KR101634246B1 - Method for providing standing out degree information of subject and digital photographing apparatus applying the method - Google Patents

Abstract

BACKGROUND OF THE INVENTION 1. Field of the Invention [0002] The present invention relates to a method for providing subject incidence information and a digital photographing apparatus for the same, and more particularly to a technique for providing a degree of incidence of a subject through contrast information of hue, . The present invention relates to a method and an apparatus for determining an object, which is an object focused on an input image, Setting an object area containing the subject and setting at least one peripheral area for confirming the incidence information of the object area around the object area; Deriving contrast information of hue, saturation, and brightness of the subject area and the surrounding area; Deriving edge information of the peripheral region; Deriving incidence information of the subject included in the subject area based on the contrast information or the edge information; And displaying the derived incidence information of the subject on a display unit; .

Subject Depth

Description

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a method for providing subject incidence information and a digital photographing apparatus for the same,

BACKGROUND OF THE INVENTION 1. Field of the Invention [0002] The present invention relates to a method for providing subject incidence information and a digital photographing apparatus for the same, and more particularly to a technique for providing incidence information of a subject through contrast information of hue, .

A variety of shooting techniques are used to highlight the subject when shooting with the digital imaging device. In the case of a digital single-lens reflex camera (DSLR), an out-focusing method is mainly used in which an iris is opened to focus on a subject in order to emphasize the subject.

In addition, by using a technique of separating a subject and a background from image data acquired in a digital photographing apparatus as disclosed in Japanese Patent Application Laid-Open No. 2009-069996 and then blurring the background to emphasize the subject, It removes the background and emphasizes the subject.

However, in the case of digital single lens reflex camera (DSLR), it is possible to use out-focusing mechanism mechanically, but in case of digital still camera (DSC), it is difficult to expect out-focusing effect of lens structure.

Also, when the background blur is applied through the image processing to emphasize the subject, there is a problem that the subject and the area close to the background appear unnatural.

However, it can be applied to all digital photographing apparatuses, and there are the following methods for achieving the purpose of emphasizing the object naturally. For example, when the subject is photographed with a large contrast between color and saturation and brightness between the subject and the background, or when the subject is photographed in a simple background, the subject can be photographed without using the out-focusing technique or image processing.

FIGS. 1 to 3 are views showing how much the subject can be displayed according to the degree of contrast between the subject and the surrounding area and the edge of the surrounding area.

Referring to FIG. 1 to FIG. 3, it can be seen that the object shown in FIG. 1 is more emphasized than in FIG. 1 (a), which is photographed with a simple background with a small edge, and FIG. In the case of FIG. 2, the subject is highlighted compared to (b) in which the contrast of contrast is large (a) and the contrast of contrast is small. In the case of FIG. 3, the object is highlighted compared to (a) where contrast of color and saturation is large (b) and contrast of color and saturation is small.

That is, if there is a large visual contrast between the background and the subject, attention can be focused on the subject. In addition, if the background is complex, attention is dispersed to the background rather than focusing on the subject, so that the subject can be highlighted by shooting in a simple background.

The present invention relates to a method of providing subject incidence information and a digital photographing apparatus for the same, and more particularly, to a digital photographing apparatus for providing incidence information of a subject to a user in consideration of contrast information of color, saturation and brightness between a subject and a background, And guiding the user to the shooting composition.

According to an aspect of the present invention, there is provided an image processing method including the steps of: determining a subject that is a focused object with respect to an input image; Setting an object area containing the subject and setting at least one peripheral area for confirming the incidence information of the object area around the object area; Deriving contrast information of hue, saturation, and brightness of the subject area and the surrounding area; Deriving edge information of the peripheral region; Deriving incidence information of the subject included in the subject area based on the contrast information or the edge information; And displaying the derived incidence information of the subject on a display unit; The method comprising the steps of: (a) acquiring image information of a subject;

The step of deriving the contrast information may include converting an image of the subject area and an image of the peripheral area into an image of a gray level of color, brightness, and saturation channel mode; Deriving a histogram image for each color, brightness, and saturation channel for the converted image; Deriving a representative level value for the derived histogram of the color, brightness and saturation channel; And obtaining contrast information by comparing a representative level value of the peripheral region with a representative level value of the subject region by the hue, brightness, and saturation channels; . ≪ / RTI >

