WO2008014589A1 - Method and apparatus for comparing document features using texture analysis - Google Patents
Method and apparatus for comparing document features using texture analysis Download PDFInfo
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- WO2008014589A1 WO2008014589A1 PCT/CA2007/001158 CA2007001158W WO2008014589A1 WO 2008014589 A1 WO2008014589 A1 WO 2008014589A1 CA 2007001158 W CA2007001158 W CA 2007001158W WO 2008014589 A1 WO2008014589 A1 WO 2008014589A1
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- document
- feature
- data
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
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- 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
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- 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
- G07D7/202—Testing patterns thereon using pattern matching
- G07D7/206—Matching template patterns
Definitions
- Identification documents may include, but are not limited to, passports, VISA and identification cards.
- security features include ultraviolet (UV) threads, infrared (IR) printing, watermarks, micro printing, specialized laminates, machine-readable code and the like.
- UV ultraviolet
- IR infrared
- micro printing micro printing
- specialized laminates machine-readable code and the like.
- the security features on a given identification document, such as a passport will vary between countries and even within a country based on the date of issue.
- such features are normally detected and verified by a document reader, various brands of which are widely available in the market.
- the present invention relates to systems and methods for assisting in the determination of the authenticity of security documents based on known characteristics of similar reference security documents.
- the system and methods use digital processing to capture a digital image of the document being examined and they use a feature localization or detection technique to search for a specific feature in the document based on a stored image of a similar feature from a reference document. Once the feature on the subject document has been found, the digital image of the localized feature is transformed, by applying mathematical transforms or other image/mathematical operators, such that the result will have distinguishing characteristics that can be derived or analyzed. When the distinguishing characteristics have been analyzed, these are then compared to the stored distinguishing characteristics of similar features from reference documents.
- a score is then generated that is indicative of how similar or how different the distinguishing characteristics of the feature being examined are from the features from reference documents.
- the system may also be used such that multiple features from a single document are assessed and scored separately from one another with a final aggregate or weighted score being provided to the user for the whole document.
- Figure 4 A depicts the hierarchical organization of the elements of the knowledge base
- Figure 6B depicts a series of example features used to validate an identified security document
- Figure 7A depicts an inspector GUI
- Figure 7B depicts the display bar of the Figure 7 A inspector GUI
- Figure 20 illustrates a sample image taken from an inauthentic document
- Figure 24 illustrates a letter from an authentic document on which a contour tracking process can be applied
- Figure 25 illustrates a letter from an inauthentic document on which a contour tracking process can be applied for comparison with the letter in Fig 24;
- Figure 26 illustrates the linework from an authentic document;
- Figure 33 illustrates an inauthentic laminate when exposed to directional light
- Figure 34 depicts a block diagram illustrating the steps in the generalized approach to comparing and scoring a feature in a subject document relative to data from a known similar feature in an authentic document;
- Figure 35 depicts a flowchart illustrating the steps in a method for determining a printing process used to manufacture a subject document using the techniques described in this document;
- the DCS 100 is comprised of a general purpose computer 110 which may utilize, for example, a Windows XPTM operating system produced by MicrosoftTM Corporation.
- the general purpose computer includes a monitor, input device such as a keyboard and mouse, hard drive and processor, such as an IntelTM PentiumTM 4 processor, cooperating with the operating system to coordinate the operation of the aforementioned components.
- general purpose computer 110 could be any commercially available, off-the shelf computer including a laptop or similar device and all such devices are meant to be included within the scope of the present invention.
- General purpose computer 110 communicates with travel document reader 120 and external storage device 130.
- data stored in external storage device 130 may be alternately stored on the hard drive integral to general purpose computer 110.
- Travel document reader 120 is used to input features associated with a security document 140 (such as a passport, visa, identity card, etc.) into DCS 100 for analysis, to assist the operator with a determination as to whether security document 140 is authentic.
- security document 140 such as a passport, visa, identity card, etc.
- the operator places security document 140 onto an image capture surface associated travel document reader 120 and a portion or all of security document 140 is then exposed to various light sources.
