Image inpainting-based behavior image secret sharing

Abstract

The polynomial-based image secret sharing (ISS) scheme encodes a secret image into n shadows assigned to n participants. The secret image with high resolution is decoded by Lagrange interpolation when collecting any k or more shadows. Thus, ISS is used in applications such as distributive storage in the cloud, digital watermarking, block chain, and access control. Meaningful shadows are significant in ISS because meaningful shadows decrease the suspicion of image encryption and increase the efficiency of shadow management. Generally, previously meaningful ISS schemes were achieved through embedding the shadows into cover images using information hiding techniques and suffer from large pixel expansion and complex decoding procedure. Digital image processing, such as inpainting (texture synthesis), is a standard technique in multimedia applications. It will be highly significant if ISS can be performed in the processing of a normal digital image processing technique. Generally, the encoding method of an ISS scheme entails the use of a mathematical function that is sensitive to any slight change in the ISS output; therefore, the development of a method for performing the ISS procedure and simultaneously achieving image processing behavior is a key challenge. In this paper, we exploit the behavior ISS (BISS) and realize an image inpainting-based BISS scheme for the (k, n) threshold. Using screening operations, a secret image is encoded into the pixels of cover images by polynomial-based ISS in the processing of inpainting shadows to obtain meaningful shadows similar to the input cover images. In addition, the secret image can be losslessly decoded by Lagrange interpolation when collecting any k or more shadows. Experiments are given to confirm the efficiency of the scheme.

Keywords

• image secret sharing
• behavior image secret sharing
• image inpainting
• polynomial
• color image
• meaningful shadows