KR20010102892A - Method for watermarking of vector image - Google Patents

Abstract

The present invention relates to a method of inserting a watermark as copyright information into a vector image file having a vector-based two-dimensional or three-dimensional image and extracting the inserted watermark without an original. The present invention largely consists of a watermark embedding process and a watermark extraction process. The watermark embedding process includes creating basic parameters that do not affect the change of coordinate values, ordering for each object included in the vector image, and inserting information to express information on curves or surfaces including NURBS curves. And an insertion unit including a position selection step of selecting a position of the position, an insertion designation process of specifying a watermark insertion position based on the position selection, and an insertion step of inserting the watermark. The watermark extraction process includes an object order confirmation step for extracting the inserted watermarking, an insertion position search step for searching the insertion position based on the object order confirmation process, a confirmation step for extracting information inserted into a curve or surface, and Based on this, a watermark extraction step of extracting a watermark by extracting a basic vector is performed.

Description

Method for watermarking of vector image}

The present invention is to prevent the illegal use of the data of the image file used for computer graphics, computer drawing drawings, or the production of vector image characters using a computer to produce a shape or picture that cannot be expressed by a human The present invention relates to a watermarking technology that detects forgery and deformation by inserting the copyright information of a copyright holder into the file, and discriminates the owner. In particular, a watermarking method for extracting an inserted watermark by inserting a watermark into a vector image It is about.

Computer graphics is an innovative field that can change the existing concept of superior expressive ability, expressive technique, function and economy from copying and production. Computer graphics are widely used in almost every design. In particular, with the spread of commercialization and popularization of arts, designers are incessant to supply endlessly new designs to be selected. Due to the fact that computer graphics are used to speed up the process of creation, due diligence cannot be expressed by hand. Their image composition can be easily performed, and unexpected effects and various results can be easily obtained.

In particular, programs using vectors are widely used in the following fields. Graphic tool programs for obtaining computer graphics images include graphic editors and 3D tools. CG (ComputerGraphics) works programs are dedicated programs that display computer graphics images. There is a math program that emphasizes fractal shapes, and the function programs for basic drawing to express computer graphics are 2D, 3D graphic library, and a program for basic functions to express CG in games. Etc. These programs are widely used in subtitles and pictures required for the production of various commercial films, films, and dramas, and their application ranges are diverse in the fields of web, animation, printing, clothing, and architectural design. It is not an exaggeration to say.

However, due to the nature of digital information, not only the same copy or modified version as the original can be easily produced, but also easy to distribute, and thus illegal copying and distribution such as digital information has appeared. In particular, computer graphic files including vector programs require a relatively high cost and time at the time of production, so in case of illegal copying or distribution, the loss of the copyright or motivation of creation of the creator, as well as individual, corporate and national As it may cause a loss, it is urgent to manage and protect the copyright.

Watermarking technology is a technique of inserting a copyright holder's logo or authentication information into data for the purpose of user authentication or copyright protection, and the owner of the data can be identified by such technology. At present, various watermarking technologies for protecting various contents such as image, audio and video have been studied or studied.

However, research on two-dimensional graphics and three-dimensional digital data models as multimedia contents is difficult to develop technology compared to studies on other contents due to the shape structure of the model. Currently, new algorithms and methods have been tried. Until now, no clear solution has been established.

Accordingly, an object of the present invention is to provide a watermarking method for inserting watermarks for copyright information and various information in order to protect the copyright of a file for content produced by various vector images used by individuals and companies.

In order to achieve the above object, the present invention analyzes the overall configuration of a vector image based on a set of straight lines, curves, surfaces, polyhedrons, and points, which are components of the vector image, and changes the result even by applying various transformations including similar transformations. A new scale is created by defining a phase invariant with no and then the information is inserted into the vector image based on the scale and extracted again. The information to be inserted may be various according to the purpose of the user. For example, authentication information for the creator of a vector image file, identification information on the owner of the file, information on the use of the owner company, information to prevent unauthorized distribution, file creation date management information, inventory management information, and restraining information for unauthorized copying. For example, it can contain information on unauthorized copying, record of confidential information, and information about the distribution process. In addition, the present invention extracts the information inserted into the vector image accurately and without error.

1 is a view for explaining an operation of embedding a watermark in a vector image according to an embodiment of the present invention.

2 is a diagram for explaining an operation of extracting a watermark from a vector image according to an embodiment of the present invention.

3 is a schematic block diagram of an apparatus for embedding a watermark in a vector image according to an embodiment of the present invention;

4 is a schematic block diagram of an apparatus for extracting a watermark from a vector image according to an embodiment of the present invention;

5 is a view for explaining the selection, range, and calculation method of each object for quantifying a measure from a vector image according to an embodiment of the present invention;

6 is a diagram for explaining a difference between a bitmap image and a vector image.

