JP5987376B2 - Imaging device - Google Patents

Description

  The present invention relates to an imaging apparatus.

  2. Description of the Related Art An imaging device is known that generates a binary image by binarizing a captured image according to a condition using an average value of luminance and color information within an angle of view, and extracts a subject from the binary image. (For example, Patent Document 1).

JP 2011-0119177 A

  However, in the method of Patent Document 1, there is a possibility that the subject cannot be appropriately extracted because the hue of the subject is buried in the background (other than the subject) in the captured image.

An imaging apparatus according to the present invention is an imaging apparatus that images a subject through a lens used for focus adjustment, and a first extraction unit that extracts a plurality of first subjects included in the subject based on hue information and saturation information; A second extraction unit for extracting a second subject from the plurality of first subjects based on the area information of the first subject and the inertia moment information of the first subject extracted by the first extraction unit; A control unit that moves the lens to focus on the second subject extracted by the extraction unit, and the first extraction unit extracts the first subject stored in the storage unit in advance. The plurality of first subjects are extracted based on specific hue information and saturation information designated from the plurality of hue information and saturation information.

  According to the present invention, it is possible to appropriately extract a subject having a hue within a predetermined range.

It is a block diagram which illustrates the composition of the digital camera by one embodiment of the invention. It is a top view of an image sensor. It is a functional block diagram of an image processing part. It is an example of the histogram of an example of an imaging screen, and the Cr plane image. It is an example of the histogram of a Cr plane image. It is a hue circle representing a part of the YCbCr color space. It is a figure for demonstrating the method of designating the range of a predetermined hue based on color difference information. It is a figure for demonstrating the method of designating the range of a predetermined hue and the range of a predetermined saturation based on color difference information. It is an example of the flowchart regarding operation | movement of the classification | category evaluation part of an image processing part. It is an example of the flowchart regarding the imaging preparation operation which a digital camera performs. It is a figure which shows an example of a setting input screen.

  Hereinafter, embodiments for carrying out the present invention will be described with reference to the drawings. FIG. 1 is a block diagram illustrating the configuration of a digital camera system according to an embodiment of the present invention. A digital camera 1 illustrated in FIG. 1 includes a photographing lens 2, a lens driving unit 3, an image sensor 4, an A / D conversion unit 5, an image processing unit 6, a memory 7, a CPU 8, a nonvolatile memory 9, and a display unit 10. And a recording / reproducing unit 11.

  The photographic lens 2 is composed of a lens group including a focusing lens and a zoom lens, but is illustrated as a single lens in FIG. The focusing lens included in the photographic lens 2 is driven in the direction of the optical axis O by the lens driving unit 3.

  The photographing lens 2 forms a subject image on the imaging surface 4 a of the imaging element 4. The image sensor 4 is configured by a CMOS image sensor or the like. On the imaging surface 4a, imaging pixels having red (R), green (G), and blue (B) color filters are arranged two-dimensionally.

  FIG. 2 is a plan view showing an enlarged part of the imaging surface 4a. Image pickup pixels 40R, 40G, and 40B having R, G, and B color filters are arranged in a Bayer array on the image pickup surface 4a illustrated in FIG. The imaging pixels of the imaging device 4 photoelectrically convert the subject image formed on the imaging surface 4a into an analog imaging signal. Specifically, each of the imaging pixels 40R outputs a red (R) analog imaging signal. The imaging pixels 40G each output a green (G) analog imaging signal. The imaging pixels 40B each output a blue (B) analog imaging signal. The A / D converter 5 converts the analog imaging signal output from each of the imaging pixels 40R, 40G, and 40B into a digital imaging signal (RAW image data).

  Under the control of the CPU 8, the image processing unit 6 performs debayer processing, luminance signal generation, color difference signal generation, color image binarization processing, white processing on the digital imaging signal output from the A / D conversion unit 5. Image processing to be described later such as balance adjustment is performed. The image processing unit 6 uses the memory 7 as a buffer memory when executing image processing.

  The memory 7 is a non-volatile storage unit, and is used as a buffer memory by the image processing unit 6 and also as a work area for the CPU 8. The CPU 8 controls each part of the digital camera 1 based on a program stored in the non-volatile memory 9 and performs autofocus (AF) processing, exposure calculation, and the like. The nonvolatile memory 9 stores various programs executed by the CPU 8 and setting parameters for various image processes executed by the image processing unit 6.