- Travel document reader 120 is designed to recognize documents that are compliant with the relevant standards and specifications governing such documents.
- the security document 140 may be exposed to various forms of light such as ultraviolet (UVA and UVB), infrared (IR), red/green/blue (RGB) and white light to determine if certain expected features are present. More specifically, light emitting diodes (LEDs) expose security document 140 to UV, IR and RGB light, while a fluorescent light source exposes security document 140 to white light. In all cases, the light reflected from the surface of security document 140 is captured by a charge coupled device (CCD) or complementary metal-oxide semiconductor (CMOS) sensor, either of which converts the light into electronic signals that can be digitally processed.
- CCD charge coupled device
- CMOS complementary metal-oxide semiconductor
- Page A logical grouping of images or binary representations of data.
- a page can have properties to be inspected, e.g. page size;
- Image A binary data representation of an entity that has feature(s) to be inspected, e.g. captured with a different light source to expose certain features;
- Feature A significant object within the image entity, e.g. MRZ (machine readable zone) feature, a Maple Leaf pattern.
- MRZ machine readable zone
- a feature contains the data required to locate, process and score parts of or the entire image. Properties can be attached to a feature.
- Comparison Group A collection of comparison rules to form more complex rules to perform extra checking on the security document 140.
- the comparison group has an optional activation and deactivation time.
- An example of a comparison group is to alert the operator that all male travelers, aged between 25-40 of country UTO are to be asked for a second piece of identification during the period of April 1 to April 2, 2005;
- FIG. 4A The hierarchical arrangement of the above-noted elements is depicted in Figure 4A, with an example of a document template and a number of image features associated therewith depicted in Figure 4B.
- GUI graphical user interface
- Template builder GUI 310 allows the creation, deletion and renewal of the data that represents a document template. This basic functionality of template builder GUI 310 can either be done in a step-by-step manner for specific entities within a document template or the user can have the tool create a generic layout of a document template with default values. Template builder GUI 310 also provides an interactive visual representation of the hierarchal data in knowledge base. This allows the user to easily scan various document templates contained within knowledge base 300 and quickly apply those changes that are required.
- a template builder GUI 310 is depicted.
- Window 500 is the previously mentioned hierarchal representation of the existing templates in knowledge base 300.
- the commands for adding, removing and maintaining templates are instigated from this tree list.
- Visual display area 510 provides the user with a representation of the data with which the user is currently working. This could be graphical, binary, etc..
- Indicator lights 520 inform the user what data source the current data was obtained from during template creation.
- data entry fields 530 provide information for each of the different types of entities that make up a template.
- Template builder GUI 310 dynamically changes the set of fields for data entry depending on which entity is being manipulated. These entities include properties, features, images, reference pages, documents, rules, and portfolios previously discussed.
- a further module of the document comparison software is a document inspection engine 320 that works in collaboration with knowledge base 300 to score a document or portfolio of documents based on inspection instructions.
- Document inspection engine 320 may alternately reside in document authentication server 150 and obtain images from one or more security documents 140 scanned at one or more networked travel document readers 120.
- travel document reader 120 is just one example of the devices that reside in peripheral layer 330, with which document inspection engine communicates to obtain inspection data.
- security document 140 When security document 140 is inserted into travel document reader 120 it automatically sends signature image(s) and/or signature feature(s) to the document inspection engine 320.
- Signature image(s) and/or signature feature(s) are used to determine a document type (e.g. passport) upon which further validation processing can be initiated. More specifically, using the retrieved signature images(s) and/or signature feature(s) document inspection engine 320 determines one or more matching templates. Each template defines the additional data to be retrieved using travel document reader 120 to validate security document 140.
- signature features Important enablers for matching templates are signature features.
- document inspection engine 320 can locate, process and score features, but signature features also implement a "find matching templates" process.
- the "find matching templates” process calculates a unique signature for the security document 140 under analysis.
- This process preferably utilizes a scoring mechanism which ranks the matching templates. From the list of ranked matching templates, the highest scored template is chosen, and this template will be used in the validation of the security document 140 under analysis.