7 is a view for explaining a method of aligning each object of a vector image according to an embodiment of the present invention;

Hereinafter, exemplary embodiments of the present invention will be described in detail with reference to the accompanying drawings. In the following description, specific details such as specific components are shown, which are provided to help a more general understanding of the present invention, and it is understood that these specific details may be changed or changed within the scope of the present invention. It is self-evident to those of ordinary knowledge in Esau.

First, the term vector image used throughout the detailed description of the present invention will be described. The term vector image used in the present invention is a graphic produced by using a commonly used vector image creation tool, Adobe Illustrator, 3D Studio Max, Corel Draw, AutoCAD, Maya, etc. Unlike bitmap-type images (including "jpeg" files and "gifs" based on compression techniques) that give and values, they are graphics that are displayed as functions based on the properties of a vector. For example, in case of displaying one line, in case of bitmap type image, pixel value is assigned according to each position, but in case of vector image, coordinate of start point and end point (regardless of order) can be given and the coordinate The line is constructed based on a series of instructions based on the value. That is, it is expressed in the form of a function such as "line (star point, end point)". When enlarged, a bitmap-type image shows a matrix form, and when it is a vector image, there is no change. 6 shows a difference between a bitmap image and a vector image that appear when enlarged. FIG. 6A illustrates an enlarged line in the form of a bitmap image, and FIG. 6B illustrates an enlarged line in the form of a vector image.

The present invention quantifies the property of a vector to insert information into a vector image to implement information on a scalar basis, and combines the properties of a set of points, straight lines, curves, surfaces, and polyhedrons, which are components of the vector image. Realize a scalar implementation of the information you want to insert. Therefore, the present invention can be applied to any type of vector image produced by a tool (eg, * AL, * .MAX, * .DXF, * .3DS, etc.). In addition, since watermark information is displayed as a scalar without depending on the vector property, which is characteristic of the vector image, extraction is performed regardless of similar transformations such as zooming, translation, rotation, etc. of the vector image caused by the vector property. Make it possible. By treating each object included in the vector image independently in the entire vector image, the watermark can be extracted not only in the expansion / reduction of the entire image but also in the localization of the local object.

The present invention can be broadly divided into two processes, one for inserting a vector image watermark and the other for extracting a watermark embedded in a vector image.

The process of embedding a vector image watermark involves creating a basic factor that does not affect changes in coordinate values and various basic mapping, ordering for each object in the vector image, and three-dimensional (one-dimensional) Positioning step of selecting the position of the information (watermark) to be inserted in order to represent the information in the model, converting the watermark information to be inserted into an insertable information form And an embedding step 300 of embedding a watermark.

The watermark extraction process includes an insertion position search step of searching for an insertion position where a watermark is inserted based on an object order checking step, an object order checking step required to extract the inserted watermark information, and information inserted into a curve or surface. There is a check step for extracting and a watermark extracting step of extracting a watermark by extracting a basic factor based on this.

A detailed description of the configuration of the present invention and the insertion / extraction of the vector image watermark will be described in detail with reference to FIGS. 1 and 3. 1 is a diagram illustrating an operation of inserting a watermark into a vector image according to an embodiment of the present invention, and FIG. 2 is a block diagram of an apparatus for inserting a watermark into a vector image according to an embodiment of the present invention. Is also In FIG. 1 and FIG. 3, a vector image is expressed in two ways. One was defined as cover-data as a vector image before the watermark was inserted, and the other as stego-data as a vector image with the watermark embedded therein.

First, referring to FIG. 3, the apparatus for inserting a watermark includes an information database 50 storing information to be inserted, and an image analyzer for analyzing a vector image into which the information is to be inserted and performing a series of operations for inserting the information. 10) a watermark generator 20 for extracting information to be inserted from the information database 50 and generating a watermark to be inserted, and the watermark generator in the vector image analyzed by the image analyzer 10; And a watermark inserting unit 30 for inserting the watermark generated at 20, and an image output unit 40 for outputting the watermarked image from the watermark inserting unit 30. Hereinafter, the operation of each functional unit will be described in more detail with reference to FIG. 1.

Referring to FIG. 1, an operation of inserting a watermark into a vector image may be roughly divided into three procedures 100, 200, and 300. The first procedure 100 is a procedure of analyzing a vector image to insert information into the vector image, which is a process of generating a basic factor (101), specifying a sequence (102), and selecting an insertion position (103). Can be divided into This first procedure 100 is performed by the image analyzer 10.

The second procedure 200 is a procedure of processing information to be inserted into a vector image into an insertable form. The second procedure 200 is divided into a data creation process 201, a constraint verification process 202, and a data generation process 203 to be inserted. Can be. This second procedure 200 is performed by the watermark generator 20.

