Voronoi-based image representation applied to binary visual cryptography

• Published in: Signal processing. Image communication Vol. 87; p. 115913
• Main Authors: Melkemi, Mahmoud, Hammoudi, Karim
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier B.V 01-09-2020; Elsevier BV; Elsevier
• Subjects: Algorithms; Bandwidths; Communication networks; Computer Science; Computer Vision and Pattern Recognition; Cryptography; Encryption; Image communication; Image enhancement; Image reconstruction; Image sharing; Image transmission; Network reliability; Redundancy; Representations; Tessellation; Visual communication; Visual cryptography; Visual representation; Voronoi diagram; Visual cryptography; Voronoi diagram; Visual communication; Visual representation; Image communication; Image sharing
• ISSN: 0923-5965; 1879-2677
• DOI: 10.1016/j.image.2020.115913

A common processing scheme of Visual Cryptography (VC) consists of generating two ciphered images from a secret image. The sender transmits these key images via two different channels. The receiver collects the key images and recovers the secret image by superimposing them. In this article, Voronoi tessellation is exploited in Visual Cryptography for the first time to the best of our knowledge. The proposed Voronoi-based Visual Cryptography (VVC) technique permits to drastically reduce the amount of encoded and transmitted information by comparison with a traditional VC scheme. Hence, the technique can be used for transmissions of secret images with enforcement of the transmission reliability by enhancing the redundancy of information or with communication networks and technologies having low bandwidth and memory. Moreover, the random arrangement of the Voronoi polygons makes the transmission of the secret image more secure since the sender and the recipient use a private generator of random points. In addition, shape reconstruction properties of the image-based Voronoi representation are stated.
•Voronoi-based Visual Cryptography can drastically reduce the size of image shares.•VVC can make VC secure with a private random generator and point-based image coding.•Shape reconstruction properties of the Voronoi-based image representation are stated.•VVC can support VC for low-resource technologies and for transmission reliability.•VVC transfers powerful Voronoi properties to traditional VC schemes.