DocumentCode :
3313428
Title :
A known-energy neural network approach for visual cryptography
Author :
Yue, Tai-Wen ; Chiang, Suchen
Author_Institution :
Dept. of Comput. Sci. & Eng., Tatung Univ., Taiwan
Volume :
4
fYear :
2001
fDate :
2001
Firstpage :
2542
Abstract :
This paper introduces the so-called known-energy system based on the Q´tron neural network (NN) model, and applies it to visual cryptography. With a known-energy system, the NN intrinsically performs a goal-directed search, meaning that the NN will settle down only when its state fulfils the dedicated goal. The noise injection mechanism that makes the NN to work in such a manner is discussed. The NN built for visual cryptography in the paper is modeled as a known-energy system. The approach is completely different from the traditional ones, and the so-built NN can be used to cope with complex encrypting structures of visual cryptography. Experiments show that its result is good
Keywords :
cryptography; image coding; neural nets; noise; Qtron neural network; goal-directed search; image coding; known-energy system; noise injection; shadow images; visual cryptography; Authentication; Authorization; Books; Computer science; Cryptography; Image recognition; Neural networks; Power engineering and energy; Stacking; Target recognition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 2001. Proceedings. IJCNN '01. International Joint Conference on
Conference_Location :
Washington, DC
ISSN :
1098-7576
Print_ISBN :
0-7803-7044-9
Type :
conf
DOI :
10.1109/IJCNN.2001.938769
Filename :
938769
Link To Document :
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