KR100801085B1 - Method and apparatus for auto white controlling - Google Patents

Abstract

The present invention relates to an automatic white adjustment method and apparatus.

According to an exemplary embodiment of the present invention, when the input image includes an object having a dominant chromaticity, the method may further include providing a plurality of feature points having chromatic characteristics of the image, using the plurality of feature points. Detecting first light source information, calculating an average chromaticity of data representing chromaticity differences within a threshold and chromaticity of the first light source information, and converting the average chromaticity into a predetermined light source trajectory. And providing second light source information by mapping to the second light source information.

Automatic white adjustment, object inflow, light source

Description

Method and apparatus for automatic white control {Method and apparatus for auto white controlling}

1 is a block diagram showing an automatic white adjustment apparatus according to an embodiment of the present invention.

2 is a diagram illustrating a state in which an image is divided into a reference area and a sub area according to an embodiment of the present invention.

3 is a flowchart illustrating a process of searching for a dominant object in an input image.

4 is a diagram for describing a process of determining whether a dominant object is introduced according to an embodiment of the present invention.

5 is a flowchart illustrating a process of providing feature points of an input image.

6A to 6C are diagrams illustrating an example of image data distribution on luminance-chromatic coordinates.

7 is a flowchart illustrating a light source detection process according to an embodiment of the present invention.

8A to 8G are views for explaining a light source detection process.

<Explanation of symbols on main parts of the drawings>

110: luminance-chromatic mapping module 120: search module

130: feature analysis module 140: light source detection module

150: white control module

The present invention relates to an automatic white adjustment method and apparatus, and more particularly, to an automatic white adjustment method and apparatus that provides consistent color reproduction performance even when an object having a dominant chroma is introduced into an image.

Light has a unique color called color temperature, and Kelvin (K) is used as a unit. In general, the human visual ability automatically adjusts the sensitivity to color, so the difference in human perception of color is insignificant no matter what color temperature light shines on. However, since an image pick-up device such as a camera or a camcorder detects the color reflecting the color temperature as it is, when the light source is changed, the images picked up by the image pickup device have different colors.

For example, the image taken by the image pickup device is generally blue due to the high color temperature on sunny days, while the image taken by the image pickup device is entirely red because the sunlight during sunrise or sunset is low. It is colored. In order to solve this problem, the proposed automatic white adjustment technique is used to distort the color tone of an image when the photographed image is deflected in at least one of red (R), green (G) and blue (B) components according to the color temperature. It corrects the phenomenon. The automatic white adjustment technique here is also called automatic white balance technique.

However, the conventional automatic white adjustment technique has a problem in that color reproduction results are inconsistent even under the same light source when an object having a dominant chromaticity is introduced into an image.

An object of the present invention is to provide consistent color reproduction performance even when an object having a dominant chromaticity is introduced into an image.

The objects of the present invention are not limited to the above-mentioned objects, and other objects that are not mentioned will be clearly understood by those skilled in the art from the following description.

In order to achieve the above object, the automatic white adjustment method according to an embodiment of the present invention, when the input image includes an object having a dominant chromaticity, providing a plurality of feature points having the chromatic characteristics of the image, Detecting first light source information using the plurality of feature points, calculating an average chromaticity of data representing chromaticity differences within a threshold and chromaticity of the first light source information among data constituting the image, and Mapping the average chromaticity to a predetermined light source trajectory to provide second light source information.

In order to achieve the above object, the automatic white adjustment device according to an embodiment of the present invention, when the input image includes an object having a dominant chromaticity, feature analysis that provides a plurality of feature points having the color characteristics of the image A module, and the plurality of feature points are used to detect first light source information, calculate an average chromaticity of data representing chromaticity differences within a threshold and chromaticity of the first light source information among the data constituting the image; And a light source detection module for mapping the average chromaticity to a predetermined light source trajectory to provide second light source information.

Specific details of other embodiments are included in the detailed description and the drawings.

