WO2017141006A1 - Procédé et appareil de détection de falsification de document - Google Patents

Procédé et appareil de détection de falsification de document Download PDF

Info

Publication number
WO2017141006A1
WO2017141006A1 PCT/GB2017/050193 GB2017050193W WO2017141006A1 WO 2017141006 A1 WO2017141006 A1 WO 2017141006A1 GB 2017050193 W GB2017050193 W GB 2017050193W WO 2017141006 A1 WO2017141006 A1 WO 2017141006A1
Authority
WO
WIPO (PCT)
Prior art keywords
pixels
image
cheque
digital image
cell
Prior art date
Application number
PCT/GB2017/050193
Other languages
English (en)
Inventor
Wayne Christopher David CARLISLE
Hassan Sabry Abdul BARY
Original Assignee
Checkprint Limited
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Checkprint Limited filed Critical Checkprint Limited
Priority to EP17704525.9A priority Critical patent/EP3417429A1/fr
Publication of WO2017141006A1 publication Critical patent/WO2017141006A1/fr

Links

Classifications

    • G—PHYSICS
    • G07—CHECKING-DEVICES
    • G07D—HANDLING OF COINS OR VALUABLE PAPERS, e.g. TESTING, SORTING BY DENOMINATIONS, COUNTING, DISPENSING, CHANGING OR DEPOSITING
    • G07D7/00—Testing specially adapted to determine the identity or genuineness of valuable papers or for segregating those which are unacceptable, e.g. banknotes that are alien to a currency
    • G07D7/20—Testing patterns thereon
    • G07D7/2008—Testing patterns thereon using pre-processing, e.g. de-blurring, averaging, normalisation or rotation
    • G—PHYSICS
    • G07—CHECKING-DEVICES
    • G07D—HANDLING OF COINS OR VALUABLE PAPERS, e.g. TESTING, SORTING BY DENOMINATIONS, COUNTING, DISPENSING, CHANGING OR DEPOSITING
    • G07D7/00—Testing specially adapted to determine the identity or genuineness of valuable papers or for segregating those which are unacceptable, e.g. banknotes that are alien to a currency
    • G07D7/20—Testing patterns thereon
    • G—PHYSICS
    • G07—CHECKING-DEVICES
    • G07D—HANDLING OF COINS OR VALUABLE PAPERS, e.g. TESTING, SORTING BY DENOMINATIONS, COUNTING, DISPENSING, CHANGING OR DEPOSITING
    • G07D7/00—Testing specially adapted to determine the identity or genuineness of valuable papers or for segregating those which are unacceptable, e.g. banknotes that are alien to a currency
    • G07D7/06—Testing specially adapted to determine the identity or genuineness of valuable papers or for segregating those which are unacceptable, e.g. banknotes that are alien to a currency using wave or particle radiation
    • G—PHYSICS
    • G07—CHECKING-DEVICES
    • G07D—HANDLING OF COINS OR VALUABLE PAPERS, e.g. TESTING, SORTING BY DENOMINATIONS, COUNTING, DISPENSING, CHANGING OR DEPOSITING
    • G07D7/00—Testing specially adapted to determine the identity or genuineness of valuable papers or for segregating those which are unacceptable, e.g. banknotes that are alien to a currency
    • G07D7/20—Testing patterns thereon
    • G07D7/2016—Testing patterns thereon using feature extraction, e.g. segmentation, edge detection or Hough-transformation
    • G—PHYSICS
    • G07—CHECKING-DEVICES
    • G07D—HANDLING OF COINS OR VALUABLE PAPERS, e.g. TESTING, SORTING BY DENOMINATIONS, COUNTING, DISPENSING, CHANGING OR DEPOSITING
    • G07D7/00—Testing specially adapted to determine the identity or genuineness of valuable papers or for segregating those which are unacceptable, e.g. banknotes that are alien to a currency
    • G07D7/06—Testing specially adapted to determine the identity or genuineness of valuable papers or for segregating those which are unacceptable, e.g. banknotes that are alien to a currency using wave or particle radiation
    • G07D7/12—Visible light, infrared or ultraviolet radiation

