KR20150130030A - Method and apparatus for color filter array judgement of digital camera based on intermediate value counting - Google Patents

Abstract

The present invention relates to a digital image judging technology and, more specifically, relates to a method to judge a color filter array which estimates the color filter array from one digital image and a device thereof. The method comprises: a step of obtaining single image information; a step of estimating a shape of the color filter array by using the single image information; a step of counting a number of pixels in accordance with an intermediate value condition; a step of determining first a location of a green channel; a step of determining locations of the remaining red and blue channels; a step of estimating the color filter array by a block unit; and a step of determining whether an image is forged by the estimated color filter array.

Description

BACKGROUND OF THE INVENTION 1. Field of the Invention [0001] The present invention relates to a color filter array,

The present invention relates to a digital image discrimination technique, and more particularly, to a color filter array discrimination method and apparatus for estimating a color filter array from a digital image.

In particular, in the process of color filter interpolation, which is a digital image processing process, based on filling empty pixels from neighboring pixels, a specific pattern is obtained for each channel, the intermediate values are calculated, and the intermediate values of the three channels are utilized To a color filter array discrimination method and apparatus for estimating a color filter array.

With the rapid development of digital camera technology, many digital images have been generated as prices have decreased. In recent years, there has been a growing interest in digital forensics as an attempt to falsify such digital images.

Particularly, the technology of distinguishing the information of the photographed equipment using only the image is main. When acquiring an image, the digital camera may be used for auto-focusing, white balance adjustment, color filter interpolation, color correction, gamma correction, filtering ), And compression (compression). During this process, color filter interpolation is an essential process performed by most cameras, which can be an important clue to obtain information of the camera taken.

Takamatsu and his colleagues used a method that uses the ratio of the noise variance of the observed pixel to the interpolated pixel to determine the color filter array. The Kirchner team used color filter array synthesis methods. Since this method has a high time complexity, the research team proposed an approximate solution so that only one filtering can be done. Dirik's team used a method to find the mean square error between the original image and the re-interpolated image.

However, these techniques have a disadvantage in that they exhibit low accuracy, especially for small areas.

1. Korean Patent No. 10-1264165 2. Korean Patent Publication No. 10-2013-0020435 3. Korean Patent Publication No. 10-2011-0132770

The present invention has been made in order to solve the above problem, and it is an object of the present invention to provide a color filter array discrimination method and apparatus for a digital camera using an intermediate value aggregation for estimating a color filter array based on a basic principle of filling empty pixels from neighboring pixels The purpose is to provide.

The present invention provides a color filter array discrimination method of a digital camera using an intermediate value aggregation for estimating a color filter array based on a basic principle of filling empty pixels from surrounding pixels.

The color filter array determination method includes:

Obtaining single image information;

Estimating the shape of the color filter array using the single image information;

Counting the number of pixels matching the condition using the intermediate value condition:

Determining a position of a green channel using aggregated aggregate values of each color channel;

Determining positions of the remaining red and blue channels according to the difference of the aggregated values;

Estimating a color filter array on a block-by-block basis using the determined position of the color channel; And

And judging the forgery and falsification of the image using the estimated color filter arrangement.

In this case, the intermediate value condition may be such that the interpolated pixel is larger than the minimum value of neighboring pixels and smaller than the maximum value.

In addition, the positioning of the green channel, the red channel, and the blue channel is initialized to the values of the red channel and the blue channel, and is determined using the difference of the red and blue aggregate values.

The initialization value may be "0 ".

In addition, the pattern of the neighboring pixels may be one of cross, vertical, horizontal, and quincunx.

In the judgment of the forgery or falsification, the type of the color pattern array determined through the median value aggregation and the pattern of the region suspected of manipulating the image are compared with each other, and the region where the patterns do not coincide with each other is determined as the manipulated region .

Further, the maximum value and the minimum value may be expressed by Equation

(Where I denotes position coordinates of an image, c denotes a cross, h denotes a horizontal direction, and v denotes a vertical direction).

