WO2016080815A1 - Procédé d'inspection de faux passeport et support d'enregistrement associé - Google Patents

Procédé d'inspection de faux passeport et support d'enregistrement associé Download PDF

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Publication number
WO2016080815A1
WO2016080815A1 PCT/KR2015/012597 KR2015012597W WO2016080815A1 WO 2016080815 A1 WO2016080815 A1 WO 2016080815A1 KR 2015012597 W KR2015012597 W KR 2015012597W WO 2016080815 A1 WO2016080815 A1 WO 2016080815A1
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Prior art keywords
passport
image
inspection
contrast
forgery
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PCT/KR2015/012597
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English (en)
Korean (ko)
Inventor
이중
나기현
강태이
변준석
정도준
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대한민국(관리부서:행정자치부 국립과학수사연구원장)
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Publication of WO2016080815A1 publication Critical patent/WO2016080815A1/fr

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/10—Segmentation; Edge detection
    • G06T7/11—Region-based segmentation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/10—Image acquisition
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/20—Image preprocessing

Definitions

  • the present invention relates to a forgery passport inspection method and a recording medium thereof, and more particularly, to input the image of the inspection passport to the passport inspection system using a scanner that provides visible, infrared, and ultraviolet images, image processing and pattern recognition Technology to compare the inspection passport image with the comparison passport of the issuing country stored in the database, to validate the MRZ (Machine Readable Zone) data of the inspection passport image, to compare the histogram of the inspection passport with the pattern area of the contrast passport, By comparing the calculation results of the number of pixels, average value and standard deviation of the binary pixel data forming the pattern area of the passport against the passport, or performing geometric correction and pattern analysis to match the position and rotation angle of the passport image.
  • MRZ Machine Readable Zone
  • Passport forgery and alteration methods are used forgery or alteration.
  • the alteration of the passport information is damaged and the information is rewritten or printed and the photograph is replaced.
  • 1 is a view showing a conventional passport forgery forgery prevention unit.
  • Passport forgery prevention forgery image acquisition unit through the camera 11 A masked face region generator 12 extracting only a face region portion from the face image of the issuer; A face unique data generator 13 for extracting a feature point unique to the face from the face image image extracted by the masked face region generator 12 to determine whether or not to forgery; A 2D barcode converter 14 for converting the extracted face unique data into 2D barcode data; A passport / Visa production unit 15 for creating a passport by simultaneously inserting a portrait photograph obtained from the masked face region generator 12 and printed 2D barcode data; After entering the personal information of the passport issuer through the passport input section, the passport input and certification test (16) is used to test whether the photo of the passport matches the 2D barcode before issuing, and the final passport issued after the test is issued. Issuance unit 17 is composed.
  • the forgery passport holder passing examination unit separates the face unique data stored in the 2D barcode and the face image attached to the passport photo, and generates the face unique data from the face image and compares the face unique data of the 2D barcode.
  • a passport forgery reading unit is provided.
  • each passport has a unique pattern printed with infrared or ultraviolet ink to prevent inherent forgery, and the specific technique of analyzing the portion to identify the forgery of the passport has not been introduced.
  • An object of the present invention for solving the problems of the prior art is to input the image of the inspection passport to the passport inspection system using a scanner that provides visible light, infrared, ultraviolet light image, inspection using image processing and pattern recognition technology Compare the passport image with the issuing country's contrast passport stored in the database, validate the MRZ (Machine Readable Zone) data in the inspection passport image, compare the histogram of the pattern area of the passport with the inspection passport, or compare with the inspection passport Compare the results of the calculation of the number of pixels, average value and standard deviation of the binary pixel data that form the pattern area of the passport, or perform geometric correction and pattern analysis to match the position and rotation angle of the inspection passport image. Based on the pattern, the ultraviolet ray image of the passport As compared to the turn region for identifying the passport forgery, to a forged passport control method and a recording medium.
  • MRZ Machine Readable Zone