The step of deriving the edge information may include converting an image of the peripheral region into an image of a gray-level color, brightness, and saturation mode; Creating an edge map for any one of color, brightness or saturation of the converted image; Reconstructing the edge map by binarizing the generated edge map with a pixel having a brightness equal to or higher than a reference value and a pixel having a brightness lower than the reference value; And determining edge information corresponding to the number of pixels having brightness equal to or greater than a reference value indicated in the reconstructed edge map; . ≪ / RTI >

The peripheral area and the subject area may be polygonal, and eight peripheral areas may be set in the horizontal, vertical, and diagonal directions with respect to the subject area.

Here, in deriving the incidence information of the subject, the contrast information or the edge information may be compared with the reference information to derive the subject incidence information.

According to another aspect of the present invention, there is provided an image processing apparatus including: an area setting unit that sets a subject area including a subject focused on an input image and sets at least one peripheral area around the subject area; A contrast information deriving unit for deriving contrast information of hue, saturation, and brightness of the subject area and the surrounding area; An edge information deriving unit for deriving edge information of the surrounding area; An object incidence information deriving unit for deriving incidence information of the object included in the object area based on the contrast information or the edge information; And the like.

Here, the contrast information deriving unit may include a mode converter for converting an image of the subject area and an image of the surrounding area into an image of a gray-level color, brightness, and saturation mode; A histogram generation unit for deriving a histogram image for each color, brightness, and saturation channel for the converted image; A representative level value deriving unit for deriving a representative level value for the derived histogram for each color, brightness and saturation channel; And a contrast unit for obtaining contrast information by comparing a representative level value of the peripheral region with a representative level value of the subject region for each of the hue, brightness, and saturation channels. . ≪ / RTI >

Here, the edge information deriving unit may include a mode converter for converting the image of the peripheral area into an image of a gray level of color, brightness, and saturation channel mode; An edge map creating unit for creating an edge map for any one of color, brightness or saturation of the converted image; An edge map binarizer for reconstructing the edge map by binarizing the generated edge map with a pixel having a brightness equal to or higher than a reference value and a pixel having a brightness lower than the reference value; And an edge check unit for checking edge information corresponding to the number of pixels having brightness equal to or greater than a reference value indicated in the reconstructed edge map; . ≪ / RTI >

Here, the subject incidence information derivation unit may derive the subject incidence information by comparing the contrast information or the edge information with the reference information.

A display control unit for controlling the display unit to display the incidence information of the object derived therefrom; As shown in FIG.

Other aspects, features, and advantages will become apparent from the following drawings, claims, and detailed description of the invention.

According to the embodiment of the present invention, there is an effect that the user can guide the photographing composition setting by providing the incidence information of the subject.

In addition, the user can take an image of the subject by emphasizing the degree of the provided subject by referring to the level of the provided subject, thereby obtaining the image to be obtained by the user with a small number of attempts.

A digital camera will be described as an embodiment of the digital photographing apparatus according to the present invention. However, the digital photographing apparatus is not limited to a digital camera, and can be applied to a digital apparatus such as a digital picture signal processing unit, a camera phone equipped with an image pickup unit, and a digital camera such as a video camera.

4 is a block diagram illustrating the configuration of a digital camera according to an exemplary embodiment of the present invention.

A digital camera according to an embodiment of the present invention includes an imaging unit 10, an operation unit 20, a program storage unit 30, a buffer storage unit 40, a data storage unit 50, a display unit 60, And a digital signal processing unit (DSP) 100.

The imaging section 10 provides the input optical signal from the subject to the imaging element via the optical section. The optical unit may include at least one lens such as a zoom lens and a focus lens. In addition, the optical unit may further include a diaphragm for adjusting the amount of light. The imaging device can be a CCD (Charge Coupled Device) or a CIS (Complementary Metal Oxide Semiconductor Image Sensor) that converts an optical signal into an electric signal by forming an image of a subject by reaching an optical signal transmitted through the optical portion .