  The image processing unit 6 converts the image data after the image processing into an image file of a predetermined format (JPEG, H.264, etc.) under the control of the CPU 8. The recording / reproducing unit 11 records the image file on the memory card 13 under the control of the CPU 8. Further, the recording / reproducing unit 11 reads an image file recorded on the memory card 13 under the control of the CPU 8 and causes the display unit 10 to reproduce and display the captured image. The memory card 13 is a recording medium that is detachably attached to a card slot (not shown).

  The display unit 10 is a liquid crystal monitor or the like, and displays a through image reproduction display, a setting parameter setting screen (details will be described later), an operation menu screen, and the like under the control of the CPU 8.

  The operation member 12 includes a release switch 121, an operation switch 122, a power switch, a touch panel, and the like. When the user operates the operation member 12, an operation signal corresponding to the operation is output to the CPU 8. For example, when the release switch is pushed down to about half of the normal stroke, preparations for shooting such as the AF processing and exposure calculation are performed. When the release switch is pushed down to the normal stroke, the photographing operation is started.

  FIG. 3 is a functional block diagram illustrating a part of the image processing performed by the image processing unit 6. The image processing unit 6 includes a debayer processing unit 60, a white balance unit 61, a luminance signal generation unit 62, a color difference signal generation unit 63, a binarization processing unit 65, a classification evaluation unit 64, and a subject candidate extraction unit 66. The image processing unit 6 includes various image processing units such as a gamma correction unit in addition to the illustrated image processing unit.

  The debayer processing unit 60 performs a known debayer process (Bayer interpolation process) on the RAW image data output from the A / D conversion unit 5 to generate an RGB image. The debayer process is a process for interpolating each pixel of an RGB image by weighted addition with surrounding pixels. The RGB image has R, G, B primary color information for each pixel.

  The white balance unit 61 performs white balance processing by multiplying the RGB image generated by the debayer processing unit 60 by the white balance gain. The white balance process is a process of adjusting so that an achromatic object is captured as an achromatic image regardless of the characteristics of ambient light.

The luminance signal generation unit 62 generates luminance information Y for each pixel of the RGB image. The luminance signal generation unit 62 calculates the luminance information Y using, for example, the following equation [1]. An image represented by the luminance information Y corresponding to all pixels of the RGB image input to the luminance signal generation unit 62 is referred to as a Y plane image.
Y = 0.299 * R + 0.587 * G + 0.114 * B [1]

The color difference signal generation unit 63 generates color difference information for each pixel of the RGB image. The color difference signal generation unit 63 calculates the two color difference information Cb and Cr using, for example, the following equations [2] and [3].
Cb = −0.169 × R−0.331 × G + 0.500 × B (2)
Cr = 0.500 × R−0.419 × G−0.081 × B (3)
An image represented by the color difference information Cb corresponding to all pixels of the RGB image input to the color difference signal generation unit 63 is referred to as a Cb plane image. On the other hand, an image represented by color difference information Cr corresponding to all pixels of the RGB image is referred to as a Cr plane image.

  The RGB image is converted into a YCbCr image by the processing of the luminance signal generation unit 62 and the color difference signal generation unit 63. Hereinafter, a YCbCr image is referred to as a YCbCr image.

  The binarization processing unit 65 binarizes the RGB image to generate a binary image. The binarization processing unit 65 has a plurality of sections (references) used for binarization of RGB images. Details of the binarization processing unit 65 will be described later.

  The classification evaluation unit 64 extracts a group of white pixels (white pixel block) from the binarized image generated by the binarization processing unit 65, and calculates an evaluation value for each white pixel block. Then, the classification used for binarization is evaluated based on the evaluation value.

  The subject candidate extraction unit 66 extracts a pixel block as a subject candidate (hereinafter referred to as a subject candidate) based on the evaluation of the category evaluation unit 64. The CPU 8 performs AF processing based on the subject candidate extracted by the subject candidate extraction unit 66.

