KR20110003809A - System for watermarking in various illumination and method therefor - Google Patents

Abstract

PURPOSE: A watermarking system in various illumination environment for improving geometric transformation attack and D-A/A-D conversion attack in the use of a watermark expansion repetition pattern is provided to insert the watermark in an area of low noise by using the complex masking. CONSTITUTION: A watermark generator(100) generates a watermark basic pattern. A masking unit(200) analyzes brightness information data of a watermark insertion position. The masking unit obtains a complex masking value. A complex masking weight calculator(300) calculates the complex masking weight. A watermark insertion unit(400) generates a watermark insertion frame.

Description

Watermarking system and its method in various illuminance environments {SYSTEM FOR WATERMARKING IN VARIOUS ILLUMINATION AND METHOD THEREFOR}

The present invention is a video watermarking technique having robustness against camcorder attack in various illuminance, and more specifically, it analyzes the cognitive visual system to ensure the robustness and invisibility of the watermark inserted into the spatial region of each video frame. The present invention relates to a watermarking system and a method thereof in various illumination environments using complex masking.

The remarkable growth of information and communication technology based on wired and wireless networks and the popularization of the Internet are acting as a catalyst for the development of multimedia content service providing technology such as digital voice, still image, and video.

In addition, with the expansion of the large display market that has evolved from the analog CRT to digital LCD or PDP, users' demand for high-quality digital contents is increasing, and the type and quantity of high-quality digital contents provided in accordance with this are rapidly increasing. .

Terrestrial and cable TV began to broadcast full-HD broadcast video in earnest, and the movie market is expanding the 'digital cinema' market, which enables high-quality movie screening instead of traditional analog film. However, this trend is accelerating piracy and illegal distribution of digital content. Digital content is easier to edit, store, and transmit than existing analog content, and it is easy to produce and disseminate the same copy as the original without the deterioration of image quality. Therefore, it is urgent to develop a technology for preventing illegal copying and distribution of high quality digital contents.

Recently, watermarking technology has been in the spotlight as DRM (Digital Right Management) technology for digital video contents. However, the existing video watermarking technology does not fully play a role of protecting various types of digital video contents. Particularly, in case of high quality video content, the inserted watermark is easily removed while being converted and edited for a high resolution LCD display device as well as a portable device such as a portable multimedia player (PMP) or a personal digital assistant (PDA). In addition, the growth of the 'digital cinema' industry is also less robust to geometric variations and illuminance changes caused by illegal camcorder shooting. Therefore, the newly proposed high quality video watermarking technology must survive such a complex and complex attack.

Digital watermarking technology applied to high quality video must satisfy the characteristics of invisibility, robustness, and real-time simultaneously.

Invisibility means that the inserted watermark should not be detected by human vision, and the damage of the inserted content should be less than that of the original. In the case of digital contents that are recently being distributed, invisibility is very important because the ratio of full-HD video is high and is often displayed on a high resolution LCD or PDP. Robustness means that the inserted watermark should be detectable even after intentional or unintentional attack. Unintentional attacks on moving images mean that the watermark is removed or weakened by an action other than the purpose of removing the inserted watermark. Format changes, size conversions, and frame rate conversions are examples of unintended attacks that make video distribution and storage easier.

Also included are attacks by digital-to-analog / analog-to-digital conversion that occur during camcorder photography. Unintentional attacks by camcorder shooting cause complex geometrical deformations and distortions in the photographed image according to various illuminances that may occur during shooting. Intentional attack refers to the acts on video content for the purpose of removing the watermark. This includes collusion attacks and denoising filtering attacks to remove watermarks. In general, the invisibility and toughness required for watermarking technology are traded off. Increasing the strength of the watermark to increase the invisibility lowers the toughness, while increasing the strength of the watermark to increase the invisibility lowers the visibility. Therefore, it is necessary to develop a video watermarking algorithm that satisfies the two characteristics.

Finally, the real-time nature of the video watermarking algorithm is an increasingly important feature as the size of video content increases. In actual watermark applications such as IPTV (set-top box) or digital cinema, the watermark must be inserted at the same time as the image is displayed, so the real time of the insertion algorithm is more than the real time of the detection algorithm. A little more important.

Among the existing high quality video watermarking techniques, there are several watermarking techniques to solve the watermark detection problem for camcorder shooting and complex transformation attack.