Advantages and features of the present invention and methods for achieving them will be apparent with reference to the embodiments described below in detail with the accompanying drawings. However, the present invention is not limited to the embodiments disclosed below, but can be implemented in various different forms, and only the embodiments make the disclosure of the present invention complete, and the general knowledge in the art to which the present invention belongs. It is provided to fully inform the person having the scope of the invention, which is defined only by the scope of the claims. Like reference numerals refer to like elements throughout.

Hereinafter, exemplary embodiments of the present invention will be described in detail with reference to the accompanying drawings.

1 is a block diagram showing an automatic white adjustment apparatus according to an embodiment of the present invention.

The illustrated automatic white adjustment device includes a luminance-chromatic mapping module 110, a search module 120, a feature analysis module 130, a light source detection module 140, and a white adjustment module 150.

The luminance-chromatic mapping module 110 converts data included in the input image into YCrCb data.

The search module 120 analyzes the input image and searches for an object having a dominant chromaticity (hereinafter, referred to as a dominant object) in the image. To this end, the search module 120 may divide the input image into a plurality of reference regions and divide each of the reference regions into a plurality of sub-regions as shown in FIG. 2. Here, the reference region may be set in advance as regions where the dominant object is generally likely to flow in the image. The search module 120 may configure an average chromaticity (hereinafter referred to as an average chromaticity of the reference region) of the data (or pixels) constituting the reference region for each reference region and data configuring the subregion for each subregion included in the reference region. The average chromaticity of the pixels (or pixels) (hereinafter referred to as the average chromaticity of the sub-regions). Thereafter, the search module 120 calculates a difference value between the average chromaticity of the reference region and the average chromaticities of the subregions included in the reference region.

Among a plurality of sub-areas included in the reference area, a sub-area having an average chromaticity of one reference area and an average chromaticity of which a difference value between the average chromaticity of the reference area is less than a predetermined threshold is included in the reference area. If it occupies more than a threshold ratio, the search module 120 may determine that a dominant object has flowed into the reference region. Here, the threshold value may be set in advance to a value suitable for determining whether the dominant object is introduced through various experiments.

The feature analysis module 130 provides a plurality of feature points having chromatic features of the input image. Here, the plurality of feature points may include data having a maximum luminance value (hereinafter referred to as a maximum luminance point) and data having a minimum luminance value (hereinafter referred to as a minimum luminance point) among data constituting the input image, and a dominant object in the input image. A reference point having an average luminance and an average chromaticity of the data constituting the, and the average luminance and the average chromaticity of the data included in two groups consisting of residual data other than the data of the dominant object among the data constituting the input image. And a first clustering point having a second clustering point.

These feature points may be provided when the search module 120 detects a dominant object in the input image, and the process of providing the feature point by the feature analysis module 130 will be described later with reference to FIG. 3.

The light source detection module 140 detects primary light source information by using feature points provided by the feature analysis module 130. The primary light source information is temporary light source information used to detect final light source information in the input image. The light source detection module 140 searches for data having a chromaticity difference within a threshold and chromaticity of the primary light source information among the data constituting the input image and calculates an average chromaticity of the retrieved data. Here, the threshold represents a boundary of data that can express the light source information according to the change of environment, and may be set to an appropriate value in advance through an experiment. Thereafter, the light source detection module 140 detects final light source information by mapping a grayish point having a calculated average chromaticity to a predetermined luminance locus. The process of detecting the final light source information by the light source detection module 140 will be described later with reference to FIG. 4.

The white adjustment module 150 performs a white balancing operation on the input image using the final light source information.

In the description of FIG. 1, a module refers to a hardware component such as software or a field programmable gate array (FPGA) or an application specific integrated circuit (ASIC), and the module plays certain roles. However, modules are not meant to be limited to software or hardware. The module may be configured to be in an addressable storage medium and may be configured to execute one or more processors. Thus, as an example, a module may include components such as software components, object-oriented software components, class components, and task components, and processes, functions, properties, procedures, subroutines. , Segments of program code, drivers, firmware, microcode, circuits, data, databases, data structures, tables, arrays, and variables. The functionality provided by the components and modules may be combined into a smaller number of components and modules or further separated into additional components and modules.