The operation unit 20 is a place where a control signal from the outside of a user or the like can be input. The operation unit 20 includes a shutter-release button for inputting a shutter-release signal for exposing an image pickup device to light for a predetermined period of time, a power button for inputting power, There are various function buttons such as a wide angle-zoom button and a telephoto-zoom button for narrowing the angle of view, a mode selection of a character input mode, a shooting mode, a playback mode, a white balance setting function, and an exposure setting function selection. The operation unit 20 may have various types of buttons as described above, but the present invention is not limited thereto. The operation unit 20 may be implemented in any form such as a keyboard, a touch pad, a touch screen, and a remote controller.

The digital camera includes a program storage unit 30 for storing programs such as an operating system and an application system for driving the digital camera, a buffer storage unit 40 for temporarily storing data or result data necessary for performing an operation, And a data storage unit 50 for storing various information including an image file including a video signal and reference information for deriving the subject incidence information of the present invention.

The display unit 60 displays the operation state of the digital camera or the captured image information. The display unit 60 can provide visual information and / or auditory information to a user. The display unit 60 may include a liquid crystal display panel (LCD), an organic light emitting display panel (OLED), an electrophoretic display panel (EDD), or the like to provide visual information.

The digital camera includes a DSP 100 that processes input image signals and controls each of the components according to an external input signal.

In one embodiment of the present invention, providing the user with the incidence information of the subject can be performed in the DSP 100. [

4, the DSP 100 according to an exemplary embodiment of the present invention includes an area setting unit 110, a contrast information deriving unit 120, an edge information deriving unit 130, and a subject incidence information deriving unit 140 .

The area setting unit 110 sets the subject area and the surrounding area with respect to the input image received from the image pickup device. The subject area is an area including a subject to which the user intends to focus. The peripheral area is an area including the background around the subject and may be set to a predetermined number around the subject area.

 Here, the subject area and the surrounding area may be set as blocks of a predetermined size and shape, and may be set as blocks of 32x32 and 64x64 pixels, for example. Also, the area setting unit 110 may determine a subject area and a surrounding area using a mask, a kernel, and a window. For example, as shown in FIGS. 9, 13, 17, and 21, the square block corresponding to the subject area is located at the center, and the surrounding area is set as eight square blocks in the horizontal, vertical and diagonal directions of the subject area .

The contrast information deriving unit 120 derives information regarding the color, saturation, and brightness of the image included in the subject area and the image included in the surrounding area. Such contrast information makes it possible to check the contrast of the image of the subject area with respect to the surrounding area, by color, saturation, and brightness. In one embodiment, a representative level value in the histogram of the H (Hue), Saturation and Intensity (I) intensity channels of the subject area and a representative value in the histogram of the color, A value obtained by comparing a level value for each channel can be used as contrast information. The detailed configuration of the contrast information deriving unit 120 will be described in detail with reference to FIG.

The edge information deriving unit 130 derives edge information to check how complicated the image included in the surrounding area is. For example, an edge map is generated by detecting an edge of a surrounding area, and then an edge map is rewritten by binarizing a pixel having a brightness equal to or higher than a predetermined reference value and a pixel having a brightness lower than the reference value. The number of pixels having brightness equal to or larger than the reference value indicated in the rewritten edge map is confirmed. In one embodiment, the edge information may be the number of pixels having brightness equal to or greater than the reference value of the peripheral region thus obtained. The detailed configuration of the edge information deriving unit 130 will be described in detail with reference to FIG.

The object incidence information deriving unit 140 derives the incidence information of the object through the contrast information of the area obtained by the contrast information deriving unit 120 and the edge information of the surrounding area obtained by the edge information deriving unit 130. [ Here, the incidence information of the subject can be derived using only one of the contrast information and the edge information.

 The incidence information of the subject can be derived by comparing the reference information with the contrast information or the edge information. The reference information may be a table including contents corresponding to the subject incidence information of a predetermined numerical value with respect to the specific contrast information and content corresponding to the subject incidence information of the predetermined numerical value with respect to the specific edge information. Such a correspondence relationship may also be composed of an application program or an algorithm.

When deriving the subject incidence information, the contrast information or the edge information may be weighted according to the user's selection. For example, when it is considered that the contrast information greatly affects the incidence of the subject, the subject incidence information derivation unit 140 can derive the incidence information of the subject by weighting the contrast information by 1.5 or 2 times.