Haitsma & Kalker inserted the watermark by viewing the image as a signal on the 1D time axis and adjusting the brightness value of each frame. This method has the advantage of being robust to geometric distortion of the image and the simple algorithm, but has a problem of flickering due to the brightness change between frames.

Delannay proposed a watermarking technique that can compensate for geometrical transformations that occur during camcorder photography. However, since the original image is needed for watermark detection, it is not practical. In addition, watermark detection has a disadvantage in that a time synchronization operation between the camcorder video and the original video must be performed.

Honsinger proposed a robust technique against camcorder shooting attacks by applying repeated watermark patterns and autocorrelation functions, but shows poor results in terms of invisibility. Lubin proposed a watermarking method that inserts watermark patterns into low frequency bands temporally and spatially to ensure invisibility, robustness, and illegal watermark removal. All of the existing watermarking techniques mentioned above consider the watermark's invisibility and robustness against attack, but do not completely solve camcorder shooting and conversion attack.

Existing video watermarking algorithms use various perceptual models using the Human Visual System (HVS) to satisfy invisibility. Among them, Voloshynov-skiy's Noise Visibility Function (NVF) applied to still images shows relatively good performance. However, NVF is difficult to apply to Full-HD video because of its high computational complexity. This is because real-time watermark embedding requirements must be satisfied in HD video watermarking.

The present invention has been made in view of the above problems, and various illumination environments using complex masking based on cognitive visual system analysis to ensure the robustness and invisibility of a watermark inserted into a spatial region of each video frame Its purpose is to provide a watermarking system and method thereof.

The present invention for achieving the technical problem relates to a watermarking system in a variety of illuminance environment, using a secret key and a message, to generate a watermark basic pattern to be inserted into a frame, a predetermined size that repeats the basic pattern A watermark generator for generating a final pattern of the watermark; A masking unit which obtains a complex masking value by analyzing brightness information data of an area corresponding to a watermark insertion position based on an original image frame; A composite masking weight calculator configured to calculate a final composite masking weight using each weight calculated by the masking unit; And a watermark inserting unit generating a watermark embedding frame by adding an original image frame based on a value calculated by the complex masking weight calculator. It includes.

Meanwhile, the present invention relates to a watermarking method in various illuminance environments, wherein (a) the watermark generator generates a watermark basic pattern to be inserted into one frame using a secret key and a message, and repeats the basic pattern. Generating a final pattern of a predetermined size; (b) a process of obtaining, by the masking unit, a complex masking value by analyzing brightness information data of a region corresponding to a watermark insertion position based on the original image frame; (c) calculating, by the complex masking weight calculator, the final complex masking weight using the respective weights calculated by the masking unit; And (d) generating a watermark embedding frame by adding an original image frame to a value calculated by the complex masking weight calculating unit by a watermark embedding unit; Characterized in that it comprises a.

According to the present invention as described above, by using complex masking, it is possible to strongly insert the watermark in the area where the human eye is insensitive to noise, and by using the watermark extension repeating pattern, the DA / AD conversion attack and the geometric There is an effect that can increase the robustness against deformation attacks.

In addition, the present invention can be utilized as a technology for preventing illegal copying and distribution of high-definition content, and it is also possible to apply not only a PC but also a display device having limited performance such as a mobile phone, a PMP, a set-top box, and the like.

Specific features and advantages of the present invention will become more apparent from the following detailed description based on the accompanying drawings. In the meantime, when it is determined that the detailed description of the known functions and configurations related to the present invention may unnecessarily obscure the subject matter of the present invention, it should be noted that the detailed description is omitted.

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

The watermarking system and its method in various illuminance environments according to the present invention will be described with reference to FIGS. 1 to 7.

1 is an overall configuration diagram conceptually illustrating a watermarking system (hereinafter, referred to as a 'watermarking system') S in various illuminance environments according to the present invention, as shown in FIG. The unit 200 includes a complex masking weight calculator 300 and a watermark inserter 400.

The watermark generator 100 generates a watermark basic pattern to be inserted into one frame by using a secret key and a message, and generates a final pattern of a predetermined size by repeating the basic pattern. As shown in FIG. 1, a basic pattern generation module 110 and a final pattern generation module 120 are included.