Hereinafter, an automatic white adjustment method will be described with reference to FIGS. 3 to 8G.

3 is a flowchart illustrating a process of searching for a dominant object in an input image. The process of FIG. 3 is performed by the search module 120 of the automatic white adjustment device described with reference to FIG. 1.

When the image converted into YCrCb data is input by the luminance-chromatic mapping module 110 (S310), the search module 120 divides the input image into a plurality of reference regions as illustrated in FIG. 2 (S320). Each reference area is divided into a plurality of sub areas (S330). In FIG. 2, one image is divided into five reference regions, and each reference region is divided into sixteen sub regions, but the present invention is not limited thereto.

Thereafter, the search module 120 calculates the average chromaticity of each reference region and the average chromaticity of the subregions constituting the reference region for each reference region (S340). Thereafter, the search module 120 calculates a difference between the average chromaticities of the reference areas and the average chromaticities of the sub areas constituting the reference area for each reference area (S350).

If there is a sub-area whose difference is smaller than a predetermined threshold and the number occupies a predetermined ratio or more with respect to the total number of sub-areas constituting the reference area (S360), the search module 120 returns to the corresponding reference area. It may be determined that the dominant object is introduced (S370). A detailed example thereof will be described with reference to FIG. 4.

4 illustrates one reference region 410 on the image, and the illustrated reference region 410 is composed of 16 sub-regions. The average chromaticity of the data included in the reference area 410 is referred to as R1, and the average chromaticity of the data included in each of the 16 subregions is referred to as r1 to r16. The calculation of the average chromaticity is performed in step S340 of FIG. 3.

Thereafter, a process of comparing each of r1 to r16 with R1 and calculating a difference therebetween is performed through the process S350 performed in FIG. 3. As a result of the calculation, if the number of sub-regions having an average chromaticity whose difference with R1 is less than the threshold is eight, the proportion of the sub-regions in the reference region 410 is 50%. If the threshold ratio mentioned in the process S360 of FIG. 3 is 40%, the difference between the average chromaticity R1 of the reference region 410 and the sub-region having an average chromaticity is less than the threshold value among the subregions of the reference region 410. Since the ratio is higher than the threshold ratio, it may be determined that the dominant object is introduced into the reference region 410 by the processes S360 and S370 of FIG. 3.

On the other hand, if there is no reference region in which the dominant object exists in the image as a result of the determination in step S360, the operation of detecting the light source based on all data in the image may be performed as in the related art.

5 is a flowchart illustrating a process of providing feature points of an input image. 5 may be performed by the feature analysis module 130 of the automatic white adjustment apparatus described with reference to FIG. 1 when it is determined that the dominant object exists in the image through the process of FIG. 3.

First, the feature analysis module 130 extracts the maximum luminance point and the minimum luminance point from the data included in the image (S510). When data included in the image is distributed in the luminance-chromatic space, the maximum luminance point and the minimum luminance point may be understood as the example shown in FIG. 6A.

Thereafter, the feature analysis module 130 extracts data corresponding to the dominant object from the data included in the image (S520), and sets a reference point having the average luminance and the average chromaticity of the extracted data (S530).

Here, data corresponding to the dominant object may be detected through a chromaticity difference between the reference area and the sub area. For example, the feature analysis module 130 may calculate the average chromaticity of the reference region and the average chromaticity of each sub-region constituting the reference region with respect to the reference region determined by the search module 120 that the dominant object is introduced. Calculate Thereafter, the feature analysis module 130 may compare the average chromaticity of the reference region with the average chromaticity of each subregion and determine the data included in the subregion whose difference is smaller than the threshold as the data of the dominant object. Of course, the feature analysis module 130 may not directly calculate the average chromaticity of the reference region and the average chromaticity of the subregions, but may use the result calculated by the search module 120 to determine whether the dominant object is introduced.