-Details of the binarization processing unit 65-
The binarization processing unit 65 has a plurality of sections (references) used for binarization of RGB images. The binarization processing unit 65 binarizes the RGB image after the white balance processing is performed by the white balance unit 61. The binarization processing unit 65 uses a classification (standard) used for binarization of the RGB image. ) Is exemplified below.
(Category 1) Luminance information Y
(Category 2) Color difference information Cb
(Category 3) Color difference information Cr
(Category 4) Hue based on the color difference information Cb and the color difference information Cr (Category 5) Hue and saturation based on the color difference information Cb and the color difference information Cr

-(Category 1)-
The binarization of the image by (Category 1) will be described. The details of (Category 1) are disclosed in Patent Document 1. Binarization processing unit 65 (Category 1) when performing binarization is used to calculate the average value E _Y of the luminance information Y of all pixels in the Y plane image. Then, the binarization processing unit 65 compares the luminance information Y of each pixel of the Y plane image with the average value _EY, and binarizes the Y plane image. For example, the binarization processing unit 65 converts a Y plane image pixel satisfying Y> E _Y into a white pixel, converts a Y plane image pixel satisfying Y ≦ E _Y into a black pixel, A binary image B1 is generated. In addition, the binarization processing unit 65 generates a complement image B10 of the first binary image B1.

-(Category 2)-
The binarization of the image by (Category 2) will be described. Details of (Category 2) are disclosed in Patent Document 1. When performing binarization using (Category 2), the binarization processing unit 65 calculates an average value E _Cb of the color difference information Cb of all the pixels of the Cb plane image. Then, the binarization processing unit 65 compares the color difference information Cb of each pixel of the Cb plane image with the average value E _Cb , converts the pixel of the Cb plane image satisfying Cb> E _Cb into a white pixel, The pixel of the Cb plane image where Cb ≦ E _Cb is converted into a black pixel. A binary image generated by the binarization processing unit 65 using (Section 2) is referred to as a second binary image B2.

-(Category 3)-
The binarization of the image by (Category 3) will be described. Details of (Category 3) are disclosed in Patent Document 1. Binarization processing unit 65, when performing binarization using (Category 3), calculates the average value E _Cr of the color difference information Cr for all the pixels of the Cr plane image. Then, the binarization processing unit 65 compares the color difference information Cr of each pixel of the Cr plane image with the average value _ECr , converts the pixel of the Cr plane image satisfying Cr> _ECr into a white pixel, The pixels of the Cr plane image _satisfying Cr ≦ E _Cr are converted into black pixels. The binary image generated by the binarization processing unit 65 using (Section 3) is referred to as a third binary image B3.

  Using FIGS. 4A and 4B as examples, a specific example in the case of obtaining a binary image for the section (3) will be described. The same applies to (Category 1) and (Category 2). FIG. 4A illustrates an example of an imaging screen, and the imaging screen is painted with a blue sky background 100 and a vehicle 101 whose main hue is purple (black in FIG. 4A). ) And are included. It is assumed that the user is about to image the vehicle 101 as a subject.

  FIG. 4B is a histogram of the Cr plane image corresponding to the imaging screen of FIG. The horizontal axis of FIG. 4B represents the digital value of the color difference information Cr, and the vertical axis represents the frequency of the value of each color difference information Cr. FIG. 4B shows a Cr distribution 200 corresponding to the blue color of the background 100 and a Cr distribution 201 corresponding to the purple color of the vehicle 101.

Further, the average value _{E Cr} of chrominance information Cr is shown in Figure 4 (b). The distribution 200 of Cr corresponding to blue present in the left (Cr ≦ _{E Cr)} than the average value _{E Cr,} presence Cr distribution 201 corresponding to purple to the right _{(Cr> E Cr)} than the average value _{E Cr} doing. The binarization processing unit 65 converts the pixels of the background 100 in FIG. 4A to black pixels and converts the pixels of the vehicle 101 to white pixels based on the average value _ECr . In this way, when the background color and the subject color are different, there is a high possibility that a binary image in which the subject is appropriately extracted by (Section 3) is obtained.

However, in (Category 1) to (Category 3), for example, when various colors are mixed in the background, the average value _ECr or the like is not set appropriately, and the subject has the same color (black and white) as the background. There is a risk of binarization.

FIG. 5 is an example of a histogram of a Cr plane image when various colors are mixed in the background. A distribution 202 illustrated in FIG. 5 is a distribution of color difference information Cr related to the background, and spreads over the entire histogram. A distribution 203 illustrated in FIG. 5 is a distribution of color difference information Cr related to a subject (for example, the vehicle 101 in FIG. 4A), and is confused (embedded) in the distribution 202. In Figure 5, since the different colors are mixed in the background, the distribution 203 will be set on the left side of the average value E _Cr, subject from being binarized to black pixels. (Category 4) and (Category 5) described below reduce the occurrence of a situation where the subject is not appropriately binarized due to the influence of the background color as shown in FIG.

