| Previous | [ 1] | [ 2] | [ 3] | [ 4] | [ 5] | [ 6] | [ 7] | [ 8] | [ 9] | [ 10] | [ 11] | [ 12] | [ 13] | [ 14] | [ 15] | [ 16] | [ 17] | [ 18] | [ 19] | [ 20] |
¡@
Peng-Cheng Wang1,2 and Chung-Ming Wang1
1Institute of Computer Science
National Chung Hsing University
Taichung, 402 Taiwan
2Department of Information Management
Hsiuping Institute of Technology
Taichung, 412 Taiwan
We present a novel reversible data hiding scheme for point-sampled geometry in
the spatial domain. To the best of our knowledge, our scheme is the first in the literature
for recovering the original point-sampled model using little amount of information. In
contrast, other schemes generally need to store an extra large amount of bit size equal to
the payload size for reversibility. Our scheme first employs principal component analysis
(PCA) for the point-sampled model to produce three principal axes and to construct a
PCA-coordinate system. We then translate the coordinates of the original points to the
PCA-coordinate system in order to achieve robustness against translation, rotation, and
uniform scaling operations. Second, we sort the points¡¦ coordinates for each axis to yield
intervals which are the embedding positions. Finally, we utilize the left-shift operator to
shift the bit of the state value of the interval left by c bits (c >= 1) so that it creates c bits
extra storage space for embedding the payload and we store the original state value for
achieving reversibility. Experimental results show that our scheme can embed large
amounts of data with insignificant visual distortion of the original model. The data capacity
in bits achieves nearly 1.5c times the number of points in the models.
Received November 8, 2005; revised March 3 & May 8, 2006; accepted May 24, 2006.
Communicated by Ja-Ling Wu.