Definitions

  • the present invention is concerned with detection of tampering with a document.
  • it is concerned with detection of tampering with cheques.
  • Fraudsters are known to tamper with cheques in a variety of ways in order to try to obtain improper payments from banks. This may for example involve theft of bona fide cheques which are then altered prior to presentation to a bank. Tampering with a cheque covers both forgery of the cheque itself and illicit alteration of a cheque's information content.
  • cheques can be altered for fraudulent purposes. For example, by altering the payee on a completed cheque, the fraudster may divert payment into its own account. By altering the amount, the fraudster may obtain a larger payment than it is entitled to. Alteration of the cheque may be carried out in a range of different ways. For example some form of washing or coating may be applied to the cheque to remove or conceal written or printed markings before replacing them with the fraudulent information.
  • a background marking often in the form of a pattern, applied to the cheque - especially in the regions which are to be filled in by the drawer, such as the field for the amount payable - helps to reveal where markings have been removed by techniques such as washing, since the marking will be absent in the areas affected.
  • the pattern is often formed by an ultra violet ink which is not apparent to the naked eye but which can be seen under ultra violet illumination or by means of a UV sensitive camera.
  • Some of these fraud prevention measures can be put to use only where access is available to the paper cheque itself. I n a clearing system reliant entirely on exchange of digitised cheque images, opportunities for successful cheque tampering are thus potentially increased.
  • the present invention there is a computer-implemented method of testing a digital image of a cheque for indications that the cheque was subject to tampering according to any of the appended independent method claims. According to a further aspect of the present invention there is an apparatus for testing a document for tampering according to any of the appended independent product claims.
  • Figure la shows an optical image of a cheque obtained by scanning the cheque using an imaging device sensitive to light frequencies in the visible part of the spectrum (hereinafter a "visible light image”) and Figure lb is a bi-tonal version of the same image;
  • FIG 2 shows an inverted image of the same cheque obtained using a camera sensitive to ultra violet light (hereinafter, a "UV image");
  • Figure 3 shows a portion of the Figure 2 image to an enlarged scale
  • Figures 4a to 4c represent, at a pixel level, cells used for image analysis in an embodiment of the present invention.
  • Figure 5 is a highly schematic representation of a computing environment suitable for implementing the present invention.
  • the cheque 10, 10a, 10b illustrated in Figures 1 and 2 is in itself of a conventional type. It comprises a thin rectangular substrate which is paper in this example although it could in principle comprise some other suitable material, such as a polymer substrate, although not in the UK where the substrate is strictly specified and controlled.
  • the cheque's front face carries various markings, some of them printed onto the cheque during its manufacture and others filled in by the drawer (the person completing the cheque).
  • the printed markings applied during manufacture include data applied during initial printing of the cheque: a bank name/logo 12, a bank branch sort code 14, a number line comprising the cheque's serial number 16, the bank branch sort code 18 and the drawer's bank account number 20.
  • these are printed in magnetic ink, in a font which is suited to reading by MICR, the identity 22 of the drawer. This is an example of a corporate cheque where the identity is often included. A personal cheque will not show this.
  • pre-printed parts of the cheque delineate fields for insertion of information by the drawer.
  • These fields comprise: lines 24 for the payee and 26 for the legal amount - the amount payable, in words, a date line 28, a box 30 for the courtesy amount (in figures) and a signature space 32.
  • the UV image 10b of Figure 2 includes all of these markings but additionally shows a background marking 34.
  • a background marking 34 This is not seen in the visible light image 10a, nor upon inspection of the physical cheque with the naked eye, because it is formed by what is sometimes referred to as invisible UV ink - ink that is not visible to, or at least difficult to discern with, the naked eye, but is revealed by some other means.
  • the background marking 34 is visible when the cheque is imaged using a photodetector sensitive to light in the ultra violet frequency range.
  • the background marking may take a variety of forms but typically has, in relation to the other markings on the cheque, a relatively high spatial frequency. This makes its presence or absence on any chosen part of the cheque easier to discern.
  • the background marking 34 is a pattern of wavy lines closely spaced from one another and overlapping one another, which provides a high spatial frequency of variation from light to dark. In the illustrated example the background marking 34 covers much of the area of the cheque, including almost all of the information-bearing area save for the number line 16, 18, 20. In other cases the background marking may be more selectively applied. Imaging the cheque
  • the physical cheque is typically presented by the payee to a collecting bank (or other institution).
  • the collecting bank scans the physical cheque to obtain at least one digital image.
  • the first image is the visible light image 10 of Figure la and is obtained using a camera sensitive to light in the visible part of the spectrum.
  • the same optically sampled image is shown in bitonal form - that is, pixels are represented as either black or white, rather than in RGB format as in Figure la.
  • the second image is the UV image 10b of Figure 2 and is obtained using a camera sensitive to light in the ultra violet part of the spectrum.