On the other hand, an embodiment of the present invention provides an image processing apparatus comprising: an image obtaining unit obtaining single image information; An intermediate value setting unit for estimating the shape of the color filter array using the single image information and counting the number of pixels matching the condition using the intermediate value condition; The position of the green channel is first determined using the aggregated values of the color channels, the positions of the remaining red and blue channels are determined according to the difference of the aggregated values, Estimation unit estimating unit; And a determination unit for determining the forgery and falsification of the image using the estimated color filter array. The color filter array determination apparatus of the digital camera using the intermediate value aggregation is provided.

According to the present invention, in recent years, digital images are illegally photographed or maliciously modulated. However, illegally photographed images (for example, illegal shooting for corporate secret shooting, illegal shooting for sexual harassment, illegal shooting for privacy intrusion , Child pornography shooting, etc.). In other words, after making these illegal shots, you often modify the meta-data of an image or video to hide its source. At this time, since the color filter arrangement of the photographed image apparatus can be estimated only by the image itself, it can be submitted as legal proof against the image capturing apparatus of the confiscated suspect.

In addition, another effect of the present invention is that, when the image is maliciously modulated, the modulated portion can be found. Examples of such malicious tampering include the Iranian missile cloning in the article, and North Korea's image forgery for political purposes.

Since the color filter arrangement is likely to be different between the modulated part and the original, if the color filter arrangement is estimated on a block-by-block basis using the technique of the present invention, modulation presence, position, and size can be detected.

Especially, the performance is good for small blocks compared with general methods, and it can show good performance in this part.

FIG. 1 is a configuration diagram of an apparatus 100 for determining color arrangement of a digital camera using an intermediate value aggregation according to an embodiment of the present invention. Referring to FIG.
2 is a flowchart illustrating a color filter array determination process of a digital camera using an intermediate value aggregation according to an exemplary embodiment of the present invention.
FIG. 3 is an example of conceptually showing neighboring patterns of green, red and blue channels according to the flow chart shown in FIG.
4 is a conceptual diagram showing an example of determining a green pattern first according to the flowchart shown in FIG. 2, and then determining the rest.
5 is a conceptual diagram of another example of determining a green pattern first according to the flowchart shown in FIG. 2, and then determining the rest.
6 is an example of an intermediate value counting algorithm for counting the number of interpolated pixels according to the flow chart shown in FIG.
FIG. 7 is an example of a pattern determination algorithm in accordance with the flowchart shown in FIG.
8 is a graph comparing experimental results according to block sizes with general experimental results according to an embodiment of the present invention.
FIG. 9 is a graph comparing experimental results according to the degree of JPEG compression with general experimental results according to an embodiment of the present invention.

While the invention is susceptible to various modifications and alternative forms, specific embodiments thereof are shown by way of example in the drawings and will herein be described in detail. It is to be understood, however, that the invention is not to be limited to the specific embodiments, but includes all modifications, equivalents, and alternatives falling within the spirit and scope of the invention.

Like reference numerals are used for similar elements in describing each drawing.

The terms first, second, etc. may be used to describe various components, but the components should not be limited by the terms. The terms are used only for the purpose of distinguishing one component from another.

For example, without departing from the scope of the present invention, the first component may be referred to as a second component, and similarly, the second component may also be referred to as a first component. The term "and / or" includes any combination of a plurality of related listed items or any of a plurality of related listed items.

Unless otherwise defined, all terms used herein, including technical or scientific terms, have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

Terms such as those defined in commonly used dictionaries are to be interpreted as having a meaning consistent with the contextual meaning of the related art and are to be interpreted as either ideal or overly formal in the sense of the present application Should not.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, a method and apparatus for determining a color filter array of a digital camera using intermediate value aggregation according to an embodiment of the present invention will be described in detail with reference to the accompanying drawings.

For each channel of a digital image, color filter interpolation can be viewed as a problem of image interpolation for black and white images. There are various methods such as nearest-neighbor, first order bilinear, and bicubic method for the image interpolation method. Many other advanced methods are used, but most of them are based on the aforementioned methods.

For this reason, a method and apparatus for determining the color filter array of a digital camera using the intermediate value aggregation according to an embodiment of the present invention are based on the above-mentioned methods. However, the present invention is not limited to this, and it can be seen that the present invention operates well with other advanced interpolation methods as shown in the experimental results shown in FIGS.