The subject incidence information obtained by the subject incidence information deriving unit 140 may be represented by a numerical value or may be represented by a step value such as a strong-moderate-strong. It may also be displayed as subject matter accent / no.

In addition, the DSP 100 may further include a display control unit (not shown). The subject incidence information can be displayed on the display unit 60 so that the user can visually and audibly recognize the subject in the photographing mode under the control of the display control unit.

The contrast information deriving unit 120 and the edge information deriving unit 130 will be described in detail with reference to FIG. 5 and FIG.

FIG. 5 is a block diagram showing a concrete information deriving unit 120 according to an embodiment of the present invention.

Referring to FIG. 5, the first information derivation unit 120 may include a mode conversion unit 121, a histogram generation unit 122, a representative level value derivation unit 123, and a contrast unit 124.

The mode conversion unit 121 converts the subject area and the surrounding area expressed in the RGB mode into a HSI (Hue, Saturation, Intensity) mode having a gray level color channel, a saturation channel, and a brightness channel. Equation (1) is a formula for calculating brightness (I) from RGB mode, Equation (2) is a formula for calculating saturation from RGB mode and Equation (3) ).

The color coordinates in the converted HSI mode can be represented by an I-channel in the vertical direction and an S-channel and H-channel on the circular plane, as shown in FIG.

In FIG. 7, the change in intensity from white to black can be known according to the height value of the I channel, and the purity of the color can be determined according to the length of the radius in the circular plane of the S channel. Also, you can see colors such as red, yellow, blue, and green depending on the angle in the circular plane of the H channel.

The color coordinates of FIG. 7 indicate the range of intensity and color purity in the range of 0.0 to 1.0 for the I-channel and S-channel, and the range of the color for the H-channel in the range of 0 to 360 degrees. For example, when comparing the color, saturation, and brightness information of two pixels, the larger the difference between the channel values of the two pixels, the greater the contrast. In the S channel, the larger the sum of the channel values of the two pixels, Big. Also, in the case of the H channel, the color contrast is large when the angle of the channel value of the two pixels is close to 180 degrees. If the color coordinates of FIG. 7 are sampled at the gray level, the size and the angle can be expressed in 256 steps having a range value of 0 to 255. In this case, the larger the difference between the channel values of the two pixels is, the larger the contrast is, and the larger the sum of the channel values of the two pixels of the S channel, the greater the chroma contrast. Also, in the case of the H channel, when the difference between the channel values of two pixels is close to 128, the color contrast is large.

Based on the properties of the gray level HSI mode color coordinates, the color, brightness, and saturation contrast information of the subject area and the surrounding area can be grasped.

The histogram generation unit 122 derives a histogram image for each color, saturation, and brightness channel for the subject area and the surrounding area which are converted into the gray level HSI mode.

In general, a histogram shows the distribution of brightness values for pixels in an image. When a bright pixel and a dark pixel are distributed, the range and value are expressed. A histogram is referred to as a histogram graph or a histogram image. For example, in a 256 gray level image, the brightness value ranges from 0 to 255, and each brightness value, that is, the frequency of the level, is represented by the height of the graph. The histogram has a lot of image information and is used for various image processing. Also, in a preferred embodiment of the present invention, the contrast information of the subject area with respect to the surrounding area can be known by analyzing the histogram.

The representative level value extracting unit 123 derives a representative level value for the generated histogram. And a representative value for deriving the contrast of the subject area with respect to the surrounding area for each channel.

There are various methods for determining the representative level value. For example, the representative level value may designate a level value corresponding to the maximum peak of the histogram image, or may specify a level value corresponding to the average pixel frequency when it is difficult to determine the peak.

The contrast unit 124 compares the representative level value for each channel of the subject area with the representative level value for each channel of the surrounding area to derive the difference of the representative level value for each of the H, S, and I channels.

The contrast unit 124 integrates the differences of the representative level values for each channel and provides the information to the object incidence information derivation unit 140 so that the subject incidence information can be obtained by using the contrast information of the color of the subject area and the surrounding area, .

7 is a block diagram showing the edge information deriving unit 130 according to an embodiment of the present invention in more detail.