  • This image has been inverted - that is, each pixel colour value has been subtracted from the maximum colour value.
  • Scanning devices capable of scanning cheques to provide both visible light and UV images are commercially available and will be familiar to the skilled person.
  • Typical scanners have a motorised feeder which moves the cheque past an imaging head incorporating both visible and UV imaging devices.
  • the scanner may additionally read the code line by MICR.
  • the visible light and UV images 10a, 10b, are then output in digital form to a computer for processing.
  • image is used herein to refer both to the displayed image - e.g. on the screen of a computer - and to the digital data set by which this image is represented.
  • the computer processing of the images includes steps intended to detect cheque tampering. That is, the images are subject to a computer-implemented test intended to detect whether the physical cheque was tampered with prior to scanning.
  • the test is not necessarily expected to be 100% accurate. It may be subject to false positives, so that cheques which fail the test and are thus considered suspect will need to be subject to further enquiry or examination before appropriate action is taken by the relevant institution.
  • the images will be digitally transmitted from the collecting bank to the drawer's bank through a computer network, so in principle the image analysis may be carried out anywhere in the computer network - by the collecting bank, the drawer's bank, or by some intermediate authority.
  • the present invention is adaptable to any of these possibilities.
  • the method used to analyse the images comprises the following steps:
  • Step 1 The bi-tonal version 10a of the optical image is analysed to identify information- bearing fields.
  • Step 2 The information-bearing fields are each divided into tiles.
  • Step 3 Each tile is scanned to identify aberrant cells within the tile. If aberrant cells are identified, these are listed to form an output for further analysis.
  • the information-bearing fields which are used in the present embodiment are indicated by rectangles in Figure 2 and comprise a payee field 24a containing the payee line 24, a legal amount field 26a containing the legal amount lines 26, a date field 28a containing the date line 28, a courtesy amount field 30a containing the written amount box 30, and a number line field 16a containing the cheque's serial number 16, the bank branch sort code 18 and the drawer's account number 20.
  • This selection of fields is not the only one that is possible, within the scope of the present invention.
  • the fields shown are rectangular but other shapes could be used. It might be imagined that the locations of the relevant items - the amount lines, signature space etc.
  • the positions and/or the size and/or the proportions of one or more of the fields 16a, 24a, 26a, 28a, 30a are determined on the basis of analysis of one of the cheque images. More specifically in the present embodiment this analysis involves the use of character recognition. This is a technique well-known to the skilled person. It is often referred to as "OCR”, for "optical character recognition", although in this case it could in principle be applied to either the visible light image 10 its bi-tonal derivative 10a or the UV image 10b.
  • OCR optical character recognition
  • the image is analysed to find a chosen character, or chosen characters, associated with the specific field.
  • a character denoting the currency of the payment such as "£" or "$".
  • the analysis carried out in the present embodiment includes a search for this currency character and the written amount field 30a is defined at a location to the right of it.
  • the words "PAY” are typically shown on the cheque.
  • the analysis includes a search for this character string, and the payee field 24a is defined at a location to the right of it.
  • the fields 16a, 24a, 26a, 28a, 30a in this embodiment all contain information relating to the transaction being carried out by means of the cheque - the cheque's date, the payee etc. Hence they are likely areas for tampering. They are also, in this example, a ll filled with the background marking 34. That is, the area of the fields is entirely taken up either with the background marking 34 or with other printed matter of the cheque.
  • the fields 16a, 24a, 26a, 28a, 30a are divided into tiles.
  • Figure 2 shows a single tile 36 within the payee field 24a.
  • each of the fields is broken down into a set of square tiles such as the example shown.
  • the tiles 36 cover the entire field area without overlapping. This manner of division of the fields into tiles is not the only one possible within the scope of the present invention. Any other suitable pattern of tiles and/or shape of tiles could be adopted.
  • the scanning process is carried out on the UV image 10b represented in Figure 2, since this includes the background marking 34.
  • the technique could equally well be applied to the visible light image.
  • the UV image 10b consists of a set of pixels.
  • a mesh 42 is superimposed on the area of the image forming the tile 36.
  • Each square within this mesh is a single pixel.
  • the pixel values are represented according to the RGB colour model.
  • each pixel is represented by three pixel values.
  • Colour models are very familiar to the skilled person and the principles need not be explained here.
  • Other models for representing a pixel are known and may be adopted in other embodiments of the invention.
  • the invention could be implemented using digital images in which pixels are represented by fewer than three values, e.g. a greyscale image in which each pixel is represented by a single value.
  • a cell is a group of pixels. I n the present embodi ment the pixels making up a cell are contiguous. More specifically, in the present embodiment every cell is a square block of pixels having a width of five pixels along the horizontal ("X") direction and a depth of five pixels along the vertical ("Y") direction. Other sizes or shapes of cells may be adopted in other embodiments. The size of the cell is chosen with reference to the expected spatial frequency of the background marking 34. Figure 3 shows example cells 44a, 44b.