In order to generate a watermark basic pattern to be inserted into one frame, the basic pattern generating module 110 uses a secret key and a message, having a size of 48 × 48 along a Gaussian distribution having a mean of 0 and a variance of 1. A block is created, and a 48 × 48 block is expanded three times in length and width, respectively, to generate a watermark basic pattern of 144 × 144 size.

Here, the reason for extending the block three times is to enhance the low frequency characteristics of the pattern and to provide the robustness for D → A / A → D (digital → analog / analog → digital) conversion. This expansion also increases the robustness against size transformation attacks.

Theoretically, when a watermark is inserted into a Full-HD (High Definition) image of 1920 x 1080 size, the inserted watermark is detected even in a 640 x 360 size image reduced by 1/3 in width and height. Can be.

Another advantage of pattern expansion is that it can increase the robustness against image translation attacks. The watermark detection system determines whether a watermark is inserted using a cross correlation coefficient between the estimated watermark and the reference watermark pattern.

When the watermark pattern is expanded n times in width and length, it may have a relatively high cross-correlation coefficient value up to n-1 times in the left, right, up, and down directions, respectively. If you expand 3 times, you can solve the problem of synchronous destruction caused by 2 pixels of movement up, down, left, and right. This method is combined with the method using autocorrelation coefficients to solve the problem of loss of synchronization due to camcorder shooting. However, this method has a disadvantage of impairing visibility because it blocks the watermark pattern.

Accordingly, in order to solve this problem, the basic pattern generation module 110 according to the present invention includes a low pass filter 111 for the extended pattern as shown in FIG. 2. Through the low pass filter 111, a blocking phenomenon due to expansion and repetition may be reduced.

2 illustrates an example of generating, extending, repeating, and inserting a watermark pattern. The final pattern generation module 120 generates a watermark having a size of 144 x 144 generated by the basic pattern generation module 110. As shown in the drawing, the basic pattern is repeated five times horizontally and five times vertically to finally generate a 720 x 720 size watermark final pattern.

The repeated pattern has a characteristic that shows high autocorrelation at regular intervals, and thus may be used for geometric transformation estimation using autocorrelation function calculation. In addition, even if a part of the image is novel, the remaining repeated watermark pattern can be used, so that it is robust to a cropping attack.

The size of the final pattern generated repeatedly is 720 x 720. Since this size is based on a 1920x1080 Full-HD image, if the input image is smaller or larger than Full-HD, it is necessary to change the size of the final pattern.

The size is determined proportionally by calculating the relative ratio with the input video based on the Full-HD standard. The pattern generated by this process is located at the center of the input video brightness information.

In addition, the masking unit 200 performs a function of analyzing the brightness information data of the area corresponding to the watermark insertion position based on the original image frame to obtain a complex masking value, as shown in FIG. 1. The masking module 210, the brightness masking module 220, and the movement masking module 230 are included.

The purpose of this complex masking is to insert the watermark to be inserted as strongly as possible without being noticed by humans. Therefore, all three masks that make up complex masking consider the Human Visual System (HVS).

This complex masking technique increases the invisibility of the watermark and at the same time ensures the robustness of the watermark to survive the illuminance change attack that may occur during cam shooting.

First, the Noise Visibility Fuction (NVF) masking module 210 calculates a function indicating the degree of noise (NVF) when noise is added to an image.

At this time, the image has different values depending on the region characteristics of the image, and the value is between 0 and 1. The resulting value of the NVF is close to 1 in flat regions where there is little change of the image, and near the contour or the rough edges. or textured regions). Masks using NVF are more robust against noise rejection than Laplacian filters, and are more invisible to watermark embedded images.

는 지역별 분산(local variance)을,

는 영상에서의 최대 지역별 분산(maximum local variance)을, D

[50, 150] 는 실험적 조정 값을 나타내고 있다.That is, the NVF masking module 210 calculates the NVF through the following [Equation 1]. here,

Is the local variance,

Is the maximum local variance in the image, D

[50, 150] represent experimental adjustment values.

[Equation 1]

를 다음의 [수식 2] 에 의해 계산한다. In addition, the NVF masking module 210 is the local texture masking weight to obtain

Is calculated by the following [Equation 2].

를 구한다.In the equation, S ₀ and S ₁ determine the watermark embedding strength according to the regions where the change of the local component values is small and the regions where the variation is small. In other words, the local texture masking weights are calculated by using NVF values obtained from local component values and two appropriate values (S ₀ and S ₁ ).

