Hi Sir,
I am an Mtech Student. As part of my mini project I need the code for color extended visual cryptograohy using error diffusion .Can you please send me the code to my email id -anudevsree87[at]gmail.com.
Posts: 14,118
Threads: 61
Joined: Oct 2014
The secret image can be retrieved if at least k of the actions overlap, whereas nothing can be obtained if less than k parts are known. The previous EVCS schemes are for black-and-white or pixel-expanding images. In this article, we propose the first k-out-of-n EVCS for colour images without pixel expansion. The scheme also improves the contrast of the n actions and the reconstructed secret image (ie, the superimposed image of any more ko parts) allowing users to specify the level of each primary colour (ie red, green and blue) Thus Like the reconstructed secret image.
This document proposes a method to create copyright protection of digital images. The method proposed in this work is based on visual cryptography using LPG with PCA. The proposed method is working on selecting random pixels from the original digital image rather than the specific pixel selection. In today's scenario the protection of digital data is most needed in every part of life. More robust methods are being developed to protect the property rights of multimedia. In this work, an invisible watermark technique is proposed to embed multiple binary watermarks in digital medical images based on the concept of Visual Cryptography (VC). The proposed scheme incorporates the watermarks without modifying the original host image. Cryptography is nothing more than the secret sharing of the text. Likewise visual cryptographic scheme (VCS) is to share secret images. The VCS extension is Embedded Extended Visual Cryptography. A secret image is divided into actions and the stacking of actions will reveal the secret image. The recovered secret image quality is less in terms of loss of resolution and contrast. In this article we introduce an extended visual cryptographic scheme for the colour image using LPG with PCA; This can help improve the visual quality of the retrieved image. Due to the local pixel search with Principal Component Analysis (PCA) due to this, we can embed and extract multiple secret images with very good quality.
It can be understood in the following video: