Blind Scheme with Histogram Peak Estimation for Histogram Modication-Based Lossless Information Embedding

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Masaaki Fujiyoshi

Abstract

In this paper, a simple scheme for histogram modification-based lossless information embedding (HM-LIE) is proposed. The proposed scheme is free from memorizing side information, i.e., blind. A HMLIE scheme modifies particular pixel values in an image in order to embed information in it on the basis of its histogram, i.e., tonal distribution. The scheme recovers the original image as well as extracts embedded information from a distorted image conveying embedded information. Most HM-LIE schemes should memorize a set of image-dependent side information per image. The proposed scheme does not have to memorize such information to avoid costly identification of the distorted image carrying embedded information because of the introduction of two mechanisms. One is estimating side information on the basis of a simple statistic, and the other is concealing not only main information but also a part of the side information in the image. These approaches make the proposed scheme superior to the conventional blind schemes in terms of the quality of images
conveying embedded information.

Article Details

How to Cite
[1]
M. Fujiyoshi, “Blind Scheme with Histogram Peak Estimation for Histogram Modication-Based Lossless Information Embedding”, ECTI-CIT Transactions, vol. 7, no. 2, pp. 97–106, Apr. 2016.
Section
Artificial Intelligence and Machine Learning (AI)