.

[Equation 2]

As will be described later, the local texture masking weight calculated by the NVF masking module 210 is finally multiplied by the watermark after calculation with the weight values obtained through the other two maskings.

The watermarking system S according to the present invention was selected as S ₀ = 5.0 and S ₁ = 1.0 in consideration of the robustness after the watermark insertion, the peak signal to noise rate (PSNR), and the subjective quality level.

The computational complexity of obtaining mask values from these NVFs is quite large. Therefore, the NVF masking module 210 according to the present invention, as shown in Figure 3 in order to satisfy the real-time for the watermark embedding in the HD image in the watermark embedding process, 720 × 720 size of the insertion region The NVF is calculated after reducing the size to 1/2 of the width and 1/2 to the length. The NVF value of the reduced size is expanded to the original insertion area size and applied.

On the other hand, the human eye has a characteristic insensitive to the amount of change in the pixel where the brightness around the pixel is relatively dark or bright. FIG. 4 illustrates an allowable change amount according to a peripheral brightness value of a pixel in consideration of a human visual system (HVS) side. According to the graph of FIG. 4, it can be seen that when the ambient brightness value of a pixel is around 75, it is most sensitive to the corresponding pixel change amount, and is insensitive to the corresponding pixel change at an ambient brightness value close to 0 or 255. By using this feature, if you insert the watermark value after adjusting the intensity of the watermark value according to the pixel value, it becomes possible to insert more strongly without being noticeable.

의 주변 밝기 값

을 구하는 수식이다. Equation 3 below is a specific pixel at position (x, y) in frame t.

Ambient brightness value of

Is the formula to obtain.

[Equation 3]

At this time, B (i, j) of the 5x5 size is as follows.

을 계산한다.The watermarking system S according to the present invention uses a table reference method when obtaining a brightness masking value to satisfy real-time. That is, the brightness masking module 220 pre-creates the weight table defined according to the graph shape of FIG. 4, which is an allowable change amount graph according to the brightness value, and then, when inserting, the brightness weighting value by simply referring to the table.

.

[Equation 4]

On the other hand, according to the HVS for video, the human eye is less sensitive to noise in a region with a lot of motion than a region with a little movement. The motion masking technique uses such characteristics to compare the before and after frames, inserting the watermark hard in the region with large motion, and weakly inserting the region in the small motion. In video compression techniques such as MPEG and H.264, motion vectors are used as a method of determining whether each region moves in the current frame.

This technique is a method of predicting motion by dividing an image into blocks of a certain size and then comparing the block of the current frame to measure the motion with the block value around the position in the previous or subsequent frame. However, the computational complexity is so large that it is difficult to apply to real time high quality video watermarking techniques.

) 를 계산한다. Therefore, in order to satisfy real time, the motion masking module 230 according to the present invention determines the motion of the local area by using the local average value of the before and after frames. That is, the motion masking module 230 obtains the motion amount of the current frame compared to the previous frame through the following [Equation 5], and tabulates the graph of FIG.

) Is calculated.

Specifically, the value of md (x, y, t) is obtained by the following [Equation 5], the graph of FIG. 5 is tabulated, and the motion masking weight is obtained by using [Equation 6].

[Equation 5]

[Equation 6]

값은 따로 구할 필요 없이 밝기 마스킹을 계산할 때 구해진 값을 사용하면 되기 때문에 움직임 마스킹 가중치 계산 복잡도는 매우 낮아진다. here,

The complexity of the motion masking weight calculation is very low because the calculated value can be used when calculating the brightness masking without any value.

)를 계산한 후, 워터마크 생성부(100)를 통해 생성된 워터마크 최종패턴(W)과 곱을 수행한다.The complex masking weight calculator 300 uses the respective weights calculated by the masking unit 200 to determine the final composite masking weight (

) Is multiplied by the watermark final pattern W generated by the watermark generator 100.

