KR102580076B1 - Apparatus and method for generating hash - Google Patents

Abstract

A hash generation device according to an embodiment of the present invention includes a memory storing a hash generation program; and a processor that executes the hash generation program, wherein the hash generation program divides the digital image data received from the photographing device into a predetermined size for the Y signal and performs sampling on the entire divided image. Hash information is generated by extracting feature points through , and the digital image data is in YUV format.

Description

Hash generation device and method {APPARATUS AND METHOD FOR GENERATING HASH}

The present invention relates to a hash generation device and method for generating hash information of digital image data.

CCTV footage or videos stored in a black box installed in a vehicle or DVR (Digital Video Recorder) are used as important evidence in the criminal investigation process. However, because there is a possibility of forgery and alteration of these images, courts strictly require the authenticity of digital images as evidence.

In other words, in order for the authenticity of digital evidence to be recognized, its integrity, identity, and reliability must be recognized. As a technical method for proving such authenticity, a method of checking whether the hash values of the original video and the copy video are the same is known.

A representative method of generating a hash value of an image is the sub-sampling method. As shown in Figure 1, the sub-sampling method extracts feature points for the corners of objects included in the original image and uses the feature points. Then, the edge of the object is extracted and hash information is generated.

However, the subsampling method has a problem in that the integrity reliability is not high because it extracts feature points only for some areas of the image. To solve this problem, extracting feature points for the entire image increases the extraction time and requires high computer specifications. Required additional problems arise.

Recently, as the resolution of video has increased and the amount of video that needs to be encrypted has increased, a considerable amount of time has been spent on encryption. In the case of server-class computers, there may be no particular problem with the increase in video capacity, but in an environment where video devices are recently becoming smaller and edge computing technology is expanding, there is a need to reduce the time required for video encryption. Therefore, technology to solve these problems is required.

One object of the present invention is to provide a hash generation device and method for dividing digital image data into Y signals and generating hash information using feature points for the entire divided image.

The object of the present invention is not limited to the problems mentioned above, and other problems not mentioned will be clearly understood by those skilled in the art from the description below.

As a technical means for solving the above-described technical problem, a hash generation device according to an embodiment of the present invention includes a memory storing a hash generation program; and a processor that executes the hash generation program, wherein the hash generation program divides the digital image data received from the photographing device into a predetermined size for the Y signal and performs sampling on the entire divided image. Hash information is generated by extracting feature points through , and the digital image data is in YUV format.

In addition, a hash generation method according to an embodiment of the present invention includes dividing digital image data received from a photographing device into a predetermined size for a Y signal; and generating hash information by extracting feature points through sampling of the entire segmented image, wherein the digital image data is in YUV format.

According to the means of solving the problem of the present application described above, integrity reliability can be increased by using feature points for the entire image, the time required to extract feature points can be shortened by dividing and sampling the image, and the time required to extract feature points can be reduced. Because the time is shortened, it can be applied to lightweight devices, minimizing economic and time factors.

Figure 1 is an example diagram for explaining a conventional method of generating hash information.
Figure 2 is a block diagram schematically showing the configuration of a hash generation device according to an embodiment of the present invention.
Figure 3 is an example diagram for explaining the process of generating hash information.
Figure 4 is a flowchart illustrating a hash generation method according to an embodiment of the present invention.

Hereinafter, the present invention will be described in detail with reference to the attached drawings. However, the present invention may be implemented in various different forms and is not limited to the embodiments described herein. In addition, the attached drawings are only intended to facilitate understanding of the embodiments disclosed in this specification, and the technical idea disclosed in this specification is not limited by the attached drawings. In order to clearly explain the present invention in the drawings, parts not related to the description are omitted, and the size, shape, and shape of each component shown in the drawings may be modified in various ways. Throughout the specification, identical/similar parts are given identical/similar reference numerals.

The suffixes "module" and "part" for components used in the following description are given or used interchangeably only for the ease of preparing the specification, and do not have distinct meanings or roles in themselves. Additionally, in describing the embodiments disclosed in this specification, if it is determined that detailed descriptions of related known technologies may obscure the gist of the embodiments disclosed in this specification, the detailed descriptions are omitted.

