KR20160066318A - Apparatus and method for generating a random nuber using a prefer image - Google Patents

Abstract

Disclosed are an apparatus for generating a random number based on an image and a method for the same. An image-based apparatus for generating a random number according to an aspect of the present invention comprises: an image division unit which generates n sub-images by dividing an input color image by the number (n) of random numbers to be generated; an image processing algorithm selection unit which randomly selects an image processing algorithm to be applied to each of the n sub-images; an image processing unit which applies the selected image processing algorithm to each of the n sub-images, and acquires gray-scale images; and a random number calculation unit which generates n random numbers by using pixel values of the respective gray-scale images acquired from the n sub-images.

Description

[0001] APPARATUS AND METHOD FOR GENERATING A RANDOM NUBER USING A PREFER IMAGE [0002]

The present invention relates to a random number generation apparatus and a method thereof, and more particularly, to an apparatus and a method for generating a random number based on an image.

Random number generators (RNGs) can be used in a variety of electronic devices, such as lottery machines, gambling machines, scientific modeling simulations, financial modeling simulations, program or algorithm testing, solving equations, and computer security. Encrypted random number generators may be more suited to computer security applications such as cryptography, digital signatures (including non-repudiation), personal communication protocols, and message integrity.

A random number is a series of numbers assembled into a finite number of numbers, with no periodicity, and each numerical value is independently determined regardless of the arrangement of numbers that preceded it. This includes random numbers (such as ordinal numbers, exponential numbers, Pawsong random numbers, regular random numbers, etc.) or empirically derived random numbers according to the theoretical distribution.

In other words, a random number means a bit sequence having a randomness or a number corresponding to the bit string.

A random number generator is a device that makes it impossible to generate a random password without knowing it without my special key. Until now, pseudo random number generators have been used in many areas due to high product price, CPU performance, and physical limitations of devices such as memory. However, due to their limitations, the era of true random number generation (TRNG) It is a sign to open.

On the other hand, a true random number generator should have the following three conditions.

First, it must be unpredictable which bit value to have before the bit is generated.

Second, there is no correlation between the previously generated bit value and the bit value to be generated later (uncorrelated).

Third, the generated bit stream should be unbiased to any one bit.

For example, the pseudo-random number generator generates a random number according to a predetermined order, and it is difficult to satisfy the three conditions described above because a constant random number is generated according to the input seed.

In addition, in the case of a pure random number generator, since there is no correlation between random number generation, the above three conditions are satisfied, but a large amount of computation is required to generate random numbers, which limits resource utilization such as CPU performance.

According to an aspect of the present invention, there is provided a method of generating a random number by applying a randomly selected image processing algorithm to each sub-image obtained by dividing an input image, And a random number generation apparatus with improved randomness of generation and a method thereof.

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

According to an aspect of the present invention, there is provided an apparatus for generating a random number based on an image, comprising: an image division unit for dividing an input color image by a number (n) of random numbers to be generated, Wow; An image processing algorithm selection unit for randomly selecting an image processing algorithm to be applied to each of the n sub images; An image processor for applying a selected image processing algorithm to each of the n sub-images to obtain a gray-scale image; And a random number operation unit for generating n random numbers using pixel values of each of the n sub-images converted into gray scale.

The random number operation unit converts each of the n sub-images converted into gray scale into an integral image, and calculates a sum of pixel values for each of the n sub-images converted into the gray scale.

In addition, the random number calculator performs a mod operation on the pixel value sum of each of the n sub-images converted into the gray scale to generate n random numbers.

The random number operation unit randomly allocates an order to each of the n sub-images converted into the gray scale, and determines a digit place in which the n random numbers are to be arranged according to the assigned order.

The apparatus for generating a random number based on an image according to an aspect of the present invention further includes an ordering unit for randomly assigning order to each of the n sub-images, wherein the random number calculating unit calculates You can determine the digit position where the random number will be placed.

According to another aspect of the present invention, there is provided a method of generating a random number based on an image, the method comprising the steps of: (a) generating n sub-images by dividing an input color image by a number n of random numbers to be generated; (b) randomly selecting an image processing algorithm to be applied to each of the n sub-images; (c) applying a selected image processing algorithm to each of the n sub-images to obtain a gray-scale image; And (d) generating n random numbers using the pixel values of each of the n sub-images converted to gray scale.

The step (d) may include converting each of the n sub-images converted to gray scale into an integral image, and calculating a sum of pixel values for each of the n sub-images converted into the gray scale; And modulating the pixel value sum of each of the n sub-images converted into the gray scale to generate n random numbers.