-(Category 4)-
The binarization of the image by (Category 4) will be described. In binarization using (Category 4), the YCbCr image is binarized. In binarization using (Category 4), the range of hues to be converted into white pixels is specified by specifying the range of color difference information Cb and color difference information Cr. The hue range is set on a hue circle as shown in FIG. A hue circle 300 illustrated in FIG. 6 represents a YCbCr color space, and is a perfect circle having a predetermined radius and centering on the center 301. By specifying the color difference information Cb and the color difference information Cr, it is possible to specify a predetermined hue and saturation color shown in the hue circle 300. FIG. 6 shows the approximate positions of the red, yellow, and purple hues on the hue ring 300.

  FIG. 7 is a diagram illustrating an example of a hue range set in the YCbCr color space. In FIG. 7, in order to make the drawing easy to see, the hue ring 300 is illustrated by a white circle. FIG. 7 illustrates a first straight line 311 and a second straight line 312 that pass through the origin of the YCrCb color space (the center 301 of the hue ring 300). The inclination a of the first straight line 311 and the inclination b of the second straight line 312 are different from each other.

The hatched area in FIG. 7 illustrates the hue range 320 set by the binarization processing unit 65 using (Section 4). The hue range 320 is a range that satisfies the following conditional expression [4] in a closed region surrounded by the first straight line 311, the second straight line 312, and the outer periphery of the hue ring 300. Here, the coefficient k1 = a and the coefficient k2 = 1 / b. a and b are inclinations of the first straight line 311 and the second straight line 312, respectively.
Cb-Cr * k1> 0 and Cr-Cb * k2> 0 ... [4]

  The binarization processing unit 65 converts a pixel in which the color difference information Cr corresponding to the pixel and the color difference information Cb corresponding to the pixel satisfy the conditional expression [4] among the pixels of the YCbCr image into a white pixel, A pixel that does not satisfy the conditional expression [4] is converted into a black pixel. The binary image generated by the binarization processing unit 65 using (Section 4) is referred to as a fourth binary image B4.

  When binarizing a YCbCr image using (Category 4), if the coefficient k1 and the coefficient k2 are appropriately selected, the subject distribution 203 is mixed in the background distribution 202 as shown in FIG. Even so, only pixels having a hue (for example, bluish purple, purple, magenta, etc. in FIG. 5) that substantially matches the hue corresponding to the distribution 203 (purple in FIG. 5) are converted to white pixels. Can do.

  A plurality of combinations of the coefficient k1 and the coefficient k2 are stored as setting parameters in the nonvolatile memory 9, and a combination of the coefficient k1 and the coefficient k2 used by the CPU 8 is designated. The image processing unit 6 uses the coefficient k1 and the coefficient k2 specified by the CPU 8. The nonvolatile memory 9 includes a range of hues that are rare in nature (for example, bluish purple, purple, magenta, etc.) and a range of hues that are easily confused in the background of nature (for example, yellowish orange, yellow, etc.) The coefficient k1 and the coefficient k2 for designating the color of the green color of the stems and leaves that can be seen) are stored.

-(Category 5)-
The binarization of the image by (Category 5) will be described. In binarization using (Category 5), the YCbCr image is binarized. In binarization using (Category 5), the range of hue and saturation to be converted into white pixels is specified using the color difference information Cb and the color difference information Cr. The range of hue and saturation is set on the hue circle 300 of FIG. 7 in the same manner as (Category 4).

  When the binarization processing unit 65 binarizes the YCbCr image using (Section 5), the binarization processing unit 65 sets a range of hue and saturation on the hue ring 300 representing the YCbCr color space. FIG. 8 is a diagram illustrating an example of hue and saturation ranges set on the hue circle 300.

  FIG. 8 shows the first straight line 311 and the second straight line 312 that pass through the origin of the YCbCr color space (center 301 of the hue ring 300), and the origin of the YCbCr color space (center 301 of the hue ring 300) as the center of the circle. A perfect circle 313 is shown. The first straight line 311 and the second straight line 312 are the same as those described in (Category 4), and are used to set the hue range. The perfect circle 313 is used to set a saturation range. The radius T of the perfect circle 313 is set to be equal to or less than the radius of the hue circle 300.

The hatched area in FIG. 8 illustrates the hue and saturation range 321 set by the binarization processing unit 65 using (Section 5). The hue and saturation range 321 is a closed region surrounded by the first straight line 311, the second straight line 312, the perfect circle 313, and the outer periphery of the hue ring 300, and satisfies the following conditional expression [5]. . Here, the coefficient k1 = a and the coefficient k2 = 1 / b. a and b are inclinations of the first straight line 311 and the second straight line 312, respectively.
Cb-Cr × k1> 0 and Cr-Cb × k2> 0 and Cb ² + Cr ² ≧ T
... [5]

  The binarization processing unit 65 converts a pixel in which the color difference information Cr corresponding to the pixel and the color difference information Cb corresponding to the pixel satisfy the conditional expression [5] among the pixels of the YCbCr image into a white pixel, A pixel that does not satisfy the conditional expression [5] is converted to a black pixel. A binary image generated by the binarization processing unit 65 using (Section 5) is referred to as a fifth binary image B5.

  The radius T used as a threshold value for determining the saturation range is designated by the CPU 8. The image processing unit 6 uses the coefficient k1, the coefficient k2, and the radius T (threshold value T) specified by the CPU 8.

  The radius T (threshold value T) is stored in the nonvolatile memory 9 as a setting parameter together with a combination of the coefficient k1 and the coefficient k2. The value of the radius T (threshold value T) is set for each combination of the coefficient k1 and the coefficient k2 (that is, for each predetermined hue range). For example, in the case of a hue range that is rare in nature (for example, bluish purple, purple, magenta, etc.), the range is set to a value that is about 20% to 30% of the radius of the hue circle 300, , Yellowish orange, yellow, etc., which are often found in the color of the flower and are easily confused with the green color of the stem and leaves), the value is set to about 70% of the radius of the hue ring 300.

-Processing of the category evaluation unit 64-
The processing of the category evaluation unit 64 will be described with reference to FIG. FIG. 9 illustrates a flowchart relating to the processing of the category evaluation unit 64. The binarization image generated by the binarization processing unit 65 is input to the category evaluation unit 64.

  In step S660, the category evaluation unit 64 executes a process called a labeling process. The labeling process is to extract a group of white pixels (white pixel block) from the input binary image and give identification information called a label to the white pixel block. The classification evaluation unit 64 gives different labels to the white pixel blocks separated in the binary image by the labeling process.

  In step S661, the classification evaluation unit 64 calculates the area of each white pixel block labeled in step S660. For example, the number of white pixels constituting each white pixel block is calculated, and this is used as the area.

  In step S662, the classification evaluation unit 64 calculates the moment of inertia of the binary image (the moment of inertia around the centroid of the white pixel) around the centroid of the white pixel. For example, the classification evaluation unit 64 calculates, for each pixel of the binary image, a product obtained by multiplying the binary value (0 or 1) of the pixel and the square of the distance from the center of gravity of the white pixel to the pixel. Then, the sum of the products calculated for each pixel is calculated as the moment of inertia around the center of gravity of the white pixel.

In step S663, the classification evaluation unit 64, for each white pixel block labeled in step S660, is based on the area of the white pixel block calculated in step S661 and the moment of inertia around the center of gravity of the white pixel calculated in step S662. The first evaluation value is calculated by the following equation [6].
First evaluation value = area of white pixel block / moment of inertia around the center of gravity of the white pixel [6]

  In step S664, the segment evaluation unit 64 calculates a second evaluation value related to the segment when the input binary image is generated based on the first evaluation value calculated for each white pixel block in step S663. For example, the maximum value of the first evaluation value calculated for each white pixel block in step S663 is set as the second evaluation value related to the classification.

―Image preparation operation―
FIG. 10 is an example of a flowchart regarding an imaging preparation operation of the digital camera 1 executed by a CPU 8 using FIG. The imaging preparation operation illustrated in FIG. 11 is started when the release switch included in the operation member 12 is pushed down to about half of the normal stroke.

  In step S801, the CPU 8 controls the imaging device 4, the A / D conversion unit 5, and the debayer processing unit 60 of the image processing unit 6 to generate an RGB image related to the subject image. In step S802, the CPU 8 controls the luminance signal generation unit 62 and the color difference signal generation unit 63 of the image processing unit 6 to generate luminance information Y and color difference information Cb and Cr for each pixel of the RGB image. Thereby, the RGB image related to the subject image is converted into the YCbCr image related to the subject image.