Throughout the specification, when a part is said to be “connected (connected, contacted, or combined)” with another part, this means not only when it is “directly connected (connected, contacted, or combined),” but also when it has other members in between. It also includes cases where they are “indirectly connected (connected, contacted, or combined).” Additionally, when a part is said to "include (equip or provide)" a certain component, this does not exclude other components, unless specifically stated to the contrary, but rather "includes (provides or provides)" other components. It means you can.

Terms representing ordinal numbers, such as first, second, etc., used in this specification are used only for the purpose of distinguishing one component from another component and do not limit the order or relationship of the components. For example, the first component of the present invention may be named a second component, and similarly, the second component may also be named a first component.

Hereinafter, a digital image data management device according to an embodiment of the present invention will be described.

FIG. 2 is a block diagram schematically showing the configuration of a hash generating device according to an embodiment of the present invention, and FIG. 3 is an exemplary diagram illustrating a process in which the hash generating device generates hash information.

When describing the hash generation device 100 according to an embodiment of the present invention with reference to FIG. 2, the hash generation device 100 includes an I/O module 110, a memory 120, a processor 130, and a storage. Includes unit 140.

Next, the I/O module 110 receives digital image data captured from the photographing device 200 or transmits the digital image data to an external communication network or external computing device. To this end, the I/O module 110 is connected to a wired network such as a Local Area Network (LAN), a Wide Area Network (WAN), or a Value Added Network (VAN), or a mobile radio network. It may include a communication module that uses any type of wireless network, such as a communication network or a satellite communication network.

The memory 120 stores a hash generation program that generates hash information of digital image data stored in the storage unit 140. The hash generation program divides the YUV format digital image data received from the imaging device 200 into predetermined sizes for the Y signal, extracts feature points through sampling of the entire divided image, and generates hash information. Create. Here, the reason for using the YUV format is that the more colors the image data expresses, the larger the data size is. The YUV format, which includes brightness and blue and red information, has a smaller data size than the RGB format, which includes information on all colors. Because. Also, the reason for using only the Y signal is that the Y signal does not include color information but only brightness information, and has a smaller capacity than the U and V signals that include color information, enabling faster hash generation.

Next, when describing the operation of the hash generation program in detail with reference to FIG. 3, the hash generation program captures consecutive image frames 1 or video clips 1 for digital image data received from the photographing device 200. And after encoding each, the Y signal is extracted. Here, the hash generation program encodes the video frame (1) or video clip (1) using a video codec such as H.264 or H.265.

Next, the hash generation program divides the video frame or video clip video frame (1) or video clip (1) into predetermined sizes and extracts feature points through sampling of the entire divided image (2). do. Then, the hash generation program generates hash information by stacking a plurality of segmented images (2) and a plurality of sampling information (3) matching feature points for each.

Here, the hash generation program simultaneously performs sampling on a plurality of image segments (2) and extracts feature points by applying (Convolution Layer) to each sampled image segment (2). Additionally, the digital image data received from the photographing device 200 is in YUV format or converted from RGB format to YUV format.

The processor 130 executes the hash generation program stored in the memory 120. The processor 130 may include various types of devices that control and process data. The processor 130 may refer to a data processing device built into hardware that has a physically structured circuit to perform functions expressed by codes or instructions included in a program. In one example, the processor 130 may include a microprocessor, a central processing unit (CPU), a processor core, a multiprocessor, an application-specific integrated circuit (ASIC), or an FPGA ( It may be implemented in the form of a field programmable gate array, etc., but the scope of the present invention is not limited thereto.

The storage unit 140 may store hash information about digital image data and encoded digital image data.

As described above, in the present invention, digital image data in YUV format is divided into predetermined sizes centered on the Y signal, and hash information is generated using feature points for the entire divided image.

Therefore, by using feature points for the entire image, integrity reliability can be increased, and by dividing and sampling the image, the time required to extract feature points can be shortened. Since the time required to extract feature points is shortened, it can be applied to lightweight devices. This allows economic and time factors to be minimized.