In the step (d), a random order is assigned to each of the n sub-images converted into the gray scale, and a digit place in which the n random numbers are arranged is determined according to the assigned order .

The method of generating a random number based on an image according to another aspect of the present invention may further include the step of assigning a random order to each of the n sub-images. In this case, the step (d) includes determining a digit place in which the n random numbers are arranged according to the assigned order.

According to the present invention, a random number is generated by applying a randomly selected image processing algorithm to each divided sub-image, and the processed random number is generated, thereby improving the randomness of random number generation compared to a conventional pseudo random number generator .

1 is a block diagram illustrating an image-based random number generation apparatus in accordance with an embodiment of the present invention.
2 is a flow chart illustrating a method of generating a random number based on an image in accordance with an embodiment of the present invention.
FIG. 3 is a diagram illustrating a process of generating a 6-digit random number according to an embodiment of the present invention. FIG.
4 is a diagram showing the configuration of a computer apparatus in which a random number generation method based on an image according to an embodiment of the present invention is executed.

BRIEF DESCRIPTION OF THE DRAWINGS The advantages and features of the present invention and the manner of achieving them will become apparent with reference to the embodiments described in detail below with reference to the accompanying drawings. The present invention may, however, be embodied in many different forms and should not be construed as being limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art. And is provided to fully convey the scope of the invention to those skilled in the art, and the present invention is defined by the claims. It is to be understood that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. In the present specification, the singular form includes plural forms unless otherwise specified in the specification. It is noted that " comprises, " or "comprising," as used herein, means the presence or absence of one or more other components, steps, operations, and / Do not exclude the addition.

Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings. In the drawings, like reference numerals refer to like elements throughout. In the drawings, like reference numerals are used to denote like elements, and in the description of the present invention, In the following description, a detailed description of the present invention will be omitted.

1 is a block diagram illustrating an image-based random number generation apparatus according to an embodiment of the present invention.

1, an image-based random number generation apparatus according to an embodiment of the present invention includes an image division unit 10, an algorithm selection unit 20, an image processing unit 30, and a random number calculation unit 40 do. The random number generation apparatus may further include an order assigning unit 50 for randomly assigning order to each of the n sub-images divided by the image dividing unit 10.

The image divider 10 divides the input color image into a plurality of sub images. For example, if it is assumed that n (or n-digit) random numbers are required, the image divider 10 divides the input color image into n sub-images. In this case, the color image may be divided into n sub-images having the same area, or may be divided into n sub-images having a randomly selected area.

That is, although the image divider 10 can divide the input color image into n sub-images, it is not necessary that the n sub-images have the same area, and if necessary, It should be noted that

Order arranging unit 50 randomly assigns order to each of n divided sub-images. For example, the order can be assigned from the upper left side to the lower right side of the input color image. Alternatively, it is noted that the order may be assigned from the lower-right side to the upper-left side of the input color image, and the assignment of the order for the divided sub-images may be performed randomly.

On the other hand, the order assigned to the sub-images is used to determine the digit place in which the random number generated from each sub-image is to be placed. For example, assume that a sequence of '1' is assigned to the sub-image located at the upper left and a sequence of '6' is assigned to the sub-image positioned at the highest and lower position in order to generate the 6-digit random number.

In this case, if the random number generated in the subimage (procedure 6) with the random number generated in the uppermost left subimage (sequence 1) located at the highest and lowest position of 'a' is 'b' The number can have the same value as 'axxxxb'.

In the present embodiment, the random numbers finally generated are arranged in the order of (1) - (2) - (3) - (4) - (5) - (6) It should be noted that the placement order can also be determined at random.

The image processing algorithm selection unit 20 randomly selects an image processing algorithm to be applied to each divided sub image. The image processing algorithm to be applied to each sub-image means an algorithm for gray-scale conversion of a color image. For example, such an algorithm may include Null Transformation, Inverse Transformation, Logarithm Transformation, Gamma Correlation Transformation, and Bit Plane Slicing Transformation. have.

The image processing unit 30 applies a selected image processing algorithm to each of the n sub-images to obtain a gray-scale image of n sub-images.

The random number calculator 40 generates n random numbers using the pixel values of each of the n sub-images converted into gray scale.

The random number operation unit 40 converts each of the n sub-images converted into gray scale into an integral image, calculates a sum of pixel values for each of the n sub-images converted into the gray scale, The n number of random numbers are generated by performing a mod operation on the pixel value sum of each of the n sub-images converted into the gray scale.