In the state where the distribution in the chromaticity coordinates of the data constituting the image is as shown in FIG. 6B, the data of the dominant object is extracted and the remaining data are clustered into two groups by the feature analysis module 130 as shown in FIG. 6C ( S540). Thereafter, the feature analysis module 130 sets a clustering point having an average luminance and an average chromaticity of data of each group for each clustered group (S550). Various types of clustering techniques may be used to cluster the residual data in step S540. As an example, the feature analysis module 130 may cluster residual data using a simplified K mean clustering technique.

Accordingly, the feature analysis module 130 provides five feature points having the chromatic characteristics of the input image, that is, a maximum luminance point, a minimum luminance point, a reference point, and two clustering points.

When the feature point is provided, the light source detection operation by the light source detection module 140 described with reference to FIG. 1 is performed, which will be described with reference to FIG. 7.

7 is a flowchart illustrating a light source detection process according to an embodiment of the present invention. In this flowchart, the light source detection module 140 determines whether the data of the dominant object is achromatic or chromatic, thereby determining whether to include the data of the dominant object as basic data for detecting the light source information. .

First, the light source detection module 140 calculates a chromaticity difference (hereinafter, referred to as D1) between the maximum luminance point and the minimum luminance point (S710). For example, the light source detection module 140 may project the maximum luminance point and the minimum luminance point to chromaticity coordinates (Cr-Cb coordinates) as shown in FIG. 8A, and obtain a distance between the two data in the chromaticity coordinates. When the distance is D1.

Similarly, the light source detection module 140 calculates a chromaticity difference (hereinafter referred to as D2) between two clustering points (S715).

The smaller D1 is, the more light source information is included between the chromaticity of the maximum luminance point and the chromaticity of the minimum luminance point. The larger the D2, the larger the scatter of the image. Accordingly, the light source detection module 140 may check the possibility that the color of the input image is changed due to the influence of the dominant object by comparing D1 and D2.

In more detail, first, the light source detection module 140 compares whether D1 is smaller than D2 (S720). If D1 is smaller than D2, the light source detection module 140 determines whether a reference point representing the average chromaticity value of the dominant object exists within the range of D2 on the chromaticity coordinates (S725). Here, the reference point is within the range of D2 means that the reference point exists between the chromaticity values Cr and Cb of the first clustering point and the chromaticity values Cr and Cb of the second clustering point. For example, when the first clustering point and the second clustering point exist on chromaticity coordinates as shown in FIG. 8B, an area (contrast) that is partitioned on the basis of Cr and Cb values of the first clustering point and the second clustering point If there is a reference point in the processed area), it can be said that the reference point exists in the range of D2 on the chromaticity coordinate.

If D1 is smaller than D2 and a reference point exists within the range of D2, the input image may be divided into a normal image which is not affected by the dominant object. For reference, when the input image is a normal image, an example of arrangement on the luminance-chromatic coordinates of the feature points provided by the feature analysis module 130 is illustrated in FIG. 8C.

When D1 is smaller than D2 and the chromatic average value of the dominant object exists within the range of D2, the data of the dominant object may be determined as achromatic data, and the light source detection module 140 may determine all the data included in the image. On the basis of the detection of the light source information (S730). Here, a conventional light source detection technique may be used to detect light source information.

On the other hand, if the determination result D1 of step S720 is not smaller than D2 or if the reference point indicating the average chromaticity value of the dominant object does not exist within the range D2 of the determination result of step S725, the input image is changed in color due to the influence of the dominant object. It can be classified as an unusual image that may have been. For reference, when the input image is an unusual image, an example of arrangement on the luminance-chromatic coordinates of the feature points provided by the feature analysis module 130 is illustrated in FIG. 8D. That is, even if D1 is greater than or equal to D2 or D1 is smaller than D2, if there is no reference point representing the average chromaticity value of the dominant object in the D2 range, the data of the dominant object may be chromatic data.

In order to identify whether the data of the dominant object is colored or achromatic data, the light source detecting module 140 first selects a point (hereinafter referred to as a comparison point) that is determined to be close to the light source among the maximum luminance point and the minimum luminance point (S735). . To this end, the light source detection module 140 may compare the maximum luminance point and the minimum luminance point with data having the maximum luminance and data having the minimum luminance among the data of the dominant object.