  In step S803, the CPU 8 controls the binarization processing unit 65 of the image processing unit 6, and the fourth binary image B4 (binary image generated by the binarization processing unit 65 using the section (4)). And a fifth binary image B5 (a binary image generated by the binarization processing unit 65 using the section (5)). The CPU 8 controls the binarization processing unit 65 of the image processing unit 6 by designating the combination of the coefficient k1 and the coefficient k2 stored in the nonvolatile memory 9 and the threshold value T corresponding to the combination.

  In step S804, the CPU 8 controls the segment evaluation unit 64 of the image processing unit 6, and based on the fourth binary image B4 and the fifth binary image B5 generated in step S803 (category 4) and (category 5). ) For the second evaluation value (FIG. 9).

  In step S805, the CPU 8 determines whether or not at least one of the second evaluation value related to (section 4) and the second evaluation value related to (section 5) calculated in step S804 is greater than or equal to a predetermined value. If a positive determination is made in step S805, the process proceeds to step S806, and if a negative determination is made, the process proceeds to step S807.

  In step S806, the CPU 8 extracts a white pixel block as a subject candidate from white pixel blocks included in the binary image generated using the classification determined to be equal to or greater than the predetermined value in step S805. For example, a white pixel block having a first evaluation value equal to or greater than a predetermined value is extracted as a subject candidate. In step S805, if the second evaluation values of (Category 4) and (Category 5) are both equal to or greater than the predetermined value, the second evaluation values are compared with each other, and the white pixel block of any division is selected as the subject candidate. It may be determined whether or not.

  In step S807, the CPU 8 controls the binarization processing unit 65 of the image processing unit 6 to generate the first binary image B1 and the complement image B10 (the binarization processing unit 65 uses the section (1)). ) And second binary image B2 (binary image generated by binarization processing unit 65 using section (2)) and third binary image B3 (binarization processing unit 65 uses section (3)). To generate a binary image).

  In step S808, the CPU 8 controls the segment evaluation unit 64 of the image processing unit 6 to generate the first binary image B1, the second binary image B2, the third binary image B3, and the complement image B10 generated in step S807. Based on the above, the second evaluation values related to (Category 1) to (Category 3) are calculated (FIG. 9).

  In step S809, the CPU 8 extracts a white pixel block as a subject candidate from white pixel blocks included in the first binary image B1, the second binary image B2, and the third binary image B3. For example, the CPU 8 performs prioritization (for example, ascending order of the second evaluation value) of (Category 1) to (Category 3) based on the second evaluation value calculated in Step S808. Then, the CPU 8 extracts a white pixel block having a first evaluation value greater than or equal to a predetermined value as a subject candidate from the binary image generated using the category with the highest priority.

  In step S810, the CPU 8 sets an AF area for the subject candidate extracted in step S806 or step S809, and executes AF processing.

According to the embodiment described above, the following operational effects can be obtained.
The digital camera 1 according to the present invention includes an image sensor 4 that captures a subject image and outputs a captured image, a color difference signal generation unit 63 that generates color difference information Cb and color difference information Cr for each pixel of the captured image, and color difference information. A category evaluation unit 64, a binarization processing unit 65, and a subject candidate extraction unit 66 that specify a predetermined range of Cb and Cr and extract subject candidates having a hue within a predetermined range (hue range 320 in FIG. 7). With. By having such a configuration, it is possible to appropriately extract a subject having a hue within a predetermined range.

The embodiment described above can be implemented with the following modifications.
(Modification 1) The arrangement of the imaging pixels on the imaging surface 4a is not limited to the Bayer arrangement.
(Modification 2) The process of step S807 in FIG. 10 may be performed in parallel with the process of step S803.

(Modification 3) The values of the coefficients k1 and k2 may be set to different values for each white balance gain of the white balance unit 61. Different coefficients k1 and k2 are stored in the non-volatile memory 9 for each white balance gain of the white balance unit, and the CPU 8 may read them based on the settings of the white balance unit 61.

(Modification 4) The coefficients k1 and k2 and the predetermined threshold T may be set by the user. FIG. 11 is an example of a setting input screen for the user displayed on the display unit 10 to set the coefficients k1 and k2 and the predetermined threshold T. In the setting input screen 900 of FIG. 11, the hue circle 300, the first line segment display 901 for setting the coefficient k1, the second line segment display 902 for setting the coefficient k2, and the threshold T are set. A circle display 903 is displayed. The first line segment display 901 and the second line segment display 902 are line segments from the center 301 of the hue ring 300 to the outer periphery of the hue ring 300. The inclination of the first line segment display 901 and the second line segment display 902 can be set by the user via the operation switch 122. The center of the circle display 903 coincides with the center 301 of the hue ring 300. The radius of the circle display 903 can be set by the user via the operation switch 122.