The third procedure 300 is a process of inserting the inserted data 203 generated through the second procedure 200 into the vector image insertion position selected in the first procedure 100. The watermark insertion unit 30 Takes place).

Through the above three procedures, the vector image is changed from cover data to stego data.

The first process of the first procedure 100, that is, the process of generating a basic factor 100, is a key procedure of the present invention. Hereinafter, the procedure of generating the basic factor will be described in detail.

First, the basic factor must satisfy the following two conditions.

1) It should not be related to the change of coordinate value.

Using only the coordinate value itself as a basic argument is impossible to insert. Even if you can insert it, it will disappear after some basic conversion. For example, it is not possible to insert information into the coordinate values themselves, because typical coordinate transformations, that is, the most basic transformations such as translation, rotation, and zooming, will change the coordinate values themselves. Therefore, even when using coordinate values, there must be other criteria or factors. The basic factor proposed by the present invention also satisfies the above condition.

2) Cover data and stego data must be able to maintain certain independence.

According to the method for extracting the inserted information, watermarking techniques can be largely divided into two types. This is the case where the cover data is necessary for extracting the inserted information, and the case where the cover data is not necessary for extracting the inserted information. Inserting watermark information into a vector image means changing the vector image (cover-data) itself. In the present invention, the cover data is not required to extract information from the stego data. Therefore, there must be some independence between cover data and stego data.

In order to generate the basic factors satisfying the above two conditions, in the present invention, in particular, the characteristic of the vector image is analyzed and various transformations (for example, mapping transformation, affine transformation, projective transformation [射影 變換] ]) To be firm. In addition, the vector image does not consider vectorability but applies the concept of measure commonly used in metrology space to apply scalar shape, not vector.

The vector image can be divided into three types according to the composition of space. That is, it is a vector image of one-dimensional space [R], a vector image of two-dimensional space [R ² ], and a three-dimensional space [R ³ ] vector image. At this time, the one-dimensional space and the two-dimensional space can be considered as a special case of the three-dimensional space. Since the vector space itself contains the characteristics of the metrology, it is possible to apply to the measures used in the metrology space.

One-dimensional and two-dimensional spaces can be thought of as special cases of three-dimensional spaces in metrology spaces, but measures in metrological spaces in vector spaces are expressed differently in their construction. For example, a measure of one-dimensional space is represented by a length, a measure of a two-dimensional space is represented by an area, and a measure of a three-dimensional space is represented by a volume. These measures in metrology space are invariant for the translation or rotation transformations, which are the most basic transformations in vector image editing. That is, even when the mapping transformation is applied to a vector image, the measure in metrology space does not change.

In the case of a zoom (proportional transformation) transformation, which is one of similar transformations to a vector image, the scale is not invariant. In addition, there is a need to unify the components of the one-dimensional vector image, the components of the two-dimensional vector image, and the components of the three-dimensional vector image.

In the present invention, a new system constant is applied when constructing a basic factor so that it can be applied to both invariants irrelevant to the scaling (proportional) transformation and components of 1 to 3D vector images. On the basis, a proportional operation similar to the unit of scale is performed to form a basic factor.

Hereinafter, a process of configuring the basic factor value according to the present invention will be described in detail.

Step 1: First, analyze the basic elements included in the vector image. Components of a vector image include straight lines, curves, surfaces, polyhedra, and points. These straight lines, curves, surfaces, polyhedrons, points, etc. are combined to form one complete vector image. The analysis of the components of the vector image includes the following.

First, the function of the curve (or straight line, curved surface, polyhedron, etc.) of the vector image is composed. The function here refers to the representation of a curve (or straight line, surface, or polyhedron). In other words, is the method of constructing a curve (or straight line, curved surface, or polyhedron) using "Line"? Information on whether or not using a "spline" method or a NURBS method.

Second, how many dimensions are the space occupied by curves (or straight lines, surfaces, and polyhedrons)? The concept of space occupied by curves is a bit complicated. Vector images are often represented by the values of the coordinates displayed in the Cartesian coordinate system, which correlate with the maximum and minimum values in each direction among the coordinates of all points used to display the curve. For example, when one line segment is represented by two points (0, 0, 0) and (4, 4, 4), the section occupying the entire space of the line segment is determined by the two points.

Third, it is about how much spatial measure the curve (or straight line, curved surface, polyhedron, etc.) occupies in the whole vector image. The value of a measure is calculated | required according to the result obtained by the above process. ID and order are assigned to each image element based on the measure value.

Step 2: For each member selected, proceed as follows. If it is a one-dimensional element, it is a measure of its length as a measure of the one-dimensional range in which the object is contained. In the case of a two-dimensional element, the area is quantified as a measure of the two-dimensional range in which the object is included. In the case of a three-dimensional object, the volume is quantified as a measure of the three-dimensional range. The selection, range, and calculation method of each object for digitization will be described in detail with reference to FIG. 5 below (as an example of a three-dimensional measure) together with an equation used.