The color filter array discrimination method of the digital camera using the intermediate value aggregation according to an embodiment of the present invention comprises two processes. The first of these is an intermediate value aggregation process that meets a predefined interval. The second step is an estimation process for estimating the color filter array using these aggregate values. Details are described below.

FIG. 1 is a configuration diagram of an apparatus 100 for determining color arrangement of a digital camera using an intermediate value aggregation according to an embodiment of the present invention. Referring to FIG. Referring to FIG. 1, the color filter array determining apparatus 100 includes an image obtaining unit 110 for obtaining single image information, an image obtaining unit 110 for estimating the shape of the color filter array using the single image information, An intermediate value setting unit 120 for counting the number of pixels corresponding to the conditions using the aggregated values of the respective color channels, and the position of the green channel is first determined using the aggregated values of the respective color channels, and the remaining red and blue An estimator 130 for determining the position of the channel and estimating the color filter array on a block basis by using the determined position of the color channel, and a determiner 140 for determining the forgery or falsification of the image using the estimated color filter array. And the like.

2 is a flowchart illustrating a color filter array determination process of a digital camera using an intermediate value aggregation according to an exemplary embodiment of the present invention. Referring to FIG. 2, a step S210 of obtaining single image information, a step S220 of estimating the shape of the color filter array using only the single image information itself, a step S220 of estimating the shape of the color filter array, (S230), the position of the green channel is first determined using the aggregated values of the respective channels, and the positions of the remaining red and blue channels are determined according to the difference of the aggregated values (S240), estimating a color filter array on a block-by-block basis (S250), and determining a forgery or falsification of an image using the color filter array (S260).

FIG. 3 is an example of conceptually showing neighboring patterns of green, red and blue channels according to the flow chart shown in FIG. FIG. 3 illustrates a process of interpolating blank pixel values of an image through a color filter array in a photographing process using a bilinear interpolation method. The first linear interpolation is performed by interpolating neighboring pixels in the form of a cross 310, a vertical and a horizontal 320, and a quincunx 330.

In addition, the green channel forming the image is interpolated using a neighboring pixel pattern in the form of a cross 310, and the red and blue channels are interpolated using neighboring pixels in the form of vertical and horizontal (320) The interpolation is performed using neighboring pixel patterns in the form of a quincunx 330 (i.e., corresponding to steps S210 and S220 of FIG. 2).

therefore,

Of the image

The minimum value and / or the maximum value for each pattern can be defined as the following equation.

Generally interpolated pixels are affected by neighboring pixels. Intuitively, it is natural that most interpolated pixels are intermediate values that are larger than the minimum value of neighboring pixels and smaller than the maximum value. In fact, most interpolation algorithms have these characteristics.

In the case of the green channel, this condition is satisfied with a probability of 100% for the adjacent pixel interpolation method and the linear interpolation method, and about 98% for the case of the bilinear interpolation method.

If the number of pixels in an image is 128 × 128, for example, 16,384 pixels are considered. Therefore, even if bilinear interpolation is used, 16,056 pixels satisfy the condition and 328 pixels are misdiagnosed. The algorithm shown in Fig. 6 is used to count the number of pixels satisfying the intermediate value condition (step S230 in Fig. 2). That is, FIG. 6 is an example of an intermediate value counting algorithm for counting the number of interpolated pixels.

The position of the pixel having the intermediate value, that is, the interpolated pixel, is determined according to the shape of the pattern of the color filter array. Also, since the interpolated pixel has a medium value that is larger than the minimum value of neighboring pixels and smaller than the maximum value, the pattern of the color filter array is determined by compiling the intermediate value.

4 is a conceptual diagram of an example of determining green pattern 410 first according to the flowchart shown in FIG. 2, and then determining the rest. 5 is a conceptual diagram of another example of determining a green pattern first according to the flowchart shown in FIG. 2, and then determining the rest. Referring to Figures 4 and 5, most color filter interpolation algorithms begin interpolation from the green channel. The reason for this is that the human eye is sensitive to the middle band of the visible light, because the green channel has the most.

After estimating the color filter for the green channel, it estimates the red and blue patterns. This method is generally used most of the time.

Thus, as in the algorithm shown in Figure 6, the median aggregate value for the green channel

. Referring to FIG. 6, the number of pixels satisfying the intermediate value condition is calculated by dividing the sum of the positions of the pixels by the even and odd numbers.