The random number calculator 40 determines a digit place of the generated n random numbers and arranges n random numbers accordingly. At this time, the random number calculator 40 may randomly assign an order to each of the n sub-images converted into gray scale and determine a digit place in which the n random numbers are to be arranged according to the assigned order have.

The number place in which the generated random number is to be arranged may be implemented so that the ordering unit 50 first allocates each of the n sub-images as described above. Alternatively, the random number calculator 40 converts n To each of the sub-images. In this case, the arrangement of the order arranging unit 50 is not required.

Hereinafter, a process of generating a random number based on an image according to an embodiment of the present invention will be described with reference to FIGS. 2 and 3. FIG.

FIG. 2 is a flowchart illustrating an image-based random number generation method according to an embodiment of the present invention. FIG. 3 illustrates a process of generating a 6-digit random number according to an exemplary embodiment of the present invention.

First, referring to FIG. 2, the image divider 10 divides an input color image into a plurality of sub images (S10).

For example, assuming that six random numbers are required, the input image is divided into six sub-images as shown in FIG. In this case, the color image may be divided into six sub-images having the same area, or may be divided into six sub-images having a randomly selected area. In Fig. 3, sub-images divided into six equal parts having the same area are exemplarily shown. Hereinafter, a process of generating a random number based on the divided sub-images will be described.

Then, the order arranging unit 50 randomly assigns the order to each of the six divided sub-images (S20). For example, the order can be assigned from the upper left side to the lower right side of the input color image. Alternatively, it is noted that the order may be assigned from the lower-right side to the upper-left side of the input color image, and the assignment of the order for the divided sub-images may be performed randomly.

Fig. 3 shows an example in which the order is assigned from the upper left to the lower right of the input color image. That is, the order of '1' is assigned to the sub-image located at the upper left of the input image, and the order of '6' is assigned to the sub-image located at the farthest lower position.

Then, the image processing algorithm selection unit 20 randomly selects an image processing algorithm to be applied to each sub-image segmented (S30).

The image processing algorithm to be applied to each sub-image means an algorithm for gray-scale conversion of a color image. For example, such an algorithm may include Null Transformation, Inverse Transformation, Logarithm Transformation, Gamma Correlation Transformation, and Bit Plane Slicing Transformation. have.

For example, a null transformation algorithm is selected as an image processing algorithm to be applied to the first sub-image a, and an inverse transformation algorithm, an image to be applied to the sixth sub-image f, As a processing algorithm, a gamma correlation transformation algorithm may be selected.

As described above, the randomness of the random number generated in each sub-image can be increased by randomly selecting the image processing algorithm to be applied to each sub-image.

Then, the image processing unit 30 obtains a gray-scale image of the six sub-images by applying the selected image processing algorithm to each of the six sub-images (S40).

Next, the random number calculator 40 generates six random numbers using the pixel values of the six sub-images converted into gray scale (S50).

The process of generating six random numbers using six sub-images can be performed by calculating a sum of pixel values of each sub-image. As shown in FIG. 3, each pixel of the gray-scale-converted sub-image has a pixel value ranging from 0 to 255. The sum of pixel values can be easily calculated by obtaining an integral image for each sub-image.

Here, the integral image means an image in which the sum of pixel values up to the previous pixel is added to each pixel. For example, the pixel value is summed starting from the pixel value of the pixel located at the upper left side, and the sum of the pixel values of all the pixels is assigned to the pixel located at the bottommost position.

The random number calculator 40 performs a mod operation on the sum of the pixel values calculated in each of the six sub images to generate six random numbers.

3, the sum of the pixel values calculated in the first sub-image a is 87, the sum of the pixel values of the second sub-image b is 1593, the pixel of the third sub-image c, (D) is 781, the sum of the pixel values of the fifth sub-image (e) is 833, and the sum of the pixel values of the sixth sub-image (f) is 5 .

The mod operation represents a remaining operation using a predetermined value (for example, 11), and a mod b means a remainder when a is divided by b. Accordingly, if the result of performing the mod operation on each sub-image is shown, in the first sub-image (a), the result obtained by dividing the sum 87 of the pixel values by 11 and the remainder of 10 will be output.

Similarly, in the second sub-image b, 9, 9 in the third sub-image c, 0 in the fourth sub-image d, 8 in the fifth sub-image e, 5 is output as a mod operation result.

Thereafter, the random number calculator 40 arranges the random numbers output from the respective sub images in the order assigned in step S20. As a result, a result such as 10/9/8/0/8/5 is output as shown in Fig.

In the above embodiment, it has been described that the order of determining the digit position in each sub-image segmented in step S20 is allocated.