Symbols in mathematical representations of measures for convenience of explanation Use in this case, Is expressed as d for displaying a one-dimensional object, S for displaying a two-dimensional object, and V for displaying a three-dimensional object. 5 is a description of the quantization of the measure of the vector image. As shown in FIG. 5, in the case of a three-dimensional image, a measure is expressed as a volume value in the overall space. First, as shown in (a) of FIG. 5, based on the coordinate values of the x, y, and z axes of the xyz, yzx, and xzy planes. Obtain That is, the measure of the three-dimensional object is obtained by the following equation (1). Indeed, many vector image creation tools have defined these measures as immutable attributes of objects (examples of some object attributes are listed in Table 1 below).

_{= V = d 1 · d 2} · d 3

D ₁ · d ₂ · d ₃ in Equation 1 is a value relating to the X-axis, Y-axis, and Z-axis of “Dimensions” in the object property table (Table 1 below). Then, the distance between the point and the closest point is obtained based on the element of the three-dimensional object (such as a line used to construct the object). Here, the point may be arbitrarily designated by the user as a coordinate value. For example, it may be a point approaching the Y-axis maximum value "max (y)" or the center position of the vector space among the coordinate values including the X-axis maximum value "max (x)". After selecting the coordinates (x ₂ , y ₂ , z ₂ ) of the point closest to the point (x ₁ , y ₁ , z ₁ ), the distance is obtained according to Equation 2 below.

The distance of these points can be calculated by the number of elements included in one object. That is, when various functions such as a line, a "spline", and the like are used for an element included in an object, the distance d exists for each element, and thus, various information expressions are provided.

As a result Based on the values of and d we get the default argument values. Basic arguments are defined by the following formula: That is, the value obtained by Equation 1 The proportional expression is obtained based on the d value obtained by Equation 2 and Equation 2, and the final basic factor value α is obtained by multiplying the proportional value by the system characteristic constant ω. This calculation process is shown in Equation 3 below.

Here, the function s (V) is a function for applying the measure according to the value of each dimension. In the case of 1-dimensional, the distance value is applied. In the 3D Becomes Ω in the above formula is a system specific constant. System-specific constants are used to scale to control the range of changes in α that will act as the base factor. The other can give different values depending on the characteristics of the various types of vector images.

Step 3: One reference value is determined by the basic factor value α. The method of determining is the same as the method of generating the basic factor, and the value is called α ₀ . The value of α ₀ is determined by the point at which it is inserted. That is, the value of α is determined by the coordinates (x ₂ , y ₂ , z ₂ ) of the point closest to the point (x ₁ , y ₁ , z ₁ ), whereas the value of α ₀ is the coordinate of one point. This value is obtained based on the insertion of. However, the point to be inserted is a point to be inserted between or near the point (x ₂ , y ₂ , z ₂ ) nearest to the point (x ₁ , y ₁ , z ₁ ). Insertion proceeds with the elements of the object. There is a constant relation between α and α ₀ . Α ₀ is selected based on the characteristics of the vector image. This insertion also inserts a point between the first point and the second point of the curve (or other object's element) to perform "pattern construction / information representation". Insertion is determined by the values of α, α ₀ .

If the information you want to insert is {0},

Insert the point so that α ₀ <α by comparing the values of α ₀ and α at the point to be inserted.

If the information you want to insert is {1},

Comparing the values of α ₀ and α, insert the point so that α ₀ > α.

Hereinafter, the first procedure 100 of FIG. 1, the second process 102, that is, the ordering process will be described in detail with reference to FIG. 5. The ordering process is an important procedure of the present invention as well as the creation of basic arguments. If the user specifies the order in the order or other method based on the creation process of the vector image without applying the rule, the information on the order disappears when the conversion such as the format conversion of the vector image is performed. The order of each object is specified by using the structural characteristics of the vector image.

Every object in a vector image has its own properties. These properties are independent of the parameters of the base target. The properties of these objects include the name of the object, the color of the line, and the ability to cast shadows. This is the property that an object always has after it is first created. Table 1 shows the attributes of each object.

Properties name Yes Name Box01, Line01, Circle01, etc. Dimensions X, Y, Z, Vertices, Faces, etc. Rendering Control Visibility, Renderable, etc. Motion blur Enabled status (None, Object, Image check Display properties Backface Cull, Edges Only Vertex Ticks, etc. Mental ray rendering control (May depend on object)

The most important attribute here is "Dimensions". In the present invention, for the insertion of the watermark, the elements are aligned on the basis of the two-dimensional scale and the three-dimensional scale, which allow the insertion of points using the attribute "Dimensions" for each object. If these attributes are not defined, "Dimensions" should be obtained by the coordinate values. The priority order in which sorting can proceed is determined by the following equation (4).