  • a forgery passport inspection method includes a control unit, a storage unit connected to the control unit and stored a contrast passport image, an input unit connected to the control unit and means for inputting a user's command, and the control unit Is executed in a passport inspection system which is connected to and comprises a display unit displaying the inspection results;
  • a passport preparation step in which the preparation passport and the inspection passport are prepared.
  • a test result display step in which the passport forgery test result is displayed on the display unit.
  • the forgery passport inspection method and its recording medium according to the present invention are quick and simple using only software that implements the proposed technology of a scanner and passport inspection system for scanning an inspection passport image including a pattern region formed of visible light, infrared rays, or ultraviolet rays. Passport forgery and identification can be identified, thus increasing the speed of passport inspection, such as immigration, and maximizing the reliability of passport inspection by verifying the authenticity of passport through quantitative inspection.
  • the proposed forgery passport inspection method automatically calculates and provides similarity through quantitative comparison between the inspection passport (the passport to be inspected) and the comparison passport (the standard passport of the issuing country), thereby minimizing the errors caused by the subjective judgment.
  • the proposed forgery passport inspection method provides a normalization and overlapping cutoff comparison method that can help subjective detailed comparison between the inspection passport and the comparison passport, complementing the limitation of quantitative inspection to secure the reliability of passport inspection, and thus using the forged passport. Has the effect of reducing
  • 1 is a view showing a conventional passport forgery forgery prevention unit.
  • Figure 2 is a schematic diagram of a forgery passport inspection system according to the present invention.
  • FIG. 3 is an internal configuration diagram of a passport inspection system according to an embodiment of the present invention.
  • FIG. 4 is a flowchart illustrating a forgery passport inspection method according to the present invention.
  • FIG. 5 is a flowchart illustrating a step in which a histogram of a check passport pattern region and a histogram of a contrast passport pattern region are compared.
  • FIG. 6 is a flowchart illustrating a passport comparison step in which a calculation result of the number of pixels, an average value, and a standard deviation of binarized pixel data constituting a pattern area of a passport and a passport is compared.
  • FIG. 7 is a flowchart illustrating a passport image correction step of performing a geometric correction to match the position and rotation angle of the contrast passport and inspection passport image between the contrast passport image search step and the passport contrast step.
  • FIG. 8 is a diagram for explaining the conversion after applying the result of the second derivative using the Laglacian of Gaussian (LoG) of the inspection passport image to the box filter using the Hessian matrix as the interest point of the inspection passport image.
  • LiG Laglacian of Gaussian
  • FIG. 9 is a schematic diagram of an image pyramid constructed by constructing a scale space and up-scaling the result of a second derivative using a Laglacian of Gaussian (LoG) of an inspection passport image. The figure shown.
  • LiG Laglacian of Gaussian
  • FIG. 10 is a diagram illustrating calculating a Haar-wavelet response in x and y directions for neighbors within a predetermined distance from a feature point after selecting a feature point of an inspection passport image.
  • the passport to be examined is referred to as an 'test passport'
  • the standard passport of the issuing country according to each nationality is referred to as a 'contrast passport'.
  • Figure 2 is a schematic diagram of a forgery passport inspection system according to the present invention.
  • the forgery passport inspection system compares the image of the inspection passport with the image of the contrast passport and checks the forgery of the passport, and the passport inspection system 110 is connected to the visible ray (Visible Ray) or infrared ( Infrared Rays, or Ultraviolet Ray (Ultraviolet Rays) pattern region is formed of a scanner 120 for scanning an image formed.
  • visible ray Visible Ray
  • infrared Infrared Rays
  • Ultraviolet Ray Ultraviolet Ray
  • FIG. 3 is an internal configuration diagram of a passport inspection system according to an embodiment of the present invention.
  • the passport inspection system 110 is connected to the scanner 120, and compares the inspection passport image scanned by the scanner 120 with the image of the contrast passport to the control unit 111 for checking forgery and alteration of the passport, and the control unit 111.
  • the control unit 111 which stores the inspection passport image and the contrast passport image is stored, and is connected to the input unit 113 and the control unit 111, which are means for inputting a user's command.
  • the display unit 115 is displayed, and the connection unit 119 connected to the scanner 120.
  • FIG. 4 is a flowchart illustrating a forgery passport inspection method.