- an operator can select the preferred template from the list.
- Figure 6A depicts an example of a signature feature that looks at the colour distribution of sub images to calculate a unique signature for an incoming image. This signature is used to search, score and rank matching templates.
- Feature locating, processing and scoring are most commonly methods exported from image and data processing libraries or DLLs.
- a machine readable zone (MRZ) feature uses an image utility for page segmentation and a multi font OCR engine will be called to recognize the letters.
- MRZ scoring is based on advanced comparators and libraries that have been developed according to ICAO standards.
- Another example is a pattern recognition feature that locates sub images and uses a normal cross correlation algorithm which generates a number used for scoring.
- Figure 6B depicts example features which are located, processed and scored as part of the validation process for security document 140.
- Scoring security document 140 is a user- weighted summary of scoring all pages, all comparison groups and all properties attached to security document 140.
- Scoring pages is a user- weighted summary of scoring all data, images and scoring all properties attached to the page.
- Scoring data and images is a user-weighted summary of scoring all features and properties attached to the page.
- Scoring a feature involves a user- weighted summary of all properties, property locations and feature location scores. As will be discussed in relation to Figures 7A and 7B, the results of the scoring are displayed in an inspector GUI (element 340 in Figure 3)
- inspector GUI includes a search bar 780.
- search bar 780 includes: location code entry 780A to specify what country, province, county or any other similar geopolitical designation to which a document template belongs; document type code entry 780B to specify to what set of documents the template belongs.
- Examples include visa, passport, financial card and identifying certificates; document name entry 780C to specify the exact name of the document template that the user may desire to use for an inspection; a "Browse” button 780D, which utilizes the information from the three above-mentioned entry fields to display template information in the main inspection window; a "Clear” button 780E, which clears all data retrieved from the knowledge database 300 from the screen; an "Execute” button, 780F which utilizes the information from the above-mentioned entry fields while instigating an inspection process for acquired images; an "Auto- Selection” button 780G, which turns ON or OFF the option of the user to select a template during the inspection process when a perfect template match cannot be acquired. In the ON state a list of templates is presented to the user for use. In the OFF state the best match template is used for the inspection process; and a "Cancel” button 780H, which interrupts and stops an inspection process before it is complete
- an optional module of the document comparison software includes a guardian component 350 which assigns user access privileges to view and modify knowledge base 300 when either template builder GUI or inspector GUI 340 are in use.
- a user with insufficient privileges is denied access to certain areas of knowledge base 300 in template builder mode or to certain results in inspection mode. For example, if the system administrator does not want the user to even be aware that a certain feature for a specified document exists and can be analyzed then access to that feature in knowledge base 300 will be denied and the results of that feature analysis will remain hidden.
- the area or feature is analyzed by the analysis module 830. Data from this analysis is then gathered. Data regarding the feature or area analyzed is, generally, then retrieved by a data retrieval module 850. The data gathered by analysis module is then compared by the comparison module 860 with data retrieved by the data retrieval module 850.
- the resulting image from the processing is received by an analysis module 830.
- the analysis module 830 analyzes the resulting image from the isolation module 810 and produces a result that can be compared with stored data derived from a reference security document.
- the result of the analysis module 830 can then be used by the comparison module 860 to determine how close or how far the feature being examined is from a similar feature on a reference security document.
- the data for the reference security document is retrieved by a data retrieval module 850 from the database. Once the relevant data for the relevant feature of the reference security document has been retrieved, this data is compared with the data from the analysis module 830 by the comparison module 860.
- the result of the comparison is then received by the score generation module 870 which determines a score based on the similarities or closeness between the sets of data compared by the comparison module 860.
- the score generated may be adjusted based on user selected preferences or user or system mandated weights on the data.
- reference document is used to refer to documents against which subject documents will be compared with.
- features are associated with documents such that reference documents will be associated with reference features.
- Features associated with subject documents are compared with reference features associated with reference documents.
- These reference documents may be authentic or authenticated documents, meaning documents which are known to be legitimate or have been authenticated as being legitimate and not forgeries.