The order of precedence is as follows. First of all, the order of objects. Calculate the measures of all objects and use the objects sorted in the order of riding or ascending based on the results. Another way is to divide the measure into intervals. Measure of the smallest object And measure the largest object And sort the objects based on their user-defined intervals. There may be various types of user defined sections. For example, when the number of sections is N, the measure section length of each section may be expressed by Equation 5 below.

In Equation 5, n = 1, 2, ..., N.

Each section may contain one or several objects. This is to prevent attacks to add or delete objects when editing. 7 shows the results of the alignment based on the head procedure of the vector image. Sort by two-dimensional and three-dimensional measures. Here, each object included in the vector image is represented by O _i as a symbol, and the components related to the two-dimensional scale and the components related to the three-dimensional scale in the object are represented by O _2j and O _3k , respectively. I, j, and k are indices each component has. After sorting, it would look like this: If N is the number of objects included in the vector image, s and p are the number of components according to the 2D and 3D scales, the result of the alignment is expressed as in Equation 6 below.

{O ₁ , O ₂ , ..., O _n } where O _i = {O _i1 , O _i2 , ..., O _is }

7 is an example of an analysis process for a vector image. As shown in FIG. 7, the vector image is composed of several objects. In the example shown here, the head consists of ten parts, such as "Head" and "Revol1". The ten parts were named by "head", "Revol1", and so on, respectively. Each "Dimensions" property is shown in Table 2 below.

Objectname Dimensions (X) Dimensions (Y) Dimensions (Z) Head 4.95 4.208 6.385 132.997 Revol1 5.165 5.113 1.634 43.152 Revol2 5.136 5.085 1.973 51.528 Cyl1 0.394 0.367 5.004 0.7236 Cyl2 0.639 0.33 5.003 1.055 Cyl3 0.394 0.33 5.002 0.6504 Sphere1 0.617 0.322 0.484 0.0962 Sphere2 0.617 0.322 0.484 0.0962 Sphere5 0.901 0.901 0.451 0.3661 Sphere6 0.324 0.141 0.35 0.01599

The minimum value of the measure of the vector image as described in Table 2 above , The maximum value is to be.

After sorting, {O ₁ , O ₂ , ..., O _n } is

{Sphere6, Sphere1, Sphere2, Sphere5, Cyl3, Cyl1, Cyl2, Revol1, Revol2, Head}

2. {Head, Revol2, Revol1, Cyl2, Cyl1, Cyl3, Sphere5, Sphere2, Sphere1, Sphere6} (in descending order)

3. {Head}, {Revol2, Revol1, Cyl2, Cyl1, Cyl3, Sphere5, Sphere2, Sphere1, Sphere6} (divide by segment, N = 2)

In the example of FIG. 7, all are defined as three-dimensional measures.

Next, a third process 103 of the first procedure 100 of FIG. 1, that is, an insertion position selection process 103 will be described.

Insertion position selection process 103 is closely related to the construction method of the vector image. There are three ways to construct a vector image. That is, a vector image construction method based on a polygon, a vector image construction method based on a Bezier plane, and a vector image construction method based on NURBS.

Polygon-based construction methods are often used to produce images with clear geometrical properties, such as architectural models, while consuming computer resources and weakening delicate vector images. The construction method by Bezier face is used for smooth model and many complicated shapes. The construction method by NURBS is currently the most popular technology and is used for a wide range of industrial models and motion picture production. NURBS is used for the manufacture of almost all models. The weakness of NURBS is that it is difficult to create a model with right angles. The present invention is mainly based on the immutable properties of objects included in vector images, i.e., inserting measures and arbitrary coordinate values. The types of coordinates are as follows. The two-dimensional points are "Smooth" points, "Corner" points, "Bézier" points, and "Bezier Corner" points. Table 3 below describes the types of points in detail.

"Smooth" dot Both sides of the point are smoothly connected curved segments "Corner" point Both sides of the point are usually straight line segments, and the angle of the line segments on both sides of the point can be adjusted arbitrarily. "Bezier" point The characteristic of Bezier curves is that they control the curve with polygons. Thus, these points adjust the curve by tangent lines. How the variable subtracted line is tangent. "Bezier Corner" dot Unlike the Bezier points, the segments on both sides can be adjusted at any angle.

There are two types of NURBS curves. That is, the "Point" curve and the CV curve. The definition of a point is actually the same as a Bezier point. However, there is a focus on B-SPlINE, not uniform values. The points used in NURBS are often referred to as "Control Point" and "Knot vector".

In the present invention, any point inserted by the user compares the values of α ₀ and α such that α ₀ > α or α ₀ <α. At this time, the values may be changed or inserted more points for all the points. In order not to change the shape of each object, insert two or three points in consideration of the effect of the insertion of one point. However, when inserting, it is assumed that the matter about "Dimensions" which is an object property does not change.