  • the forgery passport inspection method includes a control unit 111, a storage unit 117 connected to the control unit 111 and storing a contrast passport image, and an input unit 113 connected to the control unit 111 and a means for inputting a user's command. And a display unit 115 connected to the control unit 111 and displaying a test result;
  • An inspection passport image is acquired and stored in the storage unit 117 through a scanner 120 that scans a passport image including a visible ray, an infrared ray, or an ultraviolet ray pattern region.
  • Obtaining an inspection passport image A validation step of performing validation of MRZ (Machine Readable Zone) data on the image of the inspection passport;
  • MRZ Machine Readable Zone
  • FIG. 5 is a flowchart illustrating a passport comparison step in which a histogram of a check passport pattern region is compared with a histogram of a passport pattern region.
  • the passport comparison step may include a pattern area separation step of separating the inspection passport and a unique pattern area formed by ultraviolet or infrared rays from the comparison passport, and histogram data of the pattern area separated from the inspection passport and the contrast passport image. Histogram data extraction step is extracted, and the histogram data contrast step is compared with the histogram of the passport pattern region contrasted with the histogram of the inspection passport pattern region.
  • FIG. 6 is a flowchart illustrating a passport comparison step in which a calculation result of the number of pixels, an average value, and a standard deviation of binarized pixel data constituting a pattern area of a passport and a passport is compared.
  • the passport comparison step may include: a pattern area separation step of separating pattern areas from the inspection passport and the comparison passport; A binarization step in which the separated pattern region is binarized; A comparison passport calculation step of calculating the number of pixels, an average value, and a standard deviation of the binarized pixel data forming the pattern region of the comparison passport; An inspection passport calculation step of calculating the number of pixels, an average value, and a standard deviation of the binarized pixel data forming the pattern region of the inspection passport; And a calculation result comparison step in which the calculation result for the passport is compared with the calculation result for the passport.
  • FIG. 7 is a flowchart illustrating a passport image correction step of performing a geometric correction to match the position and rotation angle of the contrast passport and inspection passport image between the contrast passport image search step and the passport contrast step.
  • a correction of the passport image is further performed by performing a geometric correction to match the position and rotation angle of the contrast passport and the inspection passport image;
  • the passport image correction step includes calculating a Hessian matrix of pixels forming a contrast passport image with a check passport image, generating a scale space for the pixels forming each image, and upscaling.
  • Image pyramid is generated, a feature point group is selected from an image of each scale, a Haar-wavelet response is calculated for the feature point group, and a dominant is generated from the Haar-wavelet response result.
  • the direction is calculated, and the coordinates of the pixels constituting the image of the contrast passport and the inspection passport with respect to the detected feature points are reset, and the rotational displacement is reset so that the dominant directions coincide with each other and stored in the storage unit 117.
  • a scanner 120 is connected to the control unit 111, and in the obtaining of the inspection passport image, the visible light image, the ultraviolet image, and the infrared image of the inspection passport scanned by the scanner 120 are stored in the storage unit 117; In the pattern region separation step, the pattern region in the visible light image, the ultraviolet image, and the infrared image is separated.
  • the passport comparison step includes a pattern area separation step of separating an image of a pattern area from an inspection passport and a contrast passport, and histogram data of each pixel of the image of the separated pattern area (x-axis is 8 bits each of R, G, and B values).
  • the histogram data extraction step of extracting the R, G, and B values, and the y-axis frequency (number)) and the histogram data comparison step in which the histogram of the passport pattern area is compared with the histogram of the passport pattern area.
  • a histogram contrast step A binarization step in which each pixel of the image of the separated pattern region is binarized to black and white by a threshold extracted by finding an inflection point in the contrast distribution of the image using the Otsu algorithm, and the binarization forming the pattern region of the contrast passport.
  • a comparison passport operation step in which the processed pixel data is calculated (number of black and white pixels, average value and standard deviation);
  • An inspection passport calculation step in which the binarized pixel data constituting the pattern area of the inspection passport is calculated (the number of black and white pixels, the average value and the standard deviation), and an operation in which the operation result of the passport is compared with that of the inspection passport.