- reference documents may be inauthentic documents or documents known or proven to be fake, forgeries, or otherwise illegitimate. If the reference document being used is an authentic document, the features associated with a subject document are compared to the features associated with an authentic document to positively determine the presence of features expected to be on an authentic document.
- a feature on the reference document corresponds very closely (if not exactly) to a similar feature on the subject document, then this is an indication of a possible authenticity of the subject document.
- the reference document used is an inauthentic document or a known forgery, then a close correlation between features associated with the subject document and on features associated with the reference document would indicate that the subject document is a possible forgery.
- the use of an inauthentic document can thereby positively determine the possibility, if not a probability, of a forgery.
- using an inauthentic document as a reference document can negatively determine the possibility of the authenticity of a subject document. This is because if the features of the subject document do not closely correlate with the features of an inauthentic document, then this may indicate the authenticity of the subject document.
- the analysis performed by the analysis module 830 and the data retrieved by the data retrieval module 850 may be based upon the manufacturing techniques used to create the security document. As such, techniques involved in the printing, layering, or any other method of manufacturing the security document may be used as the basis of the analysis. Thus, if a certain printing technique produces certain characteristics in the finished product and there characteristics are not present in the security document under analysis, this fact can be used to assist in determining the authenticity or inauthenticity of the security document. Similarly, the presence of characteristics not expected of a specific manufacturing process, such as, for example, a specific printing technique, can be used as an indication for determining an authenticity or inauthenticity of a document.
- the feature/area isolation module 810 is used to localize or isolate a feature or area of the digital image from the image capture module.
- the feature or area may be a letter from a machine readable zone, a specific section of the background of the document, a hologram, or any other feature or area susceptible to analysis.
- One method which may be implemented by this module 810 is based on having a reference digital image of an area or feature being searched for in the digital image from the image capture module 800. The method, in essence, reduces to searching the digital image for an area or feature that matches the smaller reference digital image. This is done by using normalized cross-correlation.
- the correlation factor equals 1 if there is, at point (u,v), an exact match between the reference digital image and the subject digital image.
- the average value over a window as large as the reference digital image is subtracted from each pixel value of the subject digital image with the window being centered on the pixel being evaluated. This is very similar to applying an averaging filter to the subject digital image.
- the subject digital image is normalized by padding the edges with mirror values. To best illustrate the above process, Figs 9-13 are provided.
- Figure 9 illustrates a sample reference digital image.
- Figure 10 illustrates a sample subject image.
- the image in Fig 9 must be found in the subject image of Fig 10.
- a boxed area in Fig 10 shows where the reference image may be found.
- the issue of average values at the edges of the subject image was raised above and, to address this, the edges of the subject image are padded with mirror values, resulting in Fig 11.
- a mirror image of the edges of the subject image is added to every edge. This process normalizes the subject image to produce Fig 12 which will be used to search for the reference image.
- Normalized cross-correlation determines the level of correlation between the two images.
- Fig 13C illustrates the result. A distance of 0.81 between the two images is found. Such a score is considered low as a distance of at least 0.9 is to be expected from cross-correlating two images from genuine documents.
- the blurry edges of the image in Fig 13B is in contrast to the sharp edges of the image in Fig 13 A.
- the printing process used to manufacture the document in Fig 13 A produces clear, sharp edges.
- the printing process used to manufacture the document in Fig 13B produces blurry edges.
- a Fast Fourier Transform is applied to the localized image to result in an illustration of the power spectrum of the image.
- the power spectrum reveals the presence of specific frequencies and this frequency signature can be used to determine how similar one feature is to a similar feature in a reference security document.
- Figs 14-21 are provided.
- a reference image of an area with a repetitive printing pattern (such as microprinting) is illustrated.
- This reference image is derived from a reference security document and provides a reference by which subject images may be measured.
- an FFT is applied to the reference image
- an image of its power spectrum or frequency spectrum emerges (see Fig 15).
- specific frequencies are present (see circles in Fig 15).
