Image Size Invariant Visual Cryptography for General Access Structures Subject to Display Quality Constraints

• Published in: IEEE transactions on image processing Vol. 22; no. 10; pp. 3830 - 3841
• Main Authors: Lee, Kai-Hui, Chiu, Pei-Ling
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.10.2013; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Applied sciences; Construction; controllable display quality; Cryptography; Design engineering; Detection, estimation, filtering, equalization, prediction; Exact sciences and technology; general access structures; Image processing; Image quality; Information, signal and communications theory; Maintenance; Mathematical analysis; Mathematical models; Optimization; pixel expansion; Pixels; Signal and communications theory; Signal processing; Signal, noise; Systematics; Telecommunications and information theory; Vectors; Vectors (mathematics); Visual; Visual secret sharing scheme; Visualization; Encryption; Decryption; Optimization; Image quality; general access structures; Visual secret sharing scheme; Codebook; pixel expansion; Simulated annealing; Security of data; controllable display quality; Binary image; Secret sharing; Cryptography; Computer aid
• ISSN: 1057-7149; 1941-0042; 1941-0042
• DOI: 10.1109/TIP.2013.2262290

Conventional visual cryptography (VC) suffers from a pixel-expansion problem, or an uncontrollable display quality problem for recovered images, and lacks a general approach to construct visual secret sharing schemes for general access structures. We propose a general and systematic approach to address these issues without sophisticated codebook design. This approach can be used for binary secret images in non-computer-aided decryption environments. To avoid pixel expansion, we design a set of column vectors to encrypt secret pixels rather than using the conventional VC-based approach. We begin by formulating a mathematic model for the VC construction problem to find the column vectors for the optimal VC construction, after which we develop a simulated-annealing-based algorithm to solve the problem. The experimental results show that the display quality of the recovered image is superior to that of previous papers.