In more detail, the light source detection module 140 uses an overlap between the chromaticity difference (hereinafter, referred to as D3) of the data having the maximum luminance and the data having the minimum luminance among the data of the dominant object (hereinafter, referred to as D3) and D1. You can select a comparison point. Here, overlapping of D1 and D3 means that the chromaticity value of the chromaticity area bounded by the chromaticity value of the maximum luminance point and the chromaticity value of the minimum luminance point in the dominant object is the chromaticity value of the data having the maximum luminance and the minimum luminance. This means that it overlaps with the chromaticity area around them. For example, in the state where the maximum luminance point, the minimum luminance point, and the data having the maximum luminance and the minimum luminance in the dominant object exist on the chromaticity coordinates as shown in FIG. 8E, the maximum luminance point and the minimum luminance are present. An area 810 partitioned on the basis of Cr and Cb values of a point is partitioned on the basis of the Cr and Cb values of the data 830 having the maximum luminance and the data 840 having the minimum luminance in the dominant object. If overlapping with 820, it can be said that D1 and D3 overlap.

In general, when the chromaticity data transitions due to the luminance change, the chromaticity value of the high luminance existing in the entire image is shifted to the chromaticity value of the higher luminance, or the chromaticity value of the low luminance existing in the entire image is relative. In the case of transition to a chromaticity value of lower luminance, these chromaticity values tend to become achromatic. Therefore, when D1 and D3 overlap on chromaticity coordinates and one of the maximum luminance point and the minimum luminance point is included in the range of D3 (chromatic region 820 of FIG. 8E), the point is determined to be a comparison point close to the light source. In the case of FIG. 8E, since the maximum luminance point is included in the area 820, it may be determined as the comparison point closest to the light source. Also, if D1 and D3 overlap and none of the maximum and minimum luminance points fall within the range of D3, the minimum luminance data is determined to be the closest comparison point to the light source, and if D1 and D3 do not overlap, the maximum luminance point and A point whose chromaticity distance is further from the range of D3 among the minimum luminance points is determined as the comparison point nearest to the light source.

When the comparison point determined to be close to the light source is selected among the comparison maximum luminance point and the minimum luminance point, the light source detection module 140 calculates a chromaticity difference (hereinafter referred to as D4) between the chromaticity of the selected comparison point and the average value of the chromaticity of the clustering points. (S740). In addition, the light source detection module 140 calculates a chromaticity difference (hereinafter referred to as D5) between the chromaticity of the comparison point selected in step S735 and the average chromaticity (chrominity of the reference point) of the data constituting the dominant object (S745).

If D4 is greater than D5 (S750), the light source detection module 140 determines the data of the dominant object as achromatic data and detects the light source information based on all data in the image (S730).

However, if D4 is not larger than D5, the light source detection module 140 determines the data of the dominant object as chromatic color data and detects the primary light source information based on the remaining data excluding the data of the dominant object in the image (S755). A light source detection technique used to detect the primary light source in step S755 may also use a conventional technique as in step S730. However, process S755 differs from process S730 in that residual data excluding data of the dominant object is used in the image to detect the primary light source.

When the primary light source information is detected, the light source detection module 140 searches for data having a chromaticity difference within a threshold from the primary light source information among the data constituting the image as shown in FIG. 8F (S760). The average chromaticity of the data is calculated (S765).

Thereafter, the light source detection module 140 detects final light source information by mapping the average chromaticity calculated in step S765 on a predetermined light source locus (illuminant locus) (S770). Here, the light source trajectory may be a trend line based on the saturation of a plurality of various types of light sources (for example, D65, D50, Cool White Fluorescent (A), A, etc.), which is illustrated in FIG. 8G. 8G shows the light source trajectory on the chromaticity plane Cr-Cb and the average chromaticity calculated in step S765. The final light source information has the chromaticity of the point at which the average chromaticity is projected perpendicular to the light source trajectory.

According to this process, the light source detection module 140 may prevent the light source information from being altered due to the influence of the dominant object.