- These peaks in the spectrum indicate the presence of frequencies in the power spectrum of authentic documents and that other authentic documents which have the same microprinting pattern should have similar frequencies in their power spectrum.
- the sharpness of the microprinting affects the sharpness, height, and even the presence of the peaks in the spectrum. As such, the less sharp the microprinting, the lesser and the lower are the peaks in the spectrum.
- the power spectrum of the subject image is to be compared to the power spectrum of the reference image.
- Fig 16 illustrates a subject image from a known inauthentic document that tries to recreate the microprinting illustrated in Fig 14.
- the microprinting in the subject image is blurred and is not as sharp as the microprinting in the reference image of Fig 14.
- the power spectrum that results is shown in Fig 17.
- a comparison of Figs 15 and 17 clearly show two different power spectra. The characteristic peaks in Fig 15 are not present in Fig 17 and a comparison of the two images, or at least of the peaks present in the two spectra, easily shows that the two power spectra are quite different.
- FIGs 18-21 another example is illustrated of how the power spectrum may be used to compare images taken from authentic and inauthentic documents.
- Figure 18 illustrates a sample image taken from an authentic document. After applying a mathematical transform to the image, the power spectrum of Figure 19 results. As can be seen from Fig 19, the frequency that corresponds to the repeating line sequence in the background of Fig 18 is located in the lower right quadrant of the power spectrum.
- Figure 20 illustrates an image taken from an inauthentic document. After applying a mathematical transform to the image, the power spectrum of Fig 21 results. As can be seen, the relevant frequency that should correspond to a repeating line sequence, and which should be found in the lower right quadrant, is missing from the lower right quadrant of Fig 21.
- a frequency which is not present in the power spectrum of Fig 19 is found in the upper right quadrant of Fig 21 (see upper right quadrant of Fig 21).
- the presence of this unexpected frequency in the upper right quadrant and the absence of the expected frequency in the lower right quadrant is indicative of the absence of the repeating line sequence from the background of the image in Fig 20.
- the power spectrum of the reference image need not be stored in the database. Rather, the analyzed data from the reference power spectrum of the reference image is stored for comparison with the data gathered from the analysis of the power spectrum of the subject image.
- the subject image is, in this case, received by the analysis module 830 that applies the FFT and extracts the relevant data (such as the size and location of the peaks in the power spectrum) from the resulting power spectrum image.
- the analysis module 830 analyzes the results of the application of a mathematical transform to the subject image and produces a result that is mathematically comparable with the stored reference data.
- the analysis module 830 determines which frequencies are present, which peaks are present in the power spectrum, and how many peaks there are in the spectrum.
- the subject power spectrum is filtered to remove frequencies outside a predetermined frequency range. Thus, frequencies outside the stored range of fmin and fmax are discarded. Then, a threshold is applied to the remaining frequencies - if a frequency value is below the stored threshold, then that frequency cannot be a peak.
- peak conditions the conditions which determine if a point on the power spectrum is a peak or not
- peak conditions may be as follows with (x,y) being the coordinates for a point on the subject power spectrum :
- the number of peaks found is returned as the result of the analysis module 830.
- the reference power spectrum should have also undergone the same analysis and the number of peaks for the reference power spectrum may be stored in the database as the reference data.
- the comparison module 860 After the number of peaks is found for the subject power spectrum, this result is received by the comparison module 860.
- the reference data from reference security documents in this case the number of peaks for the reference power spectrum, is then retrieved by the data retrieval module 850 from the database 160 and is passed on to the comparison module 860.
- the comparison module 860 compares the reference data with the result from the analysis module 830 and the result is passed to the score generation module 870.
- the comparison module 860 quantifies how different the reference data is from the result received from the analysis module 830.