  • Each cell can be identified by reference to a coordinate, say the coordinate of its top left pixel.
  • the cell 44a in Figure 3 is thus cell (0,0), the origin of the coordinate system being at the top left of the tile 36.
  • Each cell is subject to an aberrance test. According to the outcome of this test, the cell is identified either as aberrant or as normal. Cells identified as aberrant are suggestive of tampering and their coordinates are stored for further reference. In the present embodiment the aberrance test has only two possible outcomes - normal or aberrant.
  • the aberrance test as applied to the cell 44a proceeds as follows. One pixel in the cell serves as a reference pixel. In the present embodiment the reference pixel for each cell is its top left pixel. For the cell 44a, which is cell (0,0), the reference pixel is thus pixel (0,0). However any other pixel in the cell could be chosen as the reference pixel in another embodiment.
  • the aberrance test comprises a preliminary test and a full test.
  • the full test is carried out only if the result of the preliminary test shows it to be necessary.
  • the preliminary test comprises a comparison of the reference pixel against another pixel in the cell, to establish whether they are similar to within a chosen margin. In the present embodiment this comparison is made using the R,G,B pixel values and the chosen margin is plus or minus five in each of the pixel values. Also the reference pixel is compared to its immediate neighbour in the same row.
  • Each box represents a pixel and contains its RGB values.
  • the pixel immediately to the right of the reference pixel is compared against the reference pixel. If it has
  • the full test is to be carried out on the cell. If not, the cell is treated as non-aberrant and the process move on to the next cell (see below). In the example, the values do fall within the relevant ranges, so the full test proceeds.
  • the full test involves comparing each of the remaining pixels in the cell against the reference pixel in the same manner and counting the number that match the reference pixel. At a programming level, this may for example be done using a pair of nested loops to scan along each row or column in succession. The full test thus returns a value which may in this example be between 1 and 24. A high value shows that the cell contains a large number of matches, which is considered indicative of potential tampering. Cells whose matching pixel count is above a chosen threshold are identified as aberrant and their coordinates are recorded to form the output of the process. For example cells may be treated as aberrant if their matching pixel count is above 90% of the number of pixels in the cell (more than 21, in the present example).
  • the cells may in principle be tested in any order but in the present embodiment this is done in a raster pattern, with cells on the first row being tested in sequence, then cells on the second row being tested in sequence and so on.
  • Figure 4a shows the first cell 44a to be tested which is cell (0,0).
  • Figure 4b shows the second cell to be tested which is cell (1,0) and which overlaps the first. Scanning proceeds along the first row in the direction shown by an arrow in Figure 4b until the end of the row is reached whereupon the scan, the scan reverts to the first cell (0,1) of the second row ( Figure 4c) and so on and passes along the second row, before moving to the third row and so on.
  • Table 2 gives an example of a cell which is identified as aberrant. In this case all pixels in the cell match the reference pixel to within the chosen tolerance.
  • Table 3 is an example where the full test on the cell does not proceed.
  • the reference pixel values of 10,10,10 are compared against the values of the first neighbouring pixel - 20,20,20 - and since these fall outside the relevant range there is no match and the cell is not tested further.
  • the treatment of the results is in part a matter for the institution carrying out the image analysis.
  • One possibility is that if even a single aberrant cell is identified in the image then the cheque in question is identified as possibly having been subject to tampering and is referred for inspection by a human operative.
  • results of the above described image analysis method are taken into account along with results of some other image analysis method - either by a human operative or by means of a software-implemented algorithm - to determine whether a document should be treated as potentially having been subject to tampering.
  • a second method of analysing the digital images to provide an indication of possible tampering will now be described. The method may be additional or alternative to the first.
  • the image densities of selected regions of the cheque are compared against a reference image density for the cheque. Differences between image density of one or more of the selected regions and the reference image density are - if outside a certain tolerance band - interpreted as suggestive of tampering.
  • Image density is a numerical value or values attributed to a certain region of the image and calculated from the values of pixels within that region. It can be representative of the average brightness and/or colour of the image over the chosen region.
  • image in bitmap form that is, an image in which each pixel has only two possible values, black or white
  • greyscale image it can be the average pixel value - that is, the sum of all pixel values divided by the number of pixels.
  • image in RGB form it can for example be an average of the three values over all pixels, to provide a single image density, or the R, G and B values may each be averaged separately to give three values.
  • image densities are calculated using pixel values from the UV image 10b.
  • the regions used for calculation of image density omit those regions of the cheque which carry markings (printing or writing) that are included in the visible light image 10a - i.e. regions bearing visible markings.
  • This is achieved by making use of both the UV image 10b and the bi-tonal version 10a of the visible light image 10.