)를 계산한다. That is, by applying each weight calculated through the masking unit 200 to the following [Equation 7], the final complex masking weight (

Calculate

[Formula 7]

와

값은 최종 복합적 마스킹 가중치의 세기를 조절하는 값으로서 0부터 1 사이의 값을 갖게 된다. 이렇게 계산된 최종 복합적 마스킹 가중치(

)는 삽입할 워터마크 패턴을 영상의 거친 지역, 밝기가 상대적으로 어둡거나 밝은 부분, 그리고 프레임간 움직임이 심한 곳에 좀 더 강하게 삽입될 수 있도록 하는 역할을 한다.here

Wow

The value adjusts the strength of the final complex masking weight and has a value between 0 and 1. The final composite masking weight calculated this way (

) Allows the watermark pattern to be inserted more strongly to be inserted in the rough area of the image, the relatively dark or bright part of the image, and the place where the movement between the frames is severe.

As described above, the complex masking technique applied to the watermark system S proposed in the present invention imparts robustness in which an inserted watermark can be detected even for an image photographed in various illumination environments.

)와, 워터마크 생성부(100)를 통해 생성된 워터마크 최종패턴(W)과 곱을 수행한다. Afterwards, the complex masking weight calculator 300 calculates the complex masking weight (

) And the watermark final pattern W generated by the watermark generator 100.

The watermark inserting unit 400 generates a watermark embedding frame Y by adding the original image frame X to the value calculated by the complex masking weight calculator 300.

The process as described above may be represented as in [Equation 8].

[Equation 8]

The watermarking method using the above-described system S will be described with reference to FIGS. 6 to 8 as follows.

6 is a flowchart illustrating a watermarking method in various illuminance environments according to the present invention, FIG. 7 is a detailed flowchart illustrating a process of generating a watermark final pattern according to the present invention, and FIG. 8 is a complex diagram according to the present invention. A detailed flow chart of the process of obtaining masking values.

As shown in FIG. 6, the watermark generator 100 generates a watermark basic pattern to be inserted into one frame using a secret key and a message, and generates a final pattern of a predetermined size in which the basic pattern is repeated. Perform the process (S100).

In detail, as illustrated in FIG. 7, the basic pattern generation module 110 of the watermark generator 100 may generate a watermark basic pattern to be inserted into one frame by using a secret key and a message. Create a 48 x 48 block with a Gaussian distribution of 0 and a variance of 1, and expand the 48 x 48 block three times horizontally and vertically to create a 144 x 144 watermark base pattern. It generates (S110). At this time, in order to prevent the invisibility from being impaired due to the blocking of the pattern, the blocking phenomenon is reduced through the low pass filter 111 (S120).

Thereafter, the final pattern generation module 120 repeats the 144 x 144 size watermark basic pattern generated by the basic pattern generation module 110 horizontally 5 times and vertically 5 times to finally produce 720 x 720 size water. A mark final pattern is generated (S130).

Next, as shown in FIG. 6, the masking unit 200 analyzes brightness information data of a region corresponding to the watermark insertion position based on the original image frame to obtain a complex masking value (S200). ).

) 를 상기 [수식 2] 에 의해 계산한다(S220). In detail, as illustrated in FIG. 8, the NVF masking module 210 of the masking unit 200 calculates the degree of noise, that is, the NVF when noise is added to the image through Equation 1 (S210). Afterwards, the NVF masking module 210 calculates the local texture masking weight (

) Is calculated by the above Equation 2 (S220).

)를 계산한다(S230).In addition, the brightness masking module 220 pre-creates a weight table defined according to the shape of the allowable variation graph according to the brightness value in consideration of the human visual system (HVS) aspect, and then, when inserted, refers to the brightness weight (

) Is calculated (S230).

) 를 계산한다(S240).In addition, the motion masking module 230 obtains the motion amount compared to the previous frame by using [Equation 5] and [Equation 6] motion masking weight (

) Is calculated (S240).

)를 계산한 후, 워터마크 생성부(100)를 통해 생성된 워터마크 최종패턴(W)과 곱을 수행한다(S300).Next, as illustrated in FIG. 6, the complex masking weight calculator 300 may use the respective weights calculated by the masking unit 200 to determine the final complex masking weight (

) Is multiplied by the watermark final pattern W generated by the watermark generator 100 (S300).

,

,

을 이용하여, 상기 [수식 7] 에 의해 계산된 복합적 마스킹 가중치(

)와, 워터마크 생성부(100)를 통해 생성된 워터마크 최종패턴(W)과 곱을 수행한다. That is, the complex masking weight calculation unit 300 is a weight

,

,

Using the complex masking weight calculated by Equation 7

) And the watermark final pattern W generated by the watermark generator 100.

