value for judging whether or not to correct the image photographed by backlight. . In the next step 172,
As described above, R of the face area extracted by the face extraction circuit 36,
The G and B three-color photometric data (the data in which the face flag is input as a set) is read, and the subject density Dnf of the face area on the negative film is calculated from the photometric data.

When the calculation of the object density Dnf is completed, the routine proceeds to step 174, where it is determined whether or not Dnf ≦ dag. If the determination is affirmative terminates this routine and a correction value K ₁ to be described later to zero. When the condition of Dnf ≦ dag is satisfied, when the reflectivity of the subject's face is substantially small, proper exposure, backlight and overall underexposure are performed, or when the reflectivity of the subject's face is standard. This is the case of strong backlight. Therefore, there is no need for correction based on the density of the face.

If a negative determination is made in step 174, the flow advances to step 176 to determine whether or not Dnf ≧ Dnm. If the determination is affirmative, the face density of the subject without the need for correction by concentration of the face to the same or greater than the target face density, the correction value K ₁ to end the present routine is set to 0.

If a negative determination is made in step 176, then dag <Dnf <Dnm. If this condition is satisfied, the flash exposure or the overexposure is performed when the reflectance of the subject's face is substantially small. , Or when the reflectance of the subject's face is standard, the case is a weak backlight or an overall underexposure. When the reflectivity of the subject's face is substantially small, there is no need to correct for the face density in the case of strobe exposure or overall overexposure. Therefore, correction based on the face density in the case of underexposure is necessary. The inventor of the present invention has found that the characteristics of the cumulative histogram of the original image due to the strobe exposure change gradually (so-called
Focusing on the point where there are two shoulders), in the present embodiment, the presence / absence of the above-mentioned correction is determined based on the distribution of a histogram that describes this condition below. Instead of using the cumulative histogram, it may be simply determined from the density histogram whether or not the mountain is a single peak.

In step 178, as shown in FIG. 10, a cumulative histogram is obtained for the density of the region other than the face region extracted, and the process proceeds to step 180. As the density of the area other than the face area, the sum or average value of the R, G, and B three-color photometric data (the data in which the face flag is input as a set) other than the face area extracted by the face extraction circuit 36 is used. . In the next step 180, a differential characteristic is obtained after smoothing the obtained cumulative histogram (see FIG. 11). At this time, the presence of a differential value equal to or smaller than a predetermined value (for example, 0) indicates that there is a gradual change (so-called two shoulders) in the characteristic of the cumulative histogram as shown by the broken line in FIG. I have. Therefore, in the next step 182, it is determined whether or not there are two shoulders by determining the presence or absence of a differential value that is equal to or less than a predetermined value. It determines that the correction value K ₁ to end the present routine is set to 0.

On the other hand, if the result of the determination in step 182 is negative and the shoulder is less than 2, the flow advances to step 184 to calculate the correction value K ₁ based on the following equation (13). After the calculation is completed, this routine ends.

[0063]

(Equation 13)

Here, K_a, K_bIs a constant, and FD is
This is the face area average density. In the next step 188, face extraction
The R, G, B photometry data of the face area extracted by the output circuit 36
Data, correction value K₁ And calculated by the average density calculation circuit 38.
Screen average density D_i(I = R, G, and B
) And the proper exposure amount E according to the following equation:_iTo
> Calculate and output to the driver 42. Driver 42 is suitable
Positive exposure E _iCalculates the exposure control value from
It controls the filter 16.

[0065] l _og E _i = however _{LM i · CS i · (DN} i -D i) + PB i + LB i + MB i + NB i + K 1 + K 2 --- (8), each symbol is as follows.

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

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

DN: standard negative density value. D: Average density value of print frame.

PB: A correction balance value for standard color paper, which is determined according to the type of color paper.

LB: For a standard printing lens. The correction lens balance value is determined according to the type of the printing lens.

MB: a correction value (master balance value) for a change in the printing light source and a change in the paper developing performance.

NB: Negative balance (color balance) value determined by the characteristics of the negative film.

K ₁ : density correction amount. K ₂ : color correction amount.

It should be noted that the density correction amount K ₁ in the above equation (8) may be used as the correction value obtained by the film inspection apparatus, and the color correction amount K ₂ may be expressed using the face area average density as follows.

[0075]

[Equation 14]

Here, K _c is a constant. Furthermore, the density correction amount K ₁ in equation (8), the color correction amount K ₂ is a correction amount determined by the film detecting device, the average concentration FD of average density D _i a face region of the print frame in formula (8) _i
The exposure amount may be obtained in place of the above. In this case, the replaced by the average density of the predetermined reference density correction amount K ₁ in step 186 is replaced with the average density FD _i of step 184 is the extracted face region. Thus, the routine shown in FIG. 9 can be executed.