  • the bi-tonal visible light image 10a is analysed to determine which of its pixels falls in an area carrying visible printing or writing.
  • the UV image 10b is registered with the visible light image.
  • the pixels in the UV image 10b corresponding to the pixels in the visible light image identified as carrying visible printing or writing are excluded from the calculation of image density.
  • the relevant pixels can be selected by application of a suitable numerical criterion to the pixel RG B values. For instance, noting that RGB values of 0,0,0 denote perfect black, the relevant criterion might be that a pixel is treated as bearing a visible marking if its RGB values are all below some threshold. Using this criterion, the pixels of the visible light image 10a can be divided into (a) pixels corresponding to regions of the cheque which do not carry visible markings ("marked pixels”) and (b) pixels corresponding to regions of the cheque which do carry visible markings.
  • the UV and visible light images 10a, 10b are not precisely aligned.
  • the position on the physical cheque represented by pixel (0,0) in the visible light image 10a may be offset by some small distance from the position on the physical cheque represented by pixel (0,0) in the UV image 10b.
  • Registration of the visible light and UV images 10a, 10b involves compensating for this offset. In the simplest case, this simply involves addition of some numerical offset to the pixel coordinates of one of the images.
  • pixels in the visible light and UV images 10a, 10b having the same coordinates correspond to the same position on the physical cheque. Pixels of the UV image 10b having coordinates which match the marked pixels of the visible light image 10a can then be excluded from the calculation of the image density.
  • the image density thus obtained characterises what may be referred to as the background part of the cheque - the area of the cheque which lacks visible markings, although it typically does carry the background marking 34.
  • the reference image density is intended to represent the average or typical image density of the relevant areas of the cheque. It may be calculated based on a large area of the cheque. In Figure 2, a large rectangle 38 taking in the majority of the cheque's information bearing area including the date line 38, lines 24 and 26 for the payee and the legal amount, the box 30 for the written amount and the signature space, is used for this calculation. Selection of regions for testing
  • the process involves selecting further, normally smaller, regions of the cheque, calculating the image density of each of the selected regions, and comparing the image density of each selected region with the reference image density.
  • the individual regions of the cheque selected for this process will be referred to herein as "tiles".
  • the process of selecting them proceeds somewhat similarly to steps 1 and 2 of the first testing method described above.
  • the image is first analysed to identify information bearing fields of the cheque, e.g. using OCR as described above.
  • the information bearing fields are then broken down into tiles for testing.
  • each tile involves calculating its image density as described above and then determining whether the tile's image density value differs from the reference image density by more than a predetermined margin. If it does, this is interpreted as indicative of possible tampering.
  • Some cheques have somewhat variable printing quality in relation to the background marking 34. For example cheques sometimes have bands where the background marking 34 is especially feint. Such variations are expected to affect the image density in those areas and may thus lead to false positives. For this reason the present method may advantageously be combined with some other mode of testing (e.g. the first method described above) or with other means of enquiry into the legitimacy of the transaction effected by the cheque.
  • the first analysis method described above proves ineffective with certain cheques whose UV markings do not form a consistent, intricate background to the relevant regions of the cheque. For example, some existing cheques have, in place of such a background, merely a logo repeated at several spatial locations. An alternative mode of analysis is thus needed.
  • the method described above is modified to include an additional step of identifying the bank that issued the cheque and selecting the mode of analysis based on the bank in question.
  • the bank is identified in the present embodiment by reading the sort code 18 from its number line. In the present embodiment this reading is done by OCR on the scanned image, although as noted above the number line may also be read using MICR. That technique could be used in other embodiments.
  • the system maintains a list of those banks whose cheques lack a consistent, intricate background and thus need to be analysed in a different manner.
  • the system maintains a record of cheque characteristics for the banks in question.
  • the UV background on the cheques of a certain bank consist of the bank's logo at several known spatial locations
  • the system is provided with the relevant logo image and its locations.
  • the testing of the cheque then consists of looking for the relevant images at the relevant locations, by known image analysis techniques. If the images do not appear in the expected locations and form, the cheque may be identified as aberrant.
  • Figure 5 shows in block diagram form major elements of a system that can be used to carry out the invention, comprising a digital cheque scanner 50 arranged to pass data to a computing device 52 through a network 54 which may be a local area network.
  • the computing device 52 is arranged to output data through a further network 56, which may be the internet and which may lead to a cheque clearing system through which cheque images are exchanged between financial institutions.
  • Another computing device 58 may receive images and/or other data through the wide area network.
  • the methods described above may be implemented in either of the computing devices 52, 58.

