MMMar 29, 2018

High Capacity Image Data Hiding of Scanned Text Documents Using Improved Quadtree

arXiv:1803.11286v16 citations
Originality Incremental advance
AI Analysis

This is an incremental improvement for secure document transfer applications.

The paper tackles the problem of low embedding capacity in image steganography for scanned text documents by exploiting their sparse properties, achieving higher capacity than random-message methods.

In this paper, an effective method was introduced to steganography of text document in the host image. In the available steganography methods, the message has a random form. Therefore, the embedding capacity is generally low. In the proposed method, the main underlying idea was the sparse property of scanned documents. The scanned documents were converted from gray-level form to binary values by halftoning idea and then the information-included parts were extracted using the improved quadtree and separated from document context. Next, in order to compress the extracted parts, an algorithm was proposed based on reading the binary string bits, ignoring the zero behind the number, and converting them to decimal values. Embedding capacity of the proposed method is higher than that of other available methods with a random-based message. Therefore, the proposed method can be used in the secure and intangible transfer of text documents in the host image.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

Your Notes