However, as another embodiment, it is also possible to arrange the random numbers generated in the order of the determined numerical digits after determining the numerical digits in each sub-image converted to gray scale in step S50. It should be noted that step S20 is not necessary in this embodiment.

Meanwhile, the image-based random number generation method according to the embodiment of the present invention can be implemented in a computer system or recorded on a recording medium. 4, the computer system includes at least one processor 121, a memory 123, a user input device 126, a data communication bus 122, a user output device 127, And may include a storage 128. Each of the above-described components performs data communication via the data communication bus 122. [

The computer system may further include a network interface 129 coupled to the network. The processor 121 may be a central processing unit (CPU) or a semiconductor device that processes instructions stored in the memory 123 and / or the storage 128.

The memory 123 and the storage 128 may include various forms of volatile or nonvolatile storage media. For example, the memory 123 may include a ROM 124 and a RAM 125.

Accordingly, an image-based random number generation method according to an embodiment of the present invention can be implemented in a computer-executable method. When the image-based random number generation method according to an embodiment of the present invention is performed in a computer device, computer-readable instructions can perform the recognition method according to the present invention.

Meanwhile, the above-described image-based random number generation method according to the present invention can be implemented as computer-readable codes on a computer-readable recording medium. The computer-readable recording medium includes all kinds of recording media storing data that can be decoded by a computer system. For example, there may be a ROM (Read Only Memory), a RAM (Random Access Memory), a magnetic tape, a magnetic disk, a flash memory, an optical data storage device and the like. The computer-readable recording medium may also be distributed and executed in a computer system connected to a computer network and stored and executed as a code that can be read in a distributed manner.

While the present invention has been described in connection with what is presently considered to be practical exemplary embodiments, it is to be understood that the invention is not limited to the disclosed embodiments, but, on the contrary, It is to be understood that the invention may be embodied in other specific forms. It is therefore to be understood that the above-described embodiments are illustrative in all aspects and not restrictive. The scope of the present invention is defined by the appended claims rather than the detailed description, and all changes or modifications derived from the scope of the claims and their equivalents shall be construed as being included within the scope of the present invention.

Claims (9)

An image divider for dividing an input color image by a number (n) of random numbers to be generated to generate n sub images;
An image processing algorithm selection unit for randomly selecting an image processing algorithm to be applied to each of the n sub images;
An image processor for applying a selected image processing algorithm to each of the n sub-images to obtain a gray-scale image; And
A random number operation unit for generating n random numbers using the pixel values of each of the n sub-
A random number generator for generating a random number based on the image.
2. The apparatus of claim 1,
Converting each of the n sub-images converted into gray scale into an integral image, and calculating a sum of pixel values for each of the n sub-images converted into the gray scale
A random number generation device based on an image that is a random number.

The apparatus of claim 2, wherein the random number calculator comprises:
And performing a mod operation on the pixel value sum of each of the n sub-images converted into the gray scale to generate n random numbers
A random number generation device based on an image that is a random number.
2. The apparatus of claim 1,
Assigning a random order to each of the n sub-images converted into the gray scale, and determining a digit place in which the n random numbers are to be arranged according to the assigned order
A random number generation device based on an image that is a random number.
The method according to claim 1,
Further comprising an ordering unit for assigning a random order to each of the n sub-images,
The random number operation unit may be configured to determine a digit position in which the n random numbers are arranged according to the assigned order
A random number generation device based on an image that is a random number. (a) generating n sub-images by dividing an input color image by a number (n) of random numbers to be generated;
(b) randomly selecting an image processing algorithm to be applied to each of the n sub-images;
(c) applying a selected image processing algorithm to each of the n sub-images to obtain a gray-scale image; And
(d) generating n random numbers using the pixel values of each of the n sub-images converted into gray scale
/ RTI > The method of claim < RTI ID = 0.0 > 1 < / RTI >
7. The method of claim 6, wherein step (d)
Converting each of the n sub-images converted into gray scale into an integral image and calculating a sum of pixel values for each of the n sub-images converted into the gray scale;
And performing a mod operation on the pixel value sum of each of the n sub-images converted into the gray scale to generate n random numbers
A method for generating a random number based on an image.
7. The method of claim 6, wherein step (d)
Assigning a random order to each of the n sub-images converted into the gray scale, and determining a digit place in which the n random numbers are to be arranged according to the assigned order
A method for generating a random number based on an image.
The method according to claim 6,
Further comprising assigning a random order to each of the n sub-images,
The step (d)
And determining a digit place in which to place the n random numbers according to the assigned order
A method for generating a random number based on an image.

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