When the final light source information is detected through a series of processes described with reference to FIGS. 3 to 8G, the white adjustment module 150 performs a white balancing operation on the input image using the detected final light source information.

Although embodiments of the present invention have been described above with reference to the accompanying drawings, those skilled in the art to which the present invention pertains may implement the present invention in other specific forms without changing the technical spirit or essential features thereof. You will understand that. Therefore, it should be understood that the embodiments described above are exemplary in all respects and not restrictive.

According to the automatic white adjustment method and apparatus of the present invention as described above, even when an object having a dominant chroma is introduced into an image, there is an effect of providing a consistent color reproduction performance.

Claims (24)

When an object having a dominant chromaticity is included in the input image, the color characteristics of the remaining data except for the data constituting the object among the data constituting the image, data constituting the object, and data constituting the object Providing a plurality of feature points having; Detecting first light source information using the plurality of feature points; Calculating an average chromaticity of data representing chromaticity differences within a threshold and chromaticity of the first light source information among the data constituting the image; And And mapping the average chromaticity to a predetermined light source trajectory to provide second light source information. The method of claim 1, Dividing the input image into a plurality of reference areas, and dividing each of the plurality of reference areas into a plurality of sub areas; Calculating, for each of the plurality of reference regions, a difference value between an average chromaticity of the reference region and an average chromaticity of each of the subregions; And And determining that the object is included in the reference area in which the ratio of the sub-area among the plurality of reference areas whose difference value is less than a predetermined threshold is greater than or equal to a threshold ratio. The method of claim 1, Providing the feature point, Extracting a maximum luminance point which is data having a maximum luminance value and a minimum luminance point which is data having a minimum luminance value among data constituting the image; Providing a reference point having an average luminance and an average chromaticity of data constituting the object; And Residual data excluding the data constituting the object among the data constituting the image is clustered into two groups, and the first clustering point and the second clustering point having an average luminance and an average chromaticity of the residual data included in each of the two groups. Automatic white adjustment method comprising the step of providing. The method of claim 3, wherein When the image is divided into a plurality of reference areas and each of the plurality of reference areas is divided into a plurality of sub-areas, a difference value of an average chromaticity with the reference area in which the image is included is included in a sub-area having a predetermined threshold value. And determining data as data constituting the object. The method of claim 3, wherein Providing the first clustering point and the second clustering point, and clustering the residual data into the two groups using a simplified K mean clustering technique. The method of claim 3, wherein Detecting the first light source information, When the first chromaticity difference between the maximum luminance point and the minimum luminance point is greater than or equal to a second chromaticity difference between the first clustering point and the second clustering point, one of the maximum luminance point and the minimum luminance point is selected as a comparison point. Doing; And If the third chromaticity difference between the average value of the chromaticity of the first clustering point and the chromaticity of the second clustering point and the chromaticity of the comparison point is less than or equal to a fourth chromaticity difference between the chromaticity of the reference point and the chromaticity of the comparison point, the image is displayed. And detecting the first light source information by using residual data except data of the object in constituent data. The method of claim 6, Detecting the first light source information, And selecting the comparison point when the first chromaticity difference is less than the second chromaticity difference and the chromaticity of the reference point does not exist within the range of the second chromaticity difference. The method of claim 6, Selecting the comparison point, When the first chromaticity difference overlaps the fifth chromaticity difference between the data having the maximum luminance and the data having the minimum luminance among the data constituting the object, the fifth chromaticity difference range among the maximum luminance point and the minimum luminance point. Automatic white adjustment method comprising the step of selecting a side included in the comparison point. The method of claim 6, Selecting the comparison point, The first chromaticity difference overlaps a fifth chromaticity difference between data having the highest luminance and data having the minimum luminance among the data constituting the object, and the maximum luminance point and the minimum luminance point are within the fifth chromaticity difference range. If not included, selecting the minimum luminance point as the comparison point. The method of claim 6, Selecting the comparison point, When the first chromaticity difference does not overlap the fifth chromaticity difference between the data having the maximum luminance and the data having the minimum luminance among the data constituting the object, the fifth chromaticity difference