  • a pixel data contrast step comprising a result contrast step.
  • Passport No Passport No, Passport No, Passport Type, Country Code, Surname, Given Name, Nationality, Sex, Date of birth, It includes social security number, date of issue, authority, date of expiry, and personal information in the description.
  • MMRZ Machine Readable Zone
  • MRZ data includes the type of passport, country code, surname, given name, passport number, nationality, date of birth, gender, expiration date, and social security number.
  • passports of various countries are printed with a unique pattern (eg, Taegeuk patterns) in infrared and ultraviolet ink, which are used to prevent passport forgery.
  • a unique pattern eg, Taegeuk patterns
  • infrared and ultraviolet ink which are used to prevent passport forgery.
  • MRZ validation is based on ICAO Document 9303 (endorsed by the International Organization for Standardization and the International Electrotechnical Commission as ISO / IEC 7501-1).
  • the second line of the MRZ area at the bottom of the passport contains the above information.
  • C stands for Checksum.
  • Four out of five checksums each validate the previous passport number, date of birth, expiration date, and personal identification code, and the last five checksums validate the entire code.
  • Each passport contains its own anti-counterfeiting element.
  • There is also a unique pattern is printed in the infrared and ultraviolet ink, in the present invention is to detect the forgery of the inspection passport by analyzing the portion of the unique pattern area of the image of the inspection passport and the contrast passport.
  • Applied techniques include geometric correction (to first position the same type of contrast passport (standard sample passport) as the inspection passport for automated analysis) and pattern analysis (UV for both passports corrected to the same position).
  • IR and infrared (UV) anti-counterfeiting device is determined whether there is a certain pattern in the anti-counterfeiting device is used to determine the authenticity using a comparative analysis algorithm for each pattern.
  • the inspection passports are obtained by the inspection passport image by varying the scanning position and the rotation angle, so the position and rotation when comparing the inspection passport and the contrast passport You need to 'geometrically correct' the angles equally.
  • the SURF algorithm finds a feature that is invariant to environmental changes by considering environmental changes such as scale, illumination, and viewpoint from multiple images. It is faster than existing algorithm by analyzing scale space with box filter using integral image.
  • first-order derivatives second-order derivatives
  • the first derivative is used with the term gradient, and it has a vector value to know the magnitude, direction, and edge direction.
  • the edge of the image is a point at which the brightness value (pixel value) of the image changes.
  • the second derivative is a derivative of the first derivative, called Laplacian.
  • Lxx, Lxy, and Lyy are convolutions of Gaussian-Laplacian second derivatives at points (x, y) in the image. sigma means scale.
  • the Hessian matrix is used in the image of the inspection passport to find the interest point.
  • Lxx (x, y, ⁇ ) is the result of the second order derivative using the Laplacian of Gaussian (LoG) of the inspection passport image and is converted as shown in FIG. 8 when applied to the box filter.
  • FIG. 8 is a diagram illustrating the results of the second derivative using the Laglacian of Gaussian (LoG) of the inspection passport image using the Hessian matrix as a feature point of the inspection passport image.
  • LiG Laglacian of Gaussian
  • FIG. 9 is a diagram illustrating an image pyramid constructed by performing scale-up and up-scaling of the result of the second derivative using a Laglacian of Gaussian (LoG) of an inspection passport image. to be.
  • LiG Laglacian of Gaussian
  • the candidate candidates are selected when the center point is the largest compared to the neighboring points by using non-maximal suppression for each.
  • an orientation is assigned to generate a descriptor of each feature point.
  • Haar- in the x and y directions with respect to neighbors within a certain distance from the feature point as shown in FIG. 14. Compute the wavelet response.
  • FIG. 10 is a diagram illustrating calculating a Haar-wavelet response in x and y directions for neighbors within a predetermined distance from a feature point after selecting a feature point of an inspection passport image.
  • the process of calculating the haar-wavelet response consists of 2.5 gradients in the x and y directions for each point for the feature point (x, y) and neighboring points (x-6: x + 6, y-6: y + 6). Calculated by multiplying Gaussian distributions with sigma values.
  • a 60 ° fan-shaped window is used to calculate the haar-wavelet response in the x and y directions for neighbors within a certain distance around the feature point (x, y). Adding all the responses in a fan-shaped window, we can create a new vector like the red arrow in Figure 14, the longest of which matches the dominant orientation.