  For example, the CPU 8 stores the inclination a of the first line segment display 901 in the nonvolatile memory 9 as the coefficient k1. Further, the CPU 8 stores the reciprocal of the slope b of the second line segment display 902 in the nonvolatile memory 9 as a coefficient k2. The CPU 8 determines a threshold value T based on the radius of the circle display 903 and stores it in the nonvolatile memory 9.

  A selection area 904 surrounded by the first line segment display 901, the second line segment display 902, the circle display 903, and the outer periphery of the hue ring 300 is a range of hue and saturation selected by the user. Color pixels in the selection area 904 are converted into white pixels by binarization using (Section 5) by the binarization processing unit 65. Note that the selection area 904 may be displayed in a different display mode from the other areas of the color wheel 300. For example, a display mode in which only the selection area 904 is blinked can be implemented.

(Modification 5) Color difference information Cg based on G-Y may be used in place of either the color difference information Cb or the color difference information Cr.
(Modification 6) In (Category 4) and (Category 5), a pixel satisfying conditional expression [4] or conditional expression [5] is converted into a black pixel, and conditional expression [4] or conditional expression [5] is changed to Unsatisfied pixels may be converted into white pixels.

  The embodiments and modifications described above are merely examples, and the present invention is not limited to these contents as long as the features of the invention are not impaired. Further, the embodiments and modifications described above may be combined and executed as long as the features of the invention are not impaired.

DESCRIPTION OF SYMBOLS 1 Digital camera 2 Shooting lens 3 Lens drive part 4 Image sensor 5 A / D conversion part 6 Image processing part 7 Memory 8 CPU
9 Non-volatile memory 10 Display unit 11 Recording / playback unit 60 Debayer processing unit 61 White balance unit 62 Luminance signal generation unit 63 Color difference signal generation unit 64 Classification evaluation unit 65 Binarization processing unit 66 Subject candidate extraction unit 300 Hue ring 320 Range 321 Hue and saturation range

Claims (8)

An imaging device that images a subject via a lens used for focus adjustment,
A first extraction unit that extracts a plurality of first subjects included in the subject based on hue information and saturation information;
A second extraction unit for extracting a second subject from the plurality of first subjects based on the area information of the first subject and the moment of inertia information of the first subject extracted by the first extraction unit;
A control unit that moves the lens so as to focus on the second subject extracted by the second extraction unit;
The first extraction unit uses the specific hue information and saturation information specified from the plurality of hue information and saturation information for extracting the first subject stored in advance in the storage unit, based on the specific hue information and saturation information. An imaging device that extracts a subject . The imaging device according to claim 1,
The first extraction unit is an image pickup apparatus that extracts the plurality of first subjects based on purple hue information from the plurality of hue information and saturation information for extracting the first subject stored in advance in a storage unit. In the imaging device according to claim 1 or 2,
The first extraction unit is configured to extract the plurality of first subjects from the plurality of hue information and saturation information for extracting the first subject stored in advance in the storage unit based on bluish violet hue information. . In the imaging device according to any one of claims 1 to 3,
The first extraction unit is configured to extract the plurality of first subjects from the plurality of hue information and saturation information for extracting the first subject stored in advance in the storage unit based on magenta hue information. . In the imaging device according to any one of claims 1 to 4,
The first extraction unit is an imaging device that extracts the plurality of first subjects based on yellow hue information from the plurality of hue information and saturation information for extracting the first subject stored in advance in a storage unit. In the imaging device according to any one of claims 1 to 5,
The first extraction unit is an imaging device that extracts the plurality of first subjects from the plurality of hue information and saturation information for extracting the first subject stored in advance in a storage unit based on orange hue information. In the imaging device according to any one of claims 1 to 6,
The specific hue information and saturation information are specified based on a set white balance setting value. In the imaging device according to any one of claims 1 to 6,
A display unit for displaying a hue circle composed of hue and saturation;
The image pickup apparatus, wherein the specific hue information and saturation information are hue information and saturation information set using a hue circle displayed on the display unit.

Images