Landscapes

  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Engineering & Computer Science (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Image Processing (AREA)
  • Health & Medical Sciences (AREA)
  • General Health & Medical Sciences (AREA)
  • Toxicology (AREA)

Abstract

L'invention concerne un procédé mis en œuvre par ordinateur pour analyser une image numérique (10a, 10b) d'un chèque ou d'un autre document afin de détecter des indications qu'il a été soumis à une falsification. L'image numérique comporte un ensemble de pixels ayant chacun une ou plusieurs valeurs de pixel. Le procédé consiste à analyser l'image numérique pour identifier des ensembles contigus de pixels sur une taille prédéterminée, tous les pixels dans un ensemble ayant des valeurs de pixel qui correspondent à celles des autres pixels de l'ensemble dans les limites d'une marge prédéterminée.
PCT/GB2017/050193 2016-02-18 2017-01-26 Procédé et appareil de détection de falsification de document WO2017141006A1 (fr)

Priority Applications (1)

Application Number Priority Date Filing Date Title
EP17704525.9A EP3417429A1 (fr) 2016-02-18 2017-01-26 Procédé et appareil de détection de falsification de document

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
GB1602835.9 2016-02-18
GB1602835.9A GB2548546A (en) 2016-02-18 2016-02-18 Method and apparatus for detection of document tampering

Publications (1)

Publication Number Publication Date
WO2017141006A1 true WO2017141006A1 (fr) 2017-08-24

Family

ID=55752834

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/GB2017/050193 WO2017141006A1 (fr) 2016-02-18 2017-01-26 Procédé et appareil de détection de falsification de document

Country Status (3)

Country Link
EP (1) EP3417429A1 (fr)
GB (1) GB2548546A (fr)
WO (1) WO2017141006A1 (fr)

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111915792A (zh) * 2020-05-19 2020-11-10 武汉卓目科技有限公司 一种图像斑马线图文的识别方法及装置
CN113096301A (zh) * 2019-12-19 2021-07-09 深圳怡化电脑股份有限公司 票据的检验方法、装置、电子设备及存储介质
US20210264583A1 (en) * 2020-02-21 2021-08-26 Accenture Global Solutions Limited Detecting identification tampering using ultra-violet imaging

Families Citing this family (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US10947103B2 (en) 2019-06-24 2021-03-16 Accenture Global Solutions Limited Beverage dispensing machine for achieving target pours for different beverages
US10726246B1 (en) 2019-06-24 2020-07-28 Accenture Global Solutions Limited Automated vending machine with customer and identification authentication
USD963407S1 (en) 2019-06-24 2022-09-13 Accenture Global Solutions Limited Beverage dispensing machine
EP3869395A1 (fr) 2020-02-21 2021-08-25 Accenture Global Solutions Limited Vérification d'identité et d'activité
CN116935200B (zh) * 2023-09-19 2023-12-19 南京信息工程大学 面向审计的图像篡改检测方法、系统、设备及存储介质

