Titlebook: Improving Image Quality in Visual Cryptography; Bin Yan,Yong Xiang,Guang Hua Book 2020 Springer Nature Singapore Pte Ltd. 2020 Data Decryp

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Introduction,ons visual cryptography is suitable and in which applications classical cryptography is preferable, in order to guide the reader to select appropriate cryptographic tools according to their intended security services. From these applications, the existing algorithms can be classified into several categories.

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Digital Halftoning, error diffusion, and direct binary search (DBS). The mathematical models for error diffusion are also discussed. Finally, some commonly used perceptual quality measures for halftone images are introduced. These measures are particularly useful when developing algorithms for grayscale images in later chapters.

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1860-4862 crypted gray scale secret images.Employs quality measures su.This book comprehensively covers the important efforts in improving the quality of images in visual cryptography (VC), with a focus on cases with gray scale images. It not only covers schemes in traditional VC and extended VC for binary se

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Introduction,n order to give the reader a general idea of this topic. Then, we identify some important applications of VC. Here, we also discuss in which applications visual cryptography is suitable and in which applications classical cryptography is preferable, in order to guide the reader to select appropriate

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Basic Visual Cryptography Algorithms,icated algorithms in later chapters. First, we introduce the general framework of VC, such as access structure and general requirements (security and contrast). Then, we introduce the classical deterministic VC with pixel expansion as developed in Naor and Shamir’s seminal work. Next, the size-invar

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Improving Visual Quality for Vector Schemes,line the basic vector VC for binary secret images. Then, we combine the AbS framework with vector VC to get better visual quality than AbS-based probabilistic VC and AbS-based random grid VC. For separate halftoning and VC encryption, we use the blackness preserving algorithm. For grayscale secret i