Efficient verification of holograms using mobile augmente reality

1. Efficient Verification of Holograms
Using Mobile Augmented Reality
PRESENTED BY,
AKHIL MUKUNDAN
ROLL NO. 29
S7 CSE
ISSAT
GUIDED BY,
Ms. NEENU SHEREEF

2. Introduction
• Paper Documents are frequently checked by inspection of security element.
• Holograms are important security element, but difficult to inspect.
• Augmented Reality can provide relevant information on standard mobile devices.
• First evaluate a series of similarity measures for matching hologram patches.
• That provides a sound basis for automatic decisions.
• Enables faster verification of documents.
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3. Contents
• Introduction
• Existing System
• Proposed Technology
• Augmented Reality
• Hologram Verification with Mobiles
• Hologram Capture
• Processing
• Interface Design
• Findings and Discussions
• Applications
• Conclusion
• References
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4. Existing System
• Holograms incorporates wide variety of security elements in it.
• They can be viewed by changing the viewing angle or by changing the
angle of incident light.
• Requires an individual to find all relevant patterns listed in a manual
by looking at the hologram.
• Only trained individuals can efficiently verify them.
• Manuals often lack an indication on the viewing direction and do not
specify requirements on lighting conditions.
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5. Contd.
• In real-world situations, manuals are not always at hand, so users fall
back to solely looking for appearance changes.
• People inspect holograms on security documents just by looking for
changes in appearance or the pure presence of rainbow colors.
• This has no particular value regarding security.
• Development of tools and algorithms for the automatic detection and
verification of holograms by laypeople deserves our interest.
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6. Proposed Technology
• Capture reference data from holograms along with a matching
approach that can be used for automatic verification at runtime.
• Performs classification, tracking and augmentation of relevant
information.
• This allows to select the correct reference information for hologram
verification.
• Ensures that the elements are observed from the correct viewpoint.
• This setup serves as a basic building block for mobile hologram
verification with appropriate user guidance and visualization.
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7. Augmented Reality
• A live direct or indirect view of a physical, real-world environment.
• Elements are augmented (or supplemented) by computer-generated
sensory input such as sound, video, graphics or GPS data.
• Replaces the real world with a simulated one.
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8. Hologram Verification with Mobiles
• Capturing hologram patches
• View alignment/user guidance
• Mobile AR prototype
• Evaluation within user study
• Revision of the prototype
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9. Hologram Capture
• Assumption
• Total radiance from a point on the hologram is dominated by a single light source
• Fixed distance to surface
• Dominant Light Source
• LED light on mobile phone
• Fixed to the camera with offset vector
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10. View alignment
Objective
• Mobile method for alignment with a given pose
• Reasonable accuracy despite mobile environment
Approach
• Visual guidance with iron sights and a virtual horizon
• 1 matching direction of the viewing ray
• 2 position along the ray
• 3 in-plane rotation
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1
2
3

11. Preprocessing
• Capturing Reference Data With moderate ambient light.
• Appearance of a hologram is largely dominated by using the LED
flashlight of mobile devices.
• The workspace consists of a hemisphere centered at the hologram on
the document.
• Capture the current video image and the corresponding pose for each
position on the hemisphere.
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12. Contd.
• We assume the hologram to be planar and project its bounding box
into the image using the recorded pose.
• Results a set of registered image patches that represent all observable
appearances of the current hologram.
• Exclude all data recorded < 5 degree and > 55 degree away from the
orthogonal view.
• In order to avoid artifacts caused by oblique views and tracking
failure.
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13. Runtime Processing
Classification and Tracking
• Identification of the document type.
Matching
• Evaluate similarity measures such as
• Perform linear scaling of matching scores using coefficients obtained
by analysis of all recorded patch data.
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1. Manual selection
2. Computing from image
1. Sum of Absolute Differences (SAD)
2. Normalized cross correlation (NCC)

14. Interface Design
• Guide the user to align the mobile device with exactly those view
points which are associated with the selected reference data.
• User-friendly hybrid interface together with automatic matching which
makes the hologram verification more accessible.
• Facts regarding interface design are:
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1. Concept and Graphical Representation
2. User-Oriented Parametrization

15. 1.Concept and Graphical Representation
• The user should be guided towards different viewing directions or
ranges.
• A 2D orientation map (projection of the conic space) is used for this
task.
• It is divided into slices that are aligned on one or more tracks.
• We record several shots per slice that differ at least by a given angle
threshold.
• Small arrows around the cursor serve as movement indicators.
• The upper arc switches from red to green with increasing slice
coverage.
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16. Contd.
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17. 2.User-Oriented Parametrization
• Changes in orientation generally took place roughly along the vertical
and horizontal axes.
• Conducted an experiment with people.
• They are asked to record a hologram document with smartphone.
• Provided two approaches:
• Both approaches made considerable differences.
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1. Document and phone held on their hands
2. Document placed on a table

18. Orientation changes
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Fig 1 Fig 2

19. Findings and Discussion
• Holograms can be assessed by the system immediately after image
capture, which takes approximately 15 seconds.
• A subsequent decision by the user takes another 20s.
• The system was able to assess the hologram correctly in all cases.
• Users were unsure about the validity of the hologram in 10.94
percent of all cases.
• Succeeded to give a correct decision in 85.94 percent of all cases
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20. Contd.
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21. Applications
• Detection of fake documents.
• Counterfeit currency detection.
• Enhanced verification of passports and visa.
• For checking identity cards.
• Can replace barcode system.
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22. Conclusion
• Capture of holograms and view alignment worked reasonably well.
• Hologram verification on mobiles seams feasible.
• Takes less amount to complete verification than that of manual
method.
• Verification is possible under optimal lighting conditions.
• Mobile AR systems can serve as tools for the verification of
holograms by laypeople.
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23. References
• R. L. van Renesse. Optical Document Security. Artech House, third edition, 2005.
• T.-H. Park and H.-J. Kwon. Vision inspection system for holograms with mixed
patterns. In CASE, pages 563–567, 2010.
• M. Haindl and J. Filip. Visual Texture. Advances in Computer Vision and Pattern
Recognition. Springer Verlag, 2013
• J. Jachnik, R. A. Newcombe, and A. J. Davison. Real-time surface light-field
capture for augmentation of planar specular surfaces. In ISMAR, pages 91–97,
2012
• P. Ren, J. Wang, J. Snyder, X. Tong, and B. Guo. Pocket reflectometry. n Proc.
SIGGRAPH 2011, SIGGRAPH ’11, pages 45:1–45:10, New York, NY, USA, 2011.
ACM.
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24. Thank You

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Any
Questions?