- the score generation module 870 determines, based on predetermined criteria , a score to be given to the subject security document 140 relative to the feature being examined. As an example, if the reference data had 100 peaks while the subject spectrum only had 35 peaks, then the score module may give a score of 3.5 out of 10 based on the comparison module providing a difference of 65 between the reference data and the subject data. However, if it has been previously determined that a 50% correlation between two authentic documents is good, then the same 35 peaks may be given a score of 7 out of 10 (i.e. to double the raw score) to reflect the fact that a large correlation between the peak numbers is not expected. This score generation module 870 may also, depending on the configuration, take into account other user selected factors that affect the score but that may not be derived from the subject image or the type of security document (e.g. setting a higher threshold for documents from specific countries).
- a color histogram of a specific region of the subject image may be generated by the analysis module 830 which also measures the various distributions of color within the resulting histogram.
- the distributions of color in the subject histogram would then be passed on to the comparison module 860 for comparison with the distributions of color from an authentic document.
- the distributions of color from an authentic document would also have been generated or derived from a color histogram of a similar region in the authentic document. This method would be invariant to rotation in that regardless of the angle of the region being examined, the histogram would be the same.
- Histograms for a specifically shaped feature should therefore be the same regardless of the size (or scale) of the feature.
- a large maple leaf feature should have the same histogram for a smaller maple leaf feature as long as the two features have the same shape.
- This reference histogram can then be compared to the normalized contour histogram of a similar feature in a subject security document as produced by the mathematical transform module 820.
- the subject histogram can then be analyzed by the analysis module 830 to produce its distinguishing characteristics.
- the distinguishing characteristics of the subject histogram and of the reference histogram can then be compared by the comparison module 860.
- the processes and analysis provided may be used to assist in determining an authenticity or inauthenticity of a subject document.
- the methods used in the manufacture of the subject document can be used as one of the bases by which a document's authenticity or inauthenticity is determined.
- Consistency in this sense, refers to the consistency of the sharpness of the edges of a printed feature, the consistency of the contrasts in the printing, and the consistency of the size of the printed elements.
- a section of a security document is illustrated as being isolated and localized from a larger image of a page of the document.
- the sequence of lines in the background are a mixture of skewed lines (+/- 45 degrees of skew), vertical lines, and lines skewed at smaller angles (approximately -30 degrees).
- the circled portions of the spectrum illustrates the frequencies generated by the differently skewed lines.
- An inauthentic document which does not reproduce the sharpness of the edges or the contrast of the printing of the background lines would produce a different spectrum.
- comparing the expected frequencies (their location and number) as circled in Fig 23 with the frequencies extracted from a subject document will provide a measure of the similarity between the backgrounds of a known authentic document and a subject document.
- FIG. 24 Another example of how the above noted techniques may be used is illustrated using Figs 24 and 25.
- the figures illustrate two instances of the letter A.
- the specific letter may be isolated/localized by first finding the MRZ on the document and obtaining a digital image of the zone. Then, either a pattern recognition/pattern matching process (with a specific letter's pattern being used as the pattern to be matched) can be used to locate a specific letter.
- a well known technique as thresholding can be used to create a binary image from the digital image of the MRZ. Thresholding processes such as those that are histogram based or those based on the Otsu process may be used.
- Fig 24 is taken from an authentic document while Fig 25 is taken from an inauthentic document.
- the authentic image has a stair-like contour while the inauthentic image has a relatively smooth contour.
- a contour tracking process can be used to differentiate the two and to determine that the inauthentic image does not match the authentic image.
- the contour tracking process a well-known process, would track the edge of the authentic image and track the number of an character of the direction changes.
- the letter in Fig 24 would have a preponderance of direction changes in the east- west and north-south directions.
- the letter in Fig 25 would have higher values in the northwest-southeast and northeast- southwest directions.
- the expected numbers for the different direction changes for the authentic image can be stored in the database and can be retrieved for comparison with the numbers obtained for the subject image.
- this example only uses the letter A, other letters or characters may be used.
- This feature of the hologram can be used by exposing the subject document o directional light and isolating/localizing the area where a hologram is expected. A digital image of the expected hologram area exposed to directional light can then be taken. The resulting digital image can then used when applying the cross- correlation technique explained above with an authentic image. The resulting score would provide and indication of the similarities or dissimilarities between the subject image under directional light and a stored image of an authentic hologram under directional light.