This gives you two options in the basic bayer pattern. In order to determine this, first, the values of the red and blue channels of the selected green channel pattern are initialized to zero, and then the difference between the red and blue aggregate values is determined, and the larger value is first determined (step S240).

A diagram showing the algorithm for this is shown in Fig. That is, FIG. 7 is an example of a pattern determination algorithm in accordance with the flowchart shown in FIG. Referring to FIG. 7, the green channel pattern is determined using the intermediate pixel number calculated in FIG. If the sum of pixel positions is an odd number, the number of pixels satisfying the intermediate value condition is greater than the case of the color pattern arrangement shown in FIG. Conversely, if the sum of the pixel positions is an even number and the number of pixels satisfying the intermediate value condition is larger, the case of the color pattern arrangement shown in FIG. 5 is shown.

And the number of pixels satisfying the intermediate value condition calculated in the two areas in which the patterns of the red and blue channels are not determined is used to determine each position having the largest number of pixels satisfying the intermediate value condition in the red and blue channels The position of the pattern is determined.

8 is a graph comparing experimental results according to block sizes with general experimental results according to an embodiment of the present invention. Referring to FIG. 8, a graph 810 according to an embodiment of the present invention using a Dresden database and a holding database, a graph 820 according to an embodiment of the present invention using only a Dresden database, a Dresden database, A graph 830 according to a general embodiment, a graph 840 according to a typical embodiment using only a Dresden database, and the like. As shown in FIG. 8, in general, the identification accuracy changes sharply as the crop size becomes smaller. Alternatively, according to an embodiment of the present invention, the identification accuracy changes slowly without changing abruptly.

FIG. 9 is a graph comparing experimental results according to the degree of JPEG compression with general experimental results according to an embodiment of the present invention. In general, the identification accuracy of a color filter pattern is drastically reduced even with a minimum of JPEG compression strength. Alternatively, according to one embodiment of the present invention, JPEG compression of weak intensity maintains some degree of identification accuracy.

100: Color filter array discrimination device
110: Image acquisition unit
120: intermediate value setting unit
130:
140:

Claims (8)

Obtaining single image information;
Estimating the shape of the color filter array using the single image information;
Counting the number of pixels matching the condition using the intermediate value condition:
Determining a position of a green channel using aggregated aggregate values of each color channel;
Determining positions of the remaining red and blue channels according to the difference of the aggregated values;
Estimating a color filter array on a block-by-block basis using the determined position of the color channel; And
Determining forgery and falsification of the image using the estimated color filter array;
The method of claim 1, further comprising:
The method according to claim 1,
Wherein the intermediate value condition is such that the interpolated pixel has a value greater than a minimum value of neighboring pixels and less than a maximum value A method of discriminating color filter array of digital camera using median value aggregation. The method according to claim 1,
Wherein the positioning of the green channel, the red channel, and the blue channel is initialized to a value of a red channel and a blue channel, and is determined using a difference between the aggregated values of red and blue. Color filter array identification method.
The method of claim 3,
Wherein the value of the initialization is "0 ".
3. The method of claim 2,
Wherein the pattern of the neighboring pixels is one of a cross, a vertical, a horizontal, and a quincunx.
The method according to claim 1,
The judgment of the forgery and falsification is made by comparing the type of the color pattern array determined through the median value aggregation with the pattern of the region suspected of manipulation of the image and judging the region where the pattern type does not match as the manipulated region A method for discriminating color filter array of a digital camera using intermediate value aggregation.
3. The method of claim 2,
The maximum value and the minimum value may be calculated using Equation

(Where I represents the positional coordinates of the image, c represents a cross, h represents horizontal, and v represents vertical). A method of determining a color filter array of a camera.
An image obtaining unit obtaining single image information;
An intermediate value setting unit for estimating the shape of the color filter array using the single image information and counting the number of pixels matching the condition using the intermediate value condition;
The position of the green channel is first determined using the aggregated values of the color channels, the positions of the remaining red and blue channels are determined according to the difference of the aggregated values, Estimation unit estimating unit; And
A judging unit for judging the forgery and falsification of the image using the estimated color filter arrangement;
Wherein the color filter array discriminating device comprises:

Images