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20020097903A1 (en) * 2001-01-24 2002-07-25 International Business Machines Corporation Document alteration indicating system and method
US20070017990A1 (en) * 2005-07-19 2007-01-25 Fuji Xerox Co., Ltd. Document correction detection system and document tampering prevention system
EP2645339A1 (fr) * 2012-03-30 2013-10-02 NCR Corporation Détection de taches

Family Cites Families (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5751854A (en) * 1992-08-03 1998-05-12 Ricoh Company, Ltd. Original-discrimination system for discriminating special document, and image forming apparatus, image processing apparatus and duplicator using the original-discrimination system
DE102013016120A1 (de) * 2013-09-27 2015-04-02 Giesecke & Devrient Gmbh Verfahren zum Prüfen eines Wertdokuments mit einem Polymersubstrat und einem Durchsichtsfenster und Mittel zur Durchführung des Verfahrens

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20020097903A1 (en) * 2001-01-24 2002-07-25 International Business Machines Corporation Document alteration indicating system and method
US20070017990A1 (en) * 2005-07-19 2007-01-25 Fuji Xerox Co., Ltd. Document correction detection system and document tampering prevention system
EP2645339A1 (fr) * 2012-03-30 2013-10-02 NCR Corporation Détection de taches

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113096301A (zh) * 2019-12-19 2021-07-09 深圳怡化电脑股份有限公司 票据的检验方法、装置、电子设备及存储介质
US20210264583A1 (en) * 2020-02-21 2021-08-26 Accenture Global Solutions Limited Detecting identification tampering using ultra-violet imaging
CN111915792A (zh) * 2020-05-19 2020-11-10 武汉卓目科技有限公司 一种图像斑马线图文的识别方法及装置
CN111915792B (zh) * 2020-05-19 2022-06-07 武汉卓目科技有限公司 一种图像斑马线图文的识别方法及装置

Also Published As

Publication number Publication date
GB2548546A (en) 2017-09-27
GB201602835D0 (en) 2016-04-06
EP3417429A1 (fr) 2018-12-26

Similar Documents

Publication Publication Date Title
WO2017141006A1 (fr) Procédé et appareil de détection de falsification de document
CN110598699B (zh) 一种基于多光谱图像的防伪票据鉴伪系统和方法
Chambers et al. Currency security and forensics: a survey
CN108602374B (zh) 对设置有安全元素的对象的验证
Mirza et al. Paper currency verification system based on characteristic extraction using image processing
JPH01161490A (ja) イメージ分解原稿照合システム
TW201305969A (zh) 鑑別硬幣或其他製造項目的方法與設備
Roy et al. Machine-assisted authentication of paper currency: an experiment on Indian banknotes
US7133536B2 (en) Method and system for watermark detection
Murthy et al. Design and implementation of paper currency recognition with counterfeit detection
Sharan et al. Detection of counterfeit Indian currency note using image processing
US20050129270A1 (en) Method and system for applying a watermark
Lamsal et al. Counterfeit paper banknote identification based on color and texture
WO2018130119A1 (fr) Procédé et système d'identification d'authenticité de papier-monnaie à base de nombres à doubles préfixes
Schulze et al. Evaluation of graylevel-features for printing technique classification in high-throughput document management systems
Garain et al. On automatic authenticity verification of printed security documents
CN106447904B (zh) 一种纸币的鉴别方法和装置
Chhabra et al. Detecting fraudulent bank checks
CN107170108A (zh) 一种拼接钞检测方法及系统
KR101812206B1 (ko) 위폐 감별 및 추적 시스템 및 이의 실행 방법
TWI378406B (en) Method for performing color analysis operation on image corresponding to monetary banknote
EP1791081B1 (fr) Procédé de détection d'une perforage sur les bords d'image d'une formulaire
Kumar et al. Forensic authentication of bank checks
CN109410420B (zh) 一种图像检测方法、装置和票据鉴别仪
Shoeb et al. Software system to detect counterfeit Egyptian currency

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 17704525

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE

WWE Wipo information: entry into national phase

Ref document number: 2017704525

Country of ref document: EP

ENP Entry into the national phase

Ref document number: 2017704525

Country of ref document: EP

Effective date: 20180918