- the maple leaf pattern and other reflective elements would be more visible in the authentic hologram, then the degree of similarity, and hence the matching score between the two images, would be lower than expected.
- directional light to illuminate the subject documents may also be used on features other than holograms.
- the authentic document's laminate reflects more and, because of this, artifacts on the laminate (such as the maple leaf patterns) are visible. Conversely, the inauthentic document does not fully reflect and parts of the laminate are not visible.
- a pattern matching process perhaps based on the normalized cross-correlation process explained above, used on the two images would reveal a fairly low level of similarity between the two images. The low level of similarity would result in a low score for the subject image.
- Another use of directional light relates to intaglio printing. If intaglio printing is expected on a subject document, the presence or absence of such raised printing can be detected using directional illumination and histograms.
- an image of the selected portion of the document where intaglio printing is expected is taken with illumination being at 90 degrees to the document.
- a second image of the same area, with illumination being at an angle other than 90 degrees is taken. Histograms of the two images are then generated and compared to one another. The comparison should show significant dark areas (or shadows) in the histogram of the second image. However, if the printing is not intaglio, then a comparison of the two histograms should not produce a significant difference as shadows would not be formed.
- the above methods may also be used to extract and compare not only the clearly visible features of a security document (e.g. microprinting, color of specific area, identifying indicia such as the maple leaf design) but also non- visible and hidden features as well.
- the scanner may be used to properly illuminate the subject document and reveal the presence (or absence) of security features embedded on the security document.
- the above-noted invention may be used to compare features that can be digitally scanned to provide a digital image.
- the scanner may be any suitable type of imaging device.
- Fig 34 a block diagram or flowchart of the generalized steps taken in the process explained above is illustrated. Beginning at step 900, the process starts with the generation of a digital image of the security document to be examined for features. This step is executed in conjunction with the scanner that actually scans and obtains the digital image of the document or page under examination.
- Step 930 analyzes the data/image/histogram generated by the analysis module 830.
- the analysis may involve applying a mathematical transform to the image of the localized or isolated feature.
- the transform may be the application of an FFT, the application of an edge detector operator, generating a histogram (color or contour) of the feature, or the application of any other mathematical or image processing method.
- the analysis then extracts the useful data from the result and this analysis can take various forms. From the examples given above, the analysis may take the form of determining distances between elements in the histogram, determining the number, height, and/or presence of peaks in a power spectrum, and any other analysis that extracts the identifying characteristics of the result after that application of a mathematical transform. These identifying characteristics or metrics should be easily quantifiable and should be easy to compare mathematically with reference data stored in the database.
- Step 950 actually compares the metrics from the feature of the subject document with the reference data from the database.
- the comparison may be as simple as subtracting one number from another such that if there is an exact match, then the result should be zero. Results other than zero would indicate a less than perfect match.
- the comparison step 950 may determine a percentage that indicates how different are the two data sets being compared. From the above example of 35 peaks for the subject document and 100 peaks for the reference data, the comparison step could provide a result that notes that there is a 65% incompatibility or non-match between the two results.
- Step 960 generates the final score indicative of a similarity or non- similarity between the subject feature and the reference data derived from the reference feature. As noted above, this step may take into account user or system mandated preferences that would affect the final score.
- Step 1010 is that of obtaining a digital image of the document. As noted above, this may be done using the scanner/image device of the system described above.
- Step 1020 then isolates the feature or area to be tested. This feature may be the hologram, a background, a specific letter in a machine readable zone, or a portion of the laminate. This feature may be any section of the document which can be subjected to analysis.
- step 1030 is that of applying the test to the feature.
- This step can take the form of applying a mathematical transform to the image, illuminating the document with directional light (prior to obtaining a digital image), applying a histogram to the digital image, applying a contour tracking process to the feature, or any combination of the above.
- This step may also encompass the application of any number of processes to either the digital image or a manipulation of the document prior to the taking of the digital image.
- step 1040 covers the analysis of the resulting power spectrum of an image, the analysis of a histogram, a determination of the number and direction of contour changes, and any other analysis steps.