7, the edge information derivation unit 130 may include a mode conversion unit 131, an edge map generation unit 132, an edge map binarization unit 133, and an edge verification unit 134.

The mode conversion unit 131 converts the image of the peripheral area represented by the RGB mode into the HSI mode. Preferably, the image of the peripheral region can be converted into the gray level HSI mode. Since the details are described in the mode conversion unit 121 of FIG. 5, it is omitted.

The edge map creating unit 132 creates an edge map by displaying pixels including edge components from the image of the I channel of the peripheral region converted from the gray level HSI mode in the mode conversion unit 131. [ Here, the image for creating the edge map is not limited to the image of the I channel, and an edge map may be created from the image of the H channel or the S channel.

In an image, an edge represents the boundary of an area within an image and represents a discontinuity in pixel brightness. In other words, the brightness difference appears between the boundary of the object and the background. This corresponds to the outline of the object and gives a lot of information such as position, shape and size of the object. Detecting a pixel corresponding to an edge is referred to as edge detection, and an image represented by the detected edges is referred to as an edge map. In order to detect the edge, it is mathematically performed by partial differential operator calculation. The magnitude of the first derivative value indicates the presence or absence of an edge in the image, and the sign of the second derivative value indicates the position of the bright and dark portion of the pixel. For example, edge pixels can be detected using a Laplacian 3 × 3 mask. However, it goes without saying that edge pixels can be detected by using edge detection filters or other differential operators.

The edge map binarization unit 133 divides the pixels of the edge map into two groups and reconstructs the binarized edge map through the reference value. That is, in the edge map generated by the edge map creating unit 132, the pixel having the brightness equal to or higher than the reference value and the pixel having the brightness lower than the reference value are binarized. Then, the binarized edge map is rewritten to reflect this. For example, a pixel having a brightness higher than a reference value may be displayed in white, and a pixel having brightness lower than a reference value may be displayed in black to binarize the edge map. Through this process, only pixels whose edges are larger than the reference value can be selected. This process corresponds to a process of filtering a pixel representing an edge that can be ignored because the brightness is smaller than the reference value when deriving the edge information of the surrounding area.

Herein, the reference value is the brightness information of the pixel corresponding to the edge determined to have no significant influence on the complexity of the surrounding area in the process of determining the complexity of the surrounding area, and is a value that can be arbitrarily set.

The edge identifying unit 134 obtains the edge information of the surrounding area by checking the number of pixels having the brightness of the reference value or more in the edge map binarizing unit 133. [ The edge identifying unit 134 provides the number of pixels corresponding to the edge information to the subject incidence information deriving unit 140 so that the subject incidence information can be grasped using the edge information.

8 is a flowchart for explaining an example of a method of providing incidence information of a subject in the digital photographing apparatus according to the present invention. To facilitate understanding of the present invention, Fig. 8 will be described with reference to Figs. 9 to 12. Fig. However, it should be noted that the present invention is not limited to the examples of Figs. 9 to 12, and can be variously modified.

Enters a shooting mode (S801), and a mode for providing subject incidence information is selected (S802)

Next, the subject is confirmed (S803). For example, in the shooting mode, the subject that is in focus can be confirmed by pressing the shutter button halfway. In addition, in the face detection or motion detection mode, the face or the motion object is focused, and the object can be determined as the object. In addition, by touching a desired object on the touch screen, it is possible to focus on a touched object and fix it as an object.

When the subject is determined, a subject area and a peripheral area, which is at least one area around the subject area, are set (S804)

Referring to FIG. 9, since a face of a person is determined as a subject, one block including a face is set as a subject area. The peripheral area is an area for comparing the incidence of the subject area, and a plurality of areas adjacent to the subject area can be set and can be arbitrarily set. In Fig. 9, two blocks to nine blocks correspond to the peripheral area, and a total of eight blocks are set in the horizontal, vertical, and diagonal directions around one block.

Next, contrast information on hue, saturation and brightness between the subject area and the surrounding area is derived. (S805)

Referring to FIG. 10, first, the subject area and the surrounding area expressed in the RGB mode are converted into the gray level HSI mode. The HSI mode is an image based on a value corresponding to a color, saturation, and brightness channel through HSI color coordinates, and can be changed through a known equation. In FIG. 10, the HSI mode of the gray level is shown. Here, the gray level is expressed by sampling each channel from 0 to 255 in the HSI color coordinates.

