Mobile interactive hologram verification

Verification of paper documents is an important part of checking a person's identity, authorization for access or simply establishing a trusted currency. Many documents such as passports or paper bills include holograms or other view-dependent elements that are difficult to forge and therefore are used to verify the genuineness of that document. View-dependent elements change their appearance based both on viewing direction and dominant light sources, thus it requires special knowledge and training to accurately distinguish original elements from forgeries. We present an interactive application for mobile devices that integrates the recognition of the documents with the interactive verification of view-dependent elements. The system recognizes and tracks the paper document, provides user guidance for view alignment and presents a stored image of the element's appearance depending on the current view of the document also recording user decisions. We describe how to model and capture the underlying spatially varying BRDF representation of view-dependent elements. Furthermore, we evaluate this approach within a user study and demonstrate that such a setup captures images that are recognizable and that can be correctly verified.

[1]  Dieter Schmalstieg,et al.  Real-Time Detection and Tracking for Augmented Reality on Mobile Phones , 2010, IEEE Transactions on Visualization and Computer Graphics.

[2]  Van Renesse,et al.  Optical document security , 1994 .

[3]  Andrew J. Davison,et al.  Real-time surface light-field capture for augmentation of planar specular surfaces , 2012, 2012 IEEE International Symposium on Mixed and Augmented Reality (ISMAR).

[4]  Oliver Bimber.  Combining optical holograms with interactive computer graphics , 2006, SIGGRAPH Courses.

[5]  Michael Burmester,et al.  AttrakDiff: Ein Fragebogen zur Messung wahrgenommener hedonischer und pragmatischer Qualität , 2003, MuC.

[6]  Cafer Ozkul,et al.  Application of wavelet transform to hologram analysis: three-dimensional location of particles , 2000 .

[7]  P. Hancock,et al.  Human Mental Workload , 1988 .

[8]  Gordon Wetzstein,et al.  Interacting with augmented holograms , 2005, SPIE OPTO.

[9]  John M. Snyder,et al.  Manifold bootstrapping for SVBRDF capture , 2010, ACM Trans. Graph..

[10]  Yu-Chee Tseng,et al.  AR-Based Positioning for Mobile Devices , 2011, 2011 40th International Conference on Parallel Processing Workshops.

[11]  David Nistér,et al.  Scalable Recognition with a Vocabulary Tree , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[12]  Horst Bischof,et al.  A Duality Based Algorithm for TV- L 1-Optical-Flow Image Registration , 2007, MICCAI.

[13]  Jan Owsik,et al.  A Wiener filter based correlation method intended to evaluate effectiveness of holographic security devices , 2003 .

[14]  Baining Guo,et al.  Pocket reflectometry , 2011, SIGGRAPH 2011.

[15]  Roland Siegwart,et al.  BRISK: Binary Robust invariant scalable keypoints , 2011, 2011 International Conference on Computer Vision.

[16]  Tae-Hyoung Park,et al.  An automatic inspection system for hologram with multiple patterns , 2007, SICE Annual Conference 2007.

[17]  Abhilash Pandya,et al.  Improved Telemanipulator Navigation During Display-Control Misalignments Using Augmented Reality Cues , 2010, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

[18]  Jirí Filip,et al.  Visual Texture , 2013, Advances in Computer Vision and Pattern Recognition.

[19]  Luc Van Gool,et al.  Speeded-Up Robust Features (SURF) , 2008, Comput. Vis. Image Underst..

[20]  Terry E. Duncan,et al.  Psychometric properties of the Intrinsic Motivation Inventory in a competitive sport setting: a confirmatory factor analysis. , 1989, Research quarterly for exercise and sport.

[21]  Tae-Hyoung Park,et al.  Vision inspection system for holograms with mixed patterns , 2010, 2010 IEEE International Conference on Automation Science and Engineering.