KR20230027616A - System for image-based screen crack detection computer vision - Google Patents

Abstract

The present invention relates to an image-based screen crack detection computer vision system. An image-based screen crack detection computer vision system according to an embodiment of the present invention includes: a memory for storing one or more instructions; a processor for executing the one or more instructions stored in the memory. The processor acquires a screen image from a user terminal, stores a first image obtained by capturing the screen image, stores a second image obtained by applying Gaussian blur to the first image, stores the first image and the second image, compares the images, and identify a crack area in the screen image.

Description

Image-Based Screen Crack Detection Computer Vision System {SYSTEM FOR IMAGE-BASED SCREEN CRACK DETECTION COMPUTER VISION}

The present invention relates to an image based screen crack detection computer vision system.

In the case of Korea, consumer demand for used mobile phones has increased since the implementation of the Act on the Improvement of Distribution Structure of Mobile Communication Devices (hereinafter referred to as the Dantong Act).

It has been pointed out that the burden of overall communication costs increases as the installment principal for mobile phones increases relatively compared to the past as mobile carriers' subsidy is limited when purchasing a mobile phone after the implementation of the Single Call Act. Accordingly, consumer interest in used mobile phones, which has the effect of reducing overall communication costs, is increasing as new mobile phone purchase costs are not incurred.

However, compared to the increased demand for used mobile phones, not only is there no entity that manages and supervises the used mobile phone trading market, but also consumer damage is occurring because the transparency of the market is not secured.

In the case of used mobile phones, in accordance with the current market trend, sellers are required to provide detailed information on each component and product condition of used mobile phones. It only provides approximate appearance information.

Accordingly, there is a problem in that there is a high risk of consumer damage because it is not easy to provide detailed information on the product condition (appearance condition, operating condition, etc.) and quality assurance of used mobile phones.

Solving the above-mentioned problems that may occur in second-hand transactions through portal site cafes or SNS, sellers who want to sell register the overall specifications, price, and condition of used mobile phones, and objective and reasonable inspection is conducted in the brokerage system In addition, there is a need for a system in which a buyer who wants to purchase searches for information about a registered used mobile phone and makes a transparent and fair transaction between the seller and the buyer.

The problem to be solved by the present invention is to provide an image-based screen crack detection computer vision system.

The problems to be solved by the present invention are 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.

An image-based screen crack detection computer vision system according to an embodiment of the present invention for solving the above problems includes a memory for storing one or more instructions, and a processor for executing the one or more instructions stored in the memory, wherein the processor Obtains a screen image from a user terminal, stores a first image obtained by capturing the screen image, stores a second image obtained by applying Gaussian blur to the first image, and combines the first image and the second image By comparison, crack areas in the screen image can be recognized.

An image-based screen crack detection computer vision method according to an embodiment of the present invention for solving the above problems includes acquiring a screen image from a user terminal, storing a first image obtained by capturing the screen image, and The method may include storing a second image obtained by applying Gaussian blur to the first image, and recognizing a cracked area in the screen image by comparing the first image and the second image.

An image-based screen crack detection computer vision program according to an embodiment of the present invention for solving the above problems is combined with a computer that is hardware and stored in a computer-readable recording medium to perform the image-based screen crack detection computer vision method. can be stored

Other specific details of the invention are included in the detailed description and drawings.

The present invention inspects cracks on the screen of the smartphone and inspects the inside of the hardware of the smartphone, so that when the smartphone used by the user is sold as used, the estimated price according to the degree of cracks on the screen and the condition of the hardware Predictable.

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

1 is a diagram illustrating an image-based screen crack detection computer vision system according to an embodiment of the present invention.
2 is a hardware configuration diagram of a computer vision device according to an embodiment of the present invention.

Advantages and features of the present invention, and methods of achieving them, will become clear with reference to the detailed description of the following embodiments taken in conjunction with the accompanying drawings. However, the present invention is not limited to the embodiments disclosed below, but may be implemented in various different forms, only these embodiments are intended to complete the disclosure of the present invention, and are common in the art to which the present invention belongs. It is provided to fully inform the person skilled in the art of the scope of the invention, and the invention is only defined by the scope of the claims.

Terminology used herein is for describing the embodiments and is not intended to limit the present invention. In this specification, singular forms also include plural forms unless specifically stated otherwise in a phrase. As used herein, "comprises" and/or "comprising" does not exclude the presence or addition of one or more other elements other than the recited elements. Like reference numerals throughout the specification refer to like elements, and “and/or” includes each and every combination of one or more of the recited elements. Although "first", "second", etc. are used to describe various components, these components are not limited by these terms, of course. These terms are only used to distinguish one component from another. Accordingly, it goes without saying that the first element mentioned below may also be the second element within the technical spirit of the present invention.

Unless otherwise defined, all terms (including technical and scientific terms) used in this specification may be used with meanings commonly understood by those skilled in the art to which the present invention belongs. In addition, terms defined in commonly used dictionaries are not interpreted ideally or excessively unless explicitly specifically defined.