Next, as shown in FIG. 11, a histogram image for each color H, chroma S, and brightness I channels of the mode-converted image is generated. Then, a representative level value for the histogram image for each channel is derived. For example, in the case of the S channel of block 1 in FIG. 11, the brightness level corresponding to the maximum peak value can be set as the representative level value. In the case of the I channel of the first block, the brightness level corresponding to the average pixel frequency can be set as the representative level value. As described above, a representative level value is set for each histogram image for each channel for the subject area and the surrounding area, which are shown in FIG.

Next, the representative level value derived from the subject area (block 1) is compared with the representative level value derived from the plurality of peripheral areas (blocks 2 to 9). Thus, the difference value between the representative level values of the subject area and the surrounding area for each channel can be used as the contrast information.

The process of obtaining the contrast information will be described with reference to FIG. The representative level value of one block of the H channel is compared with the representative level value of the two blocks to obtain the difference of the level values and the representative level value of one block of the H channel is compared with the representative level value of the three blocks, This process is repeated in which the subject area and the surrounding area are prepared for each channel. When comparing a plurality of peripheral areas with respect to the subject area, a value obtained by averaging a plurality of representative level value differences obtained by repeatedly comparing the representative level value of the subject area with the representative level values of the plurality of peripheral areas as described above is referred to as contrast information can do. However, in another embodiment, one peripheral region may be derived by using any of the peripheral regions, and the difference value obtained by comparing the representative level value of the derived one peripheral region with the representative level value of the subject region may be used as the contrast information.

The edge information of the surrounding area is derived (S806)

First, the image of the peripheral region expressed in the RGB mode is converted into the HSI mode. Preferably, the image of the peripheral region can be converted into the gray level HSI mode.

Next, an edge map is created for the image expressed by any one of the color, saturation, or brightness channel among the converted images. Then, the pixels composing the edge map are binarized into pixels having a brightness equal to or higher than the reference value and pixels having a brightness lower than the reference value, and then the binarized edge map is rewritten. 12 shows the result of creating a binary edge map for the I-channel of the gray level of the peripheral area (blocks 2 to 9). Pixels with brightness less than the reference value for the gray level I channel edge map are expressed as black, and pixels having brightness above the reference value are represented as white.

Next, the number of pixels having brightness equal to or greater than the reference value in the binarized edge map is checked. The number of pixels thus obtained corresponds to the edge information. When there are a plurality of peripheral regions as shown in FIG. 12, the number of pixels having a certain brightness or more included in the peripheral region may be averaged to be the number of pixels corresponding to the edge information of the present invention. However, the present invention is not limited to this, and a value obtained by averaging the number of pixels having a certain brightness or more included in the selected peripheral region and selecting a plurality of peripheral regions may be used as the edge information.

The incidence information of the subject is derived through the contrast information and the edge information obtained in steps S805 and S806 (S807)

In one embodiment, the contrast information and the edge information are compared with the reference information to derive the incidence information of the subject. The reference information may be composed of a table. If the contrast information is within a certain reference information range, the degree of incidence of the subject is determined. If the edge information is within a predetermined reference information range, Or the like may be variously disclosed. The process of comparing the contrast information and the edge information with the reference information to derive the incidence information of the subject can be implemented by an application program or an algorithm.

For example, it is assumed that the difference of the brightness channel representative level values corresponding to the contrast information is 20, the difference of the representative level values of the saturation channel is 10, and the difference of the representative level values of the color channel is 2. It is also assumed that the number of pixels equal to or larger than the reference brightness value corresponding to the edge information is 200 pixels. In this case, when the difference of the representative level value in the reference information is 5 or less, it is assumed that the incidence of the subject is 20%, 5-15 is 40%, 15-25 is 60%, and the number of pixels is 150-250 Assume that the degree of incidence on Pisa is 30%. Therefore, in this case, the degree of incidence of the subject by the contrast information is 60% in lightness, 40% in saturation, 20% in color, and the incidence of the subject by edge information is 30%. Thus, the degree of appearance of the final subject can be derived using the average value of the information. However, the method of calculating the incidence degree of the subject in this manner is not limited to the above-described example, as long as it satisfies only the reference information.