As described above, the insertion position is selected by comparing the values of α ₀ and α to find a point satisfying the condition (α ₀ > α or α ₀ <α), and inserting a point at the position. Through this analysis, some information can be inserted into the figures.

As described above, in order to insert the watermark, a control point or another kind of point must be additionally inserted at the designated position as described above. However, the insertion of the point must consider the deformation of the vector image and ensure the constant connectivity. In other words, there should be no visual change before and after insertion. Under the premise of ensuring such connectivity, there are various ways of inserting points so that the shape of the vector image remains unchanged. Hereinafter, three methods will be described as examples using a Bezier curve-based vector image as an example.

The first method is to increase the number of direct control points (hereinafter referred to as 'method I'), the second method is to insert a point by subdivision (method II), and the third is a direct control point. This method combines the method of increasing the number of (method I) and the subdivision method (method II).

Method I:

Is called the control point of the Bezier curve, Is called a control point with one control point added. A control point that forms a new Bezier curve of n + 1 control points for a Bezier curve of n control points in Is given by Equation 7 below.

At this time, the inserted point considering the change of the curve Is determined as follows.

By applying the above method, a control point for expressing watermark information on the Bezier curve is added.

Method II:

Subdivisions make one Bezier curve into two new Bezier curves, which are the same as the original curve when the two new curves are concatenated. While there is no change in the visual effect of the shape of the curve, the file size of the vector image is large. Bezier curves can be subdivided based on any parameter value. For convenience of explanation, the subdivision method will be described using a cubic Bezier curve as an example. The parameter t is based on a specific value t = 1/2. The cubic Bezier curve is expressed by Equation 8 as follows.

A new Bezier curve representing the first half of the original Bezier curve Is called a control point Is a new Bezier curve representing the second half of the original curve It is called a point. therefore Silver new Bezier curve Are control points that represent Corresponds to Silver new Bezier curve Which indicates Corresponds to You get the following equation:

Here we get the following new control points:

Similarly, the new control points that make up the second class can be obtained as follows.

As mentioned above, one of the important points in the subdivision method is which parameter value is based on.

Method III:

Method III is a method in which Method I and Method II are combined as needed. It is also possible to insert a new point by executing method I and then to use method II, or to insert a new point by executing method I after executing method II. However, when inserting a point at a designated position, the above two methods can be selectively applied to simplify the presentation of information. The three methods can be applied as they are even when the Bezier curve is extended to form a Bezier curved surface.

The three methods (methods I, II, and III) applied to the Bezier curves can be applied to the B-SPLINE curve or the NURBS curve. The actual Bezier curve is a special case of the B-SPLINE curve. The generalized B-SPLINE curve is the NURBS curve. The principle is the same as the criteria for setting parameter values are slightly different for each curve. However, it is important to note that in NURBS, when the method II is applied, it takes a different form depending on the function used in each section.

NURBS curves and B-SPLINEs have a lot of points that can be inserted relative to Bezier curves. That is, it is also possible to insert the watermark information by the change of the KNOT vector used to control the influence between the control points. In comparison with the above three methods, however, the shape of the vector image should be slightly changed. The weight may also be changed to a value for embedding the watermark information. Only the shape of the vector image changes.

Importantly, whether a vector image is a polygonal vector image, a Bezier vector image, or a NURBS vector image, it is completely possible to insert the desired information in the designated position. However, if the shape of the vector image is not changed, the size of the vector image is changed.

As described above with reference to FIG. 1, the second procedure 200 is a procedure of processing information to be inserted into a vector image in an insertable form. This is divided into a data creation process 201 to be inserted, a constraint condition verification process 202, and a data generation process 203 to be inserted. Hereinafter, each process will be described in detail.

The data to be inserted can be any number depending on the user's purpose. For example, authentication information for the creator of a vector image file, identification information on the owner of the file, information on the use of the owner company, information to prevent unauthorized distribution, file creation date management information, inventory management information, and restraining information for unauthorized copying. For example, it can contain information on unauthorized copying, record of confidential information, and information about the distribution process. All of this information is inserted into the vector image in the form of a bit string. Thus, the present invention allows the use of a mapping table to optimize the amount of inserts. The mapping table can be arbitrarily defined by the user. That is, it is a mapping table for expressing watermark information to be inserted. Common mapping tables include:

1) Use ASCII code table.

2) Use all lowercase letters or uppercase letters except control letters.

3) Only numbers are used to represent information.

4) Use Unicode tables.

5) Configure the mapping table by specifying the characters to be used by the user.

This procedure has the following advantages: If there are two different information in the mapping table specified by the user, it can be expressed in 1 bit. ] Can be represented by a bit. The symbol "[]" is a Gaussian symbol. Through the above process, the data to be inserted is created into a bit string.