  • matching is performed using the finally detected feature point and the descriptor of each feature point, and based on the matched result, translation is performed on the x and y axes and rotation in 2D space is performed. To match the position of the two images.
  • a unique pattern area of each passport registered in the database of the passport inspection system is retrieved and the image is extracted.
  • the image extracted from the unique pattern area of each passport is converted into a channel having a value of 8 bits for each pixel through gray-scale, and based on this, the Y, R, G, and B values (0 to 255) of the x-axis of each pixel are converted.
  • a histogram representing the frequency (number) of the axes is constructed. This is the same for both the inspection passport image entered through the scanner into the passport inspection system and the standard sample passport image retrieved from the database.
  • FIG. 11 is a channel analysis of 8-bit values for each pixel of the image extracted from the pattern area (left) of the passport using the Chi-suqare test when the pattern analysis of the pattern area image of the inspection passport and the contrast passport is performed. Based on this, the histogram (right) which shows the frequency (number) of the Y-axis with respect to the R, G, and B values (0-255) of the x-axis of each pixel is shown.
  • the histogram of the pattern area formed by infrared and ultraviolet inks of the pattern area image of the passport and the histogram of the image of the pattern area of the passport are compared with the histogram. Used. Chi-square test is a statistical technique for measuring the correlation between two discrete variables. Two histograms are used as the observed frequencies (O: Observed frequencies) and the expected frequencies (E) in Equation 2.
  • the variables included in the equation are O (observed) is the observed value (the value of the histogram bin), E (expected) is the expected value (the value of the histogram bin), and the sum of the operations for each corresponding frequency. (The number of bins is 0-255).
  • the contrast passports (standard sample passports) stored in the DB of the passport inspection system are set to the expected value (E), and the inspection passport is set to the observation value (O).
  • Equation 2 The resultant obtained through Equation 2 is used to calculate the p-value from the Chi-square distribution (chi-square distribution, ⁇ 2 distribution).
  • the final verification of passport forgery is performed by comparing the significance level stored in the database of the passport inspection system with the obtained p-value.
  • Chi-square distribution (chi-square distribution, ⁇ 2 distribution) is the sample variance when variance of ⁇ 2, and extract all samples in the sample size n from the population forms a normal distribution
  • the Chi-square distribution (chi-square distribution, ⁇ 2 distribution) with degrees of freedom of (n-1) to be.
  • p-value selects the corresponding value from the chi-square distribution table as shown in Table 3.
  • the value may change depending on the brightness of the passport image compared to the passport.
  • black and white by the threshold (binar) black and white by the threshold (binar) to extract the shade ratio is used additionally.
  • the Chi-square test uses a gray-scale space when analyzing the pattern area of the passport.
  • the value may change depending on the brightness of the passport image.
  • Each pixel of the pattern region image of the passport is binarized into black and white using a threshold using the Otsu algorithm, and the shade ratio is extracted and compared.
  • Otsu algorithm is used for binarization.
  • the Otsu algorithm extracts a threshold value that distinguishes black and white from the inflection point of the contrast image of the passport image, so that each pixel has a result independent of the brightness of the pattern region image of the passport.
  • Binary black and white images can be created.
  • the binarized pattern region image is converted to a black and white image with a channel of 1 bit per pixel.When the conversion is completed, the entire pixel of the pattern region image is read, and the number, average, and standard deviation of the black and white pixels are shown in Table 4 below. Calculate it together. The calculation is performed on all reference data of the pattern region image.
  • the mean, standard deviation, and pixel percentage (%) of the total pixel data of the pattern area image of the inspection passport and the comparison passport are respectively calculated.
  • the effective range of the shade ratio is calculated and the difference between the inspection passport (test passport) and the comparison passport (standard sample passport) is output.
  • the process of calculating the effective range of the shade ratio is first calculated using the Shade ratio average and the standard deviation of the comparative passports (standard passports), and then the probability distribution is calculated based on a certain probability (currently 10%, which is later applied by different countries). Set the effective range.
  • the final result of the pattern analysis on the passport and contrast passport areas is to compare the threshold value stored in the database for each passport with the sum of the results of the Chi-square test and the shade ratio. Whether or not is derived.