When deriving the subject incidence information, the contrast information or the edge information of the area can be weighted. For example, if the contrast information of a region has a large effect on the degree of the incidence of the subject, the contrast information of the region may be weighted 1.5 or 2 times.

Finally, the incidence information of the subject is displayed on the display unit 60. (S808) The incidence information may be represented by a numerical value, or may be expressed in a phased language such as strong-moderate-weak.

The user can continue shooting with reference to the incidence information of the displayed subject. (S809) If the level of the subject is not the level desired by the user, the subject can be changed to a background having a large contrast of color, saturation or brightness, or a simple background having a small edge.

9 to 24 illustrate a specific embodiment of a method for providing subject incidence information according to the present invention, and FIG. 8 to FIG. 9 to FIG. 12 (hereinafter, the first embodiment) have been described in detail. 13 to 16 (hereinafter referred to as a second embodiment), Figs. 17 to 20 (hereinafter, third embodiment) and Figs. 21 to 24 (fourth embodiment) The process of finding the incidence information of the subject is the same. Therefore, the description of the process is omitted here and only the results are shown

FIGS. 9 to 12 illustrate a process of examining the degree of incidence of a subject in an image having a low contrast and a low complexity in a surrounding region, which is poor in color, lightness, and saturation contrast between a subject and a surrounding region.

FIGS. 13 to 16 illustrate a procedure of sequentially examining the degree of incidence of a subject in an image having a large edge due to a poor contrast of color, lightness, and saturation between the subject and the surrounding area and a high complexity of the surrounding area.

FIGS. 17 to 20 illustrate a process of examining the degree of appearance of a subject in an image with a good contrast in color, lightness, and saturation of a subject and a peripheral region and a low complexity in a peripheral region, according to a third embodiment.

FIGS. 21 to 24 illustrate the process of examining the incidence information of a subject in an image with a high edge and a high complexity of the surrounding area, which is good in color, brightness, and saturation contrast between the subject and the surrounding area.

It is possible to grasp the information of the incidence of the subject by combining the contrast information of the color of the subject area and the surrounding area and the edge information of the surrounding area obtained through the processes of the four embodiments as described above. At this time, the contrast information or the edge information is weighted so that the incidence information of the subject can be grasped.

For example, it is said that the edge information of the surrounding area has the greatest influence on the degree of the incidence of the subject. In this case, the edge information is weighted, and the image of the second embodiment or the fourth embodiment will have a remarkably low degree of incidence of the subject. If the degree of contrast between the subject area and the surrounding area is small, the degree of appearance of the subject is considered to be the worst. In this case, the contrast information is weighted, and the image of the first embodiment or the image of the second embodiment is calculated as a result that the incidence of the subject is remarkably low.

Meanwhile, the present invention can be embodied in computer readable code on a computer readable recording medium. A computer-readable recording medium includes all kinds of recording devices in which data that can be read by a computer system is stored.

Examples of the computer-readable recording medium include a ROM, a RAM, a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device and the like, and also a carrier wave (for example, transmission via the Internet) . In addition, the computer-readable recording medium may be distributed over network-connected computer systems so that computer readable codes can be stored and executed in a distributed manner. In addition, functional programs, codes, and code segments for implementing the present invention can be easily deduced by programmers skilled in the art to which the present invention belongs.

The present invention has been described above with reference to preferred embodiments. It will be understood by those skilled in the art that the present invention may be embodied in various other forms without departing from the spirit or essential characteristics thereof. Therefore, the above-described embodiments should be considered in an illustrative rather than a restrictive sense. The scope of the present invention is indicated by the appended claims rather than by the foregoing description, and all differences within the scope of equivalents thereof should be construed as being included in the present invention.

FIGS. 1 to 3 are views showing how much the subject can be emphasized according to the degree of contrast between the subject and the surrounding area and the complexity of the surrounding area.

4 is a block diagram showing an embodiment of a digital camera according to the present invention.

5 is a block diagram showing a part of the DSP of the digital camera shown in Fig.

Fig. 6 is an explanatory diagram showing the color coordinates of the HSI mode.

