scholarly journals Image inpainting-based behavior image secret sharing

2020 ◽  
Vol 17 (4) ◽  
pp. 2950-2966
Author(s):  
Xuehu Yan ◽  
◽  
Xuan Zhou ◽  
Yuliang Lu ◽  
Jingju Liu ◽  
...  
Symmetry ◽  
2020 ◽  
Vol 12 (5) ◽  
pp. 703
Author(s):  
Xuehu Yan ◽  
Lei Sun ◽  
Yuliang Lu ◽  
Guozheng Yang

In contrast to encrypting the full secret image in classic image secret sharing (ISS), partial image secret sharing (PISS) only encrypts part of the secret image due to the situation that, in general, only part of the secret image is sensitive or secretive. However, the target part needs to be selected manually in traditional PISS, which is human-exhausted and not suitable for batch processing. In this paper, we introduce an adaptive PISS (APISS) scheme based on salience detection, linear congruence, and image inpainting. First, the salient part is automatically and adaptively detected as the secret target part. Then, the target part is encrypted into n meaningful shares by using linear congruence in the processing of inpainting the target part. The target part is decrypted progressively by only addition operation when more shares are collected. It is losslessly decrypted when all the n shares are collected. Experiments are performed to verify the efficiency of the introduced scheme.


2017 ◽  
Vol 10 (33) ◽  
pp. 1-17
Author(s):  
Ashwaq Talib Hashim ◽  
Zaid Mundher Radeef ◽  
◽  

2008 ◽  
pp. 338-343
Author(s):  
Rastislav Lukac ◽  
Konstantinos N. Plataniotis ◽  
Ching-Nung Yang

2017 ◽  
Vol 77 (7) ◽  
pp. 7865-7881 ◽  
Author(s):  
Tzung-Her Chen ◽  
Kai-Siang Lin ◽  
Chih-Hung Lin

2016 ◽  
Author(s):  
Jing-zhong Zhang ◽  
Liang Chen ◽  
Peng-guo Teng

2020 ◽  
Vol 1550 ◽  
pp. 032008
Author(s):  
Shanzheng Liu ◽  
Hang Zhang ◽  
Ying Yu ◽  
Hongliang Cai ◽  
Dan Tang

Sign in / Sign up

Export Citation Format

Share Document