Share Email Print
cover

Proceedings Paper

An enhanced smoothness evaluation for reversible data hiding in encrypted images
Author(s): Wien Hong; Tung-Shou Chen; Han-Yan Wu; Hsun-Li Chang
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper Abstract

Recently, Zhang proposed a reversible data hiding scheme for encrypted image with a low computational complexity which is made up of image encryption, data embedding and data-extraction/image-recovery phases. During the last phase, the embedded data are extracted according to a determined smoothness measuring function on each nonoverlapping block. However, not all pixels in a block are considered in his approach. This may cause higher error rate when extracting embedded data. In this paper, we propose a novel smoothness evaluating scheme to overcome the problem. Based on the Zhang's approach, we divide the pixels in each block into three different portions: four corners, four edges, and the rest of pixels. The smoothness of a whole block is determined by summing the smoothness of three portions and is utilized to extract embedded data and recovery image. Experimental results show that the proposed scheme can reduce the error rate of data-extraction/image-recovery effectively. For a given normal testing image, such as Lena, supposing that the size of each block is 8 by 8, the error rate of our approach is less than 0.6% and Zhang's method is higher than 12%. Moreover, the error rate will be zero when the size of each block is defined as 12 by 12.

Paper Details

Date Published: 8 June 2012
PDF: 5 pages
Proc. SPIE 8334, Fourth International Conference on Digital Image Processing (ICDIP 2012), 833434 (8 June 2012); doi: 10.1117/12.956483
Show Author Affiliations
Wien Hong, Yu Da Univ. (Taiwan)
Tung-Shou Chen, National Taichung Univ. of Science and Technology (Taiwan)
Han-Yan Wu, Yu Da Univ. (Taiwan)
Hsun-Li Chang, Yu Da Univ. (Taiwan)


Published in SPIE Proceedings Vol. 8334:
Fourth International Conference on Digital Image Processing (ICDIP 2012)
Mohamed Othman; Sukumar Senthilkumar; Xie Yi, Editor(s)

© SPIE. Terms of Use
Back to Top