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Abstract

L'invention concerne un procédé permettant d'inspecter un faux passeport, ainsi qu'un support d'enregistrement associé. L'invention est mise en œuvre dans un système d'inspection de passeport comprenant : une unité de commande ; une unité de stockage qui est connectée à l'unité de commande et stocke une image d'un passeport à des fins de comparaison ; une unité d'entrée qui est connectée à l'unité de commande et sert de moyen pour entrer une commande d'utilisateur ; et une unité d'affichage qui est connectée à l'unité de commande et affiche le résultat d'inspection, et comprend : une étape d'acquisition d'image de passeport inspecté permettant d'acquérir une image d'un passeport inspecté au moyen d'un scanner connecté au système d'inspection de passeport et de stocker l'image acquise dans l'unité de stockage ; une étape de vérification de validité permettant de vérifier la validité des données d'une zone lisible par machine (MRZ) dans l'image du passeport inspecté ; une étape de recherche d'image de comparaison permettant de rechercher une image d'un passeport de comparaison qui doit être comparé au passeport inspecté, à partir de l'unité de stockage ; une étape de comparaison de passeport permettant de comparer le passeport inspecté avec le passeport destiné à la comparaison ; et une étape d'affichage de résultat d'inspection de faux passeport permettant d'afficher le résultat de l'inspection sur l'unité d'affichage.
PCT/KR2015/012597 2014-11-21 2015-11-23 Procédé d'inspection de faux passeport et support d'enregistrement associé WO2016080815A1 (fr)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
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Families Citing this family (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR101996816B1 (ko) * 2017-12-19 2019-07-08 하트미디어(주) 반응형 웹에서의 웹 스타일 가이드 준수율 측정방법
KR102597955B1 (ko) 2023-06-09 2023-11-07 한국조폐공사 여권자동투입부를 구비한 여권검사장치
KR102606596B1 (ko) 2023-07-26 2023-11-29 한국조폐공사 여권 개방 및 폐쇄부를 구비한 여권검사장치

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20030027326A (ko) * 2001-09-28 2003-04-07 윤경호 위조방지용 여권 및 여권확인 및 관리시스템
KR20030027291A (ko) * 2001-09-28 2003-04-07 주식회사 한국인식기술 여권 위조 방지용 인식 시스템
KR20100130832A (ko) * 2009-06-04 2010-12-14 인천국제공항공사 출입국 절차 자동화 장치 및 그 자동화 방법
KR101438443B1 (ko) * 2014-02-21 2014-09-12 (주)하소인텍 위조 신분증 감식시스템 및 이를 이용한 감식방법

Family Cites Families (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR200293463Y1 (ko) 2002-07-31 2002-10-31 김상훈 위변조 방지용 얼굴인식 여권/비자 발급 및 공항 심사 방법

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20030027326A (ko) * 2001-09-28 2003-04-07 윤경호 위조방지용 여권 및 여권확인 및 관리시스템
KR20030027291A (ko) * 2001-09-28 2003-04-07 주식회사 한국인식기술 여권 위조 방지용 인식 시스템
KR20100130832A (ko) * 2009-06-04 2010-12-14 인천국제공항공사 출입국 절차 자동화 장치 및 그 자동화 방법
KR101438443B1 (ko) * 2014-02-21 2014-09-12 (주)하소인텍 위조 신분증 감식시스템 및 이를 이용한 감식방법

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
AMARAL: "Content-Based Image Retrieval for Medical Applications", October 2010 (2010-10-01), Retrieved from the Internet <URL:http://www.inescporto.pt/-jsc/students/2010IgorAmaral/2010relatorioIgorAmaral.pdf> *

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112215225A (zh) * 2020-10-22 2021-01-12 北京通付盾人工智能技术有限公司 一种基于计算机视觉技术的kyc证件核验方法
CN112215225B (zh) * 2020-10-22 2024-03-15 北京通付盾人工智能技术有限公司 一种基于计算机视觉技术的kyc证件核验方法

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