The term "unit" or "module" used in the specification means a hardware component such as software, FPGA or ASIC, and "unit" or "module" performs certain roles. However, "unit" or "module" is not meant to be limited to software or hardware. A “unit” or “module” may be configured to reside in an addressable storage medium and may be configured to reproduce one or more processors. Thus, as an example, a “unit” or “module” may refer to components such as software components, object-oriented software components, class components, and task components, processes, functions, properties, procedures, subroutines, segments of program code, drivers, firmware, microcode, circuitry, data, databases, data structures, tables, arrays and variables. Functions provided within components and "units" or "modules" may be combined into smaller numbers of components and "units" or "modules" or may be combined into additional components and "units" or "modules". can be further separated.

In this specification, a computer means any kind of hardware device including at least one processor, and may be understood as encompassing a software configuration operating in a corresponding hardware device according to an embodiment. For example, a computer may be understood as including a smartphone, a tablet PC, a desktop computer, a laptop computer, and user clients and applications running on each device, but is not limited thereto.

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

Although each step described in this specification is described as being performed by a computer, the subject of each step is not limited thereto, and at least a part of each step may be performed in different devices according to embodiments.

1 is a diagram illustrating an image-based screen crack detection computer vision system according to an embodiment of the present invention.

Referring to FIG. 1 , an image-based screen crack detection computer vision system according to an embodiment of the present invention may include a computer vision device 100, a user terminal 200, and an external server 300.

Here, the image-based screen crack detection computer vision system shown in FIG. 1 is according to an embodiment, and its components are not limited to the embodiment shown in FIG. 1, and may be added, changed, or deleted as necessary. there is.

The image-based screen crack detection computer vision system according to an embodiment of the present invention inspects cracks occurring on the screen and inspects the inside of the hardware of the user terminal 200, so that when the smartphone used by the user is sold second-hand, the screen screen It is possible to predict the expected price according to the degree of cracks and the condition of the hardware.

The image-based screen crack detection computer vision system can acquire and store data on the condition of the smartphone and, accordingly, the purchase cost from purchasers who purchase the smartphone, and predict the expected price using the stored data. The data obtained can be re-learned and reused to predict expected prices in the future.

The image-based screen crack detection computer vision system obtains device access rights from the user terminal 200 accessing the application or web page, and can inspect the battery, device information, and sensors of the user terminal 200. Specifically, the image-based screen crack detection computer vision system can determine whether the user terminal 200 is currently in a charging state, and determine the degree of battery consumption during load work and the degree of battery consumption over time. In addition, the image-based screen crack detection computer vision system may obtain internal storage performance and memory information of the user terminal 200 to inspect the RAM of the user terminal 200 .

The image-based screen crack detection computer vision system can inspect the state of the user terminal 200 by defining information clustering and state standards for each device through multiclass classification.

The image-based screen crack detection computer vision system can create an optimal model by learning data using Bayesian regression. Accordingly, in a situation in which the number of actual transaction data may be insufficient depending on the type of smartphone, appropriate depreciation can be predicted because learning is possible whenever data is accumulated.

The image-based screen crack detection computer vision system can increase the accuracy of the prediction service by obtaining external data when the transaction history is less than a certain number and applying different weights when the data set is more than a certain number. In addition, the accuracy of the prediction service can be further increased by reviewing whether the SNS market environment is positive or negative information through natural language processing and reflecting it to predict.

The image-based screen crack detection computer vision system may predict a sales price after a predetermined period (eg, 6 months or 1 year), and notify users of events and promotions after the predetermined period. However, the present invention is not limited thereto, and a sales price thereafter may be predicted according to a period set by the user.

In addition, the image-based screen crack detection computer vision system obtains user information such as user name, phone number, and contract information, and predicts the selling price of the smart phone during the contract expiration period to provide the information to the user.

The computer vision device 100 may acquire a screen image from the user terminal 200 and detect cracks occurring on the screen of the user terminal 200 by using the obtained image. The computer vision device 100 may capture the obtained screen image and store the first image as the captured image. The computer vision apparatus 100 may apply Gaussian blur to the first image and store the second image to which the Gaussian blur is applied.

The computer vision device 100 may compare the first image and the second image to recognize a cracked area in the screen image. Accordingly, the computer vision device 100 may detect the location and degree of cracks generated on the screen of the user terminal 200 .

The user terminal 200 may access a website or application through a network, and may receive a result of checking the computer vision device 100 or a smartphone state from the computer vision device 100 .

The user terminal 200 may include at least one of a smart phone, a tablet PC, a desktop computer, and a laptop computer having a display on at least a portion of the user terminal 200, and the computer vision device 100 in the process of executing a browser. A smartphone status check result provided from may be provided. However, it is not limited thereto.

The external server 300 may be connected to the computer vision device 100 through a network, and may store and manage various types of information for the computer vision device 100 to perform the image-based screen crack detection computer vision method.

In addition, the external server 300 may receive and store various types of information and data generated as the computer vision device 100 performs the image-based screen crack detection computer vision method. For example, the external server 300 may be a storage server provided separately outside the computer vision device 100 . Referring to FIG. 2 , the hardware configuration of the computer vision apparatus 100 will be described.

