Data hiding in curves with application to fingerprinting maps
- 19 September 2005
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Signal Processing
- Vol. 53 (10), 3988-4005
- https://doi.org/10.1109/tsp.2005.855411
Abstract
This paper presents a new data hiding method for curves. The proposed algorithm parameterizes a curve using the B-spline model and adds a spread spectrum sequence to the coordinates of the B-spline control points. In order to achieve robust fingerprint detection, an iterative alignment-minimization algorithm is proposed to perform curve registration and to deal with the nonuniqueness of B-spline control points. Through experiments, we demonstrate the robustness of the proposed data-hiding algorithm against various attacks, such as collusion, cropping, geometric transformations, vector/raster-raster/vector conversions, printing-and-scanning, and some of their combinations. We also show the feasibility of our method for fingerprinting topographic maps as well as writings and drawings.Keywords
This publication has 24 references indexed in Scilit:
- Watermarking Algorithms for 3D NURBS Graphic DataEURASIP Journal on Advances in Signal Processing, 2004
- Data Hiding in Binary Image for Authentication and AnnotationIEEE Transactions on Multimedia, 2004
- Image Registration by “Super-Curves”IEEE Transactions on Image Processing, 2004
- Robust content-dependent high-fidelity watermark for tracking in digital cinemaPublished by SPIE-Intl Soc Optical Eng ,2003
- Data hiding in digital binary imagePublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- A shape-preserving data embedding algorithm for NURBS curves and surfacesPublished by Institute of Electrical and Electronics Engineers (IEEE) ,1999
- Calculating the Hausdorff distance between curvesInformation Processing Letters, 1997
- Marking text documentsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,1997
- Part I: Modeling image curves using invariant 3-D object curve models-a path to 3-D recognition and shape estimation from image contoursIeee Transactions On Pattern Analysis and Machine Intelligence, 1994
- Automatic representation of binary imagesIeee Transactions On Pattern Analysis and Machine Intelligence, 1990