7 is a block diagram showing another part of the DSP of the digital camera shown in Fig.

8 is a flowchart showing a method of providing incidence information of a subject according to the present invention.

9 to 24 are explanatory diagrams showing specific embodiments of a method for providing subject incidence information according to the present invention.

Claims (10)

Determining an object whose focus is on the input image; Setting an object area containing the subject and setting at least one peripheral area for confirming the incidence information of the object area around the object area; Deriving contrast information of hue, saturation, and brightness of the subject area and the surrounding area; Deriving edge information of the peripheral region; Deriving incidence information of the subject included in the subject area based on the contrast information or the edge information; And And displaying the derived incidence information of the subject on a display unit, The step of deriving the edge information Converting an image of the peripheral region into an image of a gray level of color, brightness, and saturation mode; Creating an edge map for any one of color, brightness or saturation of the converted image; Reconstructing the edge map by binarizing the generated edge map with a pixel having a brightness equal to or higher than a reference value and a pixel having a brightness lower than the reference value; And Identifying edge information corresponding to the number of pixels having a brightness equal to or greater than a reference value indicated in the reconstructed edge map; Wherein the digital camera is a digital still camera. The method of claim 1, wherein The step of deriving the contrast information Converting an image of the subject area and an image of the peripheral area into an image of a gray level of color, brightness, and saturation channel mode;  Deriving a histogram image for each color, brightness, and saturation channel for the converted image; Deriving a representative level value for the derived histogram of the hue, brightness and saturation channel; And Obtaining contrast information corresponding to a difference of a representative level value of the peripheral region with respect to a representative level value of the subject region for each of the hue, brightness, and saturation channels; Wherein the digital camera is a digital still camera. delete Determining an object whose focus is on the input image; Setting an object area including the object and setting at least one peripheral area for confirming the incidence information of the object area around the object area; Deriving contrast information of hue, saturation, and brightness of the subject area and the surrounding area; Deriving edge information of the peripheral region; Deriving incidence information of the subject included in the subject area based on the contrast information or the edge information; And And displaying the derived incidence information of the subject on a display unit, The peripheral region and the subject region may be set as polygons, Wherein a total of eight peripheral regions are set in the horizontal, vertical, and diagonal directions with respect to the subject region. The method of claim 1, wherein The step of deriving the incidence information of the subject And comparing the contrast information or the edge information with reference information to derive subject incidence information. An area setting unit that sets a subject area including a subject focused on an input image and sets at least one peripheral area around the subject area; A contrast information deriving unit for deriving contrast information of hue, saturation, and brightness of the subject area and the surrounding area; An edge information deriving unit for deriving edge information of the surrounding area; And And a subject incidence information deriving unit for deriving incidence information of the subject included in the subject area based on the contrast information or the edge information, The edge information derivation unit A mode converter for converting the image of the peripheral region into an image of a gray level of color, brightness, and saturation channel mode; An edge map creating unit for creating an edge map for any one of color, brightness or saturation of the converted image; An edge map binarizer for reconstructing the edge map by binarizing the generated edge map with a pixel having a brightness equal to or higher than a reference value and a pixel having a brightness lower than the reference value; And An edge checker for deriving edge information corresponding to the number of pixels having brightness equal to or greater than a reference value indicated in the reconstructed edge map; Wherein the digital camera is provided with subject-incidence-information. The method of claim 6, wherein The contrast information deriving unit A mode converter for converting the image of the subject area and the image of the peripheral area into an image of a gray level of hue, brightness, and saturation mode; A histogram generation unit for deriving a histogram image for each color, brightness, and saturation channel for the converted image; A representative level value deriving unit for deriving a representative level value for the derived histogram for each color, brightness and saturation channel; And An area contrast unit for obtaining contrast information corresponding to a difference in the representative level value of the surrounding area with respect to the representative level value of the subject area by the hue, brightness and saturation channel; Wherein the digital camera is provided with subject-incidence-information. delete The method of claim 6, wherein The subject incidence information deriving unit And compares the contrast information or the edge information with reference information to provide subject incidence information for deriving subject incidence information. The method of claim 6, wherein A display control unit for controlling the display unit to display the derived incidence information of the subject; Wherein the digital camera is further provided with subject incidence information.

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