Figure 4 is a flowchart illustrating a hash generation method according to an embodiment of the present invention.

When explaining the hash generation method (S100) of this embodiment with reference to FIGS. 2 and 4, the hash generation method (S100) divides the Y signal of digital image data received from the photographing device 200 into a predetermined size, (Step S110), hash information is generated by extracting feature points through sampling of the entire segment of each image (step S120). Here, the digital image data received from the photographing device 200 is in YUV format or converted from RGB format to YUV format.

Next, details of each step will be described with reference to FIG. 3.

First, the process of dividing the Y signal into a predetermined size (step S110) involves capturing consecutive video frames (1) or video clips (1) of the original digital image data received from the photographing device 200. After encoding each video frame (1) or video clip (1), the Y signal is extracted and divided into predetermined sizes to generate a segmented image (2). Here, the video frame (1) or video clip (1) is encoded using a video codec such as H.264 or H.265.

In addition, the process of generating hash information (step S120) extracts feature points through sampling of the entirety of each segmented image (2), and matches the feature points for each of the multiple image segments (2). Hash information is generated by stacking the sampling information (3).

Here, sampling of a plurality of image segments 2 is performed simultaneously, and feature points are extracted by applying (Convolution Layer) to each sampled image segment 2.

The method according to an embodiment of the present invention may also be implemented in the form of a recording medium containing instructions executable by a computer, such as program modules executed by a computer. Computer-readable media can be any available media that can be accessed by a computer and includes both volatile and non-volatile media, removable and non-removable media. Additionally, computer-readable media may include computer storage media. Computer storage media includes both volatile and non-volatile, removable and non-removable media implemented in any method or technology for storage of information such as computer-readable instructions, data structures, program modules or other data.

Although the methods and systems of the present invention have been described with respect to specific embodiments, some or all of their components or operations may be implemented using a computer system having a general-purpose hardware architecture.

The description of the present application described above is for illustrative purposes, and those skilled in the art will understand that the present application can be easily modified into other specific forms without changing its technical idea or essential features. Therefore, the embodiments described above should be understood in all respects as illustrative and not restrictive. For example, each component described as unitary may be implemented in a distributed manner, and similarly, components described as distributed may also be implemented in a combined form.

The scope of the present application is indicated by the claims described below rather than the detailed description above, and all changes or modified forms derived from the meaning and scope of the claims and their equivalent concepts should be construed as being included in the scope of the present application.

100: Hash generation device
110: communication module
120: memory
130: processor
140: storage unit

Claims (8)

In a hash generation device that generates hash information of digital image data,
Memory where the hash generation program is stored; and
Including a processor executing the hash generation program,
The hash generation program is,
The digital image data received from the imaging device is divided into Y signals of a predetermined size, and feature points are extracted through sampling of the entire divided image to generate hash information.
A digital image data management device, wherein the digital image data is in YUV format. According to paragraph 1,
The hash generation program is,
A hash generation device that simultaneously performs the sampling on a plurality of segmented images. According to paragraph 1,
The hash generation program is,
A hash generation device for extracting the feature points by applying a convolution layer to each segmented image on which the sampling was performed. According to paragraph 1,
The hash generation program is,
A hash generating device that generates the hash information by stacking the plurality of segmented images and a plurality of sampling information matching the feature points for each. In a hash generation method in which a hash generation device generates hash information of digital image data,
(a) dividing the digital image data received from the photographing device into a predetermined size for the Y signal by the hash generating device; and
(b) a step of the hash generating device extracting feature points through sampling for each segmented image and generating hash information,
The digital image data is in YUV format. According to clause 5,
The step of generating the hash information is,
A hash generation method that simultaneously performs the sampling on a plurality of segmented images. According to clause 5,
The step of generating the hash information is,
A hash generation method that extracts the feature points by applying a convolution layer to each segmented image for which the sampling was performed. According to clause 5,
The step of generating the hash information is,
A method for generating the hash, wherein the hash information is generated by stacking the plurality of segmented images and a plurality of sampling information matching the feature points for each.

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