As shown in FIG. 6, the watermark inserting unit 400 generates the watermark embedding frame Y by adding the original image frame X to the value calculated by the complex masking weight calculating unit 300. (S400).

The watermarking system (S) having the above-described configuration and characteristic functions implements an efficient algorithm for real-time watermark insertion for Full-HD-quality high-definition images and applies hardware acceleration functions.

The most complex computational part of the watermarking insertion system is the complex masking weight. In order to reduce the amount of calculation for this part, the calculation was performed on the reduced area as shown in FIG. 2, and the speed was increased by a table reference method to obtain the brightness masking weight.

When motion masking was calculated, the motion was judged based on the local mean value of the front and back frames. At this time, the local average value was obtained by using the value obtained when calculating the brightness masking to enable efficient and fast calculation.

As described above and described with reference to a preferred embodiment for illustrating the technical idea of the present invention, the present invention is not limited to the configuration and operation as shown and described as described above, it is a deviation from the scope of the technical idea It will be understood by those skilled in the art that many modifications and variations can be made to the invention without departing from the scope of the invention. Accordingly, all such suitable changes and modifications and equivalents should be considered to be within the scope of the present invention.

1 is an overall configuration diagram conceptually showing a watermarking system in various illuminance environments according to the present invention.

2 is an exemplary view showing generation, extension, repetition, and insertion area of a watermark pattern according to the present invention;

Figure 3 is an exemplary view showing the NVF calculation process for satisfying the real-time properties of watermark embedding in HD-quality video according to the present invention.

Figure 4 is a graph showing the allowable amount of change in accordance with the brightness value in consideration of the HVS side according to the present invention.

5 is a graph showing a motion weight according to an operation value using local brightness values of a frame before and after considering an HVS aspect according to the present invention.

6 is an overall flowchart of a watermarking method in various illuminance environments according to the present invention;

7 is a detailed flowchart of a process of generating a watermark final pattern according to the present invention;

8 is a detailed flowchart of a process of obtaining a complex masking value according to the present invention.

** Description of symbols for the main parts of the drawing **

100: watermark generation unit 200: masking unit

300: complex masking weight calculation unit 400: watermark insertion unit

110: basic pattern generation module 120: final pattern generation module

210: NVF masking module 220: brightness masking module

230: motion masking module

Claims (17)

In watermarking systems in various illumination environments, A watermark generator 100 generating a watermark basic pattern to be inserted into one frame using a secret key and a message, and generating a final pattern of a predetermined size in which the basic pattern is repeated; A masking unit 200 that obtains a complex masking value by analyzing brightness information data of an area corresponding to a watermark insertion position based on an original image frame; The final composite masking weights using the respective weights calculated by the masking unit 200 (

A complex masking weight calculation unit 300 for calculating); And A watermark inserting unit 400 generating a watermark embedding frame by adding an original image frame based on a value calculated by the complex masking weight calculating unit 300; Watermarking system in a variety of illuminance environment comprising a. The method of claim 1, The watermark generation unit 100, Using a secret key and a message, a block having a predetermined size that follows a Gaussian distribution having a mean of 0 and a variance of 1 is generated, and the predetermined size of the block is expanded horizontally and vertically to generate a watermark basic pattern of the expanded size. A basic pattern generation module 110 for generating; And A final pattern generation module 120 repeating the watermark basic pattern generated by the basic pattern generation module 110 horizontally and vertically a predetermined number of times to finally generate a watermark final pattern having a predetermined size; Watermarking system in a variety of illuminance environment comprising a. The method of claim 2, The basic pattern generation module 110, In order to reinforce the low frequency characteristics of the pattern to give robustness to D → A / A → D (Digital → Analog / Analog → Digital) conversion, various illuminances each of which extends the block of a predetermined size horizontally and vertically Watermarking System in the Environment. The method of claim 2, The basic pattern generation module 110, A low pass filter 111 for reducing blocking due to expansion of the pattern; Watermarking system in a variety of illuminance environment further comprises. The method of claim 1, The masking unit 200, Calculate the NVF where the noise appears when the image is noisy, and use the local texture masking weight (

NVF masking module 210 to calculate a; Refer to the weight table to determine the brightness weight value (

A brightness masking module 220 for calculating); And The motion masking weight is determined by determining whether or not the motion of the local area is performed using the local average value of the before and after frames.