In this embodiment, since the determination is made using the outline and internal structure of the area, face data can be extracted from an image in which faces, grounds, trees, and the like having similar hues are mixed. .

Further, in this embodiment, based on the data of the extracted face area, the case where the reflectance of the face of the subject is small and the correction based on the face density is not necessary, and the case where the correction based on the face density at the time of backlight is necessary are described. Is determined by the face density and the histogram of the face density, so that the exposure amount can be determined so that the face of the person has an appropriate density regardless of the race or individual difference of the subject.

In this embodiment, the case where the density is measured from the image of the negative film has been described. However, a reversal film may be used.

FIG. 12 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. 12, 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. 13 shows a configuration in which the face extraction circuit of FIG. 12 is constituted by 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. 14, calculates the exposure amount, and outputs the result. In FIG. 14, 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 the image reading of one frame, and the face extracting 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 for parallel processing of mxn frames 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,

[0083]

(Equation 15)

It is possible to double the speed. This parallel processing device can be applied to the printer shown in FIG.

The present invention, besides determining the exposure amount of the photographic printing apparatus, determines the exposure amount of the digital color printer, the copy condition of the copying machine, the exposure amount of the camera, the display condition of the CRT screen, and the hard copy from the magnetic image data. Can also be applied to the determination of the amount of light when creating.

[0086]

As described above, according to the present invention, a color original image in which the reflectance of the face of a person as a subject is not less than a predetermined value is corrected based on the density of the region. Even if the reflectance of the person's face is significantly smaller than the reference value due to individual differences and races, it is possible to determine the amount of exposure to the copy material so as to obtain the optimum density. Can be obtained.

[Brief description of the drawings]

FIG. 1 is a schematic diagram illustrating a printer according to a first 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 diagram showing details of step 106 in FIG. 2;

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

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

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

FIG. 9 is a flowchart showing an appropriate exposure amount calculation routine of an appropriate exposure amount calculation circuit.

FIG. 10 is a diagram showing a cumulative histogram for face density.

FIG. 11 is a diagram showing a differential characteristic of FIG. 10;

FIG. 12 is a schematic diagram of an exposure calculation device to which the present invention is applied.

FIG. 13 is a schematic diagram of an exposure calculation device that performs parallel processing by a plurality of face extraction circuits.

FIG. 14 is a diagram showing a time chart of parallel processing.

FIG. 15 is a diagram showing a spectral reflectance characteristic of skin of each type.

[Explanation of symbols]

 28 CCD image sensor 30 Amplifier 36 Face extraction circuit 40 Appropriate exposure calculation circuit

Claims (4)

(57) [Claims] 1. A color original image is divided into a large number of pixels, each pixel is separated into three colors of red light, green light and blue light, and photometry is performed. Based on data obtained by photometry, the color original image is displayed on the color original image. Hue or color areas with the same or similar hue and saturation were obtained, it was determined whether or not the obtained color area was a human face area, and the density of the area determined to be a human face area was obtained. For a color original image in which the reflectance of the face of the person corresponding to the density is equal to or greater than a predetermined value, the correction based on the density of the area is performed to determine the amount of exposure to the copy material. An exposure amount determining method for determining an exposure amount to a copy material without performing correction based on the density of the area for a color original image in which the reflectance of the face of a person who is a subject is less than a predetermined value. 2. The method according to claim 1, wherein the correction is performed such that the average density of the area of the color original image whose reflectance of the face of the person corresponding to the obtained density is equal to or more than a predetermined value is equal to the reference density. 2. The method according to claim 1, wherein the exposure amount is determined. 3. The method according to claim 1, wherein the determined density is the inverse of the face of the person who is the subject.
Lower than the predetermined upper limit corresponding to the emissivity less than the predetermined value
For color original images that fall within a predetermined range between the limit values,
Color source whose reflectance of the face of the subject is greater than or equal to a predetermined value
Correction based on the density of the area as an image
2. The exposure amount determining method according to claim 1, wherein the exposure amount on the copy material is determined by the following method. Mosquitoes wherein the obtained density is included in the predetermined range
Against color original image, a histogram of the density of the color region other than the region of the face of the person was to estimate whether the flash exposure based on the obtained histogram, except flash exposure
The color original image is the subject only when it is estimated that
It is a color original image where the reflectance of the person's face is greater than or equal to a predetermined value.
4. The method according to claim 3, wherein a correction based on the density of the area is performed to determine an exposure amount on the copy material.