2 is a hardware configuration diagram of a computer vision device according to an embodiment of the present invention.

Referring to FIG. 2 , a computer vision device 100 (hereinafter referred to as a computing device) according to an embodiment of the present invention loads one or more processors 110 and a computer program 151 executed by the processor 110. ) may include a memory 120, a bus 130, a communication interface 140, and a storage 150 for storing the computer program 151. Here, in FIG. 2, only components related to the embodiment of the present invention are shown. Therefore, those skilled in the art to which the present invention pertains can know that other general-purpose components may be further included in addition to the components shown in FIG. 2 .

The processor 110 controls the overall operation of each component of the computing device 100 . The processor 110 includes a Central Processing Unit (CPU), a Micro Processor Unit (MPU), a Micro Controller Unit (MCU), a Graphic Processing Unit (GPU), or any type of processor well known in the art of the present invention. It can be.

Also, the processor 110 may perform an operation for at least one application or program for executing a method according to embodiments of the present invention, and the computing device 100 may include one or more processors.

In various embodiments, the processor 110 may temporarily and/or permanently store signals (or data) processed in the processor 110 (RAM: Random Access Memory, not shown) and ROM (ROM: Read -Only Memory, not shown) may be further included. In addition, the processor 110 may be implemented in the form of a system on chip (SoC) including at least one of a graphics processing unit, RAM, and ROM.

Memory 120 stores various data, commands and/or information. Memory 120 may load computer program 151 from storage 150 to execute methods/operations according to various embodiments of the present invention. When the computer program 151 is loaded into the memory 120, the processor 110 may perform the method/operation by executing one or more instructions constituting the computer program 151. The memory 120 may be implemented as a volatile memory such as RAM, but the technical scope of the present disclosure is not limited thereto.

The bus 130 provides a communication function between components of the computing device 100 . The bus 130 may be implemented in various types of buses such as an address bus, a data bus, and a control bus.

The communication interface 140 supports wired and wireless Internet communication of the computing device 100 . Also, the communication interface 140 may support various communication methods other than Internet communication. To this end, the communication interface 140 may include a communication module well known in the art. In some embodiments, communication interface 140 may be omitted.

The storage 150 may non-temporarily store the computer program 151 . When performing the image-based screen crack detection computer vision method through the computing device 100, the storage 150 may store various types of information necessary to provide the image-based screen crack detection computer vision method.

The storage 150 may be a non-volatile memory such as read only memory (ROM), erasable programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), flash memory, or the like, a hard disk, a removable disk, or a device well known in the art. It may be configured to include any known type of computer-readable recording medium.

Computer program 151 may include one or more instructions that when loaded into memory 120 cause processor 110 to perform methods/operations in accordance with various embodiments of the invention. That is, the processor 110 may perform the method/operation according to various embodiments of the present disclosure by executing the one or more instructions.

In one embodiment, the computer program 151 includes obtaining a screen image from a user terminal, storing a first image obtained by capturing the screen image, and generating a second image obtained by applying Gaussian blur to the first image. and storing and comparing the first image and the second image to recognize cracked areas in the screen image. can

Steps of a method or algorithm described in connection with an embodiment of the present invention may be implemented directly in hardware, implemented in a software module executed by hardware, or implemented by a combination thereof. A software module may include random access memory (RAM), read only memory (ROM), erasable programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), flash memory, hard disk, removable disk, CD-ROM, or It may reside in any form of computer readable recording medium well known in the art to which the present invention pertains.

Components of the present invention may be implemented as a program (or application) to be executed in combination with a computer, which is hardware, and stored in a medium. Components of the present invention may be implemented as software programming or software elements, and similarly, embodiments may include various algorithms implemented as data structures, processes, routines, or combinations of other programming constructs, such as C, C++ , Java (Java), can be implemented in a programming or scripting language such as assembler (assembler). Functional aspects may be implemented in an algorithm running on one or more processors.

Although the embodiments of the present invention have been described with reference to the accompanying drawings, those skilled in the art to which the present invention pertains can be implemented in other specific forms without changing the technical spirit or essential features of the present invention. you will be able to understand Therefore, it should be understood that the embodiments described above are illustrative in all respects and not restrictive.

100: computing device
200: user terminal
300: external server

Claims (3)

a memory that stores one or more instructions; and
a processor to execute the one or more instructions stored in the memory;
the processor,
Acquiring a screen image from a user terminal, storing a first image obtained by capturing the screen image, storing a second image obtained by applying Gaussian blur to the first image, and comparing the first image and the second image Recognizing a crack area in the screen image,
Image-based screen crack detection computer vision system.
In a method performed by a computing device,
obtaining a screen image from a user terminal;
storing a first image obtained by capturing the screen image;
storing a second image obtained by applying Gaussian blur to the first image; and
Recognizing a crack area in the screen image by comparing the first image and the second image;
An image-based screen crack detection computer vision method.
A computer program stored in a computer-readable recording medium to be combined with a computer, which is hardware, to perform the method of claim 2.

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