A movement masking module 230 for calculating a); Watermarking system in a variety of illuminance environment comprising a. The method of claim 5, The NVF masking module 210 calculates an NVF through Equation 1 below. [Equation 1]

here,

Is the local variance,

Is the maximum local variance in the image, D

[50, 150] is the experimental adjustment value. The method of claim 5, The NVF masking module 210, based on the NVF through the formula [2] below the texture texture masking weight (

Watermarking system in various illuminance environments, [Equation 2]

Where S ₀ and S ₁ are the watermark embedding strengths according to the regions where the variation of the local component values is small and the regions are large. The method of claim 5, The NVF masking module 210, A watermarking system in various illumination environments, characterized in that the NVF is calculated after reducing an insertion region having a predetermined size to a predetermined size horizontally and vertically, and applying the reduced size of the NVF value back to the original insertion region size. The method of claim 5, The weight table is a watermarking system in various illuminance environments, characterized in that the weight table is defined according to the allowable change amount according to the brightness value. The method of claim 5, The brightness masking module 220 may refer to the weight table to determine a brightness weight value through Equation 4 below.

Watermarking system in various illuminance environments, [Equation 4]

here,

Is a specific pixel at position (x, y) in frame t

Ambient brightness value of. The method of claim 5, The motion masking module 230 obtains the local mean value (md (x, y, t)) of the front and back frames through [Equation 5] below, and calculates an operation value using the area brightness value of the front and back frames. After graphing the motion weight according to the table, the motion masking weight (

Watermarking system in a variety of illuminance environments, characterized in that the. [Equation 5]

[Equation 6]

The method of claim 1, The complex masking weight calculation unit 300, The weight calculated by the masking unit 200 (

,

,

) Is applied to Equation 7 below to obtain the final composite masking weight (

) And multiply the watermark final pattern (W) generated by the watermark generation unit (100). [Formula 7]

The method of claim 1, The watermark inserting unit 400, In various illumination environments, the watermark embedding frame Y is generated by adding the original image frame X to the value calculated by the complex masking weight calculator 300 through Equation 8 below. Watermarking system. [Equation 8]

In the watermarking method in various illumination environments, (a) generating, by the watermark generator 100, a watermark basic pattern to be inserted into one frame using a secret key and a message, and generating a final pattern of a predetermined size in which the basic pattern is repeated; (b) a process of obtaining, by the masking unit 200, a complex masking value by analyzing brightness information data of an area corresponding to a watermark insertion position based on the original image frame; (c) the composite masking weight calculation unit 300 uses the respective weights calculated by the masking unit 200 to determine the final composite masking weight (

) And multiplying the watermark final pattern (W) generated by the step (a); And (d) the watermark inserting unit 400 generating the watermark embedding frame Y by adding the original image frame X to the value calculated by the complex masking weight calculating unit 300; Watermarking method in a variety of illuminance environment comprising a. The method of claim 14, The (a) process, (a-1) generating, by the basic pattern generation module 110, a block having a predetermined size according to a Gaussian distribution having a mean of 0 and a variance of 1 using a secret key and a message; (a-2) generating, by the basic pattern generation module 110, the watermark basic pattern of the expanded size by expanding the blocks having the predetermined size horizontally and vertically; And (a-3) The final pattern generation module 120 repeats the watermark basic pattern generated by the basic pattern generation module 110 horizontally and vertically a predetermined number of times to finally generate a watermark final pattern having a predetermined size. step; Watermarking method in a variety of illuminance environment comprising a. The method of claim 14, Step (b) is, (b-1) the NVF masking module 210 calculates an NVF which is a degree of noise when noise is added to an image; (b-2) The local texture masking weight value desired by the NVF masking module 210 (

Calculating; (b-3) The brightness masking module 220 pre-creates the weighting table defined according to the shape of the allowable change amount graph according to the brightness value, and then refers to the table when inserting the brightness weighting value (

Calculating; And (b-4) The motion masking module 230 determines whether or not the motion of the local area is moved by using the local mean value of the before and after frames.

Calculating; Watermarking method in a variety of illuminance environment comprising a. The method of claim 15, After step (a-2) and before step (a-3), (a-2-1) the basic pattern generating module 110 reducing the blocking phenomenon due to the expansion of the pattern through the low pass filter 111; Watermarking method in a variety of illuminance environment further comprising a.

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