among the maximum luminance point and the minimum luminance point. Selecting the side closer to the range as the comparison point. The method of claim 1, The light source trajectory is a trend white line using the saturation of a plurality of different light sources. The method of claim 1, And performing a white balancing operation of the image using the second light source information. When an object having a dominant chromaticity is included in the input image, the color characteristics of the remaining data except for the data constituting the object among the data constituting the image, data constituting the object, and data constituting the object A feature analysis module providing a plurality of feature points having a; And Detecting first light source information using the plurality of feature points, calculating average chromaticity of data representing chromaticity differences within a threshold and chromaticity of the first light source information among data constituting the image, and calculating the average chromaticity. And a light source detecting module configured to provide second light source information by mapping to a predetermined light source trajectory. The method of claim 13, The input image is divided into a plurality of reference areas, each of the plurality of reference areas is divided into a plurality of sub areas, and the average chromaticity of each of the plurality of reference areas and the average chromaticity of each of the sub areas are divided. And a search module for calculating a difference value between the plurality of reference areas and determining that the object is included in a reference area having a ratio of a sub-area whose difference value is less than a predetermined threshold among the plurality of reference areas. Device. The method of claim 13, The feature analysis module extracts a maximum luminance point which is data having a maximum luminance value and a minimum luminance point which is data having a minimum luminance value among data constituting the image, and calculates an average luminance and an average chromaticity of data constituting the object. A first clustering having an average luminance and an average chromaticity of data included in each of the two groups by providing a reference point having the data, and clustering the residual data except the data constituting the object among the data constituting the image into two groups Automatic white adjustment device providing a point and a second clustering point. The method of claim 15, When the image is divided into a plurality of reference areas and each of the plurality of reference areas is divided into a plurality of sub-areas, a difference value of an average chromaticity with the reference area in which the image is included is included in the sub-area that is less than a predetermined threshold. And a search module for determining data as data constituting the object. The method of claim 15, The feature analysis module is configured to cluster the residual data into the two groups using a simplified K mean clustering technique. The method of claim 15, The light source detecting module is any one of the maximum luminance point and the minimum luminance point when the first chromaticity difference between the maximum luminance point and the minimum luminance point is greater than or equal to a second chromaticity difference between the first clustering point and the second clustering point. Is selected as a comparison point, and the third chromaticity difference between the average value of the chromaticity of the first clustering point and the chromaticity of the second clustering point and the chromaticity of the comparison point is the fourth chromaticity between the chromaticity of the reference point and the chromaticity of the comparison point. If the difference is less than the automatic white adjustment device for detecting the first light source information using the remaining data except the data of the object from the data constituting the image. The method of claim 18, And the light source detecting module selects the comparison point when the first chromaticity difference is smaller than the second chromaticity difference and there is no chromaticity of the reference point within a range of the second chromaticity difference. The method of claim 18, When the first chromaticity difference overlaps a fifth chromaticity difference between the data having the maximum luminance and the data having the minimum luminance among the data constituting the object, the light source detection module is configured to select the at least one of the maximum luminance point and the minimum luminance point. The automatic white adjustment apparatus which selects the side included in a 5th chromaticity difference range as the said comparison point. The method of claim 18, The light source detection module is configured such that the first chromaticity difference overlaps with a fifth chromaticity difference between data having a maximum luminance and data having a minimum luminance among data constituting the object, and wherein the maximum luminance point and the minimum luminance point are the first chromaticity difference. And selecting the minimum luminance point as the comparison point if it is not within the five chromaticity range. The method of claim 18, The light source detection module is configured to, among the maximum luminance point and the minimum luminance point, when the first chromaticity difference does not overlap with a fifth chromaticity difference between data having the highest luminance and data having the minimum luminance among the data constituting the object. And selecting a side closer to the fifth chromaticity difference range as the comparison point. The method of claim 13, The light source trajectory is a trend white line using a saturation of a plurality of different light sources. The method of claim 13, And a white adjusting module configured to perform white balancing of the image using the second light source information.

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