In addition, the vector image has a limitation on the information to be inserted due to the complexity of the configuration. In other words, it is impossible to insert any amount of information. The amount that can be inserted into the vector image is determined by the following, as shown in Table 4.

Vector image Insertion amount of watermark information Number of objects Directly proportional to the number of objects The elements contained in the object Directly proportional to the number of elements in the object The number of bins in the sort Directly proportional to the number of segments Number of points Correlated with the number of points

As can be seen in Table 4, it can be seen that the amount of information that can be inserted is reduced as a simple vector image. When the insertion position process 103 of the first procedure 100 shown in FIG. 1 is performed, information about how much bit information to insert is generated. The amount of information to be inserted must be equal to or less than the amount of information that can be inserted. This is solved based on the result of the insertion position selection process 103 in this constraint verification process 202. The inserted data indicates bit string information that has undergone the constraint verification.

The third procedure 300 of FIG. 1 is a process of inserting the inserted data generated through the second procedure 200 into the vector image insertion position selected in the first procedure 100. Through the above three procedures, the vector image is changed from cover data to stego data.

Hereinafter, the process of extracting the inserted information from the stego data, that is, the watermark extraction process, will be described in detail with reference to FIGS. 2 and 4.

First, referring to FIG. 4, an apparatus for extracting embedded information from a watermark-embedded vector image performs a series of operations for extracting a watermark, such as analyzing an information insertion position in a watermark-embedded vector image. The watermark information extraction unit 21 and the watermark information extraction unit 21 for reading the information in the form of bit strings of the inserted watermark based on the insertion position of the vector image analyzed by the image analysis unit 11 and extraction. And a watermark information restoring unit 31 for restoring the bit stream to information that can be checked by the user based on the mapping table used when the corresponding watermark information is inserted.

Extracting the watermark is the reverse process of inserting the watermark. Extracting a watermark can be roughly divided into three procedures.

Referring to FIG. 2, the first procedure 110 of watermark extraction is similar to the first procedure 100 at the time of watermark embedding, which is also a method for analyzing a vector image to form a basic factor. The first process 111 of configuring the basic parameters of the first procedure 110 is the same as the procedure for embedding the watermark. The second process 112 of the first procedure 110 is a part of extracting the designation order. When inserting a watermark, the reverse procedure for finding the specified order was used. Wow It is closely related to the value of. It also has a relationship with section selection at insertion. The third process 113 of the first procedure 110 is a process of selecting an inserted point. This first procedure 110 is performed by the image analyzer 11.

The second procedure 210 is a procedure of reading the information in the form of a bit string of the inserted watermark based on the insertion point of the vector image. The final third procedure 310 is a process of restoring the inserted bit string to user information that can be checked by the user based on the mapping table used at the time of insertion. The second procedure 210 is performed by the watermark information extraction unit 21, and the third procedure 310 is performed by the watermark information recovery unit 31.

Hereinafter, each procedure of the watermark extraction will be described in more detail. First, the basic parameter construction process 111, the designation order extraction process 112, and the selection vertex selection process 113 of the first procedure 110 are performed based on the distinction between the stego data and the cover data. There is a difference. The difference from the process of inserting the watermark in the part of analyzing the vector image to construct the basic factor lies in the distinction between the cover data when the watermark is inserted and the stego data when the watermark is extracted. That is, the difference between the basic factor constructed by the cover data and the basic factor constructed by the stego data. After the new point is inserted, the value is wrong if you get the default argument. Therefore, when configuring the basic parameters, the synchronization bit included in the first part of the insertion information should be used. In this part, the synchronization parameter is used to apply the default parameter values applied at insertion time. Applying regularly is an expression to enable extraction by considering the effect of the insertion of synchronization bits on the value of the basic factor. Finding the required spots when creating the default arguments is the same as for inserting a watermark. Since the sync bit is applied at the beginning, or The position of the spot that satisfies is detected. If you apply [1111111] as a sync bit, It can be thought of as a series of spots that satisfy. Therefore, based on the above conditions Can be found. That is, a spot Is less. The process of extracting the designation sequence and the process of selecting the inserted point is the same as the process of embedding the watermark.

A bit sequence extraction operation, which is a second procedure 210, consists of an insertion point detection process 211, a comparison process 212, and a bit string construction process 213 of a vector image. These processes are also the reverse process when inserting watermarks. Default argument values configured by the insertion of and points Based on the comparison process 211, one bit string 213 is configured based on the comparison result.

In other words, the result of comparing the default If,

Add {0} to the bit string,

Comparing the default factors If,

Add {1} to the bit string.

The third procedure 310 is a process of restoring the inserted bit string to user information that can be checked by the user based on the mapping table used at the time of insertion. This process requires a process of interval matching. The processing in the interval matching process is as follows.