- This step may also cover the obtaining of the image of a document after the document has been illuminated by directional light. This step gathers the data to be compared to the expected data stored in a database.
- the data generated in step 1040 may be the image of a hologram or laminate illuminated by directional light while the data retrieved fro mthe database would be a similar, albeit confirmed authentic, hologram or laminate also illuminated by a similar directional light.
- the comparison can therefore be the application of the normalized cross-correlation process between the two images.
- another possible comparison would be a comparison of the number and direction of contour changes for at least one letter from a machine readable zone.
- Yet another possibility would be the comparison of two images (taken at different angles) of the same printing to determine if intaglio printing was used.
- the final step, step 1060 is that of generating a score based on the results of the comparison.
- the score may be an indication of similarity or differences between the data from the database and the data gathered from the feature on the subject document. Depending on the implementation and the user's preferences, a higher score may indicate a higher likelihood that the subject document was produced or printed using a technique similar to that use to produce the document from which the data in the database was derived from. Of course, no single test may be able to definitively determine the manufacturing or printing process used to create a document. As such, the score may be an aggregate, weighted or otherwise, of scores generated by multiple tests applied to the same document.
- the data in the database may not merely relate to data from authentic documents but may relate to inauthentic documents as well.
- the tests in the process given above may confirm if the subject document was produced using inkjet technology.
- the data in the database would therefore have to be derived from known inauthentic documents created using inkjet based techniques.
- inauthentic documents or documents which are known forgeries may also be used as reference documents.
- Known features of inauthentic documents may be used as the reference by which subject documents are judged or compared against.
- One example of such a feature are hidden patterns in authentic documents that appear if these authentic documents are copied or otherwise improperly used. Referring to Fig 36, an image of a background of an authentic document is illustrated. If this authentic document was copied in a conventional manner (e.g. by way of a photocopier), a hidden pattern, illustrated in Fig 37 appears. The image of the hidden pattern (the word VOID in the example) may be used as the reference image which will be processed and against which the subject document is compared with.
- Such computer instructions can be written in a number of programming languages for use with many computer architectures or operating systems. Furthermore, such instructions may be stored in any memory device, such as semiconductor, magnetic, optical or other memory devices, and may be transmitted using any communications technology, such as optical, infrared, microwave, or other transmission technologies. It is expected that such a computer program product may be distributed as a removable medium with accompanying printed or electronic documentation (e.g., shrink wrapped software), preloaded with a computer system (e.g., on system ROM or fixed disk), or distributed from a server over the network (e.g., the Internet or World Wide Web).
- some embodiments of the invention may be implemented as a combination of both software (e.g. , a computer program product) and hardware. Still other embodiments of the invention may be implemented as entirely hardware, or entirely software (e.g., a computer program product).
Abstract
Description
Claims
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CA2658566A CA2658566C (en) | 2006-07-31 | 2007-06-28 | Method and apparatus for comparing document features using texture analysis |
DE112007001791.0T DE112007001791B8 (en) | 2006-07-31 | 2007-06-28 | Method for determining the authenticity of a document by means of a texture analysis and computer-readable medium |
GB0823621A GB2452663B (en) | 2006-07-31 | 2007-06-28 | Method and apparatus for comparing document features using texture analysis |
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US11/496,166 US7920714B2 (en) | 2006-07-31 | 2006-07-31 | Method and apparatus for comparing document features using texture analysis |
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CA (1) | CA2658566C (en) |
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Also Published As
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DE112007001791B4 (en) | 2015-05-07 |
CA2658566C (en) | 2013-02-12 |
CA2658566A1 (en) | 2008-02-07 |
GB2452663B (en) | 2011-11-09 |
US20080030798A1 (en) | 2008-02-07 |
DE112007001791T5 (en) | 2009-07-30 |
US7920714B2 (en) | 2011-04-05 |
GB2452663A (en) | 2009-03-11 |
DE112007001791B8 (en) | 2015-07-09 |
GB0823621D0 (en) | 2009-02-04 |
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