A high capacity approach to embedding orthogonal data in binary images using morphological transform domain.

Introduction

Binary image data embedding is a technique used in digital image processing to hide information within an image without affecting its visual quality. It is a form of steganography where data is hidden in a cover image using various algorithms and transformations. One of the popular techniques used for binary image data embedding is the morphological transform domain. In this domain, morphological operations such as erosion and dilation are applied to images, which can help in embedding data without being easily detected.

Problem Statement

The main issue with traditional approaches to binary image data embedding is the limited capacity for hiding data. The existing systems often have low payload capacity, which means that they can only hide a small amount of information within an image. This can be a major limitation when it comes to applications where a large amount of data needs to be embedded securely.

Existing System

In the existing system, binary image data embedding techniques rely on simple algorithms such as LSB (Least Significant Bit) embedding or spatial domain transformations. These techniques have limited capacity and can be easily detected by attackers using statistical analysis or other data extraction methods. Moreover, these techniques can also affect the visual quality of the image, making it less suitable for applications where image quality is critical.

Disadvantages

– Low capacity for hiding data
– Vulnerability to detection
– Impact on visual quality of the image

Proposed System

The proposed system for binary image data embedding is an orthogonal data embedding approach in the morphological transform domain. This approach aims to increase the capacity for hiding data within a binary image while maintaining the visual quality of the image. By using morphological operations in the transform domain, it is possible to embed data in a way that is robust against detection and extraction.

Advantages

– High capacity for hiding data
– Robust against detection
– Preserves visual quality of the image

Features

The proposed system for orthogonal data embedding in the morphological transform domain offers several key features that make it a superior approach compared to traditional techniques. Some of the notable features include:

– Enhanced data hiding capacity: The system can hide a larger amount of data within a binary image without affecting its visual quality.
– Robustness against attacks: The use of morphological operations in the transform domain makes the embedded data more resistant to detection and extraction.
– Improved image quality: The system preserves the visual quality of the image by ensuring that the embedding process does not introduce any noticeable distortions.
– Flexibility in data embedding: The system allows for flexible embedding of data in different parts of the image, making it harder for attackers to pinpoint the hidden information.
– Compatibility with existing systems: The proposed approach can be easily integrated into existing image processing systems without requiring major changes to the underlying algorithms.

Conclusion

In conclusion, the proposed system for orthogonal data embedding in the morphological transform domain is a high-capacity approach that overcomes the limitations of existing binary image data embedding techniques. By leveraging morphological operations in the transform domain, it offers a robust and efficient way to hide data within images while preserving their visual quality. This system has the potential to find applications in various fields where secure and efficient data hiding is required, making it a valuable contribution to the field of digital image processing.