1) Remove the sync bit.

The synchronization bit is a value used to obtain a basic parameter value without cover data, and is not used as watermark information. The synchronization bit is removed in the interval matching process.

2) Necessary as an inverse of the ordering process applied when inserting a watermark. When inserting, alignment used to sort objects, calculate the measure of the object, and then divide the object into the order of measure, the order of measure, or the measure into intervals. Depending on which method you have applied, apply it accordingly in the section of interval contrast. In the example of FIG. 2, since a method of dividing a measure into intervals is applied, when the bit string 213 is subjected to the interval matching process, it is represented in the form of data 312 in which the interval matching process is performed. E.g,,

Step 1: 111000111110001110000111111 (when divided into 9 sections)

Step 2: 111,000,11111,000,111,00,00,111,111

Step 3: 101010011 (Result Value)

The data 312 which has passed the interval matching process is restored to the specific watermark information 400 based on the mapping table 313 applied when the watermark is inserted.

With the above configuration, the watermark insertion / detection operation of the vector image according to the features of the present invention can be performed.

Meanwhile, in the above description of the present invention, specific embodiments have been described, but various modifications may be made without departing from the scope of the present invention. Therefore, the scope of the present invention should not be defined by the described embodiments, but by the claims and equivalents of the claims.

As described above, the present invention analyzes the overall composition of a vector image based on a set of straight lines, curves, surfaces, polyhedrons, and points which are components of the vector image, and the phase remains unchanged even though various transformations including similar transformations are applied. By defining the invariant, a new scale can be created, and information can be inserted into the vector image and extracted again based on the scale. In this case, the information to be inserted is based on the authentication information for the creator of the vector image file, the confirmation information about the owner of the file, the information related to the use of the owner company, information to prevent unauthorized distribution, file creation date management information, inventory management information, without permission It can be restraining information about copying, check information about unauthorized copying, recording of confidential information, information about distribution process, etc., and thus can protect copyright and prevent unauthorized distribution of vector images.

Claims (10)

In the watermarking method of a vector image, Obtaining a basic factor that is not affected by changes in coordinate values and basic mapping of each object in the original vector image, Assigning an order according to preset criteria for each object included in the vector image; Converting the information to be inserted into a preset insertable information type; Selecting an insertion position of the information on the object of the vector image by using the basic factor; And inserting a dot at the predetermined insertion position of the respective objects according to the embeddable information type to generate a vector image having a watermark inserted therein. The method of claim 1, wherein the obtaining of the basic factor comprises: analyzing a member of the vector image; Measured figures for length, area and volume along each dimension for each analyzed element To obtain the step, Obtaining a distance d between the reference point closest to the preset reference point at each member element; Quantified measure And calculating a final basic factor α by using a proportional value with respect to the distance d. The method according to claim 2, wherein the ordering criteria for each object aligns the objects, and calculates a measure of each object to divide the riding order, the descending order, and the measure of the measure of each object into sections. Watermarking method characterized in that using. The method of claim 2, wherein the insertion position of the information is the basic factor, the distance between the preset reference point and the point at which the information is to be inserted, and the quantified measure. And selecting a bit of the information to be inserted according to the result of the size comparison with the value obtained using the proportional value of. The watermarking method of claim 1, further comprising checking whether the information to be inserted is equal to or less than an amount of information that can be inserted according to the insertion position of the information. The method of claim 1, wherein the method of inserting a point at the selected insertion position comprises at least one of a method of directly increasing the number of control points and a method of inserting a point by a subdivision. Watermarking method, characterized in that the vector image prevents deformation. In the watermarking method of a vector image, Extracting the basic factors which are not affected by the change of the coordinate values and the basic mapping of each element in the watermarked vector image, Assigning an order according to preset criteria for each element included in the vector image; Selecting an insertion position of the information by using the basic factor in each element of the vector image; And extracting information inserted into the corresponding position by extracting a point from the selected insertion position in the designated order of the respective elements. The method of claim 7, wherein the obtaining of the basic factor comprises: analyzing a member of the vector image; Measured figures for length, area and volume along each dimension for each analyzed element To obtain the step, Obtaining a distance d between the reference point closest to the preset reference point at each member element; Quantified measure And calculating a final basic factor α by using a proportional value with respect to the distance d. The method of claim 8, wherein the ordering criteria for each object aligns the objects, and calculates a measure of each object to divide the riding order, the descending order, and the measure of the measure of each object into sections. Watermarking method characterized in that using. The method of claim 8, wherein the insertion position of the information comprises the basic factor, the distance between the preset reference point and the point from which the information is extracted, and the quantified measure. And selecting the bit of the information to be extracted according to the result